Foto: Program "Matter and Technologies" ©Copyright: BengsDMA

Matter > Matter and Technologies - All Topics

Foto: One of the most powerful computers in Saxony is located at the Helmholtz Center Dresden-Rossendorf. ©Copyright: HZDR/Oliver KilligThe contribution of HZDR to the Helmholtz-topic “Data Management and Analysis” is strongly aligned with the overall activities of the topic, with strong integration with the activities in the topic "Accelerator Research and Development" and the topic "Matter – Dynamics, Mechanisms and Control" in the program MML. Central goal is the implementation of a comprehensive digitization strategy for the Research Field MATTER. The focus is on the development, application, provision, and integration of innovative digital solutions for handling and analyzing the extreme volumes and rates of complex data coming from machines, experiments and simulations, research and application of artificial intelligence for knowledge extraction from experiments and simulations, the application of frontier technologies such as exascale computing and quantum computing to model complex states of matter as well as digital twins of machines, experiments and the complex systems studied by them. Important infrastructures are the central computing facilities of HZDR.


  • • Implementation of a comprehensive digitization strategy for the Research Field MATTER
  • • Develop, apply, deploy, and integrate innovative digital solutions for handling and analyzing the extreme volumes and rates of complex data from machines, experiments, and simulations
  • • Exploration and application of artificial intelligence for knowledge extraction from experiments and simulations
  • • Application of pioneering technologies such as exascale computing and quantum computing to model complex states of matter
  • • Implementing digital twins of machines, experiments and the complex systems they study

Press Releases

Involved HZDR institutes




  • Bosoni, E.; Beal, L.; Bercx, M. et al.
    How to verify the precision of density-functional-theory implementations via reproducible and universal workflows
    Nature Reviews Physics 6(2024), 45-58 (10.1038/s42254-023-00655-3)
  • Prasoon, A.; Yang, H.; Hambsch, M. et al.
    On-water surface synthesis of electronically coupled 2D polyimide-MoS2 van der Waals heterostructure
    Communications Chemistry 6(2023)1, 280 (10.1038/s42004-023-01081-3)
  • Carlomagno, J. P.; Contrera, G.; Grunfeld, A. G. et al.
    Thermal twin stars within a hybrid equation of state based on a nonlocal chiral quark model compatible with modern astrophysical observations
    Physical Review D 109(2024), 043050 (10.1103/PhysRevD.109.043050)
  • Eingorn, M.; O’Briant, B.; Diouf, A. et al.
    Backreaction in cosmic screening approach’
    Physics Letters B 839(2023), 137797 (10.1016/j.physletb.2023.137797)
  • Seibel, J.; Fittolani, G.; Mir Hosseini, S. H. et al.
    Visualizing Chiral Interactions in Carbohydrates Adsorbed on Au(111) by High-Resolution STM Imaging
    Angewandte Chemie 62(2023)39, e202305733 (10.1002/anie.202305733)
  • Nolkemper, K.; Antonietti, M.; Kühne, T. D.-S. et al.
    Kinetically Stable and Highly Ordered Two-Dimensional CN2 Crystal Structures
    Journal of Physical Chemistry C 128(2023)1, 330-338 (10.1021/acs.jpcc.3c03539)
  • Schade, R.; Kenter, T.; Elgabarty, H. et al.
    Breaking the exascale barrier for the electronic structure problem in ab-initio molecular dynamics
    International Journal of High Performance Computing Applications 37(2023)5, 530-538 (10.1177/10943420231177631)
  • Avateev, O.; Nolkemper, K.; Kühne, T. D.-S. et al.
    Extent of carbon nitride photocharging controls energetics of hydrogen transfer in photochemical cascade processes
    Nature Communications 14(2023)1, 7684 (10.1038/s41467-023-43328-6)
  • Haldar, S.; Bhauriyal, P.; Ramuglia, A. R. et al.
    Sulfide-Bridged Covalent Quinoxaline Frameworks for Lithium–Organosulfide Batteries
    Advanced Materials 35(2023)16, 2210151 (10.1002/adma.202210151)
  • Roy, P. K.; Antonatos, N.; Li, T. et al.
    2D Few-Layered PdPS: Toward High-Efficient Self-Powered Broadband Photodetector and Sensor
    ACS Applied Materials and Interfaces 15(2023)1, 1859-1870 (10.1021/acsami.2c18125)
  • Senkovska, I.; Bon, V.; Abylgazina, L. et al.
    Understanding MOF Flexibility: An Analysis Focused on Pillared Layer MOFs as a Model System}
    Angewandte Chemie 62(2023)33, e202218076 (10.1002/anie.202218076)
  • Yu, H.; Sun, J.; Heine, T.
    Predicting Magnetic Coupling and Spin-Polarization Energy in Triangulene Analogues
    Journal of Chemical Theory and Computation 19(2023)12, 3486-3497 (10.1021/acs.jctc.3c00175)
  • Vogelsberg, E.; Moors, M.; Sorokina, A. S. et al.
    Solution-Processed Formation of DNA-Origami-Supported Polyoxometalate Multi-Level Switches with Countercation-Controlled Conductance Tunability
    Chemistry of Materials 35(2023)14, 5447-5457 (10.1021/acs.chemmater.3c00776)
  • Gärtlein, C.; Ivanytskyi, O.; Sagun, V. et al.
    Hybrid star phenomenology from the properties of the special point
    Physical Review D 108(2023), 114028-1-114028-13 (10.1103/PhysRevD.108.114028)
  • Yu, H.; Heine, T.
    Magnetic Coupling Control in Triangulene Dimers
    Journal of the American Chemical Society 145(2023)35, 19303-19311 (10.1021/jacs.3c05178)
  • Schwarz, A.; Alon-Yehezkel, H.; Levi, A. et al.
    Thiol-based defect healing of WSe2 and WS2
    npj 2D Materials and Applications 7(2023)1, 59 (10.1038/s41699-023-00421-0)
  • Mendgen, P.; Dejid, N.; Olson, K. et al.
    Nomadic ungulate movements under threat: Declining mobility of Mongolian gazelles in the Eastern Steppe of Mongolia
    Biological Conservation 286(2023), 110271 (10.1016/j.biocon.2023.110271)
  • Haldar, S.; Waentig, A. L.; Ramuglia, A. R. et al.
    Covalent Trapping of Cyclic-Polysulfides in Perfluorinated Vinylene-Linked Frameworks for Designing Lithium-Organosulfide Batteries
    ACS Energy Letters 8(2023)12, 5098-5106 (10.1021/acsenergylett.3c01548)
  • Shu, X.; Hu, L.; Heine, T. et al.
    Rational Molecular Design of Redox-Active Carbonyl-Bridged Heterotriangulenes for High-Performance Lithium-Ion Batteries
    Advanced Science (2024), 2306680 (10.1002/advs.202306680)
  • Zang, Y.; Wu, Q.; Wang, S. et al.
    Unveiling Pseudo-Inert Basal Plane for Electrocatalysis in 2D Semiconductors: Critical Role of Reversal-Activation Mechanism
    Advanced Energy Materials (2024), 2303953 (10.1002/aenm.202303953)
  • Chen, D.-H.; Vankova, N.; Jha, G. et al.
    Ultrastrong Electron-Phonon Coupling in Uranium-Organic Frameworks Leading to Inverse Luminescence Temperature Dependence
    Angewandte Chemie (2024), e202318559 (10.1002/anie.202318559)
  • Martinetto, V.; Shah, K.; Cangi, A. et al.
    Inverting the Kohn-Sham equations with physics-informed machine learning
    Machine Learning: Science and Technology 5(2024), 015050 (10.1088/2632-2153/ad3159)
  • Stein, F.; Hutter, J.
    Massively Parallel Implementation of Gradients within the Random Phase Approximation: Application to the Polymorphs of Benzene
    Journal of Chemical Physics 160(2024)2, 024120 (10.1063/5.0180704)
  • Zeng, Z.; Wodaczek, F.; Liu, K. et al.
    Mechanistic insight on water dissociation on pristine low-index TiO2 surfaces from machine learning molecular dynamics simulations
    Nature Communications 14(2023), 6131 (10.1038/s41467-023-41865-8)
  • Moldabekov, Z.; Shao, X.; Pavanello, M. et al.
    Imposing correct jellium response is key to predict the density response by orbital-free DFT
    Physical Review B 108(2023)23, 235168 (10.1103/PhysRevB.108.235168)
  • Davoodi Monfared, M.; Batista, A.; Mertel, A. et al.
    A Web-Based COVID-19 Tool for Testing Residents in Retirement Homes: Development Study
    JMIR Formative Research 7(2023), e45874 (10.2196/45875)
  • Tucker, M.; Schipper, A.; Adams, T. et al.
    Behavioral responses of terrestrial mammals to COVID-19 lockdowns
    Science 380(2023), 1059-1064 (10.1126/science.abo6499)
  • de Oliveira Silvano, N.; Barci, D. G.
    The role of multiplicative noise in critical dynamics
    Physica A: Statistical Mechanics and its Applications 630(2023), 129246 (10.1016/j.physa.2023.129246)
  • Callow, T. J.; Nikl, J.; Kraisler, E. et al.
    Physics-enhanced neural networks for equation-of-state calculations
    Machine Learning: Science and Technology 4(2023), 045055 (10.1088/2632-2153/ad13b9)
  • Dornheim, T.; Schwalbe, S.; Moldabekov, Z. et al.
    Ab initio path integral Monte Carlo simulations of the uniform electron gas on large length scales
    Journal of Physical Chemistry Letters 15(2024), 1305-1313 (10.1021/acs.jpclett.3c03193)
  • Saraiva De Menezes, J. F.
    Comparando las estimaciones de selección de hábitat mediante modelos de distribución de especies y step selection functions
    Ecosistemas 32(2023)2, 2455 (10.7818/ECOS.2455)
  • Tahmasbi, H.; Ramakrishna, K.; Lokamani, M. et al.
    Machine Learning-Driven Structure Prediction for Iron Hydrides
    Physical Review Materials 8(2024), 033803 (10.1103/PhysRevMaterials.8.033803)
  • Röpke, G.; Dornheim, T.; Vorberger, J. et al.
    Virial coefficients of the Uniform Electron Gas from Path Integral Monte Carlo Simulations
    Physical Review E 109(2024), 025202 (10.1103/PhysRevE.109.025202)
  • Wicaksono, D. C.; Hecht, M.
    UQTestFuns: A Python3 library of uncertainty quantification (UQ) test functions
    The Journal of Open Source Software 8(2023)90, 5671 (10.21105/joss.05671)
  • Muhammad, S. R.; Tomasz, W.; Kuc, A. B. et al.
    Composition-dependent absorption of radiation in semiconducting MSi2Z4 Monolayers
    Physica Status Solidi (B) 261(2024)3, 2300570 (10.1002/pssb.202300570)
  • Ivimey-Cook, E. R.; Pick, J. L.; Bairos-Novak, K. R. et al.
    Implementing code review in the scientific workflow: Insights from ecology and evolutionary biology
    Journal of Evolutionary Biology 36(2023)10, 1347-1356 (10.1111/jeb.14230)
  • Ramakrishna, K.; Lokamani, M.; Baczewski, A. et al.
    Impact of electronic correlations on high-pressure iron: insights from time-dependent density functional theory
    Electronic Structure 5(2023), 045002 (10.1088/2516-1075/acfd75)
  • Eschle, J.; Gal, T.; Giordano, M. et al.
    Potential of the Julia programming language for high energy physics computing
    Computing and Software for Big Science 7(2023)1, 10 (10.1007/s41781-023-00104-x)
  • Suma Balakrishnan, S. L.; Lokamani, M.; Ramakrishna, K. et al.
    Ab initio insights on the ultrafast strong-field dynamics of anatase TiO2
    Physical Review B 108(2023), 195149 (10.1103/PhysRevB.108.195149)
  • Eingorn, M.; Yilmaz, E.; Yukselci, A. E. et al.
    Mass density vs. energy density at cosmological scales
    Physics Letters B 851(2024), 138564 (10.1016/j.physletb.2024.138564)
  • Moldabekov, Z.; Schwalbe, S.; Böhme, M. et al.
    Bound state breaking and the importance of thermal exchange-correlation effects in warm dense hydrogen
    Journal of Chemical Theory and Computation 20(2023), 68-78 (10.1021/acs.jctc.3c00934)
  • Davoodi Monfared, M.; Senapati, A.; Mertel, A. et al.
    On the optimal presence strategies for workplace during pandemics: A COVID-19 inspired probabilistic model
    PLOS ONE 18(2023)5, 1 (10.1371/journal.pone.0285601)
  • Tolias, P.; Dornheim, T.; Moldabekov, Z. et al.
    Unravelling the nonlinear ideal density response of many-body systems
    EPL - Europhysics Letters 142(2023), 44001 (10.1209/0295-5075/acd3a6)
  • Dornheim, T.; Tolias, P.; Groth, S. et al.
    Fermionic physics from ab initio path integral Monte Carlo simulations of fictitious identical particles
    Journal of Chemical Physics 15(2023), 164113 (10.1063/5.0171930)
  • Maddu, S.; Sturm, D.; Cheeseman, B. L. et al.
    STENCIL-NET for equation-free forecasting from data
    Scientific Reports 13(2023), 12787 (10.1038/s41598-023-39418-6)
  • Davoodi Monfared, M.; Rezaei, J.
    Bi-sided facility location problems: an efficient algorithm for k-centre, k-median, and travelling salesman problems
    International Journal of Systems Science: Operations & Logistics 10(2023)1, 2235814-2235834 (10.1080/23302674.2023.2235814)
  • Götz, A.; Le Gall, E.; Konrad, U. et al.
    LEAPS Data Strategy
    European Physical Journal Plus 138(2023), 617 (10.1140/epjp/s13360-023-04189-6)
  • Davoodi Monfared, M.; Batista, A.; Senapati, A. et al.
    Personnel Scheduling during the COVID-19 Pandemic: A Probabilistic Graph-Based Approach
    Healthcare 11(2023)13, 1917-1934 (10.3390/healthcare11131917)
  • Moldabekov, Z.; Vorberger, J.; Lokamani, M. et al.
    Averaging over atom snapshots in linear-response TDDFT of disordered systems: A case study of warm dense hydrogen
    Journal of Chemical Physics 159(2023), 014107 (10.1063/5.0152126)
  • Brilenkov, M.; Yilmaz, E.; Eingorn, M.
    Cosmological Perturbations Engendered by Discrete Relativistic Species
    European Physical Journal C 83(2023), 601 (10.1140/epjc/s10052-023-11803-5)
  • Blaschke, D.; Cierniak, M.; Ivanytskyi, O. et al.
    Thermodynamics of quark matter with multi-quark clusters
    European Physical Journal A 60(2024), 14 (10.1140/epja/s10050-023-01229-8)
  • Maslov, K.; Blaschke, D.
    Effect of mesonic off-shell correlations in the PNJL equation of state
    Physical Review D 107(2023), 094010 (10.1103/PhysRevD.107.094010)
  • Dornheim, T.; Böhme, M.; Moldabekov, Z. et al.
    Electronic density response of warm dense hydrogen on the nanoscale
    Physical Review E 108(2023), 035204 (10.1103/PhysRevE.108.035204)
  • Hentschel, T. W.; Kononov, A.; Olmstead, A. et al.
    Improving dynamic collision frequencies: Impacts on dynamic structure factors and stopping powers in warm dense matter
    Physics of Plasmas 30(2023), 062703 (10.1063/5.0143738)
  • Adoni, W. Y. H.; Lorenz, S.; Shaik Fareedh, J. et al.
    Investigation of Autonomous Multi-UAV Systems for Target Detection in Distributed Environment: Current Developments and Open Challenges
    Drones 7(2023)4, 263 (10.3390/drones7040263)
  • Kheybari, S.; Davoodi Monfared, M.; Salimirad, A. et al.
    Bioethanol sustainable supply chain design: A multi-attribute bi-objective structure
    Computers & Industrial Engineering 180(2023), 109258 (10.1016/j.cie.2023.109258)
  • Ueberholz, K.; Bozyk, L.; Bussmann, M. et al.
    XUV Fluorescence Detection of Laser-Cooled Stored Relativistic Ions
    Atoms 11(2023)2, 39 (10.3390/atoms11020039)
  • Hernandez Acosta, U.; Kämpfer, B.
    Strong-field QED in Furry-picture momentum-space formulation: Ward identities and Feynman diagrams
    Physical Review D 108(2023)1, 016013 (10.1103/PhysRevD.108.016013)
  • Kumar, S.; Tahmasbi, H.; Ramakrishna, K. et al.
    Transferable Interatomic Potentials for Aluminum from Ambient Conditions to Warm Dense Matter
    Physical Review Research 5(2023), 033162 (10.1103/PhysRevResearch.5.033162)
  • Alston, J.; Keinath, D.; Willis, C. et al.
    Environmental drivers of body size in North American bats
    Functional Ecology 37(2023)4, 1020-1032 (10.1111/1365-2435.14287)
  • Chen, D. Y.; Wang, H. B.; Wen, W. Q. et al.
    Explanation for the observed wide deceleration range on a coasting ion beam by a CW laser at the storage ring CSRe
    Nuclear Instruments and Methods in Physics Research A 1047(2023), 167852 (10.1016/j.nima.2022.167852)
  • Ataei, H.; Davoodi Monfared, M.
    The p-center problem under locational uncertainty of demand points
    Discrete Optimization 47(2023), 100759-100771 (10.1016/j.disopt.2023.100759)
  • Moldabekov, Z.; Pavanello, M.; Boehme, M. P. et al.
    Linear-response time-dependent density functional theory approach to warm dense matter with adiabatic exchange--correlation kernels
    Physical Review Research 5(2023)2, 023089 (10.1103/PhysRevResearch.5.023089)
  • Ser-Giacomi, E.; Martinez Garcia, R.; Dutkiewicz, S. et al.
    A Lagrangian model for drifting ecosystems reveals heterogeneity-driven enhancement of marine plankton blooms
    Nature Communications 14(2023), 6092 (10.1038/s41467-023-41469-2)
  • Ódor, G.; Papp, I.; Deng, S. et al.
    Synchronization transitions on connectome graphs with external force
    Frontiers in Physics 11(2023), 1150246 (10.3389/fphy.2023.1150246)
  • Dornheim, T.; Tolias, P.; Moldabekov, Z. et al.
    Energy response and spatial alignment of the perturbed electron gas
    Journal of Chemical Physics 158(2023)16 (10.1063/5.0146503)
  • Konar, D.; Sarma, A. D.; Bhandary, S. et al.
    A shallow hybrid classical-quantum spiking feedforward neural network for noise-robust image classification
    Applied Soft Computing 136(2023), 110099 (10.1016/j.asoc.2023.110099)
  • Tolias, P.; Lucco Castello, F.; Dornheim, T.
    Quantum version of the integral equation theory based dielectric scheme for strongly coupled electron liquids
    Journal of Chemical Physics 158(2023), 141102 (10.1063/5.0145687)
  • Simoes Silva, I. M.; Fleming, C. H.; Noonan, M. J. et al.
    movedesign: Shiny R app to evaluate sampling design for animal tracking movement studies
    Methods in Ecology and Evolution 14(2023)9, 2216-2225 (10.1111/2041-210X.14153)
  • Dornheim, T.; Moldabekov, Z.; Ramakrishna, K. et al.
    Electronic Density Response of Warm Dense Matter
    Physics of Plasmas 30(2023), 032705 (10.1063/5.0138955)
  • Dornheim, T.; Böhme, M.; Chapman, D. et al.
    Imaginary-time correlation function thermometry: A new, high-accuracy and model-free temperature analysis technique for x-ray Thomson scattering data
    Physics of Plasmas 30(2023), 042707 (10.1063/5.0139560)
  • Dornheim, T.; Wicaksono, D. C.; Suarez Cardona, J. E. et al.
    Extraction of the frequency moments of spectral densities from imaginary-time correlation function data
    Physical Review B 107(2023)15, 155148 (10.1103/PhysRevB.107.155148)
  • Konar, D.; Bhattacharyya, S.; Gandhi, T. K. et al.
    3D Quantum-inspired Self-supervised Tensor Network for Volumetric Segmentation of Medical Images
    IEEE Transaction on Neural Networks and Learning Systems (2024), 10038494 (10.1109/TNNLS.2023.3240238)
  • Tripathi, R.; Reza, A.; Su, G. et al.
    A network-based approach to identifying correlations between phylogeny, morphological traits and occurrence of fish species in US river basins.
    PLOS ONE 18(2023), e0287482 (10.1371/journal.pone.0287482)
  • Su, G.; Mertel, A.; Brosse, S. et al.
    Species invasiveness and community invasibility of US freshwater fish fauna revealed via trait-based analysis
    Nature Communications 14(2023)1, 2332 (10.1038/s41467-023-38107-2)
  • Demers, J.; Fagan, W.; Potluri, S. et al.
    The relationship between controllability, optimal testing resource allocation, and incubation-latent period mismatch as revealed by COVID-19
    Infectious Disease Modelling 8(2023)2, 514-538 (10.1016/j.idm.2023.04.007)
  • Wells, H. B. M.; Crego, R. D.; Alston, J. et al.
    Wild herbivores enhance resistance to invasion by exotic cacti in an African savanna
    Journal of Ecology 111(2023)1, 33-44 (10.1111/1365-2745.14010)
  • Zavalani, G.; Shehu, E.
    A note on the rate of convergence of integration schemes for closed surfaces
    Computational and Applied Mathematics 43(2024), 92 (10.1007/s40314-024-02611-y)
  • Suarez Cardona, J. E.; Hecht, M.
    Polynomial differentiation decreases the training time complexity of physics-informed neural networks and strengthens their approximation power
    Machine Learning: Science and Technology 4(2023), 045005 (10.1088/2632-2153/acf97a)
  • Thekke Veettil, Sachin K.; Zavalani, G.; Hernandez Acosta, U. et al.
    Global Polynomial Level Sets for Numerical Differential Geometry of Smooth Closed Surfaces
    SIAM Journal on Scientific Computing 45(2023)4, A1995-A2018 (10.1137/22M1536510)
  • Svensson, P.; Campbell, T.; Graziani, F. et al.
    Development of a new quantum trajectory molecular dynamics framework
    Philosophical Transactions of the Royal Society A 381(2023), 20220325 (10.1098/rsta.2022.0325)
  • Moldabekov, Z.; Lokamani, M.; Vorberger, J. et al.
    Assessing the accuracy of hybrid exchange-correlation functionals for the density response of warm dense electrons
    Journal of Chemical Physics 158(2023), 094105 (10.1063/5.0135729)
  • Moldabekov, Z.; Lokamani, M.; Vorberger, J. et al.
    Non-empirical mixing coefficient for hybrid XC functionals from analysis of the XC kernel
    Journal of Physical Chemistry Letters 14(2023)5, 1326-1333 (10.1021/acs.jpclett.2c03670)
  • Li, R.; Kudryashev, M.; Yakimovich, A.
    A weak-labelling and deep learning approach for in-focus object segmentation in 3D widefield microscopy
    Scientific Reports 13(2023)1, 12275 (10.1038/s41598-023-38490-2)
  • Fan, K.; Dhammapala, R.; Harrington, K. et al.
    Machine learning-based ozone and PM2.5 forecasting: Application to multiple AQS sites in the Pacific Northwest
    Frontiers in Big Data 6(2023), 1124148 (10.3389/fdata.2023.1124148)
  • Mertel, A.; Zbíral, D.; Stachoň, Z. et al.
    Historical geocoding assistant
    SoftwareX 14(2021), 100682 (10.1016/j.softx.2021.100682)
  • Roy, M.; Senapati, A.; Poria, S. et al.
    Role of assortativity in predicting burst synchronization using echo state network
    Physical Review E 105(2022), 064205 (10.1103/PhysRevE.105.064205)
  • Fu, X.; Patel, H. P.; Coppola, S. et al.
    Quantifying how post-transcriptional noise and gene copy number variation bias transcriptional parameter inference from mRNA distributions
    eLife 11(2022), e82493. (10.7554/eLife.82493)
  • Hecht, M.; Sbalzarini, I. F.
    Biggs Theorem for Directed Cycles and Topological Invariants of Digraphs
    Advances in Pure Mathematics 11(2021), 573-594 (10.4236/apm.2021.116037)
  • Zhuk, O.; Shulga, V.
    Effect of Medium on Fundamental Interactions in Gravity and Condensed Matter
    Frontiers in Physics 10(2022), 875757 (10.3389/fphy.2022.875757)
  • Canay, E.; Eingorn, M.; McLaughlin, I. A. et al.
    Effect of peculiar velocities of inhomogeneities on the shape of gravitational potential in spatially curved universe
    Physics Letters B 831(2022), 137175 (10.1016/j.physletb.2022.137175)
  • Fiedler, L.; Modine, N.; Schmerler, S. et al.
    Predicting electronic structures at any length scale with machine learning
    npj Computational Materials 9(2023)1, 115 (10.1038/s41524-023-01070-z)
  • Davoodi Monfared, M.; Ghaffari, M.
    Learning-based systems for assessing hazard places of contagious diseases and diagnosing patient possibility
    Expert Systems With Applications 213(2023)1, 1 (10.1016/j.eswa.2022.119043)
  • Dornheim, T.; Vorberger, J.; Moldabekov, Z. et al.
    Analysing the dynamic structure of warm dense matter in the imaginary-time domain: theoretical models and simulations
    Philosophical Transactions of the Royal Society A 381(2023)2253 (10.1098/rsta.2022.0217)
  • Dietrich, W.; Kumar, S.; Poser, A. J. et al.
    Magnetic induction processes in hot Jupiters, application to KELT-9b
    Monthly Notices of the Royal Astronomical Society 517(2022), 3113-3125 (10.1093/mnras/stac2849)
  • Schörner, M.; Witte, B. B. L.; Baczewski, A. D. et al.
    Ab initio study of shock-compressed copper
    Physical Review B 106(2022), 054304 (10.1103/PhysRevB.106.054304)
  • Fiedler, L.; Hoffmann, N.; Mohammed, P. et al.
    Training-free hyperparameter optimization of neural networks for electronic structures in matter
    Machine Learning: Science and Technology 3(2022), 045008 (10.1088/2632-2153/ac9956)
  • Dornheim, T.; Böhme, M.; Kraus, D. et al.
    Accurate temperature diagnostics for matter under extreme conditions
    Nature Communications 13(2022), 7911 (10.1038/s41467-022-35578-7)
  • Dornheim, T.; Moldabekov, Z.; Tolias, P. et al.
    Physical insights from imaginary-time density--density correlation functions
    Matter and Radiation at Extremes 8(2023), 056601 (10.1063/5.0149638)
  • Moldabekov, Z.; Böhme, M.; Vorberger, J. et al.
    Ab Initio Static Exchange-Correlation Kernel across Jacob’s Ladder without Functional Derivatives
    Journal of Chemical Theory and Computation 19(2023)4, 1286-1299 (10.1021/acs.jctc.2c01180)
  • Ódor, G.; Deng, S.; Hartmann, B. et al.
    Synchronization dynamics on power grids in Europe and the United States
    Physical Review E 106(2022), 034311 (10.1103/PhysRevE.106.034311)
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