Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

Gallium is classified as a technology metal as it is important for technological innovations. It is also referred to as a strategic metal, which emphasizes its economic relevance. In addition, gallium is a critical raw material that is strategically important but only available in limited quantities. However, recycling dissolved gallium from lowconcentration
wastewater is often not done due to the lack of suitable technologies.
This research presents a membrane-based approach using the siderophore Desferrioxamine B for the recycling of gallium. Nanofiltration membranes were used to separate gallium from other metal impurities (such as arsenic). The membranes recovered about 70% of gallium from low-concentrated synthetic wastewater.
Afterward, the membranes were tested using industrial wastewater, and a similar recovery rate was observed. A model was developed to predict operation parameters that would lead to the highest recovery rate of gallium with the minimum impurities. The model showed that recycling more than 90% of gallium from wastewater is possible using this approach. Therefore, the siderophore-assisted nanofiltration approach demonstrated in this research showed great potential for the sustainable recycling of gallium from industrial wastewater.

Large Language Models (LLMs) have gained significant popularity in recent years for their ability to answer questions in various fields. However, these models have a tendency to "hallucinate" their responses, making it challenging to evaluate their performance. A major challenge is determining how to assess the certainty of a model's predictions and how it correlates with accuracy. In this work, we introduce an analysis for evaluating the performance of popular open-source LLMs, as well as gpt-3.5 Turbo, on multiple choice physics questionnaires. We focus on the relationship between answer accuracy and variability in topics related to physics. Our findings suggest that most models provide accurate replies in cases where they are certain, but this is by far not a general behavior. The relationship between accuracy and uncertainty exposes a broad horizontal bell-shaped distribution. We report how the asymmetry between accuracy and uncertainty intensifies as the questions demand more logical reasoning of the LLM agent, while the same relationship remains sharp for knowledge retrieval tasks.

Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a significant challenge. Simulation-based inference (SBI) addresses this by enabling Bayesian inference for simulators, identifying parameters that match observed data and align with prior knowledge. Unlike traditional Bayesian inference, SBI only needs access to simulations from the model and does not require evaluations of the likelihood-function. In addition, SBI algorithms do not require gradients through the simulator, allow for massive parallelization of simulations, and can perform inference for different observations without further simulations or training, thereby amortizing inference. Over the past years, we have developed, maintained, and extended sbi, a PyTorch-based package that implements Bayesian SBI algorithms based on neural networks. The sbi toolkit implements a wide range of inference methods, neural network architectures, sampling methods, and diagnostic tools. In addition, it provides well-tested default settings but also offers flexibility to fully customize every step of the simulation-based inference workflow. Taken together, the sbi toolkit enables scientists and engineers to apply state-of-the-art SBI methods to black-box simulators, opening up new possibilities for aligning simulations with empirically observed data.

Background and purpose: In recent years, ultra-high dose rate (UHDR) irradiation has emerged as a promising innovative approach to cancer treatment. Characteristic feature of this regimen, commonly referred to as FLASH effect, demonstrated primarily for electrons, photons or protons, is the improved
normal tissue sparing, while the tumor control is similar to the one of the conventional dose-rate (CDR) treatments. The FLASH mechanism is, however, unknown. One major question is whether this effect is maintained when using densely ionizing (high-LET) heavy nuclei.

Materials and Methods: Here we report the effects of 20 Gy UHDR heavy ion irradiation in clinically relevant conditions, i.e., at high-LET in the spread-out Bragg peak (SOBP) of a 12C beam using an osteosarcoma mouse model.

Results: We show that UHDR irradiation was less toxic in the normal tissue compared to CDR while maintaining tumor control. The immune activation was also comparable in UHDR and CDR groups. Both UHDR and CDR exposures steered the metagenome toward a balanced state.

Conclusions: These results suggest that the UHDR irradiations can improve the safety and effectiveness of heavy ion therapy, and provide a crucial benchmark for current mechanistic FLASH models. However, additional experiments are needed to validate these findings across other animal and tumor models.

There is compelling evidence that head injury is a significant environmental risk factor for Alzheimer's disease (AD) and that a history of traumatic brain injury (TBI) accelerates the onset of AD. Amyloid-β plaques and tau aggregates have been observed in the post-mortem brains of TBI patients; however, the mechanisms leading to AD neuropathology in TBI are still unknown. In this study, we hypothesized that focal TBI induces changes in miRNA expression in and around affected areas, resulting in the altered expression of genes involved in neurodegeneration and AD pathology. For this purpose, we performed a miRNA array in extracts from rats subjected to experimental TBI, using the controlled cortical impact (CCI) model. In and around the contusion, we observed alterations of miRNAs associated with dementia/AD, compared to the contralateral side. Specifically, the expression of miR-9 was significantly upregulated, while miR-29b, miR-34a, miR-106b, miR-181a and miR-107 were downregulated. Via qPCR, we confirmed these results in an additional group of injured rats when compared to naïve animals. Interestingly, the changes in those miRNAs were concomitant with alterations in the gene expression of mRNAs involved in amyloid generation and tau pathology, such as β-APP cleaving enzyme (BACE1) and Glycogen synthase-3-β (GSK3β). In addition increased levels of neuroinflammatory markers (TNF-α), glial activation, neuronal loss, and tau phosphorylation were observed in pericontusional areas. Therefore, our results suggest that the secondary injury cascade in TBI affects miRNAs regulating the expression of genes involved in AD dementia.

Traumatic brain injury represents a significant global health burden and has the highest prevalence among neurological disorders. Even mild traumatic brain injury can induce subtle, long-lasting changes that increase the risk of future neurodegeneration. Importantly, this can be challenging to detect through conventional neurological assessment. This underscores the need for more sensitive diagnostic tools, such as electroencephalography, to uncover opportunities for therapeutic intervention. Progress in the field has been hindered by a lack of studies linking mechanistic insights at the microscopic level from animal models to the macroscale phenotypes observed in clinical imaging. Our study addresses this gap by investigating a rat model of mild blast traumatic brain injury using both immunohistochemical staining of inhibitory interneurons and translationally relevant electroencephalography recordings. Although we observed no pronounced effects immediately post-injury, chronic time points revealed broadband hyperexcitability and increased connectivity, accompanied by decreased density of inhibitory interneurons. This pattern suggests a disruption in the balance between excitation and inhibition, providing a crucial link between cellular mechanisms and clinical hallmarks of injury. Our findings have significant implications for the diagnosis, monitoring, and treatment of traumatic brain injury. The emergence of electroencephalography abnormalities at chronic time points, despite the absence of immediate effects, highlights the importance of long-term monitoring in traumatic brain injury patients. The observed decrease in inhibitory interneuron density offers a potential cellular mechanism underlying the electroencephalography changes and may represent a target for therapeutic intervention. This study demonstrates the value of combining cellular-level analysis with macroscale neurophysiological recordings in animal models to elucidate the pathophysiology of traumatic brain injury. Future research should focus on translating these findings to human studies and exploring potential therapeutic strategies targeting the excitation-inhibition imbalance in traumatic brain injury.

All data will be published together with the article as electronic supplement on the article webpag

In the modern technological landscape, magnetic field sensors play a crucial role and are indispensable across a range of high-tech applications. In conjunction with magnets, magnetic field sensors can accurately detect any form of relative movement of objects without physical contact. For instance, in the precise control of robotic arms or machine tools, a permanent magnet is used as a reference. The magnetic sensor detects the relative movement of magnet by sensing changes in the magnetic field strength. These changes are converted into electrical signals, which are fed back to the control system, enabling accurate positioning and control of the device. This advanced detection technology not only greatly enhances measurement precision but also significantly extends the lifespan of equipment. Among various types of magnetic field sensors, magnetoresistive (MR) sensors stand out for their exceptional performance. The high sensitivity allows them to detect minimal changes of magnetic fields in high-precision measurements. Today, MR sensors are widely used across numerous fields, including automobile industries, information processing and storage, navigation systems, biomedical applications, etc. With their outstanding performance and wide-ranging applications, MR sensors are at the forefront of sensor technology.
Over the past decades, the rapid advancement of emerging technologies such as the internet of things (IoT), wearable electronics, digital healthcare and disposable electronics has significantly broadened the application fields for MR sensors. In turn, such innovative applications have introduced unprecedented demands. Beyond traditional metrics, these new applications require sensors to possess unconventional attributes such as flexibility/stretchability, self-healing capabilities, recyclability, transparency, and lightweight, which have presented new challenges in the design and manufacturing of MR sensors. Although there has been significant progress in developing thin-film MR sensors with these unconventional features, meeting all the practical demands remains challenging. Researchers and engineers are actively exploring new materials and manufacturing methods to address these challenges. Printing techniques stand out for their numerous inherent advantages, such as cost effectiveness, scalability, rapid prototyping, versatility, customization, and environmental friendliness. Printable MR sensors have leaped forward benefiting from the rapid development of printing manufacturing techniques, such as screen printing, inkjet printing, roll to roll printing, and 3D printing. The core advantage of these printable sensors lies in their exceptional design flexibility and customization, which enable the production of MR sensors with unconventional properties. These inks/pastes combine functional MR fillers with polymer binders. The incorporation of polymeric binders offers a range of unique attributes, including excellent flexibility and stretchability, as well as self-healing, recyclability, transparency, and lightweight properties [7,8], thus making printed MR sensors adaptable to a wide variety of applications. On the other hand, the functional fillers come in various forms (e.g., particles, wires, flakes, cubes, and complex structures) and their distribution within the binder matrix can be precisely controlled using external magnetic fields. Those together enable the creation of MR sensors with unique and tailored performance characteristics , paving the way to a wide range of applications that are otherwise unavailable.

We have developed an innovative recyclable printed magnetoresistive sensor using GMR microflakes and
AMR microparticles as functional fillers, with PECH as the elastomer binder. Under saturation magnetic
fields of 100 mT and 30 mT, these sensors respectively exhibit magnetoresistance values of 4.7% and
0.45%. The excellent mechanical properties and thermal stability of the PECH elastomer binder endow
these sensors with outstanding flexibility and temperature stability. This flexibility, low cost, and scalability
make these sensors highly suitable for integration into flexible electronic devices, such as smart security
systems and home automation. Moreover, these sensors are fully recyclable and reusable, allowing the
materials to be separated, reused, and remanufactured without loss of performance. The low energy
consumption of the production process and the recyclability of the materials significantly reduce the
environmental impact of these magnetic field sensors.

The growing interest in ferroelectric materials has witnessed the thriving prospect of bio-inspired artificial neuromorphic system, where multi-level polarization states play a crucial role. In this work, with typical BaTiO3 ferroelectric thin film as the model system, we explore the physical effects of inhomogeneity on polarization switching dynamics and neuromorphic performance. Inhomogeneous films exhibited pinched polarization–electric field hysteresis loops, leading to a high recognition accuracy of 96.03% for hand-written digits, compared to about 10.31% for homogeneous films. The inhomogeneity in switching dynamics was analyzed by inhomogeneous field mechanism. Diffusive distributions of switching time and local electric fields were observed, aligning with experimental results and the expected inhomogeneity. The prolonged domain wall depinning time and lowered energy consumption suggest the potential for multi-level polarization states, a possibility further confirmed by phase-field simulations that demonstrated their presence during long-term potentiation/depression. Our work highlights the positive influence of inhomogeneity in enhancing the performance of ferroelectric-based neuromorphic systems.

Talks for Interpore 2024

Background:

Immune-mediated Thrombotic Thrombocytopenic Purpura (iTTP) is a rare autoimmune disease characterised by the presence of anti-ADAMTS13 autoantibodies in the patient. Current lines of treatment such as plasma exchange, rituximab and corticosteroids are generalised and there is a need for a more personalised approach.
Aims:
Here, we aim to selectively deplete only the anti-ADAMTS13 autoreactive B cells from the patient using Chimeric Antigen Receptor (CAR)-T technology. Our intention is to implement the adapter CAR system “RevCAR”, already efficacious against various tumour settings, in an autoimmune milieu.
The adapter CAR platform “RevCAR” utilises a protein adapter molecule (target module – RevTM) as a toggle switch for the reactivity of the RevCAR T cells. This way, in the absence of RevTM there is no activation of RevCAR T cells. The RevCAR has a human La-antigen-derived peptide as an extracellular domain and intracellular CD28/CD3 signaling domains.
Methods:
The RevTM, on one hand binds to the RevCAR via anti-peptide single-chain fragment variable (scFv), and on the other hand to the autoreactive B cell by virtue of ADAMTS13-derived autoantigen.
3T3 fibroblasts were used to produce the RevTMs and the purification was done using affinity chromatography. Qualitative and quantitative analyses were performed to ensure the functionality and integrity of the TMs. Hybridoma cell lines expressing autoreactive anti-ADAMTS13 BCR were chosen as target cells. A co-incubation in vitro killing assay was performed to evaluate the cytotoxicity of the RevCAR platform against anti-ADAMTS13 autoreactive hybridomas.
Results:
We successfully produced the RevCAR T cells and RevTMs. The purified RevTMs also showed near-native folding as assessed by ELISA, indicating prospective binding to the autoreactive B cells. The RevTMs also bound to the T cells, suggesting efficient interaction of RevCAR, RevTM and B-cell. The RevCAR-T cells exhibited significantly high cytotoxicity against hybridomas, only in the presence of the respective RevTM.
Summary/ Conclusion:
The specific and switchable cytotoxic ability of the RevCAR-T cells presents itself as a promising strategy for using this platform in an autoimmune disease setting.

Performance assessments of geological repositories for the underground disposal of high-level radioactive waste require a deep understanding of the phenomena influencing the mobility of radionuclides, e.g. sorption, redox immobilization, surface precipitation, incorporation, etc. Reliable thermodynamic databases (TDB) are required in order to generate speciation calculations, surface complexation and reactive transport models to predict the aforementioned mechanisms. In this work, the focus was set on europium (Eu), a lanthanide used for decades as a chemical analogue of trivalent actinides (Pu, Am). This study aims at providing a reliable, robust, and internally consistent TDB for europium. Recently, results of our critical evaluation for the chloride, sulphate, phosphate, and hydroxide ligands were published and will be discussed. An example of data acquisition related to the complexation of Eu with aqueous phosphate will also be shown.

Machine learning and artificial intelligence (AI) are becoming more common in infection biology laboratories around the world. Yet, as they gain traction in research, novel frontiers arise. Novel artificial intelligence algorithms are capable of addressing advanced tasks like image generation and question answering. However, similar algorithms can prove useful in addressing advanced questions in infection biology like prediction of host-pathogen interactions or inferring virus protein conformations. Addressing such tasks requires large annotated data sets, which are often scarce in biomedical research. In this review, I bring together several successful examples where such tasks were addressed. I underline the importance of formulating novel AI tasks in infection biology accompanied by freely available benchmark data sets to address these tasks. Furthermore, I discuss the current state of the field and potential future trends. I argue that one such trend involves AI tools becoming more versatile.

High-content image-based screening is widely used in Drug Discovery and Systems Biology. However, sample preparation artefacts may significantly deteriorate the quality of image-based screening assays. While detection and circumvention of such artefacts could be addressed using modern-day machine learning and deep learning algorithms, this is widely impeded by the lack of suitable datasets. To address this, here we present a purpose-created open dataset of high-content microscopy sample preparation artefact. It consists of high-content microscopy of laboratory dust titrated on fixed cell culture specimens imaged with fluorescence filters covering the complete spectral range. To ensure this dataset is suitable for supervised machine learning tasks like image classification or segmentation we propose rule-based annotation strategies on categorical and pixel levels. We demonstrate the applicability of our dataset for deep learning by training a convolutional-neural-network-based classifier.

Inverse problems aim to determine parameters from observations, a crucial task in engineering and science. Lately, generative models, especially diffusion models, have gained popularity in this area for their ability to produce realistic solutions and their good mathematical properties. Despite their success, an important drawback of diffusion models is their sensitivity to the choice of variance schedule, which controls the dynamics of the diffusion process. Fine-tuning this schedule for specific applications is crucial but time-consuming and does not guarantee an optimal result. We propose a novel approach for learning the schedule as part of the training process. Our method supports probabilistic conditioning on data, provides high-quality solutions, and is flexible, proving able to adapt to different applications with minimum overhead. This approach is tested in two unrelated inverse problems: super-resolution microscopy and quantitative phase imaging, yielding comparable or superior results to previous methods and fine-tuned diffusion models. We conclude that fine-tuning the schedule by experimentation should be avoided because it can be learned during training in a stable way that yields better results. The code is available on https://github.com/casus/cvdm

Poster for Goldschmidt 2024

Optic deconvolution in light microscopy (LM) refers to recovering the object details from images, revealing the ground truth of samples. Traditional explicit methods in LM rely on the point spread function (PSF) during image acquisition. Yet, these approaches often fall short due to inaccurate PSF models and noise artifacts, hampering the overall restoration quality. In this paper, we approached the optic deconvolution as an inverse problem. Motivated by the nonstandard-form compression scheme introduced by Beylkin, Coifman, and Rokhlin (BCR), we proposed an innovative physics-informed neural network Multi-Stage Residual-BCR Net (m-rBCR) to approximate the optic deconvolution. We validated the m-rBCR model on four microscopy datasets-two simulated microscopy datasets from ImageNet and BioSR, real dSTORM microscopy images, and real widefield microscopy images. In contrast to the explicit deconvolution methods (eg Richardson-Lucy) and other state-of-the-art NN models (U-Net, DDPM, CARE, DnCNN, ESRGAN, RCAN, Noise2Noise, MPRNet, and MIMO-U-Net), the m-rBCR model demonstrates superior performance to other candidates by PSNR and SSIM in two real microscopy datasets and the simulated BioSR dataset. In the simulated ImageNet dataset, m-rBCR ranks in the second-best place (right after MIMO-U-Net). With the backbone from the optical physics, m-rBCR exploits the trainable parameters with better performances (from 30 times fewer than the benchmark MIMO-U-Net to 210 times than ESRGAN). This enables m-rBCR to achieve a shorter runtime (from 3 times faster than MIMO-U-Net to 300 times faster than DDPM). To summarize, by leveraging physics constraints our model reduced potentially redundant parameters significantly in expertise-oriented NN candidates and achieved high efficiency with superior performance.

Monitoring cell behaviour in hydrogel-based 3D models is critical for assessing their growth and response to cytotoxic treatment. Resazurin-based PrestoBlue and AlamarBlue reagents are frequently used metabolic activity assays when determining cell responses. However, both assays are largely applied to cell monolayer cultures but yet to have a defined protocol for use in hydrogel-based 3D models. The assays' performance depends on the cell type, culture condition and measurement sensitivity. To better understand how both assays perform, we grew pancreatic cancer cells in gelatin methacryloyl and collagen hydrogels and evaluated their metabolic activity using different concentrations and incubation times of the PrestoBlue and AlamarBlue reagents. We tested reagent concentrations of 4 % and 10 % and incubation times of 45 min, 2 h and 4 h. In addition, we co-cultured cancer cells together with cancer-associated fibroblasts and peripheral blood mononuclear cells in gelatin methacryloyl hydrogels and subjected them to gemcitabine and nab-paclitaxel to evaluate how both assays perform when characterising cell responses upon drug treatment. CyQuant assays were conducted on the same samples and compared to data from the metabolic activity assays. In cancer monocultures, higher reagent concentration and incubation time increased fluorescent intensity. We found a reagent concentration of 10 % and an incubation time of 2 h suitable for all cell lines and both hydrogels. In multicellular 3D cultures, PrestoBlue and AlamarBlue assays detected similar cell responses upon drug treatment but overestimated cell growth. We recommend to assess cell viability and growth in conjunction with CyQuant assays that directly measure cell functions.

Prostate-specific membrane antigen (PSMA) and gastrin-releasing peptide receptor (GRPR) have been used for diagnostic molecular imaging/therapy of prostate cancer (PCa). To address tumor heterogeneity, we synthesized and evaluated a bispecific PSMA/GRPR ligand (3) combining PSMA-617 (1) and the GRPR antagonist RM2 (2) with the radiometal chelator DOTA. 3 was radiolabeled with 68Ga ([68Ga]Ga-3) and 177Lu ([177Lu]Lu-3). [68Ga]Ga-3 was tested in the following PCa cell lines for receptor affinity, time kinetic cell-binding/specificity, and cell-internalization: PC-3 and LNCaP. Compared to the monomers (1 and 2), ligand 3 showed specific cell binding, similar receptor affinities, and higher lipophilicity, while its internalization rates and cell-binding were superior. Docking calculations showed that 3 can have binding interactions of PSMA-617 (1) inside the PSMA receptor funnel and RM2 (2) inside the GRPR. In vivo biodistribution studies for [68Ga]Ga-3 showed dual targeting for PSMA(+) and GRPR(+) tumors and higher tumor uptake, faster pharmacokinetic, and lower kidney uptake compared to 1 and 2.

Aim/Introduction:

Patients with locally advanced non-small-cell lung cancer (NSCLC) have a high risk of developing distant metastases. It has been shown that applying immunotherapy after radiochemotherapy can significantly improve the prognosis for affected patients. In this context, biomarkers for individualized therapy escalation are urgently needed. One such biomarker could be the total metabolic volume of primary tumor and lymph node (LN) metastases (total tumor burden, TTB). However, delineation of tumor lesions with conventional methods is time consuming and error-prone, especially for the LN metastases. The goal of this study was to investigate feasibility of such delineation with deep learning methods.

Materials and Methods:

Automated delineation was performed with a 3D U-Net convolutional neural network (CNN) developed with the nnU-Net software package [1]. The default nnU-Net training parameters were modified to provide better training stability with small lesion targets as well as to better balance sensitivity vs. positive predictive value (PPV) of lesion detection. A dataset consisting of 517 [18F]FDG-PET/CT scans of NSCLC patients was used for the network training and testing following 5-fold cross-validation scheme. In these data, the ground truth labels were defined via manual delineation and labeling of primary tumor and metastases by an experienced physician.

Results:

The derived CNN models were capable of accurate delineation, achieving a mean (median) Dice similarity coefficient of 0.831 (0.891). The sensitivity and PPV of lesion detection was 0.974/0.829/0.887 and 0.963/0.741/0.824 for primary tumor/LN metastases/union of both, respectively. Accuracy of lesion classification as primary tumor or LN metastases was 92.1%. Manually and automatically derived TTBs were highly correlated with R2=0.96 and a mean absolute difference of 5.4 ml (after rejecting 1% of the outliers).

Conclusion:

In this work, we present CNN models able to perform delineation of and discrimination between primary tumor and lymph node metastases in NSCLC in [18F]FDG-PET/CT with only sporadic manual corrections required. This provides the ability to accelerate large-scale study data evaluation in quantitative PET and has potential for clinical application.

References:

[1] Isensee, F., Jaeger, P.F., Kohl, S.A.A. et al. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods 18, 203-211 (2021)

Ziel/Aim: Patients with locally advanced non-small-cell lung cancer (NSCLC) have a high risk of developing distant metastases. It has been shown that immunotherapy after radiochemotherapy can significantly improve the prognosis. Therefore, biomarkers for individualized therapy escalation are urgently needed. One such biomarker could be the total metabolic volume of primary tumor and lymph node (LN) metastases. However, delineation of LN metastases with currently available methods is time consuming and error-prone. The goal of this study was to investigate to which extend this delineation can be performed with deep learning methods.

Methodik/Methods: Automated delineation was performed with a pretrained 3D U-Net convolutional neural network (CNN) previously derived for a different head and neck cancer delineation task. 517 [18F]FDG PET/CT scans of NSCLC patients were used for further network training and testing using a 5-fold cross-validation scheme. In these data, manual delineation and labeling of primary tumor and metastases was performed by an experienced physician serving as the ground truth for network training and testing.

Ergebnisse/Results: The derived CNN models are capable of accurate delineation, achieving a Dice similarity coefficient of 0.854. Sensitivity of lesion detection was 0.841 and positive predictive value was 0.847. Accuracy of lesion classification as primary tumor or LN metastases was 82.2%.

Schlussfolgerungen/Conclusions: In this work, we present a CNN able to perform delineation of and discrimination between primary tumor and lymph node metastases in NSCLC with only minimal manual corrections possibly required. It thus is able to accelerate study data evaluation in quantitative PET and does also have potential for clinical application.

The chemistry of actinides (An) is an ongoing subject of current research, particularly with regard to their environmental behaviour and nuclear waste disposal. From a fundamental point of view, the properties of these 5f elements differ significantly from their lanthanide homologues, where the 4f electrons are strongly shielded. Especially for the early actinides Th – Pu, a variety of oxidation states is accessible, ranging from +I to +VII. Furthermore, the 5f electrons are involved in chemical bonding. This results in characteristic magnetic and spectroscopic properties.
Yet, exploration of the coordination chemistry of the actinides significantly lags behind that of transition metals and lanthanides. As such, a fundamental understanding of the binding properties in actinide compounds is still leaving many open questions, as can be illustrated by the limited number of structurally characterized An compounds. Furthermore, previous studies have mainly focused on Th and U and hard donor ligands according to the HSAB principle, such as alkoxides or amines. In order to expand knowledge of the electronic and magnetic properties of the 5f elements, systematic studies of An complexes with different donor atoms on a fundamental level are necessary.
Previous studies have shown that with sulphur as a soft donor, higher covalent contributions can be found in the U-ligand bonds. For the systematic investigation of the An–S binding properties, we synthesized a series of AnIV complexes with the bidentate ligand pyridine-2-thiolate (PyS‾).
Using the complex [U(PyS)₄(THF)] presented by Neu et al. as a blueprint, we established two synthetic routes for the complexation of tetravalent An with PyS‾: a salt metathesis reaction with KPyS and a reaction with PyS–SiMe₃. The obtained compounds of the types [An(PyS)₄(THF)] (An: Th, U, Np, Pu) and K[An(PyS)₅] (An: Th, U) were comprehensively characterized in solution and in solid phase, by single-crystal X-ray diffraction, NMR spectroscopy, HERFD-XANES, and SQUID measurements. Supported by quantum chemical calculations, electronic and magnetic properties of the metal centres as well as bonding trends along the An series (Th – Pu) were investigated.

The 2-pyridyloxy ligand (PyO⁻) has proven to be a useful ligand to isolate heterobimetallic complexes and thus supporting bonds between transition metals (TM) and/or main-group elements. Although interesting coordination motifs can be expected especially with actinides, metal-metal interactions remain a scarce phenomenon in actinide chemistry. Together with the high coordination numbers and various oxidation states, actinide 2-hydroxypyridinolate complexes would have the necessary flexibility to form a variety actinide complexes also containing a transition metal.
Initially, we have synthesised and characterised a series of heteroleptic actinide 2-pyridone complexes [AnCl(HPyO)₇]Cl₃ starting from [AnCl₄(THF)₃] (An = Th, U, Np, Pu). [AnCl(HPyO)₇]Cl₃ complexes were found to be a good candidate to synthesise heterobimetallic complexes by the addition of [TMCl₂(THT)₂] (TM = Pd, Pt; THT = tetrahydrothiophene) and NEt₃ as a supporting base. By this approach, we were able to isolate a series of 8 complexes of the motif [TM(µ-PyO)₄An(µ-PyO)₄TM] (An = Th, U, Np, Pu; TM = Pd, Pt), that allows us to draw comparisons along the tetravalent actinide series and between palladium and platinum. These complexes have been investigated by single-crystal XRD, NMR, HERFD-XANES, and SQUID magnetometry. The experimental findings were supported by quantum chemical calculations, whereby an unexpected trend in An-TM bonding has been observed.

Nonreciprocal coupling can alter the transport properties of material media, producing striking phenomena such as unidirectional amplification of waves, boundary modes, or self-assembled pattern formation. It is responsible for nonlinear convective instabilities in nonlinear systems that drive topological dissipative solitons in a single direction, producing a lossless information transmission. Considering fluctuations, which are intrinsic to every macroscopic dynamical system, noise-sustained structures emerge permanently in time. Here, we study arrays of nonreciprocally coupled bistable systems exhibiting noise-sustained topological phase wall (or soliton) dynamics. The bifurcations between different steady states are analytically addressed, and the properties of the noise-sustained states are unveiled as a function of the reciprocal and nonreciprocal coupling parameters. Furthermore, we study critical points where the structures' characteristic size diverges with different power law exponents. Our numerical results agree with the theoretical findings.

Nonlinear waves are a robust phenomenon observed in complex systems ranging from mechanics to ecology. Fronts are fundamental due to their robustness against perturbations and capacity to propagate one state over another. Controlling and understanding these waves is then fundamental to make use of their properties. Their velocity is one of the most important properties, which can be theoretically computed only in limited conditions of the dynamical system, and it becomes elusive in the presence of spatial discreteness and nonreciprocal coupling. This work reveals that fronts in discrete systems can be treated as rigid objects when analyzing their whole trajectory instead of the instantaneous one. Then, a relationship between the front velocity and its found shape is given. The formula provides insight into fronts' long-observed properties and agrees with the approximative and parameterized methods described in the literature. Numerical simulations show perfect agreement with the theory.

We present a study of hybrid neutron stars with color superconducting quark matter cores at a finite temperature that results in sequences of stars with constant entropy per baryon, s/n_B = const. For the quark matter equation of state, we employ a recently developed nonlocal chiral quark model, while nuclear matter is described with a relativistic density functional model of the DD2 class. The phase transition is obtained through a Maxwell construction under isothermal conditions. We find that traversing the mixed phase on a trajectory at low s/n_B < 2 in the phase diagram shows a heating effect, while at larger s/nB the temperature drops. This behavior may be attributed to the presence of a color superconducting quark matter phase at low temperatures and the melting of the diquark condensate which restores the normal quark matter phase at higher temperatures. While the isentropic hybrid star branch at low s/n_B < 2 is connected to the neutron star branch, it becomes disconnected at higher entropy per baryon so that the “thermal twin” phenomenon is observed. We find that the transition from connected to disconnected hybrid star sequences may be estimated with the Seidov criterion for the difference in energy densities. The radii and masses at the onset of deconfinement exhibit a linear relationship and thus define a critical compactness of the isentropic star configuration for which the transition occurs and which, for large enough s/n_B > 2 values, is accompanied by instability. The results of this study may be of relevance for uncovering the conditions for the supernova explodability of massive blue supergiant stars using the quark deconfinement mechanism. The accretion-induced deconfinement transition with thermal twin formation may contribute to explaining the origin of eccentric orbits in some binary systems and the origin of isolated millisecond pulsars.

Themain ideas to construct theTHSRwave function are given, and the relation to other approaches such as the Brink-type cluster wave function approach is shown. The effect of the Pauli-forbidden states on the inter-cluster potential is described by the orthogonality condition model. The duality of the cluster structure and shell-model structure for nuclei in the ground state and in excited states is discussed.
Future work on nα condensate states inmore complex nuclei and the formation of cluster structures in excited nuclei is outlined.

This Topical Collection of the European Physics Journal A is devoted to recent progress in the nuclear manybody problem. In particular, it aims at a comprehensive compilation of developments related to the work of a pioneer in that field, Peter Schuck, who passed away in 2022. Together with Peter Ring, he co-authored the book on “The Nuclear Many-Body Problem”. Different concepts presented in this seminal book have been elaborated further within a broad international collaboration. For instance, the quasi-particle approaches in connectionwith nuclear superfluidity and cluster formation in nuclear systems, in particular alpha-particle condensation and quartetting at subsaturation densities, have been put forward inspired by Peter Schuck. These advances obtained in the nuclear many-body problem can also be applied to other systems, for instance solid state physics. This Topical Collection is considered as addendum and continuation of the textbook of P. Ring and P. Schuck.

Yb 5Rh6 Sn18 crystallizes with a unique structural arrangement [space group P42 /nmc, a = 9.6997(4) Å, c = 13.7710(7) Å], which is related with primitive cubic Yb 3Rh4 Sn13 and body-centered tetragonal (Sn 1−xTbx) Tb4 Rh6 Sn18 types. X-ray absorption spectroscopy showed that Yb atoms exhibit temperature-dependent valence fluctuations (VF) (i.e., intermediate valence state). Its complex mechanism is corroborated by the fact that the well-pronounced maximum in magnetic susceptibility can only be fairly described by the Bickers–Cox–Wilkins model developed for a J = 3/2 multiplet, atypical for Yb ions. Both Hall and Seebeck coefficients revealed a switch of the sign, indicating the change of charge carrier type from electrons to holes between 120 and 220 K. Both these effects together with electrical resistivity and theoretical DFT calculations confirm Yb5 Rh6Sn18 to be a metal, which disobeys the free electron gas theory. ‘Rattling’ motion of Sn1 atoms within the enlarged 16-vertices distorted Frank–Kasper polyhedra, concluded from the specific heat measurements, is argued to be the main reason for the appearance of a phonon resonance behavior, resulting in an ultra-low thermal conductivity in the studied stannide

Mineral resources are essential for reaching net-zero ambitions by 2050. There is a rising diversity of metals in electricity generation and storage technologies as well as for mobility technologies. However, little is known about the future supply of minor elements historically mined in low volumes such as indium, tellurium, germanium or tantalum. Those minor elements are found in lower concentrations in the ores of major elements and therefore rarely form economic deposits on their own. Those minor elements are generally considered as byproduct of a host (also called “target commodity”, which ensures a sufficient revenue to the mine to be profitable) in an ore, such as tellurium in porphyry ore where copper is the host. As a result, the primary supply of those minor elements depends on the supply of major elements. Such dependency is not yet accounted for in scenarios of minerals supply. To address this gap, we developed a methodology to harmonize scattered data of mineral resources estimates and to calculate the mass ratio between the byproduct and the host in ores and different material flows (concentrates, finished ore) of the primary supply chain, called byproduct-to-host (BtH) ratio. We collected crude ore tonnage and elements grade, among other key data, from state-of-the-art literature and publicly available mining company reports. Our main result is a dataset covering 3422 deposits across 141 countries providing 22 275 BtH ratios. The future supply of those minor elements can be derived by multiplying the primary production of host elements by developed BtH ratios, noting the limitations of data representativity. The open-access nature of this work facilitates the enrichment and update of this dataset in the coming years.

Mostly produced as a by-product of zinc (Zn) mining, cadmium (Cd) is used in solar cells, battery storage, alloys, pigments, plating, and in nuclear reactors. However, it is also a regulated toxic substance with a long history of environmental and health impacts. As the mining of both Zn and Cd will increase to support the global energy transition, the status of Cd as either a resource or a pollutant has major implications for global supply chains and environmental management. Here, we present a new global, site-specific database and analysis of Cd resources in Zn-bearing mineral deposits and mines. Our database, which exceeds past Cd studies in scope, transparency and replicability is made available in full to support future assessments of Cd and Zn resources, mine production and associated risks. It includes 927 sites subject to detailed geological data compilation and analysis. Collectively, these sites suggest a new global resource estimate of 3.3 Mt Cd (95% confidence interval: 2.7 – 6.1 Mt).

A preliminary geospatial analysis of sites in our database and mine toxicity indicators was also conducted. It shows that:

• A human population of approximately 3.27 million live within 10 km of sites containing Cd resources,

• ~31% of the world’s Cd resources sit within 20 km of International Union for the Conservation of Nature (IUCN) protected areas, and

• Some 28% of Cd mobilised annually by mining originates from areas hosting seasonal or permanent surface water cover.

As ~27% of Cd resources are in countries that do not refine it, our study highlights the need for further research exploring global Cd trade flows and associated emissions. Heavy metal pollution in mining and metal production regions is an ongoing challenge, and our global dataset refines our understanding of its magnitude and distribution.

Sphalerite is a trickster with the ability to incorporate a range of elements. Max Frenzel and Samuel Thiele explain how sphalerite’s tricks can be used to explore ore-forming environments and support renewable energy technologies.

The Plaka porphyry Mo-Cu system occurs in the world-class Lavrion Ag-Pb-Zn district in Attica, southern Greece. It is spatially associated with a granodiorite porphyry that intruded the Attic-Cycladic Crystalline Complex in the late Miocene, along the footwall of the Western Cycladic detachment fault. A Re-Os age of 9.51 ± 0.04 Ma indicates that molybdenite formed during the early stage of the granodiorite porphyry intrusion and that subsequent cooling was very rapid. Brittle deformation and hydrothermal fluid flow created a network of A-, B-, diopside-actinolite and D- veins, associated with potassic-, sodic-calcic- and sericitic alterations. Potassic alteration is characterized by secondary biotite + K-feldspar + quartz + magnetite ± apatite, contains disseminated molybdenite, pyrite, and chalcopyrite, and formed at 420–500 °C, at pressures up to 530 bars (< 5.3 km depth) from hydrothermal fluids that underwent phase separation. Sodic-calcic alteration is devoid of Cu-Mo mineralization and, consists of diopside + actinolite + oligoclase/andesine + titanite + magnetite ± epidote-allanite ± chlorite ± quartz, which corresponded to a temperature range of between 350 and < 500 °C. Primary magnetite, titanite and biotite crystallized between the nickel‑nickel oxide (NNO) and hematite-magnetite (HM) buffers, indicating fairly oxidizing conditions for the granodioritic magma. Hydrothermal biotite plots closer to the HM buffer suggesting increasing oxygen fugacity during exsolution of the hydrothermal fluids associated with potassic alteration. The system evolved toward more reducing conditions during sericitic alteration and associated pyrite-molybdenite mineralization. A combination of evaporated seawater and magmatic fluids likely caused formation of the sodic-calcic alteration through the decarbonation of the host marble

Curvilinear magnetism emerged as a new route to tailor properties of magnetic solitons by the choice of geometry and topology of a magnetic architecture. Here, we develop an anodized aluminum oxide template-based approach to realize hierarchical 3D magnetic nanoarchitectures of nanoflower shape. The technique provides defect-free regular arrays of magnetic nanoflowers of tunable shape with a period of 400\,nm over cm$^2$ areas. We combined advanced magnetic imaging methods with micromagnetic simulations to study complex magnetic states in nanoflowers originated due to magnetostatics-driven symmetry break in curvilinear nanomembranes. An interaction between surface and volume magnetostatic charges in 3D curved nanoflowers leads to the stabilization of asymmetric and shifted vortices as well as states with two Bloch lines. Ordered large area arrays of complex-shaped magnetic nanoarchitectures developed in this work are relevant for prospective research on 3D magnonics and spintronics.

Germanium (Ge) is a critical raw material for emerging high-tech and green industries, resulting in considerable recent interest in understanding its distribution and geochemical behavior in ore deposits. In this contribution, the distribution of Ge and related trace elements in the Fule Pb-Zn(-Ge) deposit, South China, is investigated to reveal the distribution of Ge in the hydrothermal ores and during sulfide weathering, using multiple microanalytical techniques, including scanning electron microscopy, electron probe microanalysis and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). In the Fule MVT deposit, sphalerite (ZnS) is the most significant Ge-carrier relative to other sulfides, though the five recognized textural types of sphalerite display progressive depletion in Ge from the first sphalerite generation to the late one. In the early stage, sphalerite with fine-grained chalcopyrite inclusions has the highest Ge concentrations, probably accounting for a significant proportion of the total Ge. We interpret that high Ge concentrations in the early sphalerite may be attributable to high Cu activity in the mineralizing fluids. During oxidative weathering, Ge was redistributed from its original host, sphalerite, to the weathering product willemite (Zn2SiO4) rather than smithsonite (ZnCO3), with high levels of Ge (up to 448 μg/g) present in the willemite. The formation of abundant willemite largely prevents the dispersion of Ge during weathering. In principle, willemite-hosted Ge should be fully recoverable, and the Zn-silicate ores may, therefore, be a potential target to meet future demand.
This study provides new information on how Ge behaves from sulfide- to weathering-stage in MVT systems, which directly impacts Ge mobility and deportment changes and the development of metallurgical strategies for Ge recovery.

The Irish Orefield is characterised by the presence of both Zn-Pb- and Cu-Ni-As-rich deposits, prospects, and orebodies in similar structural and stratigraphic positions. However, the genetic relationships between these mineralisation types are still debated. In this article, we present new mineralogical, paragenetic, and mineral-chemical observations from the Cu-Ni-As-rich ores at the classic Lisheen deposit, County Tipperary. These observations indicate the intimate association and cogenetic nature of these ores with the more abundant Zn-Pb-rich mineralisation. Specifically, both mineralisation types appear to have formed at the same time, under similar physicochemical conditions, and from the same ore fluids. In addition, both types of mineralisation contain elevated Ge contents. The cogenetic nature of the two mineralisation types, the relative absence of Cu-Ni-As-rich ores from most of the larger Irish-type Zn-Pb deposits compared to expectations derived from probable ore fluid compositions, and finally, the known geological characteristics of larger Cu-Ni-As-rich ore bodies, like Gortdrum, indicate that significant Cu-Ni-As-rich mineralisation could be present at lower stratigraphic levels across the Irish Orefield. Areas with extensive known Zn-Pb mineralisation are expected to be particularly prospective for such ores, which may occur at stratigraphic levels as deep as the Old Red Sandstone. This may have additional implications beyond Ireland, and could point to the potential for undiscovered Cu-rich ores in low-temperature carbonate-hosted Zn-Pb districts elsewhere.

KI-Modelle haben die Softwareindustrie, Wissenschaft und Gesellschaft in den letzten Jahren im Sturm erobert. Ihre Vorhersagen sind teilweise besser als menschliche Fähigkeiten und teilweise unverholens realitätsfern oder falsch. Aber wie können wir die Qualität der Vorhersagen einschätzen ohne gleich Use-Cases abzuschreiben oder blind KI-Methoden verbannen? In diesem Impuls möchte ich mich genau dieser Frage stellen. Meine Antwort heißt "Uncertainty Quantification". Ich werde diesen Zweig der KI-Methodik motivieren und aktuelle Ergebnisse aus der Forschung geben.

Triangulene (TRI) and its heterotriangulene (HT) derivatives are planar, triangle-shaped
molecules that, via suitable coupling reactions, can form extended organic two-dimensional
(2D) crystal (O2DC) structures. While TRI is a diradical, HTs are either closed-shell molecules
or monoradicals which can be stabilized in their cationic form.
Triangulene-based O2DCs have a characteristic honeycomb-kagome lattice. This structure
gives rise to four characteristic electronic bands, two of them forming Dirac points, while the
other two are flat and sandwich the Dirac bands. Functionalization and heteroatoms are suitable
means to engineer this band structure. Heteroatoms like boron and nitrogen shift the Fermi
level up and downwards, respectively, while bridging groups and functionalized triangulene
edges can introduce a dispersion to the flat bands.
The stable backbone architecture makes 2D HT-polymers ideal for photoelectrochemical
applications: (i) bridge functionalization can tune the band gap and maximize absorption, (ii)
the choice of the center atom (B or N) controls the band occupation and shifts the Fermi level
with respect to vacuum, allowing in some cases for overpotential-free photon-driven surface
reactions, and (iii) the large surface area allows for a high flux of educts and products.
The spin polarization in TRI and in open-shell HTs is maintained when linking them to
dimers or extended frameworks with direct coupling or more elaborate bridging groups
(acetylene, diacetylene, and phenyl). The dimers have a high spin-polarization energy and some
of them are strongly magnetically coupled, resulting in stable high-spin or broken-symmetry
(BS) low-spin systems. As O2DCs, some systems become antiferromagnetic Mott insulators
with large band gaps, while others show Stoner ferromagnetism, maintaining the characteristic
honeycomb-kagome bands, but shifting the opposite spin-polarized bands to different energies.
For O2DCs based on aza- and boratriangulene (monoradicals as building blocks), the Fermi
level is shifted to a spin-polarized Dirac point, and the systems have a Curie temperature of
about 250 K. For half-filled (all-carbon) systems, the Ovchinnikov rule, or, equivalently, the
Lieb’s theorem, is sufficient to predict the magnetic ordering of the systems, while the non-
half-filled systems ones (i.e., those with heteroatoms) obey the more involved Goodenough-
Kanamori rule to interpret the magnetism on grounds of fundamental electronic interactions.
There remain challenges in experiment and in theory to advance the field of triangulene-
based O2DCs: Coupling reactions beyond surface chemistry have to be developed to allow for
highly ordered, extended crystals. Multilayer structures, which are unexplored to date, will be
inevitable in alternative synthesis approaches. The predictive power of density-functional
theory (DFT) within state-of-the-art functionals is limited for the description of magnetic
couplings in these systems due to the apparent multi-reference character and the large spatial
extension of the spin centers.

Multinary nitrides and oxynitrides offer a range of tunable structural and optoelectronic properties. However, much of this vast compositional space remains to be explored due to the challenges associated with their synthesis. Here, reactive sputter deposition is used to synthesize isostructural polycrystalline zirconium tantalum oxynitride thin films with varying cation ratios and systematically explore their structural and optical properties. All films possess the cubic bixbyite-type structure and n-type semiconducting character, as well as composition-tunable optical bandgaps in the visible range. Furthermore, these compounds exhibit remarkably high refractive indices that exceed a value 2.8 in the non-absorbing sub-bandgap region and reach 3.2 at 589 nm for Ta-rich compositions. Photoemission spectroscopy reveals non-uniform shifts in electron binding energies that indicate a complex interplay of structural and compositional effects on interatomic bonding. In addition to being high-index materials, the measured band edge positions of the films align favorably with the water oxidation and reduction potentials. Thus, this tunable materials family offers prospects for diverse optoelectronics application, including for production of photonic metamaterials and for solar water splitting.

For research data please contact the corrsponding author. Data publications from research of Freiberg University of Mining and Technology can be found here: http://opara.zih.tu-dresden.de/handle/123456789/21.

One mode of biomolecular self-organization in aqueous environments is compartmentalization through liquid-liquid phase separation into biomolecular condensates. These condensates are created through transient, multivalent interactions between intrinsically disordered proteins. The formation of such condensates involves extensive rearrangement of the water network, including stripping away of the protein solvation shell. This work aims to find out how the dynamics of the hydrogen bond network within biomolecular condensates are modulated by co-solutes and amino acid level chemical modifications of the protein. The effects of post-translational (added in the cell after the polypeptide chain is synthesized) modifications and salts on the water network inside condensates formed by the Fused in Sarcoma (FUS) protein have been studied using Terahertz (THz) spectroscopy. This spectroscopic method probes the intermolecular hydrogen bonding network of water and reports on the protein hydration water. A comparison of spectra of FUS with added monovalent and divalent chloride salts was performed. The phase behavior of FUS shows a non-monotonic trend with respect to salt concentration, where the protein undergoes a salt-dependent reentrant phase transition. Comparison of THz spectra between the droplets formed in the low ionic strength and high ionic strength regime show a significant change in the amount of hydrophobic hydration water. Post-translational modifications were found to introduce new sub-environments of hydration water in the condensates, which disappeared in the high salt regime. These findings show, that the hydration network within biomolecular condensates is more rigid and structured in the presence of biologically introduced chemical modifications of the protein, and that a high salt concentration abolishes this effect, possibly through weakening the hydrogen bonding between water and protein.

Many proteins containing disordered regions are known to form structures called biomolecular condensates. These biomolecule-rich phases form through multivalent interactions, and allow the cell to compartmentalize its contents without lipid membranes. For a complete picture of these structures, the role of hydration effects must be considered, as it has been shown to play a key role in the formation of multiple other macromolecular structures. It is possible to study the hydration within condensates using Terahertz (THz) spectroscopy, a method using electromagnetic waves on the cusp of infrared and microwave radiation. Radiation in this range is resonant with the vibrations of hydrogen bonds between water molecules.
In the presented work, THz spectroscopy has been used to study the effects of a range of monovalent and multivalent salt ions on the solvation changes happening during condensate formation. Typically, biomolecular condensation is inhibited by salts due to the screening of electrostatic interactions. However, the protein used in this study, Fused in Sarcoma (FUS), shows a reentrant phase transition at very high salt concentrations, where the threshold concentration depends on the type of ion present. Droplets forming under these conditions show unique spectral features corresponding to the changes in the hydration of hydrophobic residues. These results seem to corroborate the hypothesis that the return of phase separation under high salt conditions is caused by the ion induced enhancement of hydrophobic interactions.

Liquid-liquid phase separation (LLPS) of macromolecules stimulates the formation of biomolecular condensates. The RNA-binding protein fused in sarcoma (FUS) undergoes phase separation, which is associated with intrinsically disordered regions (IDRs), and is enhanced in the low salt regime.[1] Although the mechanism of FUS LLPS is understood, its thermodynamic properties are known to a lesser extent. Previous studies on the thermodynamic properties of FUS were conducted using MD simulations, which do not directly measure heat. [2] Isothermal titration calorimetry (ITC) measures the heat of reactions of FUS as it undergoes LLPS in the low salt conditions. Results showed that the heat produced for FUS phase separation is temperature dependent. At the lowest temperature studied, the molar enthalpy suggests an exothermic process. As temperature increased, the process became endothermic. Upon phase separation, the thermal equilibrium baseline was not recovered, indicating a change in energetics.
Furthermore, combining ITC and microscopy, the effects of ATP concentration on the thermodynamic properties and morphological studies of FUS condensates were explored. Previous studies showed that ATP dissolves the previously formed condensates at average cellular concentrations. [3] However, microscopy images collected here reveal that the condensates assume fibril-like shapes rather than their usual spherical form when ATP was added. This distortion in shape may be due to the absence of Mg2+ ions in the solution. Furthermore, the impact of temperature on FUS condensate thermodynamics was explored, and it was observed that exothermic properties decrease as the temperature rises. The binding between ATP and FUS is estimated to be weaker because of the lower binding affinity values. These findings provide valuable insights into the thermodynamics of FUS and highlight the crucial role that temperature plays in phase separation.

ROCK-IT is a collaboration which aims to demonstrate the ability to perform complex operando catalysis experiments in a highly automated way, enabling remote operation. The project finds common solutions between different facilities which have various control systems and infrastructure. Ophyd provides a common abstraction layer to Tango, EPICS and SECoP. In the demonstrators of this project, Bluesky is used to orchestrate experiments which involve simultaneous control of a sample environment and various measurement techniques. In this presentation the challenges associated with controlling such an experiment will be presented and the proposed solutions explored.

Nonlinear THz transmission is utilized to investigate the solvation dynamics of proteins. Protein structure and function are inherently dependent on their solvation shell, and an understanding of the underlying solvation dynamics provides valuable insight into how solute-solvent interactions impact biophysical processes. Here, the results of concentration dependent z-scan experiments are reported.

The interaction between nucleotide molecules and lipid molecules plays important roles in cell activities, but the molecular mechanism is very elusive. In the present study, a small but noticeable interaction between the negatively charged phosphatidylethanolamine (PE) and Guanosine monophosphate (GMP) molecules was observed from the PE monolayer at the air/water interface. As shown by the sum frequency generation (SFG) spectra and Pi-A isotherm of the PE monolayer, the interaction between the PE and GMP molecules imposes very small changes to the PE molecules. However, the Brewster angle microscopy (BAM) technique revealed that the assembly conformations of PE molecules are significantly changed by the adsorption of GMP molecules. By comparing the SFG spectra of PE monolayers after the adsorption of GMP, guanosine and guanine, it is also shown that the hydrogen bonding effect plays an important role in the nucleotide-PE interactions. These results provide fundamental insight into the structure changes during the nucleotide-lipid interaction, which may shed light on the molecular mechanism of viral infection, DNA drug delivery, and cell membrane curvature control in the brain or neurons.

High-power coherent terahertz (THz) radiation from accelerator facilities such as free-electron lasers (FELs) is frequently used in pump-probe experiments where the pump or probe (or both) signals are intense THz pulses. Detectors for these applications have unique requirements that differ from those of low-power table-top systems. In this study, we demonstrate GaAs antenna-coupled field effect transistors (FETs) as a direct THz detector operating across a broad frequency spectrum ranging from 0.2 THz to 29.8 THz. At approximately 0.5 THz, the maximum current responsivity (ℜ I) of 0.59 mA/W is observed, signifying a noise equivalent power (NEP) of 2.27 nW/√H z. We report an empirical roll-off of f −3 for an antenna-coupled GaAs TeraFET detector. Still, NEP of 0.94 μW/√H z and a current responsivity ℜ I = 1.7μA/W is observed at 29.8 THz, indicating that with sufficient power the FET can be used from sub-mm wave to beyond far-infrared frequency range. Current and voltage noise floor of the characterized TeraFET is 2.09 pA and 6.84 μV, respectively. This characteristic makes GaAs FETs more suitable for applications requiring higher frequencies, ultra-broadband capabilities and robustness in the THz domain, such as beam diagnostics and alignment at particle accelerators.

RE-doped β-Ga₂O₃ seems attractive for future high-power LEDs operating in high irradiation environments. In this work, we pay special attention to the issue of radiation-induced defect anisotropy in β-Ga₂O₃, which is crucial for device manufacturing. Using the RBS/c technique, we have carefully studied the structural changes caused by implantation and post-implantation annealing in two of the most commonly used crystallographic orientations of β-Ga₂O₃, namely the (-201) and (010). The analysis was supported by advanced computer simulations using the McChasy code. Our studies reveal a strong dependence of the structural damage induced by Yb-ion implantation on the crystal orientation, with a significantly higher level of extended defects observed in the (-201) direction than for the (010). In contrast, the concentration and behavior of simple defects seem similar for both oriented crystals, although their evolution suggests the co-existence of two different types of defects in the implanted zone with their different sensitivity to both, radiation and annealing. It has also been found that Yb ions mostly occupy the interstitial positions in β-Ga₂O₃ crystals that remain unchanged after annealing. The location is independent of the crystal orientations. We believe that these studies noticeably extend the knowledge of the radiation-induced defect structure, because they dispel doubts about the differences in the damage level depending on crystal orientation, and are important for further practical applications.

The project “Recycling of mineral fractions from tailings” aims to separate pollutants and valuable materials tailings from tailings. The use of remaining mineral fractions for building materials as a secondary raw material is made possible. Bioleaching is used to extract metal, especially lead, mineral fraction, which have been recovered by flotation from tailings. The metals can be released from the mineral through microbial catalyzed redox reactions or complex formation. For this purpose, the mineral fractions were incubated with sulfur-oxidizing bacteria, microorganisms that form low-molecular organic acids and with low-molecular organic acids. After acidophilic bioleaching, manganese (approx. 2 g/l), iron (approx. 8.5 g/l) and zinc (approx. 1 g/l) were detected in the leaching solution. In a second campaign, microorganisms that produce low molecular weight organic acids were used and the growth of these microorganisms was inhibited. Easily mobilizable amounts of zinc and copper were identified as the reasons for this. In a third series of experiments culture supernatants with desired low molecular weight organic acid were used for leaching. This procedure allowed between 30 and 40% of the lead contained in the mineral fraction were leached.

Conventional mining and extraction methods for REEs are energy-intensive and environmentally harmful. Bioleaching processes offer a promising and eco-friendly approach to enhance the sustainability of REE extraction. This study evaluates the potential of bioleaching REEs from unprocessed carbonatitic and alkaline bulk rocks. Bioleaching experiments were conducted on a Carbonatite sample from the Fen-Complex (Norway) and two nepheline syenites (a Grennaite and a pegmatitic Grennaite from Norra Kärr, Sweden), utilizing the heterotrophic organisms Yarrowia lipolytica DSM3286 and Tea fungus Kombucha.
The results demonstrate varying recovery rates based on mineralogy and leaching methods, with preferential leaching of light or heavy REEs depending on the selected organisms. Notably, the highest leaching efficiency of 54% REE recovery was achieved with Y. lipolytica DSM3286 supernatant leaching on pegmatitic Grennaite during a 19-day experiment. Carbonatite and Grennaite samples exhibited lower maximum leaching rates of 5% and 8%, respectively. The findings demonstrate the proof-of-concept feasibility of bioleaching REEs from unprocessed bulk rock materials and highlight its strong potential, especially in providing a sustainable solution for utilizing low-grade ores and mine waste.

On the basis of an exact power history and accurate geometric modelling, plant-specific neutron fluences were calculated for in each case a pre- and convoy unit of German nuclear power plant for reactor components and for concrete and structural elements close to the reactor. These neutron fluences are the basis for determining the generated activation of the construction materials during the power operation of the plant. The calculations were supported by an extensive measurement program in the last cycles of two plants, where neutron fluence values were determined ex-perimentally with the help of activation foils (monitors). A spectral analysis was possible by using different monitor materials. The monitors were measured by gam-ma spectrometry after sampling using a high-purity germanium (HP-Ge) detector. The comparison of the calculated and measured activities shows, with a few excep-tions, good to very good agreement between the values. This means that the real ratios of neutron radiation in the elements were calculated very well and the method and model can be used to determine the activity distribution.
Due to the possibility of the accurate simulation of the resulting activities on the ba-sis of these "best estimate" calculations, detailed planning of the decommissioning can already begin during the operation of the plant. It is not necessary to wait until extensive sampling after the shutdown.
In addition, the accurate mathematical determination of the activity distribution in the components enables improved cut planning and thus minimization of the waste volume for the final storage. A further advantage would be that the necessary exper-imental activity determinations could be reduced to a few samples thanks to the supporting experiments and thereby validated neutron fluence calculations.

Motivated by the exceptional optoelectronic properties of 2D Janus layers (JLs), we explore the properties of group Va antimony-based JLs SbXY (X=Se/Te, Y=I/Br). From the Bader charges, the electric dipole moment in the out-of-plane direction of all the JLs is studied and the largest dipole moment is found to be in the SbSeI JL. Our results on the formation energy, phonon spectra, elastic constants, and ab initio molecular dynamic (AIMD) simulation, predict the energetic, vibrational, mechanical, and thermal stability of JLs. After confirming the stability, the three-dimensional phase diagram is investigated to propose the experimental conditions required to fabricate the predicted JLs. Then, the electronic band structure is calculated using different levels of theory namely generalized gradient approximation (GGA), GGA+ spin-orbit coupling (GGA+SOC), hybrid Heyd-Scuseria-Ernzerhof (HSE), and many-body perturbation theory-based Green’s function method (GW). According to the HSE results, JLs show band gaps between 1.653 and 1.852 eV. The GGA+SOC calculations reveal Rashba spin splitting in these JLs. The calculated carrier mobility using deformation potential theory shows that the electrons have exceptionally high mobility compared to holes, which assists the spatial separation of both charge carriers. The optical spectra are determined using GGA, HSE, and GW methods. With respect to GGA results, HSE and GW optical spectra show a blue shift. More accurate calculations by the GW-Bethe Salpeter equation (BSE) yield optical absorption spectra which are dominated by strong excitonic effects with excitonic binding energy (BEex) in the range of 550-800 meV. Compared to GW-BSE, the Mott-Wannier (MW) model predicts lower BEex. The strong e-h coupling is observed for dispersions along K −M in the Brillouin zone from the fat band analysis. From our study, SbSeI JL is a potential candidate for photocatalytic and photovoltaic applications due to its largest dipole moment and low excitonic binding energy.

We present a comprehensive theoretical analysis of the structural and electronic properties of a van der Waals heterostructure composed of CdS and α-Te single layers (SLs). The investigation includes an in-depth study of fundamental structural, electronic, and optical properties with a focus on their implications for photocatalytic applications. The findings reveal that the α-Te SL significantly influences the electronic properties of the heterostructure. Specifically, the optical property of the heterostructure is notably dominated by the contribution of α-Te. The layer-resolved density of states analyses indicate that the valence and conduction bands near the Fermi level are mainly determined by the α-Te SL. Band edge analyses demonstrate a type-I band alignment in the heterostructure, causing charge carriers (electrons and holes) to localize within α-Te. The electronic properties can be further modulated by external strain and electric fields. Remarkably, the CdS-α-Te heterostructure undergoes a transition from type-I to type-II band alignment when subjected to biaxial strain and an external electric field. This may be interesting for the application of the heterostructure for photocatalysis.

Layered framework materials, a rapidly advancing class of porous materials, are composed of molecular components stitched together via covalent bonds and are usually synthesized through wet-chemical methods. Computational infrared (IR) and Raman spectra are among the most important characterization tools for this material class. Besides the a priori known spectra of the molecular building blocks and the solvent, they allow for in situ monitoring of the framework formation during synthesis. Therefore, they need to capture the additional peaks from host–guest interactions and the bands from emerging bonds between the molecular building blocks, verifying the successful synthesis of the desired material. In this work, we propose a robust computational framework based on ab initio molecular dynamics (AIMD), where we compute IR and Raman spectra from the time-correlation functions of dipole moments and polarizability tensors, respectively. As a case study, we apply our methodology to a covalent organic framework (COF) material, COF-1, and present its AIMD-computed IR and Raman spectra with and without 1,4-dioxane solvent molecules in its pores. To determine robust settings, we meticulously validate our model and explore how stacking disorder and different methods for computing dipole moments and polarizabilities affect IR and Raman intensities. Using our robust computational protocol, we achieve excellent agreement with experimental data. Furthermore, we illustrate how the computed spectra can be dissected into individual contributions from the solvent molecules, the molecular building blocks of COF-1, and the bonds connecting them.

The emerging laser writing represents an efficient and promising strategy for covalent two dimensional (2D)-patterning of graphene yet remains a challenging task due to the lack of applicable reagents. Here, we report a versatile approach for covalent laser patterning of graphene using a family of trivalent organic iodine compounds as effective reagents, allowing for the engraving of a library of functionalities onto the graphene surface. The relatively weak iodine-centered bonds within these compounds can readily undergo laser-induced cleavage to in situ generate radicals localized to the irradiated regions for graphene binding, thus completing the covalent 2D-structuring of this 2D-film. The tailor-made attachment of distinct functional moieties with varying electrical properties as well as their thermally reversible binding manner enables programming the surface properties of graphene. With this delicate strategy the bottleneck of a limited scope of functional groups patterned onto the graphene surface upon laser writing is tackled.

Ferromagnetism and antiferromagnetism require robust long-range magnetic ordering, which typically involves strongly interacting spins localized at transition metal atoms. However, in metal-free systems, the spin orbitals are largely delocalized, and weak coupling between the spins in the lattice hampers long-range ordering. Metal-free magnetism is of fundamental interest to physical sciences, unlocking unprecedented dimensions for strongly correlated materials and biocompatible magnets. Here, we present a strategy to achieve strong coupling between spin centers of planar radical monomers in π-conjugated two-dimensional (2D) polymers and rationally control the orderings. If the π-states in these triangulene-based 2D polymers are half-occupied, then we predict that they are antiferromagnetic Mott-Hubbard insulators. Incorporating a boron or nitrogen heteroatom per monomer results in Stoner ferromagnetism and half-metallicity, with the Fermi level located at spin-polarized Dirac points. An unprecedented antiferromagnetic half-semiconductor is observed in a binary boron-nitrogen–centered 2D polymer. Our findings pioneer Stoner and Mott-Hubbard magnetism emerging in the electronic π-system of crystalline-conjugated 2D polymers.

The diabolical problem of pentagonal symmetry was already highlighted by the German polymath and writer Johann Wolfgang von Goethe around 1800: “The Pentagramma is causing you pain?” Faust asked Mephistopheles in the famous tragic play Faust. Indeed, among the many ways to tile the Euclidean plane, there is none incorporating regular pentagons1. The Cairo tessellation (Fig. 1a) is a possibility to completely fill two-dimensional (2D) space using congruent, albeit irregular, pentagons. In this 2D lattice, four pentagons can be combined to form a stretched hexagon of D2h symmetry (Fig. 1b), and this symmetry, again, can be mapped to a Truchet lattice2 made of squares decorated by a pattern of D2h symmetry, which is rotated by 90° in each neighbour (Fig. 1c). This arrangement is easily mapped to a regular square periodic cell (Fig. 1d). This turns the pentagon problem, at least in part, back into square or hexagon problems. Materials with the peculiar structure of the Cairo pentagonal lattice may have highly in-plane anisotropic properties with strong dependence on strain3,4, high carrier mobilities and slanted Dirac cones, which open a playground for condensed-matter physicists. However, materials with pentagonal lattices are rare, as most of them are predicted to be unstable or metastable. This is caused by the odd number of vertices in the pentagonal ring, and by the irregularity of the congruent pentagons. Notable exceptions predicted include the noble metal dichalcogenides PdS2 and PdSe2 (ref. 3). The PdSe2 monolayer with Cairo tessellation has been realized by micromechanical exfoliation from its orthorhombic bulk5. Most pentagonal noble metal dichalcogenides are, however, unstable or metastable3, and none of these forms has been realized experimentally so far. Now, writing in Nature Materials, Lina Liu and colleagues report a way to realize metastable 2D PdTe2 with the pentagonal Cairo lattice6.

While moiré structures in twisted bilayer transition metal dichalcogenides (TMDCs) have been studied for over a decade, the importance of lattice relaxation effects was pointed out only in 2021 by DiAngelo and MacDonald1, who reported the emergence of a Dirac cone upon relaxation. TMDCs of group 6 transition metals MX2 (M = Mo, W, X = S, Se) share layered structures with pronounced interlayer interactions, exhibiting a direct band gap when exfoliated to a two-dimensional (2D) monolayer. As their heterolayers are incommensurable, moiré structures are present in the bilayers even if stacked without a twist angle. This study addresses the challenge of accurately modeling and understanding the structural relaxation in twisted TMDC heterobilayers. We show that the typical experimental situation of finite-size flakes stacked upon larger flakes can reliably be modeled by fully periodic commensurate models. Our findings reveal significant lattice reconstruction in TMDC heterobilayers, which strongly depend on the twist angle. We can categorize the results in two principal cases: at or near the untwisted configurations of 0° and 60°, domains with matching lattice constants form and the two constituting layers exhibit significant in-phase corrugation—their out-of-plane displacements are oriented towards the same direction in all local stackings—while at large twist angles—deviating from the 0° and 60°—the two layers show an out-of-phase corrugation. In particular, we reveal that the lattice reconstruction results from the competition between the strain energy cost and the van der Waals energy gain. Additionally, our systematical study highlights structural disparities between heterostructures composed of different or identical chalcogen atoms. Our research not only confirms the reliability of using periodic commensurate models to predict heterostructure behavior but also enriches the understanding of TMDC bilayer heterostructures.

Exotic band features, such as Dirac cones and flat bands, arise directly from the lattice symmetry of materials. The Lieb lattice is one of the most intriguing topologies, because it possesses both Dirac cones and flat bands which intersect at the Fermi level. However, the synthesis of Lieb lattice materials remains a challenging task. Here, we explore two-dimensional polymers (2DPs) derived from zinc-phthalocyanine (ZnPc) building blocks with a square lattice (sql) as potential electronic Lieb lattice materials. By systematically varying the linker length (ZnPc-xP), we found that some ZnPc-xP exhibit a characteristic Lieb lattice band structure. Interestingly though, fes bands are also observed in ZnPc-xP. The coexistence of fes and Lieb in sql 2DPs challenges the conventional perception of the structure–electronic structure relationship. In addition, we show that manipulation of the Fermi level, achieved by electron removal or atom substitution, effectively preserves the unique characteristics of Lieb bands. The Lieb Dirac bands of ZnPc-4P shows a non-zero Chern number. Our discoveries provide a fresh perspective on 2DPs and redefine the search for Lieb lattice materials into a well-defined chemical synthesis task

Porphyrins are excellent light-harvesting complexes. Presently they are unsuitable for photovoltaic applications, as their excellent light absorbance is compensated to a large extent by their poor transport properties, where most excitons are lost by recombination. Arranging porphyrins in regular, strongly bound, lattices of surface-anchored metal-organic frameworks (PP-SURMOFs) may facilitate charge carrier dissociation, but does not significantly enhance the conductive properties. In most cases, photogenerated excitons traverse undirected, Brownian motion through a hopping process, resulting in a substantial diffusion length to reach electrodes, leading to significant exciton loss through recombination. Here, we propose to guide exciton diffusion indirectly by an external electric field. We show that electric fields, even as strong as 1 V nm−1, do not affect the HOMO-LUMO gap of the porphyrins. However, fields of 0.1 V nm−1 and even less demonstrate a notable Stark effect, with slight band gap reductions, for some PP-SURMOFs. When applied as an electric field gradient, for instance, via the substrate, it creates a unidirectional hopping pathway for the excitons. Consequently, we expect a significant reduction of exciton diffusion length leading to increased utilization of photogenerated excitons as they reach the electrodes. This strategy holds promise for integrating photoactive molecules in photovoltaic and photocatalytic applications.

2D conjugated metal–organic frameworks (2D c-MOFs) are emerging as unique electroactive materials for electronics and spintronics. The structural design and discovery of Kagome-type 2D c-MOFs exhibiting a metallic state are of paramount significance, yet remain rarely explored. Here, the solution synthesis of benzenehexol-based 2D c-MOFs based is presented on the tetrahydroxy-1,4-quinone (THQ) ligand. This study shows that controlling the pH of the reaction system to ≈7.5 yields an energetically favorable nonporous Cu3(C6O6) with a Kagome lattice, while at a pH of ≈10, the known porous Cu3(C6O6)2 with a honeycomb lattice is obtained. The crystal structures of both Cu3(C6O6)2 and Cu3(C6O6) are resolved with near-atomic precision (resolution, 1.8 Å) using an imaging technique. Unlike the p-type semiconducting behavior of Cu3(C6O6)2, theoretical studies identify Cu3(C6O6) as a metal due to its unique structural topology. The metallic state of Cu3(C6O6) is experimentally validated by terahertz time-domain spectroscopy (THz-TDS), which shows an increase in conductivity upon cooling. Scattering-type scanning near-field optical microscopy (s-SNOM) measurements further support these findings by revealing an increase in normalized reflectivity with decreasing temperature. This work provides a new avenue for tailoring the structural topology of 2D c-MOFs to attain the Kagome lattice and metallic state.

Electron beam accelerators are essential in many scientific and technological fields. Their operation relies heavily on the stability and precision of the electron beam. Traditional diagnostic techniques encounter difficulties in addressing the complex and dynamic nature of electron beams. Particularly in the context of free-electron lasers (FELs), it is fundamentally impossible to measure the lasing-on and lasingoff electron power profiles for a single electron bunch. This is a crucial hurdle in the exact reconstruction of the photon pulse profile. To overcome this hurdle, we developed a machine learning model that predicts the temporal power profile of the electron bunch in the lasing-off regime using machine parameters that can be obtained when lasing is on. The model was statistically validated and showed superior predictions compared to the state-of-the-art batch calibrations. The work we present here is a critical element for a virtual pulse reconstruction diagnostic (VPRD) tool designed to reconstruct the power profile of individual photon pulses without requiring repeated measurements in the lasing-off regime. This promises to significantly enhance the diagnostic capabilities in FELs at large.

Two-dimensional group 6 transition metal dichalcogenide (2D TMDC) bilayers show various high-symmetry stacking configurations, which have also been observed in extended domains formed in their twisted homo- and heterobilayers. The interlayer energy varies for these stacking configurations, and the energy differences determine the relative size of the stacking domains. Therefore, the precise prediction of the composition- and stacking-dependent interlayer energy is crucial to model the domain structure of 2D TMDCs in their twisted bilayer homo- and heterostructures. For the validation of approximate methods that are necessary to tackle these systems encompassing thousands of atoms precise reference data is still lacking. Here, we employ the random phase approximation (RPA) on previously validated SCAN-rVV10 geometries to obtain interaction energies of state-of-the-art accuracy on the six high-symmetry stacking configurations of MX2 (M = Mo, W; X = S, Se) bilayers and compare them with the dispersion-corrected density-functional theory (DFT) functionals Perdew–Burke–Ernzerhof (PBE)+D3(BJ), PBE-rVV10L, and SCAN-rVV10. We identify SCAN-rVV10 as most reliable DFT variant with an average deviation of 1.2 meV/atom in relative energies from the RPA reference, and a root mean squared error of less than 2 meV/atom for interlayer interaction energies. We find interlayer distances obtained by PBE+D3(BJ) as being too short, with an impact on the electronic structure, resulting in the incorrect prediction of the band gap character in some cases. A further result of this work is the significant lowering of the interlayer energy and increasing of the interlayer distance in the high-energy stacking configurations. These stackings can be accessible via shear strain and promote exfoliation.

Taking into account the electron-rich and visible light response of thiophene, first-principles calculations have been carried out to explore the photocatalytic activity of donor–acceptor polymers incorporating thiophene and boron. Honeycomb-kagome boron–thiophene (BTP) polymers with varying numbers of thiophene units and fixed B center atoms are direct bandgap semiconductors with tunable bandgaps ranging from 2.41 to 1.88 eV and show high absorption coefficients under the ultraviolet and visible regions of the solar spectrum. Fine-tuning the band edges of the BTP polymer is efficiently achieved by adjusting the pore size through the manipulation of thiophene units between the B centers. This manipulation, achieved without excessive chemical functionalization, facilitates the generation of an appropriate quantity of photoexcited electrons and/or holes to straddle the redox potential of the water. Our study demonstrates that two units between B centers of thiophene in BTP polymers enable overall photocatalytic water splitting, whereas BTP polymers with larger pores solely promote photocatalytic hydrogen reduction. Moreover, the thermodynamics of hydrogen and oxygen reduction reactions either proceed spontaneously or need small additional external biases. Our findings provide the rationale for designing metal-free and single-material polymer photocatalysts based on thiophene, specifically for achieving efficient overall water splitting.

Electron beam accelerators are essential in many scientific and technological fields. Their operation relies heavily on the stability and precision of the electron beam. Traditional diagnostic techniques encounter difficulties in addressing the complex and dynamic nature of electron beams. Particularly in the context of free-electron lasers (FELs), it is fundamentally impossible to measure the lasing-on and lasingoff electron power profiles for a single electron bunch. This is a crucial hurdle in the exact reconstruction of the photon pulse profile. To overcome this hurdle, we developed a machine learning model that predicts the temporal power profile of the electron bunch in the lasing-off regime using machine parameters that can be obtained when lasing is on. The model was statistically validated and showed superior predictions compared to the state-of-the-art batch calibrations. The work we present here is a critical element for a virtual pulse reconstruction diagnostic (VPRD) tool designed to reconstruct the power profile of individual photon pulses without requiring repeated measurements in the lasing-off regime. This promises to significantly enhance the diagnostic capabilities in FELs at large.

The GaAs based diluted magnetic semiconductor, (Ga, Mn)As, with the unique advantage of manipulating the spin and charge was widely investigated in the scientific community and considered as a potential material for the spintronic devices. However, its Curie temperature (Tc), which is limited to around 200 K, hinders the research progress of diluted magnetic semiconductors for potential device applications. Herein, we propose an approach to prepare the MnGa nanoparticles embedded in (Ga, Mn)As matrix using the magnetron sputtering deposition of Mn on GaAs surface, followed by the nano-second pulsed laser annealing (PLA), which gives a Tc above 400 K. We demonstrate that the MnGa nanoparticles are only formed in (Ga, Mn) As thin film during the nano-second PLA under a critical range of energy density (0.4–0.5 J cm−2). The highest achieved coercivity, saturation magnetization and remanent magnetization are 760 Oe, 11.3 emu cm−3 and 9.6 emu cm−3, respectively. This method for preparing the hybrid system of ferromagnetic metal/dilute magnetic semiconductor builds a platform for exploring the interesting spin transport phenomenon and is promising for the application of spintronic devices.

Technological progress and social change are causing an increasing demand for raw materials and a reassessment of traditional methods of resource extraction and waste management. Challenged by environmental impacts and decreasing metal concentrations, traditional mining practices are increasingly seen as unsustainable. This situation is exacerbated by the increasing complexity of primary and secondary raw material sources and decreasing metal content, emphasizing the urgent need for innovative solutions to ensure long-term economic and environmentally sustainable resource provision. Biomining strategies such as biosorption are promising for advancing the circular economy, enabling sustainable resource recovery, and significantly reducing pollution through more effective management of mining and landfill waste. Among the available biosorption technologies, peptide-based biosorbents are particularly promising. These biosorbents are developed using advanced biotechnological tools such as phage surface display and contain specific peptides that selectively bind the desired metal ions. This precision is critical for the recovery of valuable metals from complex waste streams such as industrial wastewater and e-waste, supporting the principles of the circular economy and improving resource sustainability. Our research focuses on the development of metal-binding peptides to improve metal recovery processes. Using high-throughput screening and next-generation sequencing, we identify peptides with high specificity and affinity for metals such as cobalt, nickel, arsenic, and others. Using isothermal titration microcalorimetry, these interactions are analyzed in detail, which contributes to understanding binding mechanisms and the optimization of the biosorption process. The newly established junior research group Pep2Rec aims to further develop these biotechnological advances. Pep2Rec aims to refine directed evolution methods to 26Saxony meets Lower Silesia: Science across Borders improve the recovery of metals from non-aqueous solutions. This includes the development of specialized peptide libraries and their application in novel biocomposites for membrane filtration technologies. These initiatives are expected to create a robust framework for a circular economy in sectors with significant potential for improving resource efficiency.

Technological advances and societal changes are transforming industrial resource demand, both in terms of volume and complexity1, pushing an overhaul in traditional practices. The shift towards bio-based "green" technologies and circular economies is pivotal for sustainable resource management and pollution reduction, minimizing waste from mining and landfilling. The development of biosorption processes, particularly through customized peptide-based biosorbents is a promising approach for metal recovery from wastewater. These biocomposites offer an eco-friendly solution, contrasting with conventional biosorbents, which often fall short in stability, selectivity, and cost-effectiveness. To close this gap, our research is developing customized peptide-based biosorbents. By applying phage surface display technology, highly specific peptides are being developed that can selectively bind metal ions such as cobalt, nickel, gallium, arsenic, indium, germanium, copper, palladium and europium2. This innovative approach combines high-throughput screening with next-generation sequencing and identifies peptide ligands that selectively bind metals, characterizing their interactions by isothermal titration microcalorimetry to determine key thermodynamic parameters3. Our peptides, which are produced sustainably and cost-effectively by recombinant expression, are used in biocomposites for use in environmentally friendly, biotechnology-based separation processes. These biocomposites, including magnetic nanoparticles and ceramic or polymeric filters, represent a significant advance in engineered metal recovery applications. Looking ahead, Pep2Rec, a new junior research group, is set to broaden directed evolution methods to include metals in non-aqueous solutions, addressing a significant gap in metal recovery from the chemical-pharmaceutical industry's organic solvents. Merging experimental techniques with rational design, and developing specialized circular peptide libraries, Pep2Rec aims to recover palladium catalysts from organic solvents. This research aims to use these innovative peptides in membrane filter technologies to establish a circular economy in an industrial sector where efficient use of resources is currently poorly practiced.

Acknowledgments: The authors thank to the German Federal Ministry of Education and Research (BMBF) for
supporting the project PepMetal 2.2 (grant number 031B1348A, 2023-2026).

References
1) Graedel, T. E. Clean Energy Technologies, Critical Materials, and the Potential for Remanufacture. Technology
Innovation for the Circular Economy: Recycling, Remanufacturing, Design, Systems Analysis and Logistics,
2024, pp. 95-100.
2) Braun, R., et al. Peptides as biosorbents–Promising tools for resource recovery. Research in Microbiology, 2018,
169, 10, pp. 649-658.
3) Schönberger, N., et al. Gallium-binding peptides as a tool for the sustainable treatment of industrial waste
streams. Journal of Hazardous Materials, 2021, 414, pp. 125366

The amount of metal-bearing waste streams coming from electronic end-of-life products, metallurgical by-products, or mine tailings to name a few is increasing worldwide. In the last decades, the potential of exploiting these waste streams as valuable secondary resources to meet the high demand for critical and economically important raw materials is becoming more prominent. In this review, fundamental principles of bio-based metal recovery technologies are discussed focusing on microbial metabolism-dependent and metabolism-independent mechanisms as sustainable alternatives to conventional chemical metal recovery methods. Modifications and adaptations in the processes of biosorption, bioaccumulation and bioelectrochemical systems are highlighted and emphasis is put on the application of metal-binding peptides and siderophores to increase selectivity in the metal recovery. Imminent challenges that arise when dealing with complex polymetallic solutions are addressed and the focus is on the optimization of bio-based technologies to recover metals efficiently and selectively from (bio-)leachates or liquid waste streams.

Gliomas are a type of malignant brain tumor where the most common mutation is a gain-of-function alteration IDH1R132H, which correlates to prognosis. Accurate assessment of this mutation is crucial for effective patient management and currently the gold standard of its detection is through invasive biopsies.The development of a PET-radiotracer that specifically binds to the IDH1R132H introduces a promising strategy for non-invasive tumor diagnosis and treatment, potentially making a significant impact on overall patient therapy. The lead compound selected for this work is LY-3410738, currently in phase I clinical trials. By modifying the molecular moieties, a library of fluorinated derivatives is synthesized. The synthesis pathway was successful but lacks enantioselectivity. Compounds were tested as enantioenriched mixture (approx. 75% ee), showing that fluorine does not interfere with inhibition potency, while differences are observed between the (S,S) and (S,R) non-fluorinated diastereomers.
Work is ongoing with alternative synthetic strategies aimed at removing the chiral center, while new parameters are being tested for HPLC-semipreparative separation.

Clay rock is considered a suitable host rock for the long-term storage of high-level radioactive waste, with bentonite used as backfill material. In the event of a worst-case scenario where water enters the repository, naturally occurring microorganisms might interact with the radionuclides, potentially altering their chemical speciation or inducing redox reactions.
Among various sulfate-reducing bacteria, Desulfosporosinus species are significant members of the microbial communities in both clay rock and bentonite. Desulfosporosinus hippei DSM 8344T, closely related to a bacterium isolated from bentonite, was selected for a detailed investigation into uranium(VI) interactions with naturally occurring microorganisms from deep geological layers.
Time-dependent experiments in artificial Opalinus Clay pore water (100 µM uranium(VI), pH 5.5) demonstrated a substantial removal of uranium from the supernatants within a short period. UV/Vis studies of the dissolved cell pellets provided clear evidence of partial reduction of uranium(VI) to uranium(IV). These findings suggest a combined association-reduction process as the mechanism of interaction.
TEM images showed uranium aggregates forming on the cell surface. Moreover, cells released membrane vesicles, possibly as a defense mechanism against cell encrustation. Additionally, HERFD-XANES measurements confirmed the reduction of uranium(VI) and revealed the presence of uranium(V) in the cell pellets, marking the first evidence of the involvement of uranium(V) in uranium(VI) reduction by sulfate-reducing microorganisms. Subsequent EXAFS measurements identified different cell-related uranium species.
This study enhances our understanding of the complexity of redox processes in the environment and contributes to the safety concept for nuclear repositories in clay rock. Moreover, it presents new insights into the uranium(VI) reduction mechanisms of sulfate-reducing bacteria.

The talk was given within DFG Equality Series, incl. a “Woman in Science – Professional Career Insight” lecture and a workshop organized by the DFG funded projects TRR386, TRR172, RTG2721, FOR2857 and SFB1423. The talk focused on my carrier development.

The ability to effectively monitor singlet oxygen (¹O₂) with fluorescence probes in biological systems is severely restricted mainly by the background autofluorescence of these systems. Though the application of lanthanide complexes as ¹O₂ monitors successfully resolves this problem with time-gated luminescence measurements, the insolubility of these complexes in an aqueous medium heavily limits their application in biological systems. Here, we present a water-soluble ¹O₂ sensor based on a chitosan−europium hybrid material. A procedure for the modification of chitosan to expand its solubility to neutral and basic pH, while maintaining its free active amine groups, is described. These are then coupled covalently to a
europium-based probe for the detection of ¹O₂. The resulting hybrid sensor is readily soluble in water across the pH scale and efficiently signals the presence of ¹O₂ at physiological pH, with the characteristic Eu³⁺ emission at 611 nm yielding up to a 15-fold increase in emission intensity and a decay time of 332 μs. Being of particular interest for time-gated measurements, this long decay time, coupled with the biocompatibility of chitosan, describes a material with potential biological applications, where ¹O₂ plays a vital role.

Mass separated focused ion beams (FIB) open a wide field for spatially resolved modification
of properties of materials at the nano scale. The key element in this technology is the ion
source providing the needed ion species. An overview on the known ion sources for FIB
applications is provided in Ref. [1, 2]. Here we present some examples of the application of
mass separated FIBs, utilizing new liquid metal alloy ion sources for the fields of nano
magnetism science and quantum technology.
The direct magnetic manipulation of Permalloy nanostructure by a focused cobalt ion beam
was demonstrated with a CoNd LMAIS [3]. The experiments were extended using a Dy LMAIS
[4], which has been employed for the spatially resolved magnetic patterning of nanostructures
[5].
A new challenge for the application of FIBs arose with the advent of quantum technology. An
example is the need for spatially controlled implantation of carbon into Si. Based on previous
results a CsC LMAIS was developed to a usable technological level and applied for the local
fabrication of G-centres for single photon emitters in highly pure silicon [6].
[1] L. Bischoff, P. Mazarov, L. Bruchhaus, and J. Gierak, Liquid Metal Alloy Ion Sources - An
Alternative for Focused Ion the focused ion beam technology, Appl. Phys. Rev. 3 (2016)
021101-1 –30
[2] K. Höflich et.al., Roadmap for focused ion beam technologies, Appl.Phys.Rev.,vol.10, no 4,
Dec 26 (2023)
[3] J. Pablo-Navarro, N. Klingner, G. Hlawacek , A. Kakay , L. Bischoff , R. Narkowicz , P.
Mazarov , R. Hübner , F. Meyer, W.Pilz, J. Lindner, and K. Lenz, Direct magnetic manipulation
of a Permalloy nanostructure by a focused cobalt ion beam, Physical Review Applied 20,
044068 (2023)
[4] L. Bischoff, N. Klingner, P. Mazarov, W. Pilz, and F. Meyer, Dysprosium Liquid Metal Alloy
Ion Source for Magnetic Nanostructures, Vac. Sci. Technol. B 40, 052802 (2022),
[5] K. Lenz, J. Pablo-Navarro, N. Klingner, G. Hlawacek, A. Kákay, L. Bischoff, R. Narkowicz, P.
Mazarov, R. Hübner, F. Meyer, W. Pilz, and J. Lindner, Local magnetic patterning of
nanostructures using cobalt and dysprosium focused ion beams, XII. Latin American
Workshop on Magnetism and Magnetic Materials, (LAW3M) 16 October 2023 – 20 October
2023. Puerto Varas, Chile
[6] M. Hollenbach, N. Klingner, P. Mazarov, F. Meyer, W. Pilz, L. Bischoff, N.V. Abrosimov, G.
Hlawacek, M. Helm, and G. V. Astakhov, Local activation of quantum in highly-purity silicon
with focused carbon Beams, http://arxiv.org/abs/2404.19592

On account of the use of platinum group metals (PGMs) as active materials in polymer electrolyte membrane water electrolyzer (PEMEL) cells, development of recycling processes for fine catalyst materials is indispensable for further scale up of hydrogen production. By applying a contrast in (de)wetting of the materials, ultrafine particles have the potential separated for recycling. The limitation of the particle size in froth flotation technology can be overcome by adding oil in the system. This study investigated the selective separation of ultrafine particles by applying a hydrophobic high internal phase water in oil emulsion containing only 5 % of organic liquid emulsified as a double emulsion in the particle dispersion. Hydrophobic cathode particles (i.e. carbon black) are selectively agglomerated in this system, allowing 90 % of the feed to be recovered in the froth phase. The recovery rate was also significantly higher than that of using the same amount of pure oil collector. In the binary particle system, 70 % of the target particles could be recovered with 90 % of grade by adding 2.8 % of the hydrophobic emulsion.

The GeoPT proficiency testing scheme, managed by the International Association of Geoanalysts (IAG), is a valuable and proven tool for geochemical laboratories performing routine analyses of silicate rocks and related materials. It can also be used as a certification protocol in accordance with ISO Guide 35:2017.
Based on the established importance of knowing the mineralogical composition of test samples to substantiate the validity of the geochemical data (Claisse and Samson 1961; Meisel, et al. 2022), the proposal was formulated to determine both the geochemical (GeoPT) and the mineralogical phase composition (MinPT) for the same sample in parallel rounds. The corresponding methodology will also be presented at the conference.
MinPT is open both for classical analyses of the phase composition using bulk methods (e.g. quantitative XRD) and for methods of so-called "automated mineralogy" (AM) using SEM- or µ-XRF-based techniques.
Both groups of methods show specific strengths and weaknesses in determining the phase inventory. For example, the limit of detection for phases in quantitative XRD is typically around 3 g/100g but can be as low as 0.5 g/100g, while AM methods can detect the smallest amounts of accessory minerals in the range of ppm. The exact determination of some solid solution compositions using XRD is commonly associated with an extremely high methodological effort (e.g., for members of the spinel and garnet supergroups), while it is comparatively straightforward for AM methods which utilise X-ray elemental analysis. On the contrary, the accurate identification of mineral groups that contain H2O, Li and B, can be particularly problematic for AM methods. The same appears for polymorphs and fine-grained materials like clays.
Using a fully characterized test sample in preparation for the parallel GeoPT and MinPT round, it is shown how the mineralogical phase composition could be analysed with good precision and accuracy in a concerted sequence of both analytical methods.

The projected increase in electric vehicle demand over the next few decades raised some concerns about whether the mining industry can meet the growing need for battery metals like nickel and cobalt, which are essential for this shift in energy technology. These metals are commonly obtained as secondary products of other metals like copper, and their future availability relies on the mining progress of the primary metal. From exploration to production, the projects go through several stages of characterisation and evaluation, and the interconnection between host and secondary metal adds complexity to understanding which mining projects advance to production. Even projects with similar geological and technical characteristics may take very different trajectories. The present study uses a retrospective analysis model to investigate the dynamics of this process for Copper, Nickel and Cobalt exploration projects. A global database of over 6,000 projects was compiled, covering their progression through major development stages over the past 20 years. Ordinal logistic regression was used for the statistical analysis of this data. Different explanatory variables, including economic, geological, technical, and geographic factors, were tested to identify the best predictors for project progress at each development stage and final product definition. The results provide essential insights into the dynamics of nickel and cobalt supply and will eventually allow more realistic forecasts to be made for future market dynamics

Whether primary lithium (Li) sources will be able to supply the rapidly growing needs of the electric mobility
transition has recently caused considerable controversy. Existing assessments need to be improved by a lack
of consideration for the decision-making processes occurring at the level of individual mining projects. In the
present contribution, we demonstrate how these processes and associated uncertainties can be incorporated
into an assessment of the likely future evolution of the global Li market. Our method uses Monte Carlo simulations
to achieve this goal. A global database of existing Li mining projects (all development stages, including case
histories) is used to build models to estimate the likelihood of each project proceeding to the next development
stage in any given year, depending on specific project characteristics such as location, deposit type, and ore
grade, as well as market conditions, i.e., Li price and demand. Iterative stochastic simulations are then run, in
which projects are moved through the development pipeline according to these estimated likelihoods, year-by year,
up to 2050. Discoveries are also included in the model to achieve realistic results over the relatively long
period covered. Simple, functional models estimate future Li demand, including uncertainty. The simulations
generate a large set of equally probable scenarios (1,000 or more) of which projects enter production when,
whether primary supply can meet demand in any given year, and what the likely mean Li price is for that year.
Summarising the data from all scenarios provides an impression of the likely evolution of the Li market up to
2050. Besides this likely market evolution, the simulation outputs can be used further to assess the probable
environmental impacts of future primary Li supply
213

Whether primary lithium (Li) sources will be able to supply the rapidly growing needs of the electric mobility
transition has recently caused considerable controversy. Existing assessments need to be improved by a lack
of consideration for the decision-making processes occurring at the level of individual mining projects. In the
present contribution, we demonstrate how these processes and associated uncertainties can be incorporated
into an assessment of the likely future evolution of the global Li market. Our method uses Monte Carlo simulations
to achieve this goal. A global database of existing Li mining projects (all development stages, including case
histories) is used to build models to estimate the likelihood of each project proceeding to the next development
stage in any given year, depending on specific project characteristics such as location, deposit type, and ore
grade, as well as market conditions, i.e., Li price and demand. Iterative stochastic simulations are then run, in
which projects are moved through the development pipeline according to these estimated likelihoods, year-by year,
up to 2050. Discoveries are also included in the model to achieve realistic results over the relatively long
period covered. Simple, functional models estimate future Li demand, including uncertainty. The simulations
generate a large set of equally probable scenarios (1,000 or more) of which projects enter production when,
whether primary supply can meet demand in any given year, and what the likely mean Li price is for that year.
Summarising the data from all scenarios provides an impression of the likely evolution of the Li market up to
2050. Besides this likely market evolution, the simulation outputs can be used further to assess the probable
environmental impacts of future primary Li supply
213

There has been considerable recent controversy whether current and new lithium mines will be able to supply the rapidly growing needs of the electric mobility transition. Mineral exploration projects are typically active for many years, and only some become operational mines. From exploration to production, the projects go through several stages of characterisation and evaluation. At each stage, decisions are made by companies and stakeholders to advance, continue or stop the project. This is a complex process, and even projects with very similar geological and technical characteristics may take very different trajectories, depending on external factors such as global market conditions and local regulatory environments. The present study investigates the dynamics of this process for lithium exploration projects. A global database of 397 lithium projects was compiled, covering their progression through major development stages between 2004 and 2022. Ordinal logistic regression was used for the statistical analysis of this data. Different explanatory variables were tested, including economic, geological, technical, and geographic factors, to identify the best predictors for project progress at each development stage. The results suggest an essential role for lithium carbonate prices, and a variable role for other factors at each stage. Critically, the already elapsed lead time and project economics, which are traditionally considered important for the prediction of the start-up of individual mines, do not appear to be relevant in all cases. The results provide important insights into the dynamics of lithium supply and will eventually allow more realistic forecasts to be made for future lithium market dynamics.

Net ecosystem production (NEP) is an important indicator of lake ecosystem function and integrity. An earlier study, restricted to one geographical region, indicated that oxygen saturation levels (DO%) might be used to predict daily NEP in shallow lakes. To test the generality of the method, we used DO% data collected in a standardised pan-European mesocosm experiment with contrasting trophic states and water levels covering a large climate gradient (from Sweden to Turkey). We corroborated these data with process-based DO simulations. The NEP ~ DO% relation depended on factors influencing gas transfer: water depth and wind. The NEP ~ DO% relation per volume became weaker with increasing depth (1–2 m) but was independent of depth when area based. Simulations indicated that the marginalisation of the depth was sensitive to wind conditions. Trophic status, temperature and light showed no or only marginal (climate zone) effects (experimental data), while the simulations indicated influence of those factors under particular wind–depth conditions. We confirmed that when considering also wind and depth effects, midday DO% potentially provides reliable estimates of daily NEP. Therefore, historical monitoring data of DO% might be used to estimate NEP, and process-based oxygen models may be valuable tool therein. We encourage further tests.

Objectives
Mutant isocitrate dehydrogenase (mIDH) has become an important biomarker for effective diagnosis, prognosis, treatment planning and patient stratification in patients with mIDH. Currently, mIDH status is determined by an invasive immunohistochemical method. A non-invasive PET imaging method for the detection of isocitrate dehydrogenase mutations represents a potentially better alternative. To date, there is no clinically available PET radiotracer targeting mIDH. In this study, we have developed [18F]SK60 and [18F]SK87 (Fig. 1) and are currently investigating their ability to visualise mIDH1.1
Methods
A SAR study was carried out starting from the structure of the mIDH inhibitor GSK321.2 Our medicinal chemistry program led to the development of dimethylated GSK321 analogues, SK60 and SK87 which were radiofluorinated in view of their high potency and selectivity towards the mIDH1R13H. To develop [18F]SK60 and [18F]SK87, various reaction parameters were investigated, for instance: fluorination agents, solvent, temperature and molar ratios between precursor and copper complex. For [18F]SK60, the ex vivo metabolic stability was investigated in female CD-1 mice at 30 min post-injection (p.i) and the biodistribution was evaluated ex vivo at 5, 15, 30 and 60 min as well as by dynamic PET scan studies (60 min) in healthy female CD-1 mice.
Results
The structural optimization and medicinal chemistry on GSK321 resulted in SK60 (IC50 mIDH1R132H = 14.5 ± 3.3 nM and IC50 wtIDH1 = 374 ± 59 nM) and SK87 (IC50 mIDH1R132H = 25.9  7.1 nM and IC50 wtIDH1 > 10,000 nM). Compounds [18F]SK60 and [18F]SK87 were successfully synthesized by copper-mediated radiofluorination from the respective Bpin and BEpin precursors, respectively. In vivo studies conducted in healthy female CD-1 mice, exhibited the excellent metabolic stability of [18F]SK60, with parent fractions of 80% and 100% in plasma and brain at 30 min p.i., respectively. The ex vivo biodistribution studies and dynamic PET scan showed a low brain uptake (0.6 % ID/g 15 min p.i.) and hepatobiliary excretion of [18F]SK60 in healthy mice.
Conclusions
This study resulted in the development of a novel series of fluorinated mIDHR132H inhibitors. Consequently, [18F]SK60 and [18F]SK87 were successfully radiofluorinated. Our preclinical evaluation of [18F]SK60 demonstrated high metabolic stability, limited brain uptake and hepatobiliary excretion in vivo in healthy mice. In general, further structural modifications in [18F]SK60 are required to enhance the brain uptake diagnosis and treatment of glioma and other tumours associated with mIDH. Currently, we are conducting the biological evaluation of [18F]SK87, the analogue with reduced lipophilicity.
References
1. Patent application number: DE 10 2024 110 434.1 (15 April 2024)
2. Okoye-Okafor, U. C.; et al. Nat. Chem. Bio. 2015, 11 (11), 878–886.

Introduction:

Copper-Mediated Radiofluorination (CMRF) is one of the most significant developments of the last decade in the production of 18F-aryl-containing radiopharmaceuticals.1 Despite extensive research and improved radiolabelling conditions, the generation of H-side product (Fig. 1) continues to be an issue in these CMRF reactions. In our research, we focused on the identification of the sources and reaction parameters influencing the “H”-side product formation in these CMRF reactions.

Methods:

The CMRF of pinacol boronic esters was optimized by varying the following parameters: solvent (DMA, DMI, n-BuOH), reaction time (5 - 20 min), temperature (110 - 130 °C), base (K2CO3) and molar ratio of precursor to Cu-complex (1:3, 2:3, 1:8). To investigate the source of protons, deuterated reagents (D2O, n-BuOD-d10, TBADCO3, K2CO3 in D2O) were used. The influence of different leaving groups of precursors [B(OH)2, Bpin, BEpin and SnBu3] was also evaluated. The effect of amounts of different eluting phase transfer catalyst (PTC) (TBAHCO3, TEHCO3, TBAOTf, DMAPHCO3) was also investigated. A time-dependent (2 to 30 min) formation of H-side product was investigated.
Results:
[18F]Biphenyl was achieved with a high radiochemical conversion of 85 % using 2 mg of biphenyl boronic ester, 10 mg of [Cu(OTf)2(Py)4] (molar ratio of 1:4) in n-BuOH:DMI (1:2, v/v) at 110 °C for 5 min. The H-side product was successfully separated from the radiofluorinated product using a ReproSil C18 PFP column (250 x 10 mm) and 54 % MeCNaq. Our deuterated experiments revealed that quenching the reaction with D2O had no influence on the H-side product formation, but the use of n-BuOD-d10 increased its generation by four folds. The different eluting PTCs (TBAHCO3, TEHCO3, TBAOTf, DMAPHCO3) implied no significant influence on the H-side product formation, however, the exclusion of K2CO3 not only improved RCC but also decreased the H-side product formation. The use of boronic acid precursor lead to an increased H-side product formation by several folds as compared to the use of pinacol boronic ester bearing precursor. Moreover, the use of a precursor with acidic protons (e.g. NH) enhance the H-side product formation. The yield of the H-side product formation reached a plateau at 10 min of reaction.
Conclusion:
Despite a number of hurdles, the CMRF reactions are currently being widely employed for the production of radiopharmaceuticals embodying a wide variety of 18F-aryl scaffolds. To overcome the purification difficulties of the 18F-radioligands due to H-side product formation, further improvements and mechanistic studies need to be undertaken.
LITERATURE
[1] Wright JS, Kaur T, Preshlock S, et al. Clin Transl Imaging. 2020 Jun;8(3):167-206.

Aim
Mutant isocitrate dehydrogenase (mIDH) has become an important biomarker for effective diagnosis, prognosis, treatment planning and patient stratification in patients with mIDH. Currently, mIDH status is determined by an invasive immunohistochemical method. A non-invasive PET imaging method for the detection of isocitrate dehydrogenase mutations represents a potentially better alternative. To date, there is no clinically available PET radiotracer targeting mIDH. In this study, we have developed [18F]SK60 and [18F]SK87 and are currently investigating their ability to visualise mIDH1.1
Methods
A SAR study was carried out starting from the structure of the mIDH inhibitor GSK321.2 Our medicinal chemistry program led to the development of dimethylated GSK321 analogues, SK60 and SK87 which were radiofluorinated in view of their high potency and selectivity towards the mIDH1R13H. To develop [18F]SK60 and [18F]SK87, various reaction parameters were investigated, for instance: fluorination agents, solvent, temperature and molar ratios between precursor and copper complex. For [18F]SK60, the ex vivo metabolic stability was investigated in female CD-1 mice at 30 min post-injection (p.i) and the biodistribution was evaluated ex vivo at 5, 15, 30 and 60 min as well as by dynamic PET scan studies (60 min) in healthy female CD-1 mice.

Results
The structural optimization and medicinal chemistry on GSK321 resulted in SK60 (IC50 mIDH1R132H = 14.5 ± 3.3 nM and IC50 wtIDH1 = 374 ± 59 nM) and SK87 (IC50 mIDH1R132H = 25.9  7.1 nM and IC50 wtIDH1 > 10,000 nM). Compounds [18F]SK60 and [18F]SK87 were successfully synthesized by copper-mediated radiofluorination from the respective Bpin and BEpin precursors, respectively. In vivo studies conducted in healthy female CD-1 mice, exhibited the excellent metabolic stability of [18F]SK60, with parent fractions of 80% and 100% in plasma and brain at 30 min p.i., respectively. The ex vivo biodistribution studies and dynamic PET scan showed a low brain uptake (0.6 % ID/g 15 min p.i.) and hepatobiliary excretion of [18F]SK60 in healthy mice.
Conclusions
This study resulted in the development of a novel series of fluorinated mIDHR132H inhibitors. Consequently, [18F]SK60 and [18F]SK87 were successfully radiofluorinated. Our preclinical evaluation of [18F]SK60 demonstrated high metabolic stability, limited brain uptake and hepatobiliary excretion in vivo in healthy mice. In general, further structural modifications in [18F]SK60 are required to enhance the brain uptake diagnosis and treatment of glioma and other tumours associated with mIDH. Currently, we are conducting the biological evaluation of [18F]SK87, the analogue with reduced lipophilicity.
References
1. Patent application number: DE 10 2024 110 434.1 (15 April 2024)
2. Okoye-Okafor, U. C.; et al. Nat. Chem. Bio. 2015, 11 (11), 878–886.

Aim
Mutant isocitrate dehydrogenase (mIDH) has become an important biomarker for effective diagnosis, prognosis, treatment planning and patient stratification in patients with mIDH. Currently, mIDH status is determined by an invasive immunohistochemical method. A non-invasive PET imaging method for the detection of isocitrate dehydrogenase mutations represents a potentially better alternative. To date, there is no clinically available PET radiotracer targeting mIDH. In this study, we have developed [18F]SK60 and [18F]SK87 and are currently investigating their ability to visualise mIDH1.1
Methods
A SAR study was carried out starting from the structure of the mIDH inhibitor GSK321.2 Our medicinal chemistry program led to the development of dimethylated GSK321 analogues, SK60 and SK87 which were radiofluorinated in view of their high potency and selectivity towards the mIDH1R13H. To develop [18F]SK60 and [18F]SK87, various reaction parameters were investigated, for instance: fluorination agents, solvent, temperature and molar ratios between precursor and copper complex. For [18F]SK60, the ex vivo metabolic stability was investigated in female CD-1 mice at 30 min post-injection (p.i) and the biodistribution was evaluated ex vivo at 5, 15, 30 and 60 min as well as by dynamic PET scan studies (60 min) in healthy female CD-1 mice.
Results
The structural optimization and medicinal chemistry on GSK321 resulted in SK60 (IC50 mIDH1R132H = 14.5 ± 3.3 nM and IC50 wtIDH1 = 374 ± 59 nM) and SK87 (IC50 mIDH1R132H = 25.9  7.1 nM and IC50 wtIDH1 > 10,000 nM). Compounds [18F]SK60 and [18F]SK87 were successfully synthesized by copper-mediated radiofluorination from the respective Bpin and BEpin precursors, respectively. In vivo studies conducted in healthy female CD-1 mice, exhibited the excellent metabolic stability of [18F]SK60, with parent fractions of 80% and 100% in plasma and brain at 30 min p.i., respectively. The ex vivo biodistribution studies and dynamic PET scan showed a low brain uptake (0.6 % ID/g 15 min p.i.) and hepatobiliary excretion of [18F]SK60 in healthy mice.
Conclusions
This study resulted in the development of a novel series of fluorinated mIDHR132H inhibitors. Consequently, [18F]SK60 and [18F]SK87 were successfully radiofluorinated. Our preclinical evaluation of [18F]SK60 demonstrated high metabolic stability, limited brain uptake and hepatobiliary excretion in vivo in healthy mice. In general, further structural modifications in [18F]SK60 are required to enhance the brain uptake diagnosis and treatment of glioma and other tumours associated with mIDH. Currently, we are conducting the biological evaluation of [18F]SK87, the analogue with reduced lipophilicity.
References
1. Patent application number: DE 10 2024 110 434.1 (15 April 2024)
2. Okoye-Okafor, U. C.; et al. Nat. Chem. Bio. 2015, 11 (11), 878–886.

Tongesteine stellen mögliche Wirtsgesteine für die Endlagerung des hochradioaktiven Abfalls in einem geologischen Tiefenlager dar. Bentonit soll dabei als Verfüllmaterial nicht nur für ein Endlager in Tonformationen, sondern auch in kristallinem Ge-stein dienen. Für ein umfassendes Sicherheitskonzept müssen neben den geologischen, geochemischen und geophysikalischen Eigenschaften eines Endlagers auch der Einfluss natürlich vorkommender Mikroorganismen in dessen Umgebung betrachtet werden. Diese können im Falle eines Wassereinbruchs mit den freigesetzten Radionukliden wechselwirken und dadurch bspw. die chemische Speziation oder den Oxidationszustand verändern.
Neben weiteren sulfatreduzierenden Mikroorganismen spielen Bakterien der Gattung Desulfosporosinus eine wichtige Rolle in den mikrobiellen Gemeinschaften sowohl in Tongestein als auch in Bentonit. Desulfosporosinus hippei DSM 8344T ist ein naher Verwandter der aus Bentonit isolierten Bakterien und wurde im Rahmen dieser Arbeit ausgewählt, um dessen Wechselwirkungen mit Uran und Europium mit Hilfe verschiedener mikroskopischer und spektroskopischer Methoden näher zu untersuchen.
Zeitabhängige Untersuchungen in synthetischer Opalinustonporenlösung (100 µM Uran(VI), pH 5,5) zeigten eine fast vollständige Entfernung des Urans aus den Über-ständen innerhalb einer kurzen Zeitspanne. TEM Aufnahmen gekoppelt mit element-spezifischer EDX-Spektroskopie zeigten eine Assoziation von Uran vorrangig auf der Zelloberfläche. Darüber hinaus bildeten die Zellen Membranvesikel als mögliche Abwehrreaktion aus, um eine Verkrustung der Zellen zu verhindern.
Außerdem konnte die Reduktion von Uran(VI) mithilfe verschiedener spektroskopischer Methoden nachgewiesen werden. Zunächst wurden die aufgelösten Zellpellets mit Hilfe der UV/Vis-Spektroskopie untersucht. Dabei zeigte sich ein ansteigender An-teil an Uran(IV) mit der Zeit. Eine vollständige Reduktion konnte allerdings nicht beobachtet werden. Dies deutet darauf hin, dass es sich bei dem Wechselwirkungsmechanismus um einen gekoppelten Sorptions-Reduktionsmechanismus handelt. HERFD-XANES-Messungen bestätigten die Reduktion von Uran(VI) in den Zellpellets. Darüber hinaus konnte die Anwesenheit von Uran(V) während des Reduktionsprozesses beobachtet werden. Dabei handelte es sich um den erstmaligen Nachweis dieser Oxidationsstufe in einem Bioreduktionsexperiment von Uran(VI) mit sulfatreduzierenden Bakterien.
Bei den Untersuchungen mit Europium zeigten TEM Aufnahmen eine Biopräzipitation von Europium mit Phosphaten auf der Zelloberfläche und lumineszenzspektroskopische Untersuchungen konnten eine Anbindung von Europium an Carboxyl- oder Phosphatgruppen auf der Zelloberfläche nachweisen.
Zusammenfassend erweitert diese Arbeit unser Verständnis für die Komplexität von Redoxprozessen in der Umwelt und trägt zu einem Sicherheitskonzept für nukleare Endlager in Tongestein bei. Darüber hinaus liefert sie neue Erkenntnisse über die Mechanismen der Uran(VI)-Reduktion durch sulfatreduzierende Bakterien.