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35174 Publications

Bremsstrahlung emission and plasma characterization driven by moderately relativistic laser-plasma interactions

Singh, S. K.; Armstrong, C.; Kang, N.; Ren, L.; Liu, H.; Hua, N.; Rusby, D. R.; Klimo, O.; Versaci, R.; Zhang, Y.; Sun, M.; Zhu, B.; Lei, A.; Ouyang, X.; Lancia, L.; Laso Garcia, A.; Wagner, A.; Cowan, T. E.; Schlegel, T.; Weber, S.; McKenna, P.; Neely, D.; Tikhonchuk, V. T.; Kumar, D.; Zhu, J.

Relativistic electrons generated by the interaction of petawatt-class short laser pulses with solid targets can be used to generate bright X-rays via bremsstrahlung. The efficiency of laser energy transfer into these electrons depends on multiple parameters including focused intensity and pre-plasma level. This paper describes the experimental results from the interaction of a high intensity petawatt-class glass laser with solid targets at a maximum intensity of 10^19 W/cm^2. In-situ measurements of specularly reflected light were used to provide an upper bound of laser absorption and to characterize focused laser intensity, the pre-plasma level and the generation mechanism of second harmonic light. The measured spectrum of electrons and bremsstrahlung radiation provide information about the efficiency of laser energy transfer.

Keywords: Plasma Physics; Bremsstrahlung; High intensity laser

Related publications

Publ.-Id: 32027

Chaotic wave dynamics in weakly magnetized spherical Couette flows

Garcia Gonzalez, F.; Seilmayer, M.; Giesecke, A.; Stefani, F.

Direct numerical simulations of a liquid metal filling the gap between two concentric spheres are presented. The flow is governed by the interplay between the rotation of the inner sphere (measured by the Reynolds number Re) and a weak externally applied axial magnetic field (measured by the Hartmann number Ha). By varying the latter, a rich variety of flow features, both in terms of spatial symmetry and temporal dependence, is obtained. Flows with two or three independent frequencies describing their time evolution are found as a result of Hopf bifurcations. They are stable on a sufficiently large interval of Hartmann numbers where regions of multistability of two, three, and even four types of these different flows are detected. The temporal character of the solutions is analyzed by means of an accurate frequency analysis and Poincaré sections. An unstable branch of flows undergoing a period doubling cascade and frequency locking of three-frequency solutions is described as well.

  • Chaos: An Interdisciplinary Journal of Nonlinear Science 30(2020), 043116
    DOI: 10.1063/1.5140577


Publ.-Id: 32025

Untersuchungen zur Optimierung der Selektivität bei der Extraktion von Indium durch gezielte Komplexbildung

Göthel, J.

Indium kann sekundärmetallurgisch aus der Prozessierung von Schlacken, Flugstäuben und metallischen Zwischenprodukten aus der Zinkdarstellung gewonnen werden. Eine weitere Möglichkeit der Indiumgewinnung stellt sich in der Aufbereitung von Rückständen des Bergbaus durch Biolaugungsprozesse dar. Höhere Konzentrationen an Eisen und Zink sind in den gewinnbaren Laugen im Vergleich zu sehr niedrigen Indiumkonzentrationen häufig präsent. Ein Trenn- und Aufbereitungsverfahren für die Verarbeitung von hydro-metallurgischen Prozesslösungen und die Gewinnung von Einsatzstoffen aus diesen wird durch Ionenaustauscherharze realisiert. Sowohl kationische als auch anionische feste Ionenaustauscherharze zeigen für Indium in sauren wässrigen Lösungen eine Affinität für die Indiumadsorption. Hinsichtlich der selektiven Adsorption von Indium gegenüber Eisen und Zink mittels festen Anionenaustauschern wurde der Einfluss der selektiven Komplexbildung von Indium durch die Zugabe von Iod in der Form von Kaliumiodid auf die Adsorption untersucht. Als Referenzsystem wurde die Indiumadsorption an festen Kationen-austauscherharzen gewählt. Die selektive Adsorption für Indium wurde aus einer vereinfachten Modelllösung der Biolaugungslösung des „ReMining“-Projektes hinsichtlich der Faktorgrößen des pH-Wertes, der Kaliumiodid- und Indiumadsorption im kleineren Maßstab im Becherglas untersucht. Die bestimmten Optima wurden auf die Prozessierung der realen Biolaugungslösung in Ionenaustauschersäulen angewandt. Indium kann in vergleichbaren quantitativen Mengen sowohl als anionischer Komplex ([InI4]-) von den getesteten Anionenaustauscherharzen A 111 und A 500 als auch von dem Kationenaustauscherharz MTS 9300 als Kation In3+ durch Adsorption aus der Modell- und Biolaugungslösung extrahiert werden. Beide Ionenaustauscher zeigen höchste Selektivitäten gegenüber Eisen, Arsen und Aluminium. Der Vergleich der Konzentrationsverhältnisse von Feed und dem Eluat zeigt, dass Eisen zu ~ 700 Mal mehr wie Indium (Fe/In = ~ 700) im Feed vorhanden ist und nach dem Ionenaustausch ~ 0,7 Mal so viel wie Indium (Fe/In = ~ 0,7) im Eluat verbleibt. Kupfer und Cadmium konnten von dem Anionenaustauscherharz A 111 nicht mit destilliertem Wasser und 0,1 M Schwefelsäure eluiert werden. In der Gesamtbetrachtung der selektiven Adsorption und Eluation von Indium aus der realen Biolaugungslösung ist das Kationenaustauscherharz MTS 9300 dem Anionenaustauscherharz A 111 vorzuziehen.

  • Diploma thesis
    TU Bergakademie Freiberg, 2020
    Mentor: Toni Helbig/Arite Werner

Publ.-Id: 32023

A bimodal soft electronic skin for tactile and touchless interaction in real time

Ge, J.; Wang, X.; Drack, M.; Volkov, O.; Liang, M.; Canon Bermudez, G. S.; Wang, C.; Zhou, S.; Faßbender, J.; Kaltenbrunner, M.; Makarov, D.

The transformative emergence of smart electronics, human-friendly robotics and supplemented or virtual reality will revolutionize the interplay with our surrounding. The complexity that is involved in the manipulation of objects in these emerging technologies is dramatically increased, which calls for electronic skins (e-skin) that can conduct tactile and touchless sensing events in a simultaneous and unambiguous way. Integrating multiple functions in a single sensing unit offers the most promising path towards simple, scalable and intuitive-to-use e-skin architectures. However, by now, this path has always been hindered by the confusing overlap of signals from different stimuli.
Here, we put forward the field of soft, flexible electronics by developing a compliant magnetic microelectromechanical platform (m-MEMS), which is able to transduce both tactile (via mechanical pressure) and touchless (via magnetic field) stimulations simultaneously and discriminate them in real time [1]. For the first time, the electric signals from tactile and touchless interactions are intrinsically separated into two different regions, allowing the m-MEMS, a single sensor unit, to unambiguously distinguish the two modes without knowing the signal history.
Owing to its intrinsic magnetic functionality, our complaint m-MEMS platform is able to discriminate magnetic vs. non-magnetic objects already upon touchless interaction. With this intrinsic selectivity, we address the long-standing problem in the field of touchless interaction – namely, the issue of interference with objects, which are irrelevant or even disturbing the interaction process. In addition, the interaction process is programmable. The sensitivity of the two interaction modes could be tuned by adjusting the magnetic field of the objects able to meet the requirements of different interaction tasks.
By using tactile and touchless sensing functions simultaneously, our m-MEMS e-skins enable complex interactions with a magnetically functionalized physical object that is supplemented with content data appearing in the virtual reality. We demonstrated data selection and manipulation with our m-MEMS e-skins leading to the realization of a multi-choice for augmented reality through three dimensional (3D) touch. Beyond the field of augmented reality, our m-MEMS will bring great benefits for healthcare, e.g. to ease surgery operations and manipulation of medical equipment, as well as for humanoid robots to overcome the challenging task of grasping.

[1] J. Ge, X. Wang, M. Drack, O. Volkov, M. Liang, G. S. Cañón Bermúdez, R. Illing, C. Wang, S. Zhou, J. Fassbender, M. Kaltenbrunner, and D. Makarov. A bimodal soft electronic skin for tactile and touchless interaction in real time. Nature Communications 10, 4405 (2019).

Keywords: flexible electronics; shapeable magnetoelectronics

  • Lecture (Conference) (Online presentation)
    2020 MRS Fall Meeting, 02.12.2020, Boston, USA

Publ.-Id: 32022

Flexible highly compliant magnetoelectronics

Canon Bermudez, G. S.; Ge, J.; Faßbender, J.; Kaltenbrunner, M.; Makarov, D.

Mechanical flexibility and even stretchability of functional elements is a key enabler of numerous applications including wearable electronics, healthcare and medical appliances. The magnetism community developed the family of high-performance shapeable magnetoelectronics [1], which contain flexible [2-4], printable [5-7], stretchable [8-11] and even mechanically imperceptible [12-16] magnetic field sensorics. The technology relies on a smart combination of thin inorganic functional elements prepared directly on flexible or elastomeric supports. The concept of shapeable magnetoelectronics is explored for various applications ranging from automotive [17] through consumer electronics and point of care [2,18] to virtual and augmented reality [14-16] applications.
Here, we will focus on the use of compliant magnetosensitive skins [14-16] for augmented reality systems. We demonstrate that e-skin compasses [14] allow humans to orient with respect to earth’s magnetic field ubiquitously. The biomagnetic orientation enables the realization of a touchless control of virtual units in a game engine using omnidirectional magnetosensitive skins (Fig. 1).
This concept was further extended by demonstrating a compliant magnetic microelectromechanical platform (m-MEMS), which is able to transduce both tactile (via mechanical pressure) and touchless (via magnetic field) stimulations simultaneously and discriminate them in real time [16] (Fig. 2). We demonstrate data selection and manipulation with our m-MEMS e-skins leading to the realization of a multi-choice menu for augmented reality through three dimensional (3D) touch. Beyond the field of augmented reality, our m-MEMS will bring great benefits for healthcare, e.g. to ease surgery operations and manipulation of medical equipment, as well as for humanoid robots to overcome the challenging task of grasping.
[1] D. Makarov et al., Appl. Phys. Rev. (Review) 3, 011101 (2016).
[2] G. Lin, D. Makarov et al., Lab Chip 14, 4050 (2014).
[3] N. Münzenrieder, D. Makarov et al., Adv. Electron. Mater. 2, 1600188 (2016).
[4] M. Melzer, D. Makarov et al., Adv. Mater. 27, 1274 (2015).
[5] D. Makarov et al., ChemPhysChem (Review) 14, 1771 (2013).
[6] D. Karnaushenko, D. Makarov et al., Adv. Mater. 24, 4518 (2012).
[7] D. Karnaushenko, D. Makarov et al., Adv. Mater. 27, 880 (2015).
[8] M. Melzer, D. Makarov et al., J. Phys. D: Appl. Phys. (Review) 53, 083002 (2020).
[9] M. Melzer, D. Makarov et al., Nano Lett. 11, 2522 (2011).
[10] M. Melzer, D. Makarov et al., Adv. Mater. 24, 6468 (2012).
[11] M. Melzer, D. Makarov et al., Adv. Mater. 27, 1333 (2015).
[12] M. Melzer, D. Makarov et al., Nat. Commun. 6, 6080 (2015).
[13] P. N. Granell, D. Makarov et al., npj Flexible Electronics 3, 3 (2019).
[14] G. S. Cañón Bermúdez, D. Makarov et al., Nature Electronics 1, 589 (2018).
[15] G. S. Cañón Bermúdez, D. Makarov et al., Science Advances 4, eaao2623 (2018).
[16] J. Ge, D. Makarov et al., Nature Communications 10, 4405 (2019).
[17] M. Melzer, D. Makarov et al., Adv. Mater. 27, 1274 (2015).
[18] G. Lin, D. Makarov et al., Lab Chip (Review) 17, 1884 (2017).

Keywords: flexible electronics; shapeable magnetoelectronics

  • Lecture (Conference) (Online presentation)
    65th Annual Conference on Magnetism and Magnetic Materials, 03.11.2020, Palm Beach, USA

Publ.-Id: 32021

Mechanically shapeable magnetic field sensor technologies

Makarov, D.

Extending 2D structures into 3D space has become a general trend in multiple disciplines, including electronics, photonics, plasmonics and magnetics. This approach provides means to modify conventional or to launch novel functionalities by tailoring curvature and 3D shape. We study fundamentals of 3D curved magnetic thin films [1] and explore their application potential for flexible electronics, eMobility and health. For these applications, we developed a technology platform known as shapeable magnetoelectronics [2], which relies on a smart combination of ultrathin polymeric foils and metallic thin films featuring magnetoresistive and Hall effects. The mechanically compliant magnetic field sensors are designed and fabricated to address the specific needs of different applications including automotive (monitoring and control of electrical machines and drives) [3-5], biosensing technologies (flexible microfluidic devices) [6,7], consumer electronics (interactive printed electronics) [8,9], orientation in space [10] as well as virtual and augmented reality devices (motion tracking and touchless human-machine interaction) [10-13].
In this presentation, we will review the approaches to fabricate mechanically shapeable magnetic field sensors as well as their magnetoresistive and mechanical performance. On the application side, we will focus on the demonstration of the shapeable sensor devices for the emerging technological fields of smart skins, soft robotics and human-machine interfaces.

[1] R. Streubel, D. Makarov et al.: Magnetism in curved geometries. Journal of Physics D: Applied Physics (Topical Review) 49, 363001 (2016).
[2] D. Makarov et al.: Shapeable magnetoelectronics. Applied Physics Reviews 3, 011101 (2016).
[3] M. Melzer, D. Makarov et al.: Wearable magnetic field sensors for flexible electronics. Advanced Materials 27, 1274 (2015).
[4] D. Ernst, D. Makarov et al.: Packaging technologies for (ultra-)thin sensor applications in active magnetic bearings. IEEE Proceedings of the 37th International Spring Seminar on Electronics Technology (ISSE), pp. 125-129 (2014). doi:10.1109/ISSE.2014.6887577
[5] I.J. Mönch, D. Makarov et al.: Flexible Hall sensorics for flux based control of magnetic levitation. IEEE Trans. Magn. 51, 4004004 (2015).
[6] G. Lin, D. Makarov et al.: Magnetic sensing platform technologies for biomedical applications. Lab Chip 17, 1884 (2017).
[7] G. Lin, D. Makarov et al.: A highly flexible and compact magnetoresistive analytic device. Lab Chip 14, 4050 (2014).
[8] D. Makarov et al.: Printable magnetoelectronics. ChemPhysChem 14, 1771 (2013).
[9] D. Karnaushenko, D. Makarov et al.: High-performance magnetic sensorics for printable and flexible electronics. Advanced Materials 27, 880 (2015).
[10] G. S. Cañón Bermúdez, D. Makarov et al.: Electronic-skin compasses for geomagnetic field driven artificial magnetoception and interactive electronics. Nature Electronics 1, 589 (2018).
[11] G. S. Cañón Bermúdez, D. Makarov et al.: Magnetosensitive e-skins with directional perception for augmented reality. Science Advances 4, eaao2623 (2018).
[12] J. Ge, D. Makarov et al.: A bimodal soft electronic skin for tactile and touchless interaction in real time. Nature Communications 10, 4405 (2019).
[13] P. N. Granell, D. Makarov et al.: Highly compliant planar Hall effect sensor with sub 200 nT sensitivity. npj Flexible Electronics 3, 3 (2019).

Keywords: flexible electronics; shapeable magnetoelectronics

  • Invited lecture (Conferences)
    27. NDVaK - Sensorik auf polymeren Oberflächen, 17.03.2021, Dresden, Germany

Publ.-Id: 32014

Artificial magnetoception enabled by wearable magnetic field sensors

Makarov, D.

In this talk I will review our activities on the realization of magnetoceptive smart skins.

Keywords: flexible electronics; shapeable magnetoelectronics

  • Lecture (others) (Online presentation)
    Seminar at the Technical University of Chemnitz, 27.01.2021, Chemnitz, Germany

Publ.-Id: 32013

Curvilinear magnetism: From curvature induced magnetochirality to shapeable magnetoelectronics

Makarov, D.

Non-collinear magnetic textures like spin spirals, chiral domain walls or skyrmions are typically stabilized by the intrinsic spin-orbit induced Dzyaloshinskii-Moriya interaction (DMI) [1]. Curvature effects emerged as a novel mean to design chiral magnetic responses relying on extrinsic parameters, i.e. geometrical curvature of thin films [2-4]. The lack of an inversion symmetry and the emergence of a curvature induced effective anisotropy and DMI are characteristic of curved surfaces, leading to curvature-driven magnetochiral effects and topologically induced magnetization patterning [5-7]. Vast majority of activities are dedicated to curved ferromagnets, where recent achievements include the development of the theory of curvilinear micromagnetism [3] and the first experimental confirmation of curvature-driven chiral effects stemming from the exchange interaction [4]. Only very recently, the focus was put also on curvilinear antiferromagnets. Pylypovskyi et al. [8] demonstrated that intrinsically achiral one-dimensional curvilinear antiferromagnets behave as a chiral helimagnet with geometrically tunable DMI and orientation of the Neel vector.
The application potential of 3D-shaped magnetic thin films is currently being explored as mechanically shapeable magnetic field sensors [9] for automotive applications, magnetoelectrics for memory devices, spin-wave filters, high-speed racetrack memory devices as well as on-skin interactive electronics [10-12].
The fundamentals as well as application relevant aspects of curvilinear ferro- and antiferromagnets will be covered in this presentation.


[1] D. Sander, DM et al., J. Phys. D 50, 363001 (2017)
[2] R. Streubel, DM et al., J. Phys. D 49, 363001 (2016)
[3] D. Sheka, DM et al., Communications Physics 3, 128 (2020)
[4] O. M. Volkov, DM et al., Phys. Rev. Lett. 123, 077201 (2019)
[5] V. Kravchuk, DM et al., Phys. Rev. Lett. 120, 067201 (2018)
[6] O. Pylypovskyi, DM et al., Phys. Rev. Appl. 10, 064057 (2018)
[7] O. Pylypovskyi, DM et al., Phys. Rev. Lett. 114, 197204 (2015)
[8] O.Pylypovskyi, DM et al., Nano Lett. (2020) doi:10.1021/acs.nanolett.0c03246
[9] D. Makarov et al., Appl. Phys. Rev. 3, 011101 (2016)
[10] S. Canon Bermudez, DM et al., Science Advances 4, eaao2623 (2018)
[11] S. Canon Bermudez, DM et al., Nature Electronics 1, 589 (2018)
[12] J. Ge, DM et al., Nature Communications 10, 4405 (2019).

Keywords: curvilinear magnetism; shapeable magnetoelectronics

  • Invited lecture (Conferences) (Online presentation)
    736. WE-Heraeus-Seminar "Magnetism at the Nanoscale: Imaging ‐ Fabrication – Physics", 06.01.2021, Bad Honnef, Germany

Publ.-Id: 32012

Implantable Highly Compliant Devices for Heating of Internal Organs

Makarov, D.

Recent advances in the field of flexible electronics have opened the door for this technology to deeply impact the health care sector. The development of sensors and actuators which are lightweight and mechanically compliant enables them to be used for continuous health monitoring, on-site therapies or soft chirurgical ads. The key feature of these novel gadgets is their ability to provide targeted treatment and diagnosis without constraining the natural motion of the body or its internal organs.
Though many of these flexible diagnostic or therapeutic devices have been successfully demonstrated already, cancer treatment remains relatively unexplored in this field. In particular, hepatocellular carcinoma (HCC, liver cancer) is one of the leading causes of cancer related mortalities worldwide with a constantly growing incidence. Numerous efforts have been devoted to the development of targeted cancer treatments which selectively destroy cancer cells and spare the healthy tissue.
We propose and develop an implantable, multifunctional and highly compliant device for targeted thermal treatment of cancerous tissues [1]. The device is fabricated on a 6-µm-thick polymeric foil, which seamlessly conforms to the soft liver tissue and allows for precisely controlled joule heating without on-site rigid parts. Its high mechanical compliance provides stable readings even upon severe mechanical deformations, enabling temperature accuracies of 0.1°C at bending radii of 2.5 mm, characteristic for mouse liver tissues. This heating device can treat tissue over the whole range of temperatures leading to fever, hyperthermia and ablation, while using a driving current as low as 10 mA. We demonstrate the electro-thermal and mechanical characterization of the devices and study various heat impact scenarios on normal and cancerous tissue using autochthonous murine HCC models.
Due to their high mechanical compliance, stability and thermal treatment versatility, the here developed devices can become a complement or alternative solution to radio frequency ablation (RFA) techniques for cancer treatment.

[1] G. S. Cãnón Bermudez, A. Kruv, T. Voitsekhivska, I. Hochnadel, A. Lebanov, A. Potthoff, J. Fassbender, T. Yevsa, and D. Makarov, “Implantable Highly Compliant Devices for Heating of Internal Organs: Toward Cancer Treatment”. Adv. Eng. Mater. 21, 1900407 (2019).

Keywords: flexible electronics; cancer treatment

  • Invited lecture (Conferences) (Online presentation)
    International Conference on Advances in Biological Science and Technology (ICABST2020), 28.10.2020, Sanya, China

Publ.-Id: 32011

Flexible magnetic field sensors

Makarov, D.

Extending 2D structures into 3D space has become a general trend in multiple disciplines, including electronics, photonics, plasmonics and magnetics. This approach provides means to modify conventional or to launch novel functionalities by tailoring curvature and 3D shape. We study fundamentals of 3D curved magnetic thin films [1] and explore their application potential for flexible electronics, eMobility and health. We put forth the concept of shapeable magnetoelectronics [2] for various applications ranging from automotive [3-5] through consumer electronics to virtual and augmented reality [6-9] applications. These activities impact several emerging research fields of smart skins, soft robotics and human-machine interfaces. In this talk, recent fundamental and technological advancements in this research field will be reviewed.

[1] R. Streubel, D. Makarov et al., J. Phys. D: Appl. Phys. (Review) 49, 363001 (2016).
[2] D. Makarov et al., Appl. Phys. Rev. (Review) 3, 011101 (2016).
[3] M. Melzer, D. Makarov et al., Adv. Mater. 27, 1274 (2015).
[4] I. J. Mönch, D. Makarov et al., IEEE Trans. Magn. 51, 4004004 (2015).
[5] D. Ernst, D. Makarov et al., IEEE Proceedings of the 37th International Spring Seminar on Electronics Technology (ISSE), pp. 125-129 (2014). doi:10.1109/ISSE.2014.6887577
[6] G. S. Cañón Bermúdez, D. Makarov et al., Science Advances 4, eaao2623 (2018).
[7] G. S. Cañón Bermúdez, D. Makarov et al., Nature Electronics 1, 589 (2018).
[8] P. N. Granell, D. Makarov et al., npj Flexible Electronics 3, 3 (2019).
[9] J. Ge, D. Makarov et al., Nature Communications 10, 4405 (2019).

Keywords: flexible electronics; shapeable magnetoelectronics

  • Invited lecture (Conferences) (Online presentation)
    MSM2020: 15th International Conference Mechatronic Systems and Materials, 01.07.2020, Bialystok, Poland

Publ.-Id: 32010

Mechanically compliant magnetic field sensor technologies

Makarov, D.

Extending 2D structures into 3D space has become a general trend in multiple disciplines including electronics, photonics, and magnetics. This approach provides means to enrich conventional or to launch novel functionalities by tailoring curvature and 3D shape. We study 3D curved magnetic thin films and nanowires where new fundamental effects emerge from the interplay of the geometry of an object and topology of a magnetic sub-system [1-3]. On the other hand, we explore the application potential of 3D magnetic architectures for the realization of mechanically shapeable magnetoelectronics [4] for automotive but also virtual and augmented reality appliances [5-7]. In this respect, we will present technological platforms allowing to realize not only mechanically imperceptible electronic skins, which enable perception of the geomagnetic field (e-skin compasses) [6], but also enable sensitivities down to ultra-small fields of sub-200 nT [8]. We demonstrate that e-skin compasses allow humans to orient with respect to earth’s magnetic field ubiquitously. Furthermore, biomagnetic orientation enables novel interactive devices for virtual and augmented reality applications. We showcase this by realizing touchless control of virtual units in a game engine using omnidirectional magnetosensitive skins. This concept was further extended by demonstrating a compliant magnetic microelectromechanical platform (m-MEMS), which is able to transduce both tactile (via mechanical pressure) and touchless (via magnetic field) stimulations simultaneously and discriminate them in real time [7]. Those devices are crucial for interactive electronics, human-machine interfaces, but also for the realization of smart soft robotics with highly compliant integrated feedback system as well as in medicine for physicians and surgeons. In this talk, recent fundamental and technological advancements in this novel research field will be reviewed.

[1] R. Streubel, DM et al., Magnetism in curved geometries. J. Phys. D: Appl. Phys. (Review) 49, 363001 (2016).
[2] D. Sander, DM et al., The 2017 magnetism roadmap. J. Phys. D: Appl. Phys. (Review) 50, 363001 (2017).
[3] O. M. Volkov, DM et al., Experimental observation of exchange-driven chiral effects in curvilinear magnetism. Phys. Rev. Lett. 123, 077201 (2019).
[4] D. Makarov et al., Shapeable magnetoelectronics. Appl. Phys. Rev. (Review) 3, 011101 (2016).
[5] G. S. Cañón Bermúdez, DM et al., Magnetosensitive e-skins with directional perception for augmented reality. Science Advances 4, eaao2623 (2018).
[6] G. S. Cañón Bermúdez, DM et al., Electronic-skin compasses for geomagnetic field driven artificial magnetoception and interactive electronics. Nature Electronics 1, 589 (2018).
[7] J. Ge, DM et al., A bimodal soft electronic skin for tactile and touchless interaction in real time. Nature Communications 10, 4405 (2019).
[8] P. Granell, DM et al., Highly compliant planar Hall effect sensor with sub 200 nT sensitivity. npj Flexible Electronics 3, 3 (2019).

Keywords: flexible electronics; shapeable magnetoelectronics

  • Lecture (others) (Online presentation)
    Seminar at the Karlsruhe Institute of Technology, 13.10.2020, Karlsruhe, Germany

Publ.-Id: 32009

From curvilinear magnetism to shapeable magnetoelectronics

Makarov, D.

Extending 2D structures into 3D space has become a general trend in multiple disciplines including electronics, photonics, and magnetics. This approach provides means to enrich conventional or to launch novel functionalities by tailoring curvature and 3D shape. We study 3D curved magnetic thin films and nanowires where new fundamental effects emerge from the interplay of the geometry of an object and topology of a magnetic sub-system [1-4]. On the other hand, we explore the application potential of 3D magnetic architectures for the realization of mechanically shapeable magnetoelectronics [5] for automotive but also virtual and augmented reality appliances [6-8]. In this respect, we will present technological platforms allowing to realize not only mechanically imperceptible electronic skins, which enable perception of the geomagnetic field (e-skin compasses) [7], but also enable sensitivities down to ultra-small fields of sub-200 nT [9]. We demonstrate that e-skin compasses allow humans to orient with respect to earth’s magnetic field ubiquitously. Furthermore, biomagnetic orientation enables novel interactive devices for virtual and augmented reality applications. We showcase this by realizing touchless control of virtual units in a game engine using omnidirectional magnetosensitive skins. This concept was further extended by demonstrating a compliant magnetic microelectromechanical platform (m-MEMS), which is able to transduce both tactile (via mechanical pressure) and touchless (via magnetic field) stimulations simultaneously and discriminate them in real time [8]. Those devices are crucial for interactive electronics, human-machine interfaces, but also for the realization of smart soft robotics with highly compliant integrated feedback system as well as in medicine for physicians and surgeons. In this talk, recent fundamental and technological advancements in this novel research field will be reviewed.

[1] R. Streubel, DM et al., Magnetism in curved geometries. J. Phys. D: Appl. Phys. (Review) 49, 363001 (2016).
[2] D. Sander, DM et al., The 2017 magnetism roadmap. J. Phys. D: Appl. Phys. (Review) 50, 363001 (2017).
[3] O. M. Volkov, DM et al., Experimental observation of exchange-driven chiral effects in curvilinear magnetism. Phys. Rev. Lett. 123, 077201 (2019).
[4] V. P. Kravchuk, DM et al., Multiplet of Skyrmion states on a curvilinear defect: Reconfigurable Skyrmion lattices. Phys. Rev. Lett. 120, 067201 (2018).
[5] D. Makarov et al., Shapeable magnetoelectronics. Appl. Phys. Rev. (Review) 3, 011101 (2016).
[6] G. S. Cañón Bermúdez, DM et al., Magnetosensitive e-skins with directional perception for augmented reality. Science Advances 4, eaao2623 (2018).
[7] G. S. Cañón Bermúdez, DM et al., Electronic-skin compasses for geomagnetic field driven artificial magnetoception and interactive electronics. Nature Electronics 1, 589 (2018).
[8] J. Ge, DM et al., A bimodal soft electronic skin for tactile and touchless interaction in real time. Nature Communications 10, 4405 (2019).
[9] P. Granell, DM et al., Highly compliant planar Hall effect sensor with sub 200 nT sensitivity. npj Flexible Electronics 3, 3 (2019).

Keywords: curvilinear magnetism; shapeable magnetoelectronics

  • Lecture (others)
    Seminar at the Johannes Kepler University Linz, 12.08.2020, Linz, Austria

Publ.-Id: 32008

Curvilinear Magnetism: Fundamentals and Applications

Makarov, D.

There is one aspect, which is in common to the majority of fundamentally appealing and technologically relevant novel magnetic materials, namely their non-collinear magnetic textures like spin spirals, chiral domain walls or skyrmions [1]. These textures are typically driven by the Dzyaloshinskii-Moriya interaction (DMI). Recently, curvature effects emerged as a novel mean to design chiral magnetic properties by relying on extrinsic parameters, e.g. geometry of thin films [2]. In particular, novel effects occur when the magnetization is modulated by curvature leading to new magnetization configurations and is implications on the spin dynamics due to topological constraints. Advances in this novel field solely rely on the understanding of the fundamentals behind the modifications of magnetic responses of 3D-curved magnetic thin films [3-5] and nanowires [6,7]. The lack of an inversion symmetry and the emergence of a curvature induced effective anisotropy and DMI are characteristic of curved surfaces, leading to curvature-driven magnetochiral effects and topologically induced magnetization patterning [8,9]. The application potential of 3D-shaped objects is currently being explored as mechanically reshapeable magnetic field sensorics [10] for flexible interactive electronics [11-13], magnetic field sensors [14-18], curvilinear magnetoelectrics for memory devices [19], spin-wave filters and high-speed racetrack memory devices [20]. To advance in this research field, novel theoretical methods and fabrication/characterization techniques [21-24]. The fundamentals as well as application relevant aspects of curvilinear nanomagnets will be covered in this presentation.

[1] D. Sander, DM et al., “The 2017 Magnetism Roadmap”, J. Phys. D 50, 363001 (2017).
[2] R. Streubel, DM et al., “Magnetism in curved geometries”, J. Phys. D 49, 363001 (2016).
[3] Y. Gaididei et al., “Curvature Effects in Thin Magnetic Shells”, Phys. Rev. Lett. 112, 257203 (2014).
[4] V. Kravchuk, DM et al., “Multiplet of Skyrmion States on a Curvilinear Defect: Reconfigurable Skyrmion Lattices”, Phys. Rev. Lett. 120, 067201 (2018).
[5] O. V. Pylypovskyi, DM et al., “Chiral Skyrmion and Skyrmionium States Engineered by the Gradient of Curvature”, Phys. Rev. Appl. 10, 064057 (2018).
[6] O. M. Volkov, DM et al., “Mesoscale Dzyaloshinskii-Moriya interaction: geometrical tailoring of the magnetochirality”, Scientific Reports 8, 866 (2018).
[7] O. M. Volkov, DM et al., “Experimental observation of exchange-driven chiral effects in curvilinear magnetism”, Phys. Rev. Lett. 123, 077201 (2019).
[8] O. V. Pylypovskyi, DM et al., “Coupling of Chiralities in Spin and Physical Spaces: The Möbius Ring as a Case Study”, Phys. Rev. Lett. 114, 197204 (2015).
[9] J. A. Otalora et al., “Curvature-Induced Asymmetric Spin-Wave Dispersion”, Phys. Rev. Lett. 117, 227203 (2016).
[10] D. Makarov et al., “Shapeable magnetoelectronics”, Appl. Phys. Rev. 3, 011101 (2016).
[11] S. Canon Bermudez, DM et al., “Magnetosensitive e-skins with directional perception for augmented reality”, Science Advances 4, eaao2623 (2018).
[12] S. Canon Bermudez, DM et al., “Electronic-skin compasses for geomagnetic field driven artificial magnetoreception and interactive electronics”, Nature Electronics 1, 589 (2018).
[13] J. Ge, DM et al., “A bimodal soft electronic skin for tactile and touchless interaction in real time”, Nature Comm. 10, 4405 (2019).
[14] D. Karnaushenko, DM et al., “Self-assemled on-chip integrated giant magneto-impedance sensorics”, Adv. Mater. 27, 6582 (2015).
[15] G. Lin, DM et al., “A highly flexible and compact magnetoresistive analytic device”, Lab Chip 14, 4050 (2014).
[16] N. Münzenrieder, DM et al., “Entirely flexible on-site conditioned magnetic sensorics”, Adv. Electron. Mater. 2, 1600188 (2016).
[17] C. Becker et al., “Self-assembly of highly sensitive 3D magnetic field vector angular encoders”, Science Advances 5, eaay7459 (2019).
[18] M. Kondo et al., “Imperceptible magnetic sensor matrix system integrated with organic driver and amplifier circuits”, Science Advances 6, eaay6094 (2020)
[19] O. M. Volkov, DM et al., “Concept of artificial magnetoelectric materials via geometrically controlling curvilinear helimagnets”, J. Phys. D: Appl. Phys. 52, 345001 (2019).
[20] M. Yan et al., “Beating the Walker Limit with Massless Domain Walls in Cylindrical Nanowires”, Phys. Rev. Lett. 104, 057201 (2010).
[21] R. Streubel, DM et al., “Retrieving spin textures on curved magnetic thin films with full-field soft X-ray microscopies”, Nature Comm. 6, 7612 (2015).
[22] T. Kosub, DM et al., “Purely antiferromagnetic magnetoelectric random access memory”, Nature Comm. 8, 13985 (2017).
[23] M. Huth et al., “Focused electron beam induced deposition meets materials science”, Microelectron. Engineering 185-186, 9 (2018).
[24] M. Nord, DM et al., “Strain Anisotropy and Magnetic Domains in Embedded Nanomagnets”, Small 15, 1904738 (2019).

Keywords: curvilinear magnetism; shapeable magnetoelectronics

  • Invited lecture (Conferences) (Online presentation)
    The 2020 Magnetism and Magnetic Materials Conference, 04.11.2020, Palm Beach, USA

Publ.-Id: 32007

Overview of recent advances in flexible highly compliant magnetoelectronics

Makarov, D.

Recent rapid advances and eagerness of portable consumer electronics stimulate the development of functional elements towards being lightweight, flexible, and wearable. Next generation flexible appliances aim to become fully autonomous and will require ultra-thin and flexible navigation modules, body tracking and relative position monitoring systems. Key building blocks of navigation and position tracking devices are magnetic field sensors. In this presentation, recent developments in the emerging field of flexible magnetic field sensorics and its applications in printed electronics, eMobility, virtual and augmented reality settings will be reviewed.

Keywords: flexible electronics; shapeable magnetoelectronics

  • Invited lecture (Conferences) (Online presentation)
    2020 IEEE Electron Devices Technology and Manufacturing Conference (EDTM), 06.04.2020, Penang, Malaysia

Publ.-Id: 32006

Magnetosensitive e-skins for interactive devices

Canon Bermudez, G. S.; Makarov, D.

The growth of electronics and computer science in the last years has brought humans and machines closer than ever before. As this trend continues, new kinds of human-machine interactions are needed in a hyperconnected world. A key element for these interactions is flexible electronics, which attempts to seamlessly link living and artificial entities using electronic skins (e-skins). E-skins merge the functionality of standard electronics with the soft, stretchable, and biocompatible qualities of human skin or tissue. So far, the focus has been to reproduce the traditional functions associated with human skin, such as, temperature, pressure, and chemical detection. New developments have also introduced nonstandard sensing capabilities like magnetic field detection, to give birth to the field of magnetosensitive e-skins. Adding a supplementary information channel—an electronic sixth sense—could trigger new applications in the fields of cognitive psychology and human-machine interactions. Here, we review recent advances in magnetosensitive e-skins, which utilize the full interaction potential of the magnetic field vector to detect position, orientation, and mechanical stimuli. These magnetosensitive e-skins open exciting possibilities for touchless and gestural control in virtual and augmented reality, sensory substitution, and multimodal sensing; beyond the limitations of optics-based systems.

Keywords: flexible electronics; interactive electronics; magnetosensitive smart skins

Publ.-Id: 32004

Local and nonlocal spin Seebeck effect in lateral Pt-Cr2O3-Pt devices at low temperatures

Muduli, P.; Schlitz, R.; Kosub, T.; Hübner, R.; Erbe, A.; Makarov, D.; Goennenwein, S. T. B.

We have studied thermally driven magnon spin transport (spin Seebeck e_ect, SSE) in heterostructures of antiferromagnetic Cr2O3 and Pt at low temperatures. Monitoring the amplitude of the local and nonlocal SSE signals as a function of temperature, we found that both decrease with increasing temperature and disappear above 100 K and 20 K, respectively. Additionally, both SSE signals show a tendency to saturate at low temperatures. The nonlocal SSE signal decays exponentially for intermediate injector-detector separation, consistent with magnon spin current transport in the relaxation regime. We estimate the magnon relaxation length of our Cr2O3 films to be around 500 nm at 3 K. This short magnon relaxation length along with the strong temperature dependence of the SSE signal indicates that temperature-dependent inelastic magnon scattering processes play an important role in the intermediate range magnon transport. Our observation is relevant to low-dissipation antiferromagnetic magnon memory and logic devices involving thermal magnon generation and transport.

Keywords: spin Seebeck effect; antiferromagnetic spintronics

Publ.-Id: 32003

Coding and decoding stray magnetic fields for multiplexing kinetic bioassay platform

Liu, Y.; Lin, G.; Chen, Y.; Mönch, J. I.; Makarov, D.; Walsh, B. J.; Jin, D.

Polymer microspheres can be fluorescently-coded for multiplexing molecular analysis, but their usage has been limited by the fluorescent quenching and bleaching and crowded spectral domain with issues of cross-talks and background interference. Each bioassay step of mixing and separation of analytes and reagents require off-line particle handling procedures. Here, we report stray magnetic fields can code and decode a collection of hierarchically-assembled beads. By the microfluidic assembling of mesoscopic superparamagnetic cores, diverse and non-volatile stray magnetic field response can be built in the series of microscopic spheres, dumbbells, pears, chains and triangles. Remarkably, the set of stray magnetic field fingerprints are readily discerned by a compact giant magnetoresistance sensor for parallelised screening of multiple distinctive pathogenic DNAs. This opens up the magneto-multiplexing opportunity and could enable streamlined assays to incorporate magneto-mixing, washing, enrichment and separation of analytes.
This strategy therefore suggests a potential point-of-care testing solution for efficient kinetic assay.

Keywords: magnetic field sensor; microfluidics; bioassays

Publ.-Id: 31999

L10 Ordered Thin Films for Spintronic and Permanent Magnet Applications

Hafarov, A.; Prokopenko, O.; Sidorenko, S.; Makarov, D.; Vladymyrskyi, I.

Materials with strong perpendicular magnetic anisotropy (PMA) are fundamentally appealing and also relevant for numerous applications especially reconsidering their practical relevance for the enhancement of the energy product for thin film based permanent magnets and realization of energy efficient and miniaturized spintronic devices. In contrast to materials exhibiting PMA due to surface anisotropy, these applications would benefit from thin films where PMA stems from a strong uniaxial magnetocrystalline anisotropy (Ku). In this regard, magnetic thin films with chemically ordered L10 structure, representing alternation of A and B atomic planes along the c direction, are considered as most promising due to the high Ku values and finely tunable magnetic properties. Typical representatives of L10 structures are ordered binary phases, e.g. FePt, FePd, MnAl, MnGa, or NiFe, etc. phases. In the case when the c axes of the L10 structure is normal to the film plane, remarkably strong PMA could can be achieved. Another important property of L10 structures is their thermodynamic stability providing resistance of corresponding devices against thermal processing. Here, we will review the application prospects of L10 ordered magnetic thin films for spintronic and permanent magnet technologies.

Keywords: L10 alloys; perpendicular magnetic anisotropy

  • Book chapter
    A. Kaidatzis, S. Sidorenko, I. Vladymyrskyi, D. Niarchos: Modern Magnetic and Spintronic Materials. NATO Science for Peace and Security Series B: Physics and Biophysics, Dordrecht: Springer, 2020, 978-94-024-2033-3
    DOI: 10.1007/978-94-024-2034-0_4

Publ.-Id: 31998

Influence of a low-Z thin substrate on a microwire hard x-ray source driven by a picosecond laser pulse for point-projection x-ray radiography

Meng-Ting, L.; Guang-Yue, H.; Huang, L.; Jian, Z.

In the point-projection hard x-ray radiography of dense matter, for example, an inertial confinement fusion implosion capsule at stagnation time, a picosecond laser driven gold microwire is used to produce a short pulse point, bremsstrahlung hard x-ray source. The microwire was held by a low-Z CH thin substrate commonly used to promote experimental performance. We explored the influence of the low-Z thin substrate on the microwire bremsstrahlung hard x-ray source via particle-in-cell and Monte Carlo simulations. It was shown that both of the microwires, with or without the low-Z thin substrate, could emit more intense hard x-ray radiation than the radiator buried in the equal-density substrate, which benefited from efficient electron recirculation. The freestanding microwire exhibited further enhanced electron recirculation compared to that with the low-Z thin substrate, while the increased hot electrons were only present for the energetic electrons of >1 MeV. Thus, the freestanding microwire could produce significantly more intense MeV gamma x-ray emission with respect to that with the substrate, but an ignorable increment was exhibited at the softer x-ray emission of 10–200 keV. These results provided valuable insights into the design of backlighter targets in point-projection x-ray radiography, such as a freestanding microwire being preferred in MeV gamma-ray radiography, while the microwire with the CH thin substrate could be used in the 10–200 keV hard x-ray Compton radiography of an implosion capsule.


  • Secondary publication expected from 24.12.2021

Publ.-Id: 31997

PIConGPU Performance and Scaling Results on Summit

Widera, R.; Bastrakov, S.; Debus, A.; Garten, M.; Pausch, R.; Steiniger, K.; Bussmann, M.; Hübl, A.

This talk present recent performance and scaling results of Particle-in-Cell code PIConGPU on the Summit supercomputer. PIConGPU is an open-source plasma simulation code for the Exascale era. It implements a wide range of core Particle-in-Cell numerical schemes and extensions, in-situ diagnostics, and high-performance I/O. Using single-source programming approach powered by alpaka library, PIConGPU runs on a variety of modern hardware, including both CPUs and GPUs. We demonstrate that it scales from a single workstation up to the full Summit supercomputer.

Keywords: Large-scale computing; Scalability; GPGPU; Plasma simulation; Particle-in-Cell

  • Lecture (Conference) (Online presentation)
    Supercomputing Frontiers Europe 2020, 23.-25.03.2020, Warszawa, Polska

Publ.-Id: 31996

Pedal to the Metal: Designing a Scalable Particle-in-Cell Code PIConGPU

Bastrakov, S.; Widera, R.; Debus, A.; Garten, M.; Pausch, R.; Steiniger, K.; Hübl, A.; Bussmann, M.

PIConGPU is an open-source Particle-in-Cell simulation code for the Exascale era. It implements a wide range of core Particle-in-Cell numerical schemes and extensions, in-situ diagnostics, and high-performance I/O. With a single source code base, PIConGPU runs on a variety of modern hardware, including both CPUs and GPUs, and scales from a single workstation up to the largest supercomputers. Following up the two recent talks concerning physical and numerical features of PIConGPU, this talk will focus on the computer science and software design aspects of the code and the underlying software stack. The talk concerns PIConGPU core data structures, typical patterns of parallel processing, and software design approach to enable efficient and scalable single-source implementation. It also presents performance and scaling results on the Summit supercomputer.

Keywords: Particle-in-Cell; plasma simulation; scalable computing; single-source programming; PIConGPU; alpaka

  • Lecture (others)
    CASUS Seminar, 01.10.2020, Görlitz, Deutschland

Publ.-Id: 31995

alpaka Parallel Programming - Online Tutorial

Stephan, J.; Bastrakov, S.; Widera, R.; Ehrig, S.; Bussmann, M.

Alpaka (Abstraction Library for Parallel Kernel Acceleration) provides a library and tools for programming compute accelerators on a device agnostic level. This online tutorial will give an introduction to Alpaka combined with online exercises.

Keywords: alpaka; parallel programming; accelerators; C++

  • Open Access Logo Lecture (others) (Online presentation)
    alpaka Parallel Programming - Online Tutorial, 29.06.-03.07.2020, Genf, Schweiz


Publ.-Id: 31993

Lessons Learned Developing Frameworks with SYCL

Stephan, J.

alpaka is a header-only C++ library for developing portable high-performance programs. Much like SYCL, it aims to abstract away the differences between accelerator types and vendors. In 2019 an experimental SYCL backend was developed in order to target FPGAs. In my talk I will focus on the challenges I faced during the SYCL backend development as well as conceptual differences between SYCL and other heterogeneous programming platforms.

Keywords: SYCL; alpaka; parallel programming; C++

  • Open Access Logo Lecture (others) (Online presentation)
    SYCL Summer Sessions 2020, 31.08.-04.09.2020, London, United Kingdom

Publ.-Id: 31992

Synthesis and biological evaluation of a novel 18F-labeled radiotracer for PET imaging of the adenosine A2A receptor

Lai, T. H.; Toussaint, M.; Teodoro, R.; Dukic-Stefanovic, S.; Kranz, M.; Deuther-Conrad, W.; Moldovan, R.-P.; Brust, P.

The adenosine A2A receptor (A2AR) has emerged as a potential non-dopaminergic target for the treatment of Parkinson’s disease and thus, the non-invasive imaging with positron emission tomography (PET) is of utmost importance to monitor the receptor expression and occupancy during an A2AR-tailored therapy. Aiming at the development of a PET radiotracer, we herein report the design of a series of novel fluorinated analogs based on the structure of the A2AR antagonist tozadenant, and the preclinical evaluation of [18F]TOZ1. Autoradiography proved A2AR-specific in vitro binding of [18F]TOZ1 to striatum of mouse and pig brain. Investigations of the metabolic stability in mice revealed parent fractions of more than 76% and 92% of total activity in plasma and brain samples, respectively. Dynamic PET/magnetic resonance imaging (MRI) studies in mice revealed a brain uptake but no A2AR-specific in vivo binding.

Keywords: adenosine A2A receptor; fluorine-18; positron emission tomography; tozadenant

Publ.-Id: 31991

Development of 18F-labeled radiotracers for PET imaging of the adenosine A2A receptor: Synthesis, radiolabeling and preliminary biological evaluation

Lai, T. H.; Schröder, S.; Toussaint, M.; Dukic-Stefanovic, S.; Kranz, M.; Ludwig, F.-A.; Fischer, S.; Steinbach, J.; Deuther-Conrad, W.; Brust, P.; Moldovan, R.-P.

The adenosine A2A receptor (A2AR) represents a potential therapeutic target for neurodegenerative diseases. Aiming at the development of a positron emission tomography (PET) radiotracer to monitor changes of receptor density and/or occupancy during the A2AR-tailored therapy, we designed a library of fluorinated analogs based on a recently published lead compound. Among those, the highly affine 4-fluorobenzyl derivate (PPY1; Ki(hA2AR) = 5.3 nM) and the 2-fluorobenzyl derivate (PPY2; Ki(hA2AR) = 2.1 nM) were chosen for 18F-labeling via an alcohol-enhanced copper-mediated procedure starting from the corresponding boronic acid pinacol ester precursors. Investigations of the metabolic stability of [18F]PPY1 and [18F]PPY2 in CD-1 mice by radio-HPLC analysis revealed parent fractions of more than 76% of total activity in the brain. Specific binding of [18F]PPY2 on mice brain slices was demonstrated by in vitro autoradiography. In vivo PET/magnetic resonance imaging (MRI) studies in CD-1 mice revealed a reasonable high initial brain uptake for both radiotracers, followed by a fast clearance.

Keywords: adenosine A2A receptor; fluorine-18; positron emission tomography

Publ.-Id: 31990

Improved in vivo PET imaging of the adenosine A2A receptor in the brain using [18F]FLUDA, a deuterated radiotracer with high metabolic stability

Lai, T. H.; Toussaint, M.; Teodoro, R.; Dukic-Stefanovic, S.; Gündel, D.; Ludwig, F.-A.; Wenzel, B.; Schröder, S.; Sattler, B.; Moldovan, R.-P.; Falkenburger, B. H.; Sabri, O.; Deuther-Conrad, W.; Brust, P.

Purpose: The adenosine A2A receptor has emerged as a therapeutic target for multiple diseases, and thus the non-invasive imaging of the expression or occupancy of the A2A receptor has potential to contribute to diagnosis and drug development. We aimed at the development of a metabolically stable A2A receptor radiotracer and report herein the preclinical evaluation of [18F]FLUDA, a deuterated isotopologue of [18F]FESCH.
Methods: [18F]FLUDA was synthesized by a two-step one-pot approach and evaluated in vitro by autoradiographic studies as well as in vivo by metabolism and dynamic PET/MRI studies in mice and piglets under baseline and blocking conditions. A single-dose toxicity study was performed in rats.
Results: [18F]FLUDA was obtained with a radiochemical yield of 19% and molar activities of 72 180 GBq/µmol. Autoradiography proved A2A receptor-specific accumulation of [18F]FLUDA in the striatum of mouse and pig brain. In vivo evaluation in mice revealed improved stability of [18F]FLUDA compared to [18F]FESCH, resulting in the absence of brain-penetrant radiometabolites. Furthermore, the radiometabolites detected in piglets are expected to have a low tendency for brain penetration. PET/MRI studies confirmed high specific binding of [18F]FLUDA towards striatal A2A receptor with a maximum specific-to-non-specific binding ratio in mice of 8.3. The toxicity study revealed no adverse effects of FLUDA up to 30 µg/kg, ~ 4000-fold the dose applied in human PET studies using [18F]FLUDA.
Conclusions: The new radiotracer [18F]FLUDA is suitable to detect the availability of the A2A receptor in the brain with high target specificity. It is regarded ready for human application.

Keywords: adenosine receptors; A2A receptor; neurodegeneration; positron emission tomography; fluorine-18; FESCH

Publ.-Id: 31989

Mirror twin boundaries in MoSe₂ monolayers as one dimensional nanotemplates for selective water adsorption

Li, J.; Joseph, T.; Ghorbani Asl, M.; Kolekar, S.; Krasheninnikov, A.; Batzill, M.

Water adsorption on transition metal dichalcogenides and other 2D materials is generally governed by weak van der Waals interactions. This results in a hydrophobic character of the basal planes, and defects may play a significant role in water adsorption and water cluster nucleation. However, there is a lack of detailed experimental investigations on water adsorption on defective 2D materials. Here, by combining low-temperature scanning tunneling microscopy (STM) experiments and density functional theory (DFT) calculations, we study in that context the well-defined mirror twin boundary (MTB) networks separating mirror-grains in 2D MoSe2. These MTBs are dangling bond-free extended crystal modifications with metallic electronic states embedded in the 2D semiconducting matrix of MoSe2. Our DFT calculations indicate that molecular water also interacts similarly weak with these MTBs as with the defect-free basal plane of MoSe2. However, in low temperature STM experiments, nanoscopic water structures are observed that selectively decorate the MTB network. This localized adsorption of water is facilitated by functionalization of the MTBs by hydroxyls formed by dissociated water. Hydroxyls may form by dissociating of water at undercoordinated defects or adsorbing of radicals from the gas phase in the UHV chamber. Our DFT analysis indicates that the metallic MTBs adsorb these radicals much stronger than on the basal plane due to charge transfer from the metallic states into the molecular orbitals of the OH groups. Once the MTBs are functionalized with hydroxyls, molecular water can attach to them, forming water channels along the MTBs. This study demonstrates the role metallic defect states play in the adsorption of water even in the absence of unsaturated bonds that have been so far considered to be crucial for adsorption of hydroxyls or water.

Keywords: van der Waals materials; water adsorption; defect engineering; hydroxylation; metallic defect states; molecular scale adsorption template


  • Secondary publication expected from 18.12.2021

Publ.-Id: 31988

Microwave-assisted spectroscopy of vacancy-related spin centers in hexagonal SiC

Shang, Z.; Berencen, Y.; Hollenbach, M.; Zhou, S.; Kraus, H.; Ohshima, T.; Astakhov, G.

Optically active spin centers associated with atomic-scale defects in SiC are promising candidates for quantum technology owing to their outstanding optical and spin properties. Photoluminescence as a mature optical investigating tool is widely used for the identification of spin defects and exploration of their properties. However, in the case of spectrally overlapped contributions from different types of defects, the traditional photoluminescence measurement cannot be used to separately obtain their optical and vibrational properties, such as the local phonon energy and the Debye-Waller factor. Here, we apply spin resonant microwave-assisted spectroscopy to investigate the optical and vibrational properties of silicon vacancies in 6H-SiC and divacancies in 4H- and 6H-SiC. We isolate contributions from each type of defect, investigate their local vibrational modes and obtain the Debye-Waller factor. This work proves that microwave-assisted spectroscopy is a suitable tool for the investigation of optical and vibrational properties of a large variety of spin defects.

Keywords: silicon carbide; spin centers; photoluminescence; local phonon energy; Debye-Waller factor; microwave-assisted spectroscopy


Publ.-Id: 31987

Geological Remote Sensing

Booysen, R.; Gloaguen, R.; Lorenz, S.; Zimmermann, R.; Nex, P.

Remote sensing is commonly defined either as the data acquisition about an object or a process at a distance or the scanning of the Earth by satellite or high-flying aircraft. In the present article, we will consider all the relevant sensors and techniques that allow the imaging, measurement and monitoring of the Earth’s surface from a distance greater than 10 m.

Publ.-Id: 31986

Crystallization of optically thick films of CoxFe80−xB20: Evolution of optical, magneto-optical, and structural properties

Sharma, A.; Hoffmann, M. A.; Matthes, P.; Hellwig, O.; Kowol, C.; Schulz, S. E.; Zahn, D. R. T.; Salvan, G.

CoFeB alloys are highly relevant materials for spintronic applications. In this work, the crystallization of CoFeB alloys triggered by thermal annealing was investigated by x-ray diffraction techniques and scanningelectron microscopy, as well as spectroscopic ellipsometry and magneto-optical Kerr effect spectroscopy forannealing temperatures ranging from 300 to 600◦C. The transformation of∼100-nm-thick CoxFe(80−x)B20filmsfrom amorphous to polycrystalline was revealed by the sharpening of spectral features observed in optical andmagneto-optical dielectric functions spectra. The influence of B on the dielectric function was assessed bothexperimentally and by optical modeling. By analyzing the Drude component of the optical dielectric function,a consistent trend between the charge-carrier scattering time/resistivity and the annealing temperature wasobserved, in agreement with the electrical investigations by means of the four-point-probe method.

Publ.-Id: 31984

Manipulating the Energy Balance of Perpendicular-Anisotropy Synthetic Antiferromagnets by He+-Ion Irradiation

Koch, L.; Samad, F.; Lenz, M.; Hellwig, O.

He+-ion irradiation enables controlled postdeposition modification of layered magnetic thin-film sys-tems. The degree of modification and its depth profile can be tuned by the irradiation dose and energy.Here, we use magnetometry and magnetic force microscopy to explore the impact of gentle He+-ion irra-diation on synthetic antiferromagnets, consisting of ferromagnetic Co/Pt multilayers with perpendicularmagnetic anisotropy, which are antiferromagnetically (AF) coupled via Ru interlayers. This system showsa rich variety of magnetic domain patterns due to the strong competition between different magnetic ener-gies. We show that AF interlayer exchange and perpendicular interface anisotropy energy are graduallyreduced by the ion irradiation while the demagnetization energy is mainly preserved, which thus results inmultiple successive magnetic-phase transitions.

Publ.-Id: 31983

Algorithms for the Exploration of an Automated STM DAQ Hardware Development Process based on Continuous Integration for the Mu2e Experiment

Ufer, R.; Voigt, M.; Müller, S.; Knodel, O.

This project contains the source code for the evaluation of an automated process which converts algorithms written in C/C++ to Data Acquisition (DAQ) hardware cores on Field Programmable Gate Arrays (FPGAs) using Continuous Integration (CI). The cores are building blocks of the DAQ for the Stopping-Target-Monitor of the MU2E experiment currently in construction at FERMILAB (USA). The MU2E experiment will search for Charged Lepton Flavor Violation (CLFV) looking for the direct decay of a muon into an electron.

Keywords: Data Management; DAQ; FPGA; Mu2e

  • Software in the HZDR data repository RODARE
    Publication date: 2021-01-07
    DOI: 10.14278/rodare.720
    License: BSD-3-Clause


Publ.-Id: 31982

Edge localization of spin waves in antidot multilayers with perpendicular magnetic anisotropy

Pan, S.; Mondal, S.; Zelent, M.; Szwierz, R.; Pal, S.; Hellwig, O.; Krawczyk, M.; Barman, A.

We study the spin-wave dynamics in nanoscale antidot lattices based on Co/Pd multilayers with perpendicularmagnetic anisotropy. Using time-resolved magneto-optical Kerr effect measurements we demonstrate that thevariation of the antidot shape introduces significant change in the spin-wave spectra, especially in the lowerfrequency range. By employing micromagnetic simulations we show that additional peaks observed in themeasured spectra are related to narrow shell regions around the antidots, where in-plane domain structures areformed. This is because the magnetic anisotropy in these regions is reduced due to the Ga(+)ion irradiation duringthe focused ion beam milling process of the antidot fabrication. The results point at possibilities for exploitationof localized spin waves in out-of-plane magnetized thin films, which are easily tunable and suitable for magnonicapplications.

Publ.-Id: 31981

Numerical simulation of liquid metal batteries

Weber, N.

Der Vortrag gibt einen Überblick über die Simulation von Flüssigmetallbatterien.

  • Invited lecture (Conferences) (Online presentation)
    Seminarreihe “Liquid metal technologies”, 15.01.2021, Morelia, Mexiko

Publ.-Id: 31980

UAS-based hyperspectral and magnetic mineral exploration targeting Ni-PGE mineralization on Northern Disko Island, West Greenland

Jackisch, R.; Zimmermann, R.; Heincke, B.; Karinen, A.; Salmirinne, H.; Pirtijärvi, M.; Lorenz, S.; Madriz Diaz, Y. C.; Gloaguen, R.

Geologic mapping in arctic regions faces demanding challenges, from accessibility to weather, light and infrastructure conditions. Field expeditions need to cover substantial area, and mostly are supported by satellite and airborne data. While named methods offer large-scaled insights, they often lack the required resolution for precise ground investigations. The rise of unmanned aerial systems (UAS) as new state-of-the-art platform in geoscience provides the means needed to close that scale gap.

Fieldwork within the frame of the EIT project MULSEDRO focused on the Paleocene flood basalt province of Disko Island (West Greenland). On the example of the Qullissat area, we demonstrate how UAS can bring new insights into strategies for magmatic Ni-PGE exploration in the area. Mineralization is associated to basalt sills of the Asuk Member, emplaced locally in coal-bearing cretaceous sandstones. We conducted photogrammetric outcrop modelling, interpretation of orthoimagery, multi- and hyperspectral based lithological classification and analysis of magnetic data. While magnetics give the location, orientation and subsurface extension of the basaltic sills, spectral imaging, in particular with focus on the iron absorption feature, reveals mineral proxies due to sulphide weathering. A total of 216 line-km for magnetics and 18.5 km2 of multi- and hyperspectral data was covered.

First results show that integration of drone-borne spectroscopic and magnetic data highlights potential local mineralization. Based on our results, possible indications for mineralization are linear features in the first vertical derivative of the magnetic data and specific iron absorptions in the spectral data. Resulting maps are validated using handheld spectroscopy, ground magnetics, susceptibility measurements, combined with geochemistry and mineralogy of rock samples examined in the laboratory. Conclusively, the study solidifies UAS as highly valuable tool for exploration.

Keywords: unmanned aerial vehicles; magnetics; multispectral; hyperspectral; Greenland


Publ.-Id: 31977

Science Blog: Game of drones – unmanned aerial vehicles in mineral exploration and geological mapping

Salmirinne, H.; Heincke, B.; Jackisch, R.; Saartenoja, A.

Over the last ten years, unmanned aerial vehicles (UAV), commonly called drones, and related systems have rapidly developed. Everyman’s drones are available on store shelves to take photos and videos of holidays, one’s own house and garden, and for many other private reasons. With the general advances in robotics and digitalization, drones have also been increasingly utilized for various commercial applications. This trend can additionally be seen in geosciences. A key question arising for many geoscience applications is whether drones could be used as platforms to carry out more demanding surveys with remote sensing and geophysical sensors that have traditionally been mounted on aircraft or have been carried by workers on the ground. The answer is yes, drones can be used, although the integration of such sensors on drones is not straightforward. The methods themselves are typically well developed, but drones as an aspiring platform pose challenges for operating sensors and performing measurement procedures in proper ways. In particular, the need for small and lightweight sensors with a low power consumption for UAV platforms plays an important role, because they allow flexible low-cost measurements to be performed without a long preparation phase. Another aspect is that legislation, which varies from country to country, affects drone operations. Therefore, it is often difficult in practice for drone-operating companies to provide international services, and it is generally easier to obtain permission for small drones flying at low altitude only. To find a remedy for this, a common EU-wide regulation is currently in preparation. EU drone regulation (EU) 2019/947 defines the rules and procedures for different types of drone operations and is intended to be applied according to the transition period of the regulation on 31 December 2020.

In recent years, many groups all over the world – both in academia and industry – have worked on the integration of various sensor types on drones that are relevant for geological mapping and mineral exploration. Drone-borne survey systems are considered to be especially appropriate for small to medium-sized surveys that are smaller than those carried out with traditional aircraft, but larger than ground-based surveys. The goal of many companies is to offer drone-based services for this market niche.

Keywords: unmanned aerial vehicles; mineral mapping; hyperspectral imaging; magnetics

Publ.-Id: 31976

Component Decomposition-Based Hyperspectral Resolution Enhancement for Mineral Mapping

Duan, P.; Lai, J.; Ghamisi, P.; Kang, X.; Jackisch, R.; Kang, J.; Gloaguen, R.

Combining both spectral and spatial information with enhanced resolution provides not only elaborated qualitative information on surfacing mineralogy but also mineral interactions of abundance, mixture, and structure. This enhancement in the resolutions helps geomineralogic features such as small intrusions and mineralization become detectable. In this paper, we investigate the potential of the resolution enhancement of hyperspectral images (HSIs) with the guidance of RGB images for mineral mapping. In more detail, a novel resolution enhancement method is proposed based on component decomposition. Inspired by the principle of the intrinsic image decomposition (IID) model, the HSI is viewed as the combination of a reflectance component and an illumination component. Based on this idea, the proposed method is comprised of several steps. First, the RGB image is transformed into the luminance component, blue-difference and red-difference chroma components (YCbCr), and the luminance channel is considered as the illumination component of the HSI with an ideal high spatial resolution. Then, the reflectance component of the ideal HSI is estimated with the downsampled HSI image and the downsampled luminance channel. Finally, the HSI with high resolution can be reconstructed by utilizing the obtained illumination and the reflectance components. Experimental results verify that the fused results can successfully achieve mineral mapping, producing better results qualitatively and quantitatively over single sensor data.

Keywords: hyperspectral image; mineral mapping; resolution enhancement; intrinsic image decomposition


Publ.-Id: 31975

Thermal treatment of materials on short time scales

Rebohle, L.; Prucnal, S.; Cherkouk, C.; Berencen, Y.; Skorupa, I.

Important technological developments of our time such as the energy transition or digitalization require new materials and more efficient manufacturing processes. The processes of ultra-short time annealing such as flash lamp annealing (FLA) and laser annealing have the potential to make an important contribution. During such processes high temperatures are applied for very short times (nano- to milliseconds), so that only near surface regions of the material are exposed to the maximum temperature. Compared to conventional thermal treatments, ultra-short time annealing enables energy and process time savings, the use of temperature-sensitive substrates, and the synthesis of new materials in thermal non-equilibrium.
The talk is divided into two parts. After an introduction, the first part discusses the main features of FLA in comparison with other short time annealing techniques, namely rapid thermal annealing and laser annealing. Special focus is set on temperature and its determination, as this is a complex and challenging issue on short time scales. The second part deals with various examples of applying FLA to materials, ranging from semiconductor applications over printed electronics to energy materials for batteries.

Keywords: ultra-short time annealing; flash lamp annealing; ion implantation; energy materials; lithium ion battery

  • Lecture (others)
    Kooperationstreffen Universität Lublin, 08.10.2020, Lublin, Polen

Publ.-Id: 31974

BlitzLab – ein Helmholtz Innovation Lab

Rebohle, L.; Cherkouk, C.; Folgner, C.; Prucnal, S.; Schumann, T.; Krüger, S.

Der Vortrag stellt das Helmholtz Innovation Lab blitzlab vor und geht danach auf die Blitzlampenausheilung als ein innovatives Verfahren zur thermischen Behandlung von Materialien und Werkstoffen ein.

Keywords: Helmholtz Innovation Lab blitzlab; flash lamp annealing; ultra-short annealing

  • Lecture (others)
    Arbeitstreffen am IMWS, 30.09.2020, Halle, Deutschland

Publ.-Id: 31973

Functionalized silicon substrates with stripe-patterned surface-near electrostatic forces for the self-organized, stable immobilization of biomolecules

Blaschke, D.; Pahlow, S.; Fremberg, T.; Weber, K.; Müller, A. D.; Kurz, S.; Spohn, J.; Dhandapani, V.; Rebohle, L.; Skorupa, I.; Schmidt, H.

Silicon substrates with stripe-patterned surface-near electrostatic forces (SNEF) were prepared by local implantation of boron ions into n-type silicon wafers and of phosphorus ions into p-type silicon wafers in a stripe pattern of 12 µm periodicity. The dependence of SNEF on the concentration of implanted ions, post-annealing conditions, and generation of charge carriers under illumination was investigated by measuring the 1st and 2nd harmonics of the SNEF in the dark and under illumination using Kelvin probe force microscopy. The self-organized immobilization of biomolecules on silicon regions with positive charges occupying the interface states between the silicon and the native SiO2 has been demonstrated for the negatively charged single stranded deoxyribonucleic acid (DNA) and bovine serum albumin (BSA) proteins.

Keywords: surface-near electrostatic forces; Kelvin probe force microscopy; Si pn-junction; self-organized molecular immobilization; deoxyribonucleic acid; bovine serum albumin


  • Secondary publication expected from 15.04.2022

Publ.-Id: 31972

Data for: The structure in warm dense carbon

Vorberger, J.; Plageman, K.-U.; Redmer, R.

The structure of the fluid carbon phase in the pressure region of the graphite, diamond, and BC8 solid phases is investigated. We find increasing coordination numbers with an increase in density. From zero to 30 GPa, the liquid shows a decrease of packing efficiency with increasing temperature. However, for higher pressures, the coordination number increases with increasing temperature. Up to 1.5 eV and independent of the pressure up to 1500 GPa, a double-peak structure in the ion structure factors exists, indicating persisting covalent bonds. Over the whole pressure range from zero to 3000 GPa, the fluid structure and properties are strongly determined by such covalent bonds.

Related publications

  • Reseach data in the HZDR data repository RODARE
    Publication date: 2021-01-06
    DOI: 10.14278/rodare.716
    License: CC-BY-4.0


Publ.-Id: 31971

Nanosensor-Based Real-Time Monitoring of Stress Biomarkers in Human Saliva Using a Portable Measurement System

Klinghammer, S.; Voitsekhivska, T.; Licciardello, N.; Kim, K.; Baek, C.-K.; Cho, H.; Wolter, K.-J.; Kirschbaum, C.; Baraban, Larysa; Cuniberti, G.

Small molecules with no or little charge are considered to have minimal impact on signals measured by field effect transistor (FET) sensors. This fact typically excludes steroids from the family of analytes, detected by FETs. We present a portable multiplexed platform based on an array of nanowire sensors for label-free monitoring of daytime levels of the stress hormone cortisol in saliva samples, obtained from multiple donors. To achieve an effective quantification of the cortisol with FETs, we rely on the specific DNA aptamer sequences as receptors, bringing the complex “target-receptor” closer to the nanowire surface. Upon binding, cortisol induces conformational changes of negatively charged aptamers, wrapping it into a close proximity to the silicon nanowires, to efficiently modulate their surface potential. Thus, the sensors allow for a real-time assessment of the steroid biomarkers at low nanomolar concentration. The measurement platform is designed in a building-block concept, consisting of a modular measuring unit and a customizable biochip board, and operates using a complementary metal-oxide-semiconductor-integrated multiplexer. The platform is capable of continuous and simultaneous measurement of samples from multiple patients. Cortisol levels detected with the presented platform agreed well with the results obtained with a commercial high-sensitivity immunoassay


  • Secondary publication expected from 03.12.2021

Publ.-Id: 31970

Laser-driven ion accelerators for applications in radiobiology

Metzkes-Ng, J.

Laser-driven plasmas – generated in the interaction of a focused high power laser pulse with a solid surface – can sustain electrical field strengths of ~TV/m, allowing for compact and efficient particle acceleration of proton pulses with up to 100 MeV kinetic energies on ~µm spatial scales. The particle pulses feature a picosecond pulse duration at the source and extremely high pulse currents and dose, making them an ideal tool for laboratory-scale high dose-rate radiobiology research.
At the Draco Petawatt laser source, we have established and now successfully operate a source-to-sample just meter-scale setup for high dose-rate in vivo radiobiological studies based on a laser-driven proton source and a compact, versatile pulsed high-field magnetic beamline.
The setup development and preliminary experimental results will be presented, also intending to foster collaborations within HZDR for a wide range of high dose-rate applications.

Keywords: laser-driven proton acceleration; high dose-rate radiobiology

  • Lecture (others)
    HZDR Research Talk, 14.10.2020, Dresden, Deutschland
  • Lecture (others) (Online presentation)
    3rd Laser-Plasma Summer School (LAPLASS_3), 14.-18.09.2020, Salamanca, Spanien

Publ.-Id: 31969

Deep point embedding for urban classification using ALS point clouds: A new perspective from local to global

Huang, R.; Xu, Y.; Hong, D.; Yao, W.; Ghamisi, Pedram; Stilla, U.

Semantic interpretation of the 3D scene is one of the most challenging problems in point cloud processing, which also deems as an essential task in a wide variety of point cloud applications. The core task of semantic interpretation is semantic labeling, namely, obtaining a unique semantic label for each point in the point cloud. Despite several reported approaches, semantic labeling continues to be a challenge owing to the complexity of scenes, objects of various scales, and the non-homogeneity of unevenly distributed points. In this paper, we propose a novel method for obtaining semantic labels of airborne laser scanning (ALS) point clouds involving the embedding of local context information for each point with multi-scale deep learning, nonlinear manifold learning for feature dimension reduction, and global graph-based optimization for refining the classification results. Specifically, we address the tasks of learning discriminative features and global labeling smoothing. The key contribution of our study is threefold. First, a hierarchical data augmentation strategy is applied to enhance the learning of deep features based on the PointNet++ network and simultaneously eliminate the artifacts caused by division and sampling while dealing with large-scale datasets. Subsequently, the learned hierarchical deep features are globally optimized and embedded into a low-dimensional space with a nonlinear manifold-based joint learning method with the removal of redundant and disturbing information. Finally, a graph-structured optimization based on the Markov random fields algorithm is performed to achieve global optimization of the initial classification results that are obtained using the embedded deep features by constructing a weighted indirect graph and solving the optimization problem with graph-cuts. We conducted thorough experiments on ALS point cloud datasets to assess the performance of our framework. Results indicate that compared to other commonly used advanced classification methods, our method can achieve high classification accuracy. The overall accuracy (OA) of our approach on the ISPRS benchmark dataset can scale up to 83.2% for classifying nine semantic classes, thereby outperforming other compared point-based strategies. Additionally, we evaluated our framework on a selected portion of the AHN3 dataset, which provided OA up to 91.2%.

Publ.-Id: 31968

Texture-Aware Total Variation-Based Sun Glint Removal of Hyperspectral Images

Duan, P.; Lai, J.; Kang, J.; Kang, X.; Ghamisi, Pedram; Li, S.

Sun glint in hyperspectral images (HSIs) leads to undesirable spectral interference, which severely affects subsequent image interpretation, such as environmental monitoring of coastal areas. Sun glint removal methods aim to recover a high quality image without sun glint from the original image. Most methods depend on an assumption that the near infrared band is strongly absorbed by water. However, this assumption is not always reliable because the infrared radiation in shallow or turbid water can be reflected back by the seabed or sediment, rather than being fully absorbed. Therefore, the reflected infrared radiation still contains sun glint and these methods cannot sufficiently remove sun glint from HSIs. To address this problem, a texture-aware total variation (TATV)-based method is proposed to remove sun glint from HSIs. The original HSI first is formulated as a desired clean image and a sun glint image. Then, in order to remove the sun glint, we propose a variational model where the different spectral characteristics of sun glint and other surrounding materials are considered. Specifically, we propose a texture-aware total variation regularized method to heavily penalize the variation of the sun glint areas. Experiments performed on simulated and real data sets demonstrate that our method can greatly outperform other state-of-the-art methods in removing sun glint.


  • Secondary publication expected from 08.07.2021

Publ.-Id: 31967

Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources

Salcedo-Sanz, S.; Ghamisi, P.; Piles, M.; Werner, M.; Cuadra, L.; Moreno-Martínez, A.; Izquierdo-Verdiguier, E.; Muñoz-Marí, J.; Amirhosein, M.; Camps-Valls, G.

This paper reviews the most important information fusion data-driven algorithms based on Machine Learning (ML) techniques for problems in Earth observation. Nowadays we observe and model the Earth with a wealth of observations, from a plethora of different sensors, measuring states, fluxes, processes and variables, at unprecedented spatial and temporal resolutions. Earth observation is well equipped with remote sensing systems, mounted on satellites and airborne platforms, but it also involves in-situ observations, numerical models and social media data streams, among other data sources. Data-driven approaches, and ML techniques in particular, are the natural choice to extract significant information from this data deluge. This paper produces a thorough review of the latest work on information fusion for Earth observation, with a practical intention, not only focusing on describing the most relevant previous works in the field, but also the most important Earth observation applications where ML information fusion has obtained significant results. We also review some of the most currently used data sets, models and sources for Earth observation problems, describing their importance and how to obtain the data when needed. Finally, we illustrate the application of ML data fusion with a representative set of case studies, as well as we discuss and outlook the near future of the field.

Publ.-Id: 31966

Deep Metric Learning Based on Scalable Neighborhood Components for Remote Sensing Scene Characterization

Kang, J.; Fernandez-Beltran, R.; Ye, Z.; Tong, X.; Ghamisi, P.; Plaza, A.

With the development of convolutional neural networks (CNNs), the semantic understanding of remote sensing (RS) scenes has been significantly improved based on their prominent feature encoding capabilities. While many existing deep-learning models focus on designing different architectures, only a few works in the RS field have focused on investigating the performance of the learned feature embeddings and the associated metric space. In particular, two main loss functions have been exploited: the contrastive and the triplet loss. However, the straightforward application of these techniques to RS images may not be optimal in order to capture their neighborhood structures in the metric space due to the insufficient sampling of image pairs or triplets during the training stage and to the inherent semantic complexity of remotely sensed data. To solve these problems, we propose a new deep metric learning approach, which overcomes the limitation on the class discrimination by means of two different components: 1) scalable neighborhood component analysis (SNCA) that aims at discovering the neighborhood structure in the metric space and 2) the cross-entropy loss that aims at preserving the class discrimination capability based on the learned class prototypes. Moreover, in order to preserve feature consistency among all the minibatches during training, a novel optimization mechanism based on momentum update is introduced for minimizing the proposed loss. An extensive experimental comparison (using several state-of-the-art models and two different benchmark data sets) has been conducted to validate the effectiveness of the proposed method from different perspectives, including: 1) classification; 2) clustering; and 3) image retrieval. The related codes of this article will be made publicly available for reproducible research by the community.


  • Secondary publication expected from 12.12.2021

Publ.-Id: 31965

An Efficient Deep Unsupervised Superresolution Model for Remote Sensing Images

Sheikholeslami, M. M.; Nadi, S.; Naeini, A. A.; Ghamisi, P.

Superresolution (SR) has provided an effective solution to the increasing need for high-resolution images in remote sensing applications. Among various SR methods, deep learning-based SR (DLSR) has made a significant breakthrough. However, supervised DLSR methods require a considerable amount of training data, which is hardly available in the remote sensing field. To address this issue, some research works have recently proposed and revealed the capability of deep learning in unsupervised SR. This article presents an efficient unsupervised SR (EUSR) deep learning model using dense skip connections, which boosts the reconstruction performance in parallel with the reduction of computational burden. To do this, several blocks containing densely connected convolutional layers are implemented to increase the depth of the model. Some skip connections also concatenate feature maps of different blocks to enable better SR performance. Moreover, a bottle-neck block abstracts the feature maps in fewer feature maps to remarkably reduce the computational burden. According to our experiments, the proposed EUSR leads to better results than the state-of-the-art DLSR method in terms of reconstruction quality with less computational burden. Furthermore, results indicate that the EUSR is more robust than its rival in dealing with images of different classes and larger sizes.

  • Open Access Logo IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13(2020), 1937-1945
    DOI: 10.1109/JSTARS.2020.2984589

Publ.-Id: 31964

COVID-19 Outbreak Prediction with Machine Learning

Ardabili, S. F.; Mosavi, A.; Ghamisi, Pedram; Ferdinand, F.; Varkonyi-Koczy, A. R.; Reuter, U.; Rabczuk, T.; Atkinson, P. M.

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and these models are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models need to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to susceptible–infected–recovered (SIR) and susceptible-exposed-infectious-removed (SEIR) models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP; and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior across nations, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. This paper further suggests that a genuine novelty in outbreak prediction can be realized by integrating machine learning and SEIR models.

Publ.-Id: 31963

COVID-19 Pandemic Prediction for Hungary; A Hybrid Machine Learning Approach

Pinter, G.; Felde, I.; Mosavi, A.; Ghamisi, Pedram; Gloaguen, R.

Several epidemiological models are being used around the world to project the number of infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate prediction models is of utmost importance to take proper actions. Due to the lack of essential data and uncertainty, the epidemiological models have been challenged regarding the delivery of higher accuracy for long-term prediction. As an alternative to the susceptible-infected-resistant (SIR)-based models, this study proposes a hybrid machine learning approach to predict the COVID-19, and we exemplify its potential using data from Hungary. The hybrid machine learning methods of adaptive network-based fuzzy inference system (ANFIS) and multi-layered perceptron-imperialist competitive algorithm (MLP-ICA) are proposed to predict time series of infected individuals and mortality rate. The models predict that by late May, the outbreak and the total morality will drop substantially. The validation is performed for 9 days with promising results, which confirms the model accuracy. It is expected that the model maintains its accuracy as long as no significant interruption occurs. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research.

Publ.-Id: 31962

Remote Sensing Image Classification Using Subspace Sensor Fusion

Rasti, B.; Ghamisi, P.

The amount of remote sensing and ancillary datasets captured by diverse airborne and spaceborne sensors has been tremendously increased, which opens up the possibility of utilizing multimodal datasets to improve the performance of processing approaches with respect to the application at hand. However, developing a generic framework with high generalization capability that can effectively fuse diverse datasets is a challenging task since the current approaches are usually only applicable to two specific sensors for data fusion. In this paper, we propose an accurate fusion-based technique called SubFus with capability to integrate diverse remote sensing data for land cover classification. Here, we assume that a high dimensional multisensor dataset can be represented fused features that live in a lower-dimensional space. The proposed classification methodology includes three main stages. First, spatial information is extracted by using spatial filters (i.e., morphology filters). Then, a novel low- rank minimization problem is proposed to represent the multisensor datasets in subspaces using fused features. The fused features in the lower-dimensional subspace are estimated using a novel iterative algorithm based on the alternative direction method of multipliers. Third, the final classification map is produced by applying a supervised spectral classifier (i.e., random forest) on the fused features. In the experiments, the proposed method is applied to a three-sensor (RGB, multispectral LiDAR, and hyperspectral images) dataset captured over the area of the University of Houston, the USA, and a two-sensor (hyperspectral and LiDAR) dataset captured over the city of Trento, Italy. The land-cover maps generated using SubFus are evaluated based on classification accuracies. Experimental results obtained by SubFus confirm considerable improvements in terms of classification accuracies compared with the other methods used in the experiments. The proposed fusion approach obtains 85.32% and 99.25% in terms of overall classification accuracy on the Houston (the training portion of the dataset distributed for the data fusion contest of 2018) and trento datasets, respectively.

Related publications


  • Secondary publication expected from 01.12.2021

Publ.-Id: 31961

Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review

Sheykhmousa, M.; Mahdianpari, M.; Ghanbari, H.; Mohammadimanesh, F.; Ghamisi, P.; Homayouni, S.

Several machine-learning algorithms have been proposed for remote sensing image classification during the past two decades. Among these machine learning algorithms, Random Forest (RF) and Support Vector Machines (SVM) have drawn attention to image classification in several remote sensing applications. This article reviews RF and SVM concepts relevant to remote sensing image classification and applies a meta-analysis of 251 peer-reviewed journal papers. A database with more than 40 quantitative and qualitative fields was constructed from these reviewed papers. The meta-analysis mainly focuses on 1) the analysis regarding the general characteristics of the studies, such as geographical distribution, frequency of the papers considering time, journals, application domains, and remote sensing software packages used in the case studies, and 2) a comparative analysis regarding the performances of RF and SVM classification against various parameters, such as data type, RS applications, spatial resolution, and the number of extracted features in the feature engineering step. The challenges, recommendations, and potential directions for future research are also discussed in detail. Moreover, a summary of the results is provided to aid researchers to customize their efforts in order to achieve the most accurate results based on their thematic applications.

  • Open Access Logo IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13(2020), 6308-6325
    DOI: 10.1109/JSTARS.2020.3026724

Publ.-Id: 31960

Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods

Nosratabadi, S.; Mosavi, A.; Duan, P.; Ghamisi, Pedram; Filip, F.; Band, S. S.; Reuter, U.; Gama, J.; Gandomi, A. H.

This paper provides a comprehensive state-of-the-art investigation of the recent advances in data science in emerging economic applications. The analysis is performed on the novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a broad and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, is used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which outperform other learning algorithms. It is further expected that the trends will converge toward the evolution of sophisticated hybrid deep learning models.

Publ.-Id: 31959

Fusion of Dual Spatial Information for Hyperspectral Image Classification

Duan, P.; Ghamisi, P.; Kang, X.; Rasti, B.; Li, S.; Gloaguen, R.

The inclusion of spatial information into spectral classifiers for fine-resolution hyperspectral imagery has led to significant improvements in terms of classification performance. The task of spectral-spatial hyperspectral image classification has remained challenging because of high intraclass spectrum variability and low interclass spectral variability. This fact has made the extraction of spatial information highly active. In this work, a novel hyperspectral image classification framework using the fusion of dual spatial information is proposed, in which the dual spatial information is built by both exploiting pre-processing feature extraction and post-processing spatial optimization. In the feature extraction stage, an adaptive texture smoothing method is proposed to construct the structural profile (SP), which makes it possible to precisely extract discriminative features from hyperspectral images. The SP extraction method is used here for the first time in the remote sensing community. Then, the extracted SP is fed into a spectral classifier. In the spatial optimization stage, a pixel-level classifier is used to obtain the class probability followed by an extended random walker-based spatial optimization technique. Finally, a decision fusion rule is utilized to fuse the class probabilities obtained by the two different stages. Experiments performed on three data sets from different scenes illustrate that the proposed method can outperform other state-of-the-art classification techniques. In addition, the proposed feature extraction method, i.e., SP, can effectively improve the discrimination between different land covers.

Related publications

Publ.-Id: 31957

Spatial Analysis of Seasonal Precipitation over Iran: Co-Variation with Climate Indices

Dehghani, M.; Salehi, S.; Mosavi, A.; Nabipour, N.; Shamshirband, S.; Ghamisi, P.

Temporary changes in precipitation may lead to sustained and severe drought or massive floods in different parts of the world. Knowing the variation in precipitation can effectively help the water resources decision-makers in water resources management. Large-scale circulation drivers have a considerable impact on precipitation in different parts of the world. In this research, the impact of El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran was investigated. For this purpose, 103 synoptic stations with at least 30 years of data were utilized. The Spearman correlation coefficient between the indices in the previous 12 months with seasonal precipitation was calculated, and the meaningful correlations were extracted. Then, the month in which each of these indices has the highest correlation with seasonal precipitation was determined. Finally, the overall amount of increase or decrease in seasonal precipitation due to each of these indices was calculated. Results indicate the Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal precipitation, respectively. Additionally, these indices have the highest impact on the precipitation in winter, autumn, spring, and summer, respectively. SOI has a diverse impact on winter precipitation compared to the PDO and NAO, while in the other seasons, each index has its special impact on seasonal precipitation. Generally, all indices in different phases may decrease the seasonal precipitation up to 100%. However, the seasonal precipitation may increase more than 100% in different seasons due to the impact of these indices. The results of this study can be used effectively in water resources management and especially in dam operation.

Publ.-Id: 31956

Classification of Hyperspectral and LiDAR Data Using Coupled CNNs

Hang, R.; Li, Z.; Ghamisi, P.; Hong, D.; Xia, G.; Liu, Q.

In this article, we propose an efficient and effective framework to fuse hyperspectral and light detection and ranging (LiDAR) data using two coupled convolutional neural networks (CNNs). One CNN is designed to learn spectral-spatial features from hyperspectral data, and the other one is used to capture the elevation information from LiDAR data. Both of them consist of three convolutional layers, and the last two convolutional layers are coupled together via a parameter-sharing strategy. In the fusion phase, feature-level and decision-level fusion methods are simultaneously used to integrate these heterogeneous features sufficiently. For the feature-level fusion, three different fusion strategies are evaluated, including the concatenation strategy, the maximization strategy, and the summation strategy. For the decision-level fusion, a weighted summation strategy is adopted, where the weights are determined by the classification accuracy of each output. The proposed model is evaluated on an urban data set acquired over Houston, USA, and a rural one captured over Trento, Italy. On the Houston data, our model can achieve a new record overall accuracy (OA) of 96.03%. On the Trento data, it achieves an OA of 99.12%. These results sufficiently certify the effectiveness of our proposed model.


Publ.-Id: 31955

Spatial hazard assessment of the PM10 using machine learning models in Barcelona, Spain

Choubin, B.; Abdolshahnejad, M.; Moradi, E.; Querol, X.; Mosavi, A.; Shamshirband, S.; Ghamisi, P.

Air pollution, and especially atmospheric particulate matter (PM), has a profound impact on human mortality and morbidity, environment, and ecological system. Accordingly, it is very relevant predicting air quality. Although the application of the machine learning (ML) models for predicting air quality parameters, such as PM concentrations, has been evaluated in previous studies, those on the spatial hazard modeling of them are very limited. Due to the high potential of the ML models, the spatial modeling of PM can help managers to identify the pollution hotspots. Accordingly, this study aims at developing new ML models, such as Random Forest (RF), Bagged Classification and Regression Trees (Bagged CART), and Mixture Discriminate Analysis (MDA) for the hazard prediction of PM10 (particles with a diameter less than 10 µm) in the Barcelona Province, Spain. According to the annual PM10 concentration in 75 stations, the healthy and unhealthy locations are determined, and a ratio 70/30 (53/22 stations) is applied for calibrating and validating the ML models to predict the most hazardous areas for PM10. In order to identify the influential variables of PM modeling, the simulated annealing (SA) feature selection method is used. Seven features, among the thirteen features, are selected as critical features. According to the results, all the three-machine learning (ML) models achieve an excellent performance (Accuracy > 87% and precision > 86%). However, the Bagged CART and RF models have the same performance and higher than the MDA model. Spatial hazard maps predicted by the three models indicate that the high hazardous areas are located in the middle of the Barcelona Province more than in the Barcelona’s Metropolitan Area.


Publ.-Id: 31953

Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification

Hong, D.; Wu, X.; Ghamisi, P.; Chanussot, J.; Yokoya, N.; Zhu, X. X.

So far, a large number of advanced techniques have been developed to enhance and extract the spatially semantic information in hyperspectral image processing and analysis. However, locally semantic change, such as scene composition, relative position between objects, spectral variability caused by illumination, atmospheric effects, and material mixture, has been less frequently investigated in modeling spatial information. Consequently, identifying the same materials from spatially different scenes or positions can be difficult. In this article, we propose a solution to address this issue by locally extracting invariant features from hyperspectral imagery (HSI) in both spatial and frequency domains, using a method called invariant attribute profiles (IAPs). IAPs extract the spatial invariant features by exploiting isotropic filter banks or convolutional kernels on HSI and spatial aggregation techniques (e.g., superpixel segmentation) in the Cartesian coordinate system. Furthermore, they model invariant behaviors (e.g., shift, rotation) by the means of a continuous histogram of oriented gradients constructed in a Fourier polar coordinate. This yields a combinatorial representation of spatial-frequency invariant features with application to HSI classification. Extensive experiments conducted on three promising hyperspectral data sets (Houston2013 and Houston2018) to demonstrate the superiority and effectiveness of the proposed IAP method in comparison with several state-of-the-art profile-related techniques. The codes will be available from the website:

Publ.-Id: 31952

Multilevel Structure Extraction-Based Multi-Sensor Data Fusion

Duan, P.; Kang, X.; Ghamisi, P.; Liu, Y.

Multi-sensor data on the same area provide complementary information, which is helpful for improving the discrimination capability of classifiers. In this work, a novel multilevel structure extraction method is proposed to fuse multi-sensor data. This method is comprised of three steps: First, multilevel structure extraction is constructed by cascading morphological profiles and structure features, and is utilized to extract spatial information from multiple original images. Then, a low-rank model is adopted to integrate the extracted spatial information. Finally, a spectral classifier is employed to calculate class probabilities, and a maximum posteriori estimation model is used to decide the final labels. Experiments tested on three datasets including rural and urban scenes validate that the proposed approach can produce promising performance with regard to both subjective and objective qualities.

Publ.-Id: 31951

High-Rankness Regularized Semi-Supervised Deep Metric Learning for Remote Sensing Imagery

Kang, J.; Fernández-Beltrán, R.; Ye, Z.; Tong, X.; Ghamisi, P.; Plaza, A.

Deep metric learning has recently received special attention in the field of remote sensing (RS) scene characterization, owing to its prominent capabilities for modeling distances among RS images based on their semantic information. Most of the existing deep metric learning methods exploit pairwise and triplet losses to learn the feature embeddings with the preservation of semantic-similarity, which requires the construction of image pairs and triplets based on the supervised information (e.g., class labels). However, generating such semantic annotations becomes a completely unaffordable task in large-scale RS archives, which may eventually constrain the availability of sufficient training data for this kind of models. To address this issue, we reformulate the deep metric learning scheme in a semi-supervised manner to effectively characterize RS scenes. Specifically, we aim at learning metric spaces by utilizing the supervised information from a small number of labeled RS images and exploring the potential decision boundaries for massive sets of unlabeled aerial scenes. In order to reach this goal, a joint loss function, composed of a normalized softmax loss with margin and a high-rankness regularization term, is proposed, as well as its corresponding optimization algorithm. The conducted experiments (including different state-of-the-art methods and two benchmark RS archives) validate the effectiveness of the proposed approach for RS image classification, clustering and retrieval tasks. The codes of this paper are publicly available.

Publ.-Id: 31950

A Multi-Sensor Fusion Framework Based on Coupled Residual Convolutional Neural Networks

Li, H.; Ghamisi, P.; Rasti, B.; Wu, Z.; Shapiro, A.; Schultz, M.; Zipf, A.

Multi-sensor remote sensing image classification has been considerably improved by deep learning feature extraction and classification networks. In this paper, we propose a novel multi-sensor fusion framework for the fusion of diverse remote sensing data sources. The novelty of this paper is grounded in three important design innovations: 1- a unique adaptation of the coupled residual networks to address multi-sensor data classification; 2- a smart auxiliary training via adjusting the loss function to address classifications with limited samples; and 3- a unique design of the residual blocks to reduce the computational complexity while preserving the discriminative characteristics of multi-sensor features. The proposed classification framework is evaluated using three different remote sensing datasets: the urban Houston university datasets (including Houston 2013 and the training portion of Houston 2018) and the rural Trento dataset. The proposed framework achieves high overall accuracies of 93.57%, 81.20%, and 98.81% on Houston 2013, the training portion of Houston 2018, and Trento datasets, respectively. Additionally, the experimental results demonstrate considerable improvements in classification accuracies compared with the existing state-of-the-art methods.

Publ.-Id: 31949

Creation of Gold Nanoparticles in ZnO by Ion Implantation–DFT and Experimental Studies

Cajzl, J.; Jeníčková, K.; Nekvindová, P.; Michalcová, A.; Veselý, M.; Macková, A.; Malinský, P.; Jágerová, A.; Mikšová, R.; Akhmadaliev, S.

Three different crystallographic orientations of the wurtzite ZnO structure (labeled as c-plane, a-plane and m-plane) were implanted with Au + ions using various energies and fluences to form gold nanoparticles (GNPs). The ion implantation process was followed by annealing at 600°C in an oxygen atmosphere to decrease the number of unwanted defects and improve luminescence properties. With regard to our previous publications, the paper provides a summary of theoretical and experimental results, i.e., both DFT and FLUX simulations, as well as experimental results from TEM, HRTEM, RBS, RBS/C, Raman spectroscopy and photoluminescence. From the results, it follows that in the ZnO structure, implanted gold atoms are located in random interstitial positions—experimentally, the amount of interstitial gold atoms increased with increasing ion implantation fluence. During ion implantation and subsequent annealing, the metal clusters and nanoparticles with sizes from 2 to 20 nm were formed. The crystal structure of the resulting gold was not cubic (confirmed by diffraction patterns), but it had a hexagonal close-packed (hcp) arrangement. The ion implantation of gold leads to the creation of Zn and O interstitial defects and extended defects with distinct character in various crystallographic cuts of ZnO, where significant O-sublattice disordering occurred in m-plane ZnO.

Keywords: gold; ZnO; nanoparticles; ion implantation; luminescence; DFT; RBS

Publ.-Id: 31948

ComputationalRadiationPhysics/picongpu: Perfectly Matched Layer (PML) and Bug Fixes

Hübl, A.; Widera, R.; Worpitz, B.; Pausch, R.; Burau, H.; Garten, M.; Starke, S.; Grund, A.; Debus, A.; Matthes, A.; Bastrakov, S.; Steiniger, K.; Göthel, I.; Rudat, S.; Kelling, J.; Bussmann, M.

This release adds a new field absorber for the Yee solver, convolutional perfectly matched layer (PML). Compared to the still supported exponential damping absorber, PML provides better absorption rate and much less spurious reflections.

We added new plugins for computing emittance and transition radiation, particle rendering with the ISAAC plugin, Python tools for reading and visualizing output of a few plugins.

The release also adds a few quality-of-life features, including a new memory calculator, better command-line experience with new options and bash-completion, improved error handling, cleanup of the example setups, and extensions to documentation.

Please refer to our ChangeLog for a full list of features, fixes and user interface changes before getting started.

Thanks to Igor Andriyash, Sergei Bastrakov, Xeinia Bastrakova, Andrei Berceanu, Finn-Ole Carstens, Alexander Debus, Jian Fuh Ong, Marco Garten, Axel Huebl, Sophie Rudat (Koßagk), Anton Lebedev, Felix Meyer, Pawel Ordyna, Richard Pausch, Franz Pöschel, Adam Simpson, Sebastian Starke, Klaus Steiniger, René Widera for contributions to this release!

Keywords: PIConGPU; Particle-in-Cell; Laser; Plasma

  • Software in external data repository
    Publication year 2020
    Programming language: C++, Python, Shell, CMake, Dockerfile, Awk
    System requirements: Computer
    License: GPLv3+, LGPLv3+, CC-BY 4.0 (Link to license text)
    Hosted on
    DOI: 10.5281/zenodo.3875374

Publ.-Id: 31947

Domain wall damping in ultrathin nanostripes with Dzyaloshinskii-Moriya interaction

Volkov, O.; Kronast, F.; Abert, C.; Oliveros Mata, E. S.; Kosub, T.; Makushko, P.; Erb, D.; Pylypovskyi, O.; Mawass, M.-A.; Sheka, D.; Zhou, S.; Faßbender, J.; Makarov, D.

Asymmetrically sandwiched thin magnetic layers with perpendicular anisotropy and Dzyaloshinskii-Moriya interaction (DMI) is the prospective material science platform for spin-orbitronic technologies that rely on the motion of chiral magnetic textures, like skyrmions or chiral domain walls (DWs). The dynamic performance of a DW-based racetracks is defined by the strength of DMI and the DW damping. The determination of the latter parameter is typically done based on technically challenging DW motion experiments. Here, we propose a method to access both parameters, DMI constant and DW damping, yet in static experiments by monitoring the tilt of magnetic DWs in nanostripes. We experimentally demonstrate that in perpendicularly magnetized //CrO x /Co/Pt stacks, DWs can be trapped on edge roughness in a metastable tilted state as a result of the DW dynamics driven by external magnetic field. The measured tilt can be correlated to the DMI strength and DW damping in a self-consistent way in the frame of a theoretical formalism based on the collective coordinate approach.

Keywords: Nanomagnetism; Magnetic domains; Dzyaloshinskii-Moriya interaction

Publ.-Id: 31945

Depressants in scheelite flotation - Mechanism of sodium carbonate and acidified water glass and the application of process mineralogy

Kupka, N.

The European Union classified tungsten as a Critical Raw Material already in 2011, due to its high economic importance and high supply risk. Tungsten occurs under two main mineral forms, scheelite (CaWO4) and wolframite ((Fe,Mn)WO4), with scheelite’s importance increasing as wolframite resources are progressively depleting. Interest in scheelite is growing fast, as publications show: 15 % of all publications on scheelite flotation since the 1950s were published in 2019. A polar salt type mineral, scheelite is semi-soluble and exhibits a negative charge, almost regardless of the flotation conditions. It is mostly hydrophilic but can easily be floated using chemical reagents, usually at a high pH of 9 to 10. Scheelite flotation has run into serious difficulties when it is associated to a carbonaceous gangue. Other calcium-bearing minerals, such as calcite (CaCO3), apatite (Ca-phosphate) and fluorite (CaF2) all exhibit similar flotation properties and are therefore classified as semi-soluble salt-type minerals. These minerals will tend to float better than scheelite under the same circumstances and not only increase reagent consumption but heavily contaminate the concentrate, making it harder and more expensive to process for the smelter. Several depressants can be used to remedy this problem, the most used one being sodium silicate. However, this reagent is imperfect and its effect can be improved by modifying it or by combining it with other depressants. As a consequence, the focus of this work is to understand the mechanism of two important depressants in scheelite flotation, sodium carbonate and acidified sodium silicate, and linking said mechanism to mineralogy. A third depressant, colloidal silica, is studied from a performance point of view.

Keywords: froth flotation; scheelite; depressants; automated mineralogy

  • Doctoral thesis
    TUBAF, 2020
    Mentor: Prof. Urs Peuker
    174 Seiten

Publ.-Id: 31943

Uploading data to the HepDATA repository with Python using hepdata_lib

Müller, S.

Presentation at the "STRONG2020 Meeting on the Hadronic Cross Section database"

  • Lecture (Conference) (Online presentation)
    STRONG2020 Meeting on the hadronic Cross Section database, 18.12.2020, Pisa, Italy

Publ.-Id: 31942

LLAMA: Compile time automatic memory layout optimization

Gruber, B. M.

Write code once and perform well on many systems.

  • Open Access Logo Poster
    Polish delegation meeting, 29.09.2020, Görlitz, Germany


Publ.-Id: 31941

Nanoscale mechanics of antiferromagnetic domain walls

Hedrich, N.; Wagner, K.; Pylypovskyi, O.; Shields, B. J.; Kosub, T.; Sheka, D.; Makarov, D.; Maletinsky, P.

Antiferromagnets offer remarkable promise for future spintronics devices, where antiferromagnetic order is exploited to encode information. The control and understanding of antiferromagnetic domain walls (DWs) - the interfaces between domains with differing order parameter orientations - is a key ingredient for advancing such antiferromagnetic spintronics technologies. However, studies of the intrinsic mechanics of individual antiferromagnetic DWs remain elusive since they require sufficiently pure materials and suitable experimental approaches to address DWs on the nanoscale. Here we nucleate isolated, 180° DWs in a single-crystal of Cr2O3, a prototypical collinear magnetoelectric antiferromagnet, and study their interaction with topographic features fabricated on the sample. We demonstrate DW manipulation through the resulting, engineered energy landscape and show that the observed interaction is governed by the DW's elastic properties. Our results advance the understanding of DW mechanics in antiferromagnets and suggest a novel, topographically defined memory architecture based on antiferromagnetic DWs.

Publ.-Id: 31940

Cryogenic Liquid Jets for High Repetition Rate Discovery Science

Curry, C. B.; Schoenwaelder, C.; Goede, S.; Kim, J. B.; Rehwald, M.; Treffer, F.; Zeil, K.; Glenzer, S. H.; Gauthier, M.

This protocol presents a detailed procedure for the operation of continuous, micron-sized cryogenic cylindrical and planar liquid jets. When operated as described here, the jet exhibits high laminarity and stability for centimeters. Successful operation of a cryogenic liquid jet in the Rayleigh regime requires a basic understanding of fluid dynamics and thermodynamics at cryogenic temperatures. Theoretical calculations and typical empirical values are provided as a guide to design a comparable system. This report identifies the importance of both cleanliness during cryogenic source assembly and stability of the cryogenic source temperature once liquefied. The system can be used for high repetition rate laser-driven proton acceleration, with an envisioned application in proton therapy. Other applications include laboratory astrophysics, materials science, and next-generation particle accelerators.

  • Open Access Logo Journal of Visualized Experiments 159(2020), e61130
    DOI: 10.3791/61130


Publ.-Id: 31939

Comparison of experimental STEM conditions for fluctuation electron microscopy

Radic, D.; Hilke, S.; Peterlechner, M.; Posselt, M.; Wilde, G.; Bracht, H.

Variable-resolution fluctuation electron microscopy (VR-FEM) data from measurements on amorphous silicon and PdNiP have been obtained at varying experimental conditions. Measurements have been conducted at identical total electron dose and with an identical electron dose normalized to the respective probe size. STEM probes of different sizes have been created by variation of the semi-convergence angle or by defocus. The results show that defocus yields a reduced normalized variance compared to data from probes created by convergence angle variation. Moreover, the trend of the normalized variance upon probe size variation differs between the two methods. Beam coherence, which affects FEM data, has been analyzed theoretically using geometrical optics on a multi-lens setup and linked to the illumination conditions. Fits to several experimental beam profiles support our geometrical optics theory regarding probe coherence. The normalized variance can be further optimized if one determines the optimal exposure time for the nanobeam diffraction patterns.

Keywords: amorphous materials; coherence; fluctuation electron microscopy; medium-range order; nanobeam diffraction

Publ.-Id: 31938

Implementation of the academic image processing pipeline ExploreASL in an outpatient center using IntelliSpace Discovery

Ganji, S.; Pinter, N.; Petr, J.; Ajtai, B.; Fritz, J.; Mechtler, L.; Husain, S.; Fischer, A.; Barkhof, F.; Mutsaerts, H.

The use of standardized image processing pipelines is continuously increasing in radiological research with developments in computing power, image processing, and machine learning techniques. Early integration of academic processing methods into clinical research workflow would accelerate the translation of promising novel MRI techniques into the clinic. However, the integration of such tools is both resource and time consuming. While most of neurological imaging takes place in outpatient centers, resource and workflow limitations of such clinics do not allow for the application of advanced image analysis. Here, we present the integration the “ExploreASL” into the PACS-connected research platform IntelliSpace Discovery.

  • Poster
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Publ.-Id: 31936

Treatment efficacy of asymptomatic carotid artery stenosis patients evaluated by clinically applicable hemodynamic MRI and cognitive testing

Kaczmarz, S.; Göttler, J.; Petr, J.; Sollmann, N.; Schmitzer, L.; Hock, A.; Hansen, M.; Mouridsen, K.; Zimmer, C.; Hyder, F.; Preibisch, C.

Hemodynamic MRI is highly promising to improve treatment decisions in asymptomatic internal carotid artery stenosis (ICAS). However, treatment efficacy evaluations require clinically applicable techniques, such as dynamic susceptibility contrast (DSC) and resting-state BOLD-based evaluations of amplitude of low-frequency fluctuations (ALFF). We present data from 16 asymptomatic ICAS patients before and after treatment and 17 age-matched healthy controls measuring cerebral blood volume (CBV) and capillary transit-time heterogeneity (CTH) by DSC and ALFF with additional cognitive testing. We hypothesized recovery of hemodynamic impairments after revascularization. Our results confirmed this hypothesis for all parameters. Interestingly, at the same time cognitive function remained impaired

  • Lecture (Conference) (Online presentation)
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Publ.-Id: 31935

Measurement of intra- and extra-neurite perfusion by combining ASL with the NODDI DWI model

Asllani, I.; Plaindoux, A.; Petr, J.; Woods, J.; van Osch, M.; Cercignani, M.

Intra- and extra-neurite perfusion in gray and white matter were estimated by applying a spatial linear regression algorithm on ASL images using the micro-structural anatomical information derived from the NODDI analysis of the DWI data. Baseline ASL images were acquired with 4 post-labeling delay (PLD) values in order to test the hypothesis of redistribution of ASL signal across the micro-compartments with increasing PLD. Motor activation was used to investigate the sensitivity of the method for detecting changes in perfusion at the micro-structural level.

  • Poster (Online presentation)
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Publ.-Id: 31934

The long road from invention to implementation a pan-European neuroradiological survey on quantitative MRI techniques in clinical practice

Keil, V.; Smits, M.; Thust, S.; Petr, J.; Solymosi, L.; Manfrini, E.

This pan-European online survey study revealed that clinically working Neuroradiologists appreciate the additional diagnostic accuracy rendered by quantitative MRI techniques. However, the clinical implementation of many techniques is hampered by a lack of knowledge on how to acquire, post-process and interpret results of multiple quantitative MRI techniques including ASL, CEST/APT, IVIM and others. With exception of DSC and DWI in tumor imaging and stroke, the number of indications is also still limited especially regarding head/neck Radiology and neurodegenerative diseases.

  • Lecture (Conference) (Online presentation)
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Publ.-Id: 31933

Differences in quantitative glioma perfusion imaging with ASL and DSC: validation with 15O-H2O PET

Petr, J.; Verburg, N.; Kuijer, J.; Koopman, T.; Keil, V.; Warnert, E.; Barkhof, F.; van den Hoff, J.; Boellaard, R.; de Witt Hamer, P.; Mutsaerts, H.

While agreement between ASL, DSC, and PET perfusion is well established in healthy volunteers, an analogous comparison in gliomas is still missing and more challenging. We compared ASL and DSC perfusion measurements with the gold-standard of 15 O-H 2 O-PET perfusion measurements in eight patients diagnosed with gliomas. We showed the importance of normalization to the contralateral hemisphere, and identified several examples of different regional perfusion as assessed with ASL and DSC and interpreted them using the PET reference.

  • Lecture (Conference) (Online presentation)
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Publ.-Id: 31932

Arterial spin labeling signal in the Sagittal Sinus as hemodynamic proxy parameter in patients with sickle cell disease

Afzali-Hashemi, L.; Vaclavu, L.; Petr, J.; Wood, J.; Biemond, B.; Nederveen, A.; Mutsaerts, H.

Higher sagittal sinus signal is present in the ASL images of patients with sickle cell disease (SCD). The purpose of this study was to assess if the signal in the sagittal sinus is correlated with clinical parameters and if this is affected by the vasoactive stimulus. The sagittal sinus signal was measured in patients with SCD and in healthy controls. Signal in sagittal sinus of the SCD patients were significantly correlated with clinical parameters including

  • Poster
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Publ.-Id: 31931

Nonlinear plasmonic response in GaAs/InGaAs core/shell nanowires.

Rana, R.; Balaghi, L.; Fotev, I.; Schneider, H.; Helm, M.; Dimakis, E.; Pashkin, O.

We show nonlinear plasmonic response in GaAs/In0.2Ga0.8As nanowires using high field terahertz pulses. With increasing THz field, plasmon resonance is redshifted, and spectral weight decreases indicating an inhomogeneous intervalley electron scattering across the nanowire.

Keywords: Intense Terahertz pulses; Nanowires; Plasmon

  • Poster (Online presentation)
    The 22nd International Conference on Ultrafast Phenomena (UP 2020), 16.-19.11.2020, Shanghai, China

Publ.-Id: 31930

ExploreQC: A toolbox for MRI quality control in the EPAD multicentre study

Lorenzini, L.; Ingala, S.; Wottschel, V.; Wink, A. M.; Kuijer, J.; Sudre, C. H.; Haller, S.; Molinuevo, J. L.; Gispert, J. D.; Cash, D. M.; Thomas, D. L.; Vos, S.; Petr, J.; Wolz, R.; Pernet, C.; Waldman, A.; Barkhof, F.; Mutsaerts, H. J. M. M.; Epad, C.

Magnetic Resonance Imaging (MRI) of the brain is prone to artefacts that may worsen image quality and subsequent analyses. Despite the growing number of large-scale multi-institutional imaging studies, standardized approaches for defining inclusion and exclusion criteria on the basis of image data quality are still lacking and quality assessment is often based on visual inspection. We introduce ExploreQC, a MATLAB-based toolbox which implements a semi-automatic pipeline to assess QC metrics, select the most relevant parameters, and to derive informed inclusion thresholds.

  • Open Access Logo Poster (Online presentation)
    Alzheimer's Association International Conference, 27.07.2020, Virtual, Virtual
    DOI: 10.1002/alz.041952
  • Open Access Logo Abstract in refereed journal
    Alzheimer's & Dementia 16(2020), e041952
    DOI: 10.1002/alz.041952

Publ.-Id: 31929

ASL perfusion MRI in the follow-up of pediatric brain tumors

Verschuren, S.; Petr, J.; Mutsaerts, H. J.; Plasschaert, S.; Wijnen, J.; Lequin, M.; Wiegers, E.

ASL perfusion MRI in the follow-up of pediatric brain tumors

  • Open Access Logo Poster (Online presentation)
    European Society for Magnetic Resonance in Medicine and Biology, 30.09.2020, Virtual, Virtual
    DOI: 10.1007/s10334-020-00876-y
  • Open Access Logo Abstract in refereed journal
    Magnetic Resonance Materials in Physics, Biology and Medicine 33(2020)Suppl 1, P02.01
    DOI: 10.1007/s10334-020-00876-y

Publ.-Id: 31928

Accumulation of ferromanganese crusts derived from carrier-free 10Be/9Be

Lachner, J.; Ploner, M.; Steier, P.; Sakaguchi, A.; Usui, A.

The occurrence of 10Be in natural archives is commonly used to date their formation and growth on time scales of million years. Accelerator Mass Spectrometry (AMS) can perform a direct measurement of the 10Be/9Be ratio. The carrier-free method, in which no 9Be carrier is added to the original sample, is especially suitable for 10Be/9Be ratio determination in the marine environment. By normalizing the 10Be content to 9Be, temporal variations of Be uptake processes into the archive are eliminated.

Here, we present a simple method for the chemical extraction of beryllium from ferromanganese (FeMn) crusts or nodules, the measurement procedure, and the first carrier-free 10Be/9Be measurements at the 3 MV AMS facility VERA. Several tests of chemical methods are discussed including different options to short-cut and accelerate the procedure for special cases. Results from FeMn crust 237KD from cruise VA13/2 in the Pacific ocean show the known 10Be/9Be distribution with depth that is commonly related to a changing growth rate of the archive. In this context we discuss the potential influence of diffusion and adsorption processes on the age models of FeMn crusts that are based on radioactive nuclides such as 10Be and 230Th. Including an open-system behavior for these isotopes in the description of their profiles allows interpreting the accumulation of crusts with a constant growth rate over millions of years and does not require the assumption of abrupt growth changes.

Keywords: 10Be; Carrier-free 10Be/9Be; AMS; VERA; Ferromanganese crusts


Publ.-Id: 31927

Material requirements for pulsed magnets at the HLD

Zherlitsyn, S.

es hat kein Abstrakt vorgelegen

  • Lecture (Conference) (Online presentation)
    2020 Virtual MRS Spring/ Fall Meeting, 27.11.-04.12.2020, Boston, USA

Publ.-Id: 31926

Antisite disorder in the battery material LiFePO4

Werner, J.; Neef, C.; Koo, C.; Zvyagin, S.; Ponomaryov, O.; Klingeler, R.

We report detailed magnetometry and high-frequency electron spin resonance (HF-ESR) measurements which allow detailed investigation on Li-Fe antisite disorder in single-crystalline LiFePO4, i.e., exchange of Fe2+ and Li+ ions. The data imply that magnetic moments of Fe2+ ions at Li positions do not participate in long-range antiferromagnetic order in LiFePO4 but form quasifree moments. Anisotropy axes of the magnetic moments at antisite defects are attached to the main crystallographic directions. The local character of these moments is confirmed by associated linear resonance branches detected by HF-ESR studies. Magnetic anisotropy shows up in significant zero-field splittings of Δ = 220(3) GHz, Δ` ∼ 50 GHz, and a highly anisotropic g factor, i.e., ga = 1.4, gb = 2.0, and gc = 6.3. We demonstrate a general method to precisely determine Fe-antisite disorder in LiFePO4 from magnetic studies which implies a density of paramagnetic Fe2+ ions at Li positions of 0.53%.

Publ.-Id: 31925

Elastic response to the first-order magnetization process of U3Cu4Ge4

Gorbunov, D.

Es hat kein Abstrakt vorgelegen.

  • Invited lecture (Conferences) (Online presentation)
    ARHMF2020 & KINKEN Materials Science School 2020 for Young Scientists, 01.-03.12.2020, Sendai, Japan

Publ.-Id: 31924

Data for: A UV laser test facility for precise measurement of gas parameters in gaseous detectors

Fan, X.

It contains the data measured by the device and the simulation data.

Keywords: UV laser

Related publications

  • Reseach data in the HZDR data repository RODARE
    Publication date: 2020-12-17
    DOI: 10.14278/rodare.684
    License: CC-BY-1.0


Publ.-Id: 31923

Biplots for Compositional Data Derived from Generalised Joint Diagonalization Methods

Mueller, U.; Tolosana Delgado, R.; Grunsky, E. C.; McKinley, J. M.

Biplots constructed from principal components of a compositional data set are an established means to explore its features. Principal Component Analysis (PCA) is also used to transform a set of spatial variables into spatially decorrelated factors. However, because no spatial structures are accounted for in the transformation the application of PCA is limited. In geostatistics and blind source separation a variety of different matrix diagonalization methods have been developed with the aim to provide spatially or temporally decorrelated factors. Just as PCA, many of these transformations are linear and so lend themselves to the construction of biplots. In this contribution we consider such biplots for a number of methods (MAF, UWEDGE and RJD transformations) and discuss how and if they can contribute to our understanding of relationships between the components of regionalized compositions. A comparison of the biplots with the PCA biplot commonly used in compositional data analysis for the case of data from the Northern Irish geochemical survey shows that the biplots from MAF and UWEDGE are comparable as are those from PCA and RJD. The biplots emphasize different aspects of the regionalized composition: for MAF and UWEDGE the focus is the spatial continuity, while for PCA and RJD it is variance explained. The results indicate that PCA and MAF combined provide adequate and complementary means for exploratory statistical analysis.

Keywords: Semivariogram matrices; Spatial decorrelation; Structural analysis; Geochemical data

Publ.-Id: 31922

Data for: Mapping the stray fields of a micromagnet using spin centers in SiC

Bejarano, M.; Trindade Goncalves, F. J.; Hollenbach, M.; Hache, T.; Hula, T.; Berencen, Y.; Faßbender, J.; Helm, M.; Astakhov, G.; Schultheiß, H.

We utilized the following methods to obtain the presented data: optically detected magnetic resonance (ODMR), photoluminescence spectroscopy, and micromagnetic simulations in Mumax3. The experimental data were obtained on the sample which is labeled as: "HPSI 4H-SiC 30 Magnon Q #2". On that sample we investigated magnetic ellipses, sized 8 micrometer x 2 micrometer, made of Permalloy, that lie on top of a silicon carbide substrate. The measured data for all measurements (including ALL parameters) are included in the uploaded primary data subdirectories. The uploaded data is organized in folders according to the figures in the paper. Each folder contains the experimental data, together with the MuMax3 definition files, all the possible possible scripts used for evaluation and all figures included in the paper.

Related publications

  • Reseach data in the HZDR data repository RODARE
    Publication date: 2020-12-17
    DOI: 10.14278/rodare.682
    License: CC-BY-4.0


Publ.-Id: 31921

CaTeNA – Climatic and Tectonic Natural Hazards in Central Asia Final virtual workshop September 24-25 2020

Barbosa, N.; Bloch, W.; Crosetto, S.; Haberland, C.; Jarihani, B.; Kakar, N.; Metzger, S.; Mohadjer, S.; Orunbaev, S.; Ratschbacher, L.; Schurr, B.; Strecker, M.; Wang, X.

CaTeNA – Climatic and Tectonic Natural Hazards in Central Asia – is an interdisciplinary, international project funded by the German Ministry of Education and Research to study natural hazards in Central Asia. Central Asia is one of the most tectonically active regions of the world and is influenced by both the west wind zone and monsoon. CaTeNA is examining the two most serious natural hazards arising from these conditions: Earthquakes and mass movements. The project goal is to better understand the underlying processes and triggering factors and to better estimate the resulting risks. For this purpose, CaTeNA localises tectonic faults and determines deformation rates and their changes. Focus is put on two of the most active fault systems, the Main Pamir Thrust and the Darvaz Fault crossing Tajikistan and Kyrgyzstan. We try to estimate recurrence intervals of large earthquakes and to understand their relationship to mass movements using paleo-seismology, geomorphology and remote sensing. The current deformation field is characterised and quantified using the methods of space geodesy and seismology. The results will be incorporated into the openly accessible Central Asian Tectonic Database developed within the project, making it accessible to the public, stakeholders and decision-makers. They form the basis for a more accurate estimation of the risk for earthquakes and landslides. Another important project goal is the development and implementation of a dynamic risk assessment for landslides, including high-resolution, model-based precipitation and snowmelt maps. This allows for improved estimation of the effects of geological hazards on inhabited areas and traffic infrastructure. Direct and efficient risk communication is achieved through interactive visualisation based on a dynamic multilingual web GIS platform. This is an essential step on the path to an early-warning system that takes into account the most important triggering factors. This data repository provides pdf files and recorded videos of talks presented during the final online workshop of the project.

Keywords: climatic natural hazard; tectonic natural hazard; coupling mechanism; central asia

  • Open Access Logo Lecture (others) (Online presentation)
    CaTeNA – Climatic and Tectonic Natural Hazards in Central Asia Final virtual workshop, 24.-25.09.2020, Potsdam, Germany
    DOI: 10.2312/gfz.catena.2020


Publ.-Id: 31920

Window-based morphometric indices as predictive variables for landslide susceptibility models

Barbosa, N.; Andreani, L.; Gloaguen, R.; Ratschbacher, L.

Identification of areas prone to landslides is essential to mitigate associated risks. This is usually achieved using landslide susceptibility models, which estimate landslide likelihood given local terrain conditions and the location of known past events. Detailed databases covering different conditioning factors are paramount to produce reliable susceptibility maps. However, thematic data from developing countries are scarce. As a result, susceptibility models often rely on morphometric parameters derived from widely-available digital elevation models. In most cases, simple parameters such as slope, aspect, and curvature, computed using a moving window of 3{$\times$}3 pixels, are used. Recently, the use of window-based morphometric indices as an additional input has increased. These rely on a user-defined observation window size. In this contribution, we examine the influence of observation window size when using window-based morphometric indices as core predictive variables for landslide susceptibility assessment. We computed a variety of models that include morphometric indices calculated with different window sizes, and compared the predictive capabilities and reliability of the resulting predictions. All models are based on the random forest algorithm. The results improved significantly when each window-based morphometric index was calculated with a different and meaningful observation window. The sensitivity analysis highlights both the highly-informative observation windows and the impact of their selection on the model performance. We also stress the importance of evaluating landslide susceptibility results using different adapted metrics for predictive performance and reliability.

Keywords: landslide susceptibility model; morphometric indices; observation window; random forest; Tajik-Tian Shan

Publ.-Id: 31918

Improving landslide susceptibility models using morphometric indices: Influence of the observation window in the reliability of the results.

Barbosa Mejia, Laura Natalie; Andreani, Louis; Gloaguen, Richard

Estimation of landslide susceptibility in mountainous areas is a prerequisite for risk assessment and contingency planning. The susceptibility to landslide is modelled based on thematic layers of information such as geomorphology, hydrology, or geology, where detailed characteristics of the area are depicted. The growing use of machine learning techniques to identify complex relationships among a high number of variables decreased the time required to distinguish areas prone to landslides and increased the reliability of the results. However, numerous countries lack detailed thematic databases to feed in the models. As a consequence, susceptibility assessment often relies heavily on geomorphic parameters derived from Digital Elevation Models. Simple parameters such as slope, aspect and curvature, calculated under a moving window of 3x3-pixels are mostly used. Furthermore, advanced morphometric indices such as topographic position index or surface roughness are increasingly used as additional input parameters. These indices are computed under a bigger window of observation usually defined by the researcher and the goal of the study. While these indices proved to be useful in capturing the overall morphology of an entire slope profile or regional processes, little is known on how the selection of the moving window size is relevant and affects the output landslide susceptibility model.

In order to address this question, we analysed how the predicting capabilities and reliability of landslide susceptibility models were impacted by the morphometric indices and their window of observation. For this purpose, we estimate the landslide susceptibility of an area located in Tajikistan (SW Tien Shan) using a Random Forest algorithm and different input datasets. Predicting factors include commonly used 3x3-pixel morphometrics, environmental, geological and climatic variables as well as advanced morphometric indices to be tested (surface roughness, local relief, topographic position index, elevation relief ratio and surface index). Two approaches were selected to address the moving window size. First, we chose a common window of observation for all the morphometric indices based on the study area valley’s characteristics. Second, we defined an optimal moving window(s) for each morphometric index based on the importance ranking of models that include moving windows from a range of 300 to 15000 m for each index. A total of 20 models were iteratively created, started by including all the moving windows from all the indices. Predicting capabilities were evaluated by the receiver operator curve (ROC) and Precision-Recall (PR). Additionally, a measure of reliability is proposed using the standard deviation of 50 iterations. The selection of different moving windows using the feature importance resulted in better predicting capabilities models than assigning an optimal for all. On the other hand, using a single different moving window per morphometric index (eg. most important ranked by random forest) decreases the evaluating metrics (a drop of PR from 0.88 to 0.85). Landslide susceptibility models can thus be improved by selecting a variety of meaningful (physically and methodological) windows of observation for each morphometric index. A 3x3-pixel moving window is not recommended because it is too small to capture the morphometric signature of landslides.

Keywords: Landslide susceptibility; morphometry; machine learning; random forest

Publ.-Id: 31917

Impact of laser polarization on q-exponential photon tails in non-linear Compton scattering

Kämpfer, B.; Titov, A.

Non-linear Compton scattering of ultra-relativistic electrons traversing high-intensity laser pulses generates also hard photons. These photon high-energy tails are considered for parameters in reach at the forthcoming experiments LUXE and E-320. We consider the invariant differential cross sections dσ/du between the IR and UV regions and analyze the impact of the laser polarization and find q-deformed exponential shapes. (The variable u is the light-cone momentum-transfer from initial electron to final photon.) Optical laser pulses of various durations are compared with the monochromatic laser beam model which uncovers the laser intensity parameter in the range ξ=1⋯10. Some supplementary information is provided for the azimuthal final-electron/photon distributions and the photon energy-differential cross sections.


Publ.-Id: 31915

Improved accuracy in high-frequency AC transport measurements in pulsed high magnetic fields

Mitamura, Y.; Watanuki, R.; Kampert, W. A. G.; Förster, T.; Matsuo, A.; Onimaru, T.; Onozaki, N.; Amou, Y.; Wakiya, K.; Matsumoto, K. T.

We show theoretically and experimentally that accurate transport measurements are possible even within the short time provided by pulsed magnetic fields. For this purpose, a new method has been devised, which removes the noise component of a specific frequency from the Signal by taking a linear combination of the results of numerical phase detection using multiple integer periods. We also established a method to unambiguously determine the phase rotation angle in AC transport measurements using a frequency range of tens of kilohertz. We revealed that the dominant noise in low-frequency transport measurements in pulsed magnetic fields is the electromagnetic induction caused by mechanical vibrations of wire loops in inhomogeneous magnetic fields. These results strongly suggest that accurate transport measurements in short-pulsed magnets are possible when mechanical vibrations are well suppressed.

Publ.-Id: 31914

How Hyperspectral Image Unmixing and Denoising Can Boost Each Other

Rasti, B.; Koirala, B.; Scheunders, P.; Ghamisi, P.

Hyperspectral linear unmixing and denoising are highly related hyperspectral image (HSI) analysis tasks. In particular, with the assumption of Gaussian noise, the linear model assumed for the HSI in the case of low-rank denoising is often the same as the one used in HSI unmixing. However, the optimization criterion and the assumptions on the constraints are different. Additionally, noise reduction as a preprocessing step in hyperspectral data analysis is often ignored. The main goal of this paper is to study experimentally the influence of noise on the process of hyperspectral unmixing by: (1) investigating the effect of noise reduction as a preprocessing step on the performance of hyperspectral unmixing; (2) studying the relation between noise and different endmember selection strategies; (3) investigating the performance of HSI unmixing as an HSI denoiser; (4) comparing the denoising performance of spectral unmixing, state-of-the-art HSI denoising techniques, and the combination of both. All experiments are performed on simulated and real datasets.

Related publications

  • Reseach data in the HZDR data repository RODARE
    Publication date: 2020-12-16
    DOI: 10.14278/rodare.680
    License: CC-BY-4.0


Publ.-Id: 31912

Multicaloric effects in metamagnetic Heusler Ni-Mn-In under uniaxial stress and magnetic field

Gràcia-Condal, A.; Gottschall, T.; Pfeuffer, L.; Gutfleisch, O.; Planes, A.; Manosa, L.

The world’s growing hunger for artificial cold, on the one hand, and the ever more stringent climate targets, on the other, pose an enormous challenge to mankind. Novel, efficient, and environmentally friendly refrigeration technologies based on solid-state refrigerants can offer a way out of the problems arising from climate-damaging substances used in conventional vapor-compressors. Multicaloric materials stand out because of their large temperature changes, which can be induced by the application of different external stimuli such as a magnetic, electric, or a mechanical field. Despite the high potential for applications and the interesting physics of this group of materials, few studies focus on their investigation by direct methods. In this paper, we report on the advanced characterization of all relevant physical quantities that determine the multicaloric effect of a Ni-Mn-In Heusler compound. We have used a purpose-designed calorimeter to determine the isothermal entropy and adiabatic temperature changes resulting from the combined action of magnetic field and uniaxial stress on this metamagnetic shape-memory alloy. From these results, we can conclude that the multicaloric response of this alloy by appropriate changes of uniaxial stress and magnetic field largely outperforms the caloric response of the alloy when subjected to only a single stimulus. We anticipate that our findings can be applied to other multicaloric materials, thus inspiring the development of refrigeration devices based on the multicaloric effect

Publ.-Id: 31911

Field-Modulated Anomalous Hall Conductivity and Planar Hall Effect in Co3Sn2S2 Nanoflakes

Yang, S.-Y.; Noky, J.; Gayles, J.; Dejene, F. K.; Sun, Y.; Doerr, M.; Scurschii, I.; Felser, C.; Nawaz Ali, M.; Liu, E.; Parkin, S. S. P.

Time-reversal-symmetry-breaking Weyl semimetals (WSMs) have attracted great attention recently because of the interplay between intrinsic magnetism and topologically nontrivial electrons. Here, we present anomalous Hall and planar Hall effect studies on Co3Sn2S2 nanoflakes, a magnetic WSM hosting stacked Kagome lattice. The reduced thickness modifies the magnetic properties of the nanoflake, resulting in a 15-time larger coercive field compared with the bulk, and correspondingly modifies the transport properties. A 22% enhancement of the intrinsic anomalous Hall conductivity (AHC), as compared to bulk material, was observed. A magnetic field-modulated AHC, which may be related to the changing Weyl point separation with magnetic field, was also found. Furthermore, we showed that the PHE in a hard magnetic WSM is a complex interplay between ferromagnetism, orbital magnetoresistance, and chiral anomaly. Our findings pave the way for a further understanding of exotic transport features in the burgeoning field of magnetic topological phases.

Publ.-Id: 31910

HIF2alpha-associated pseudohypoxia promotes radioresistance in pheochromocytoma: insights from 3D models

Seifert, V.; Richter, S.; Bechmann, N.; Bachmann, M.; Ziegler, C. G.; Pietzsch, J.; Ullrich, M.

Pheochromocytomas and paragangliomas (PCCs/PGLs) are rare neuroendocrine tumors arising from chromaffin tissue located in the adrenal or in ganglia of the sympathetic or parasympathetic nervous system. Treatment of non-resectable or metastatic PCCs/PGLs is still limited to palliative measures, including somatostatin type 2 receptor radionuclide therapy with [177Lu]Lu-DOTA-TATE as one of the most effective approaches to date. Nevertheless, metabolic and molecular determinants of radiation response in PCCs/PGLs have not yet been characterized. This study investigates the effects of hypoxia-inducible factor 2 alpha (HIF2α) on the susceptibility of PCCs/PGLs to radiation treatments using spheroids grown from genetically engineered mouse pheochromocytoma (MPC) cells. Expression of Hif2α was associated with significantly increased resistance of MPC spheroids to external X-ray irradiation and exposure to beta particle-emitting [177Lu]LuCl3 compared to Hif2α-deficient controls. Exposure to [177Lu]LuCl3 provided increased long-term control of MPC spheroids compared to single-dose external X-ray irradiation. This study provides first experimental evidence that HIF2α-associated pseudohypoxia contributes to a radioresistant phenotype of PCCs/PGLs. Furthermore, external irradiation and [177Lu]LuCl3 exposure of MPC spheroids provide surrogate models for radiation treatments to further investigate metabolic and molecular determinants of radiation responses in PCCs/PGLs and to evaluate effects of neo-adjuvant, in particular, radiosensitizing treatments in combination with targeted radionuclide therapies.

Keywords: paraganglioma; radionuclide therapy; lutetium-177; spheroid control dose; SCD50; spheroid re-growth; irradiation; X-ray; radioresistance

Publ.-Id: 31909

Nanometer-Thick Bismuth Nanocrystal Films for Sensoric Applications

Pilidi, A.; Tzanis, A.; Helm, T.; Arfanis, M.; Falaras, P.; Speliotis, T.

The present article is concerned with investigations of the structural, surface morphological, and magnetotransport properties of DC magnetron-sputtered nanometer-thick Bi nanocrystal films on Si(111) substrates. Crystal structure and surface morphology were studied with X-ray diffraction, Raman spectroscopy, field-emission scanning electron microscopy, and atomic force microscopy. For the samples deposited at the melting point of Bi, 271 °C, equilibrium crystals formed and according to Wulff theorem acquire a specific shape determined by the surface tension. These crystals were investigated for different film thicknesses and deposition temperatures varying from 25 to 300 °C. Furthermore, magnetotransport characterization was carried out in steady and pulsed magnetic fields of up to 9 and 70 T, respectively. At low temperatures, clear weak antilocalization behavior is observed, attributed to 2D conduction channels. A nonlinear Hall resistance is also confirmed, ascribed to the coexistence of two types of carriers (p and n). This study contributes to the elucidation of the transport properties of the Bi thin films and opens new perspectives for their exploitation in modern applications such as sensorics.

Publ.-Id: 31908

Allianz Initiative: Positionspapier Digitale Dienste für die Wissenschaft – wohin geht die Reise?

Konrad, U.; Förstner, K.; Reetz, J.; Wannemacher, K.; Kett, J.; Mannseicher, F.

Aufgrund des informationstechnologischen Fortschritts, der immer stärkeren, domänenübergreifenden Vernetzung in Wissenschaft und Forschung sowie der Notwendigkeit, gemeinsam Dienste und Ressourcen zu nutzen, werden von den Akteuren in Forschung und Wissenschaft zunehmend verteilte digitale Dienste verwendet. Der Fokus dieser Handreichung liegt auf den wissenschaftlichen Informationsdiensten, zu denen man u. a. Werkzeuge für kollaboratives Arbeiten, für die Aufbereitung und Analyse von Daten sowie Dienste zum wissenschaftlichen Publizieren, aber auch Dienste für die Entwicklung von Forschungssoftware zählen kann. Dabei zielen die Fragen nach der Art der geforderten bzw. wirklich verwendeten Diensten, der Vor- und Nachteile der gegenwärtigen Nutzung sowie der eigenverantwortlichen Bereitstellung dieser Dienste unter dem Aspekt der (finanziellen) Ressourcen-

Keywords: Research Software; Open Science; Open Source; Digital Transformation; Information Technology

Publ.-Id: 31907

Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox

Rasti, B.; Hong, D.; Hang, R.; Ghamisi, P.; Kang, X.; Chanussot, J.; Benediktsson, J. A.

Hyperspectral images (HSIs) provide detailed spectral information through hundreds of (narrow) spectral channels (also known as dimensionality or bands), which can be used to accurately classify diverse materials of interest. The increased dimensionality of such data makes it possible to significantly improve data information content but provides a challenge to conventional techniques (the so-called curse of dimensionality) for accurate analysis of HSIs. Feature extraction (FE), a vibrant field of research in the hyperspectral community, evolved through decades of research to address this issue and extract informative features suitable for data representation and classification. The advances in FE were inspired by two fields of research—the popularization of image and signal processing along with machine (deep) learning—leading to two types of FE approaches: the shallow and deep techniques. This article outlines the advances in these approaches for HSI by providing a technical overview of state-of-the-art techniques, offering useful entry points for researchers at different levels (including students, researchers, and senior researchers) willing to explore novel investigations on this challenging topic. In more detail, this article provides a bird’s eye view of shallow [both supervised FE (SFE) and unsupervised FE (UFE)] and deep FE approaches, with a specific focus on hyperspectral FE and its application to HSI classification. Additionally, this article compares 15 advanced techniques with an emphasis on their methodological foundations and classification accuracies. Furthermore, to push this vibrant field of research forward, an impressive amount of code and libraries are shared on GitHub, which can be found in [131].

Related publications

  • Reseach data in the HZDR data repository RODARE
    Publication date: 2020-12-16
    DOI: 10.14278/rodare.678


Publ.-Id: 31906

Oscillatory thermal-inertial flows in liquid metal rotating convection

Vogt, T.; Horn, S.; Aurnou, J.

We present the first detailed thermal and velocity field characterization of convection in a rotating cylindrical tank of liquid gallium, which has thermophysical properties similar to those of planetary core fluids. Our laboratory experiments, and a closely associated direct numerical simulation, are all carried out in the regime prior to the onset of steady convective modes. This allows us to study the oscillatory convective modes, sidewall modes and broadband turbulent flow that develop in liquid metals before the advent of steady columnar modes. Our thermo-velocimetric measurements show that strongly inertial, thermal wind flows develop, with velocities reaching those of comparable non-rotating cases. Oscillatory bulk convection and wall modes coexist across a wide range of our experiments, along with strong zonal flows that peak in the Stewartson layer, but that extend deep into the fluid bulk in the higher supercriticality cases. The flows contain significant time-mean helicity that is anti-symmetric across the midplane, demonstrating that oscillatory liquid metal convection contains the kinematic components to sustain system-scale dynamo generation.

Publ.-Id: 31905

Data for: "Multi Optical Sensor Fusion for Mineral Mapping of Core Samples"

Rasti, B.; Ghamisi, P.; Seidel, P.; Lorenz, S.; Gloaguen, R.

Geological objects are characterized by a high complexity inherent to a strong compositional variability at all scales and usually unclear class boundaries. Therefore, dedicated processing schemes are required for the analysis of such data for mineral mapping. On the other hand, the variety of optical sensing technology reveals different data attributes and therefore multi-sensor approaches are adapted to solve such complicated mapping problems. In this paper, we devise an adapted multi-optical sensor fusion (MOSFus) workflow which takes the geological characteristics into account. The proposed processing chain exhaustively covers all relevant stages, including data acquisition, preprocessing, feature fusion, and mineral mapping. The concept includes i) a spatial feature extraction based on morphological profiles on RGB data with high spatial resolution, ii) a specific noise reduction applied on the hyperspectral data that assumes mixed sparse and Gaussian contamination and iii) a subsequent dimensionality reduction using a sparse and smooth low rank analysis. The feature extraction approach allows to fuse heterogeneous data at variable resolutions, scales, and spectral ranges as well as improve classification substantially. The last step of the approach, an SVM classifier, is robust to unbalanced and sparse training sets and is particularly efficient with complex imaging data. We evaluate the performance of the procedure with two different multi-optical sensor datasets. The results demonstrate the superiority of this dedicated approach over common strategies.

Keywords: Multi-sensor data; optical sensor; hyperspectral; hyperspectral mixed sparse and Gaussian noise reduction (HyMiNoR); spectral imaging; data fusion; feature extraction; dimensionality reduction; support vector machine (SVM); sparse and smooth low-rank analysis (SSLRA); orthogonal total variation component analysis (OTVCA); mineral exploration

Related publications

  • Reseach data in the HZDR data repository RODARE
    Publication date: 2020-07-05
    DOI: 10.14278/rodare.632
    License: CC-BY-4.0


Publ.-Id: 31904

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