Prof. Dr. Jörg Behler

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  • 2022 | Journal Article | Research Paper | 
    ​ ​Roadmap on Machine learning in electronic structure​
    Kulik, H. J.; Hammerschmidt, T.; Schmidt, J.; Botti, S.; Marques, M. A. L.; Boley, M. & Scheffler, M. et al.​ (2022) 
    Electronic Structure, 4(2).​ DOI: https://doi.org/10.1088/2516-1075/ac572f 
    ​Details  DOI 
  • 2021 | Journal Article
    ​ ​Properties of α-Brass Nanoparticles II: Structure and Composition​
    Weinreich, J.; Paleico, M. L. & Behler, J. ​ (2021) 
    The Journal of Physical Chemistry. C, Nanomaterials and interfaces, 125(27) pp. 14897​-14909​.​ DOI: https://doi.org/10.1021/acs.jpcc.1c02314 
    ​Details  DOI 
  • 2021 | Journal Article
    ​ ​General-Purpose Machine Learning Potentials Capturing Nonlocal Charge Transfer​
    Ko, T. W.; Finkler, J. A.; Goedecker, S. & Behler, J. ​ (2021) 
    Accounts of Chemical Research, 54(4) pp. 808​-817​.​ DOI: https://doi.org/10.1021/acs.accounts.0c00689 
    ​Details  DOI 
  • 2021 | Journal Article
    ​ ​Four Generations of High-Dimensional Neural Network Potentials​
    Behler, J. ​ (2021) 
    Chemical Reviews, 121(16) pp. 10037​-10072​.​ DOI: https://doi.org/10.1021/acs.chemrev.0c00868 
    ​Details  DOI 
  • 2021 | Journal Article | 
    ​ ​Mechanism of amorphous phase stabilization in ultrathin films of monoatomic phase change material​
    Dragoni, D.; Behler, J.   & Bernasconi, M.​ (2021) 
    Nanoscale,.​ DOI: https://doi.org/10.1039/D1NR03432D 
    ​Details  DOI 
  • 2020 | Preprint
    ​ ​A criticial view on e$ occupancy as a descriptor for oxygen evolution catalytic activity in LiMn$ nanoparticles​
    Schönewald, F.; Eckhoff, M.; Baumung, M.; Risch, M. ; Blöchl, P. E. ; Behler, J.  & Volkert, C. A. ​ (2020)
    ​Details  arXiv 
  • 2020 | Journal Article | Research Paper
    ​ ​Hybrid density functional theory benchmark study on lithium manganese oxides​
    Eckhoff, M.; Blöchl, P. E.   & Behler, J. ​ (2020) 
    Physical Review B, 101(20).​ DOI: https://doi.org/10.1103/PhysRevB.101.205113 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​Temperature dependence of the vibrational spectrum of porphycene: a qualitative failure of classical-nuclei molecular dynamics​
    Litman, Y.; Behler, J.   & Rossi, M.​ (2020) 
    Faraday Discussions, 221 pp. 526​-546​.​ DOI: https://doi.org/10.1039/c9fd00056a 
    ​Details  DOI 
  • 2020 | Journal Article | Research Paper
    ​ ​Predicting oxidation and spin states by high-dimensional neural networks: Applications to lithium manganese oxide spinels​
    Eckhoff, M.; Lausch, K. N.; Blöchl, P. E.   & Behler, J. ​ (2020) 
    The Journal of Chemical Physics, 153(16) pp. 164107​.​ DOI: https://doi.org/10.1063/5.0021452 
    ​Details  DOI 
  • 2020 | Journal Article | Erratum
    ​ ​Correction: A critical comparison of neural network potentials for molecular reaction dynamics with exact permutation symmetry​
    Li, J.; Song, K. & Behler, J. ​ (2020) 
    Physical Chemistry Chemical Physics, 22(47) pp. 27914​-27915​.​ DOI: https://doi.org/10.1039/d0cp90265a 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​Transferability of neural network potentials for varying stoichiometry: Phonons and thermal conductivity of Mn x Ge y compounds​
    Mangold, C.; Chen, S.; Barbalinardo, G.; Behler, J. ; Pochet, P.; Termentzidis, K. & Han, Y. et al.​ (2020) 
    Journal of Applied Physics, 127(24) pp. 244901​.​ DOI: https://doi.org/10.1063/5.0009550 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​Insights into Water Permeation through hBN Nanocapillaries by Ab Initio Machine Learning Molecular Dynamics Simulations​
    Ghorbanfekr, H.; Behler, J.   & Peeters, F. M.​ (2020) 
    The Journal of Physical Chemistry Letters, 11(17) pp. 7363​-7370​.​ DOI: https://doi.org/10.1021/acs.jpclett.0c01739 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​A flexible and adaptive grid algorithm for global optimization utilizing basin hopping Monte Carlo​
    Paleico, M. L. & Behler, J. ​ (2020) 
    The Journal of Chemical Physics, 152(9) pp. 094109​.​ DOI: https://doi.org/10.1063/1.5142363 
    ​Details  DOI 
  • 2020 | Journal Article | Research Paper
    ​ ​Closing the gap between theory and experiment for lithium manganese oxide spinels using a high-dimensional neural network potential​
    Eckhoff, M.; Schönewald, F.; Risch, M. ; Volkert, C. A. ; Blöchl, P. E.   & Behler, J. ​ (2020) 
    Physical Review B, 102(17).​ DOI: https://doi.org/10.1103/PhysRevB.102.174102 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​Global optimization of copper clusters at the ZnO(101¯0) surface using a DFT-based neural network potential and genetic algorithms​
    Paleico, M. L. & Behler, J. ​ (2020) 
    The Journal of Chemical Physics, 153(5) pp. 054704​.​ DOI: https://doi.org/10.1063/5.0014876 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​Temperature effects on the ionic conductivity in concentrated alkaline electrolyte solutions​
    Shao, Y.; Hellström, M.; Yllö, A.; Mindemark, J.; Hermansson, K.; Behler, J.   & Zhang, C.​ (2020) 
    Physical Chemistry Chemical Physics, 22(19) pp. 10426​-10430​.​ DOI: https://doi.org/10.1039/c9cp06479f 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​Properties of α-Brass Nanoparticles. 1. Neural Network Potential Energy Surface​
    Weinreich, J.; Römer, A.; Paleico, M. L. & Behler, J. ​ (2020) 
    The Journal of Physical Chemistry C, 124(23) pp. 12682​-12695​.​ DOI: https://doi.org/10.1021/acs.jpcc.0c00559 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​Accurate Global Potential Energy Surfaces for the H + CH3OH Reaction by Neural Network Fitting with Permutation Invariance​
    Lu, D.; Behler, J.   & Li, J.​ (2020) 
    The Journal of Physical Chemistry A, 124(28) pp. 5737​-5745​.​ DOI: https://doi.org/10.1021/acs.jpca.0c04182 
    ​Details  DOI 
  • 2020 | Journal Article | Research Paper | 
    ​ ​An experimentally validated neural-network potential energy surface for H-atom on free-standing graphene in full dimensionality​
    Wille, S.; Jiang, H.; Bünermann, O.; Wodtke, A. M. ; Behler, J.   & Kandratsenka, A.​ (2020) 
    Physical Chemistry Chemical Physics, 22(45) pp. 26113​-26120​.​ DOI: https://doi.org/10.1039/d0cp03462b 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​New Insights into the Catalytic Activity of Cobalt Orthophosphate Co 3 (PO 4 ) 2 from Charge Density Analysis​
    Keil, H.; Hellström, M.; Stückl, C.; Herbst‐Irmer, R. ; Behler, J.   & Stalke, D. ​ (2019) 
    Chemistry – A European Journal, 25(69) pp. 15786​-15794​.​ DOI: https://doi.org/10.1002/chem.v25.69 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Automated Fitting of Neural Network Potentials at Coupled Cluster Accuracy: Protonated Water Clusters as Testing Ground​
    Schran, C.; Behler, J.   & Marx, D.​ (2019) 
    Journal of Chemical Theory and Computation, 16(1) pp. 88​-99​.​ DOI: https://doi.org/10.1021/acs.jctc.9b00805 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Library-Based LAMMPS Implementation of High-Dimensional Neural Network Potentials​
    Singraber, A.; Behler, J.   & Dellago, C.​ (2019) 
    Journal of Chemical Theory and Computation, 15(3) pp. 1827​-1840​.​ DOI: https://doi.org/10.1021/acs.jctc.8b00770 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Parallel Multistream Training of High-Dimensional Neural Network Potentials​
    Singraber, A.; Morawietz, T.; Behler, J.   & Dellago, C.​ (2019) 
    Journal of Chemical Theory and Computation, 15(5) pp. 3075​-3092​.​ DOI: https://doi.org/10.1021/acs.jctc.8b01092 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​From Molecular Fragments to the Bulk: Development of a Neural Network Potential for MOF-5​
    Eckhoff, M. & Behler, J. ​ (2019) 
    Journal of Chemical Theory and Computation, 15(6) pp. 3793​-3809​.​ DOI: https://doi.org/10.1021/acs.jctc.8b01288 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Priming effects in the crystallization of the phase change compound GeTe from atomistic simulations​
    Gabardi, S.; Sosso, G. G.; Behler, J.   & Bernasconi, M.​ (2019) 
    Faraday Discussions, 213 pp. 287​-301​.​ DOI: https://doi.org/10.1039/C8FD00101D 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Atomistic simulations of thermal conductivity in GeTe nanowires​
    Bosoni, E.; Campi, D.; Donadio, D.; Sosso, G C; Behler, J.   & Bernasconi, M.​ (2019) 
    Journal of Physics D: Applied Physics, 53(5) pp. 054001​.​ DOI: https://doi.org/10.1088/1361-6463/ab5478 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Performance and Cost Assessment of Machine Learning Interatomic Potentials​
    Zuo, Y.; Chen, C.; Li, X.; Deng, Z.; Chen, Y.; Behler, J.   & Csányi, G. et al.​ (2019) 
    The Journal of Physical Chemistry A, 124(4) pp. 731​-745​.​ DOI: https://doi.org/10.1021/acs.jpca.9b08723 
    ​Details  DOI 
  • 2019 | Journal Article | 
    ​ ​A critical comparison of neural network potentials for molecular reaction dynamics with exact permutation symmetry​
    Li, J.; Song, K. & Behler, J. ​ (2019) 
    Physical Chemistry Chemical Physics, 21(19) pp. 9672​-9682​.​ DOI: https://doi.org/10.1039/C8CP06919K 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Ab initio thermodynamics of liquid and solid water​
    Cheng, B.; Engel, E. A.; Behler, J. ; Dellago, C. & Ceriotti, M.​ (2019) 
    Proceedings of the National Academy of Sciences of the United States of America, 116(4) pp. 1110​-1115​.​ DOI: https://doi.org/10.1073/pnas.1815117116 
    ​Details  DOI  PMID  PMC  arXiv 
  • 2018 | Journal Article
    ​ ​Nuclear Quantum Effects in Sodium Hydroxide Solutions from Neural Network Molecular Dynamics Simulations​
    Hellström, M.; Ceriotti, M. & Behler, J. ​ (2018) 
    The Journal of Physical Chemistry B, 122(44) pp. 10158​-10171​.​ DOI: https://doi.org/10.1021/acs.jpcb.8b06433 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​Structure and Dynamics of the Liquid–Water/Zinc-Oxide Interface from Machine Learning Potential Simulations​
    Quaranta, V.; Behler, J.   & Hellström, M.​ (2018) 
    The Journal of Physical Chemistry C, 123(2) pp. 1293​-1304​.​ DOI: https://doi.org/10.1021/acs.jpcc.8b10781 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​High-dimensional neural network potentials for solvation: The case of protonated water clusters in helium​
    Schran, C.; Uhl, F.; Behler, J.   & Marx, D.​ (2018) 
    The Journal of Chemical Physics, 148(10) pp. 102310​.​ DOI: https://doi.org/10.1063/1.4996819 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​Maximally resolved anharmonic OH vibrational spectrum of the water/ZnO(101¯0) interface from a high-dimensional neural network potential​
    Quaranta, V.; Hellström, M.; Behler, J. ; Kullgren, J.; Mitev, P. D. & Hermansson, K.​ (2018) 
    The Journal of Chemical Physics, 148(24) pp. 241720​.​ DOI: https://doi.org/10.1063/1.5012980 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials​
    Imbalzano, G.; Anelli, A.; Giofré, D.; Klees, S.; Behler, J.   & Ceriotti, M.​ (2018) 
    The Journal of Chemical Physics, 148(24) pp. 241730​.​ DOI: https://doi.org/10.1063/1.5024611 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions​
    Nguyen, T. T.; Székely, E.; Imbalzano, G.; Behler, J. ; Csányi, G.; Ceriotti, M. & Götz, A. W. et al.​ (2018) 
    The Journal of Chemical Physics, 148(24) pp. 241725​.​ DOI: https://doi.org/10.1063/1.5024577 
    ​Details  DOI 
  • 2018 | Journal Article | 
    ​ ​Density anomaly of water at negative pressures from first principles​
    Singraber, A.; Morawietz, T.; Behler, J.   & Dellago, C.​ (2018) 
    Journal of Physics: Condensed Matter, 30(25) pp. 254005​.​ DOI: https://doi.org/10.1088/1361-648X/aac4f4 
    ​Details  DOI 
  • 2017 | Journal Article
    ​ ​Atomistic Simulations of the Crystallization and Aging of GeTe Nanowires​
    Gabardi, S.; Baldi, E.; Bosoni, E.; Campi, D.; Caravati, S.; Sosso, G. C. & Behler, J.  et al.​ (2017) 
    The Journal of Physical Chemistry C, 121(42) pp. 23827​-23838​.​ DOI: https://doi.org/10.1021/acs.jpcc.7b09862 
    ​Details  DOI 
  • 2017 | Journal Article
    ​ ​First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems​
    Behler, J. ​ (2017) 
    Angewandte Chemie International Edition, 56(42) pp. 12828​-12840​.​ DOI: https://doi.org/10.1002/anie.201703114 
    ​Details  DOI 
  • 2017 | Journal Article | 
    ​ ​Machine learning molecular dynamics for the simulation of infrared spectra​
    Gastegger, M.; Behler, J.   & Marquetand, P.​ (2017) 
    Chemical Science, 8(10) pp. 6924​-6935​.​ DOI: https://doi.org/10.1039/C7SC02267K 
    ​Details  DOI 
  • 2017 | Journal Article | 
    ​ ​Accurate Neural Network Description of Surface Phonons in Reactive Gas-Surface Dynamics: N-2 + Ru(0001)​
    Shakouri, K.; Behler, J. ; Meyer, J. & Kroes, G.-J.​ (2017) 
    The Journal of Physical Chemistry Letters, 8(10) pp. 2131​-2136​.​ DOI: https://doi.org/10.1021/acs.jpclett.7b00784 
    ​Details  DOI  PMID  PMC  WoS 

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