Author Behler, Jörg

• 2017 | Journal Article
  ​ ​Surface phase diagram prediction from a minimal number of DFT calculations: redox-active adsorbates on zinc oxide​
  Hellström, M. & Behler, J.​ (2017) 
  Physical Chemistry Chemical Physics, 19(42) pp. 28731​-28748​.​ DOI: https://doi.org/10.1039/C7CP05182D 
  ​Details  DOI 

• 2018 | Journal Article | 
  ​ ​Analysis of Energy Dissipation Channels in a Benchmark System of Activated Dissociation: N2 on Ru(0001).​
  Shakouri, K.; Behler, J.; Meyer, J. & Kroes, G.-J.​ (2018) 
  The Journal of Physical Chemistry. C, Nanomaterials and Interfaces, 122(41) pp. 23470​-23480​.​ DOI: https://doi.org/10.1021/acs.jpcc.8b06729 
  ​Details  DOI  PMID  PMC 

• 2019 | Journal Article | 
  ​ ​One-dimensional vs. two-dimensional proton transport processes at solid–liquid zinc-oxide–water interfaces​
  Hellström, M.; Quaranta, V. & Behler, J.​ (2019) 
  Chemical Science, 10(4) pp. 1232​-1243​.​ DOI: https://doi.org/10.1039/C8SC03033B 
  ​Details  DOI 

• 2019 | Book Chapter
  ​ ​High-Dimensional Neural Network Potentials for Atomistic Simulations​
  Hellström, M.& Behler, J.​ (2019)
  In:​Pyzer-Knapp, Edward O.; Laino, Teodoro​ (Eds.), Machine Learning in Chemistry: Data-Driven Algorithms, Learning Systems, and Predictions pp. 49​-59. ​Washington, DC: ​American Chemical Society. DOI: https://doi.org/10.1021/bk-2019-1326.ch003 
  ​Details  DOI 

• 2019 | Journal Article | 
  ​ ​Accurate Probabilities for Highly Activated Reaction of Polyatomic Molecules on Surfaces Using a High-Dimensional Neural Network Potential: CHD 3 + Cu(111)​
  Gerrits, N.; Shakouri, K.; Behler, J. & Kroes, G.-J.​ (2019) 
  The Journal of Physical Chemistry Letters, 10(8) pp. 1763​-1768​.​ DOI: https://doi.org/10.1021/acs.jpclett.9b00560 
  ​Details  DOI  PMID  PMC 

• 2019 | Journal Article | 
  ​ ​New Insights in the Catalytic Activity of Cobalt Orthophosphate Co3 (PO4)2 from Charge Density Analysis​
  Keil, H.; Hellström, M.; Stückl, C.; Herbst‐Irmer, R.; Behler, J. & Stalke, D.​ (2019) 
  Chemistry – A European Journal, 25(25) pp. 15786​-15794​.​ DOI: https://doi.org/10.1002/chem.201902303 
  ​Details  DOI  PMID  PMC 

• 2019 | Journal Article | 
  ​ ​Orbital-Dependent Electronic Friction Significantly Affects the Description of Reactive Scattering of N 2 from Ru(0001)​
  Spiering, P.; Shakouri, K.; Behler, J.; Kroes, G.-J. & Meyer, J.​ (2019) 
  The Journal of Physical Chemistry Letters, 10(11) pp. 2957​-2962​.​ DOI: https://doi.org/10.1021/acs.jpclett.9b00523 
  ​Details  DOI  PMID  PMC 

• 2020 | Book Chapter
  ​ ​High-Dimensional Neural Network Potentials for Atomistic Simulations​
  Hellström, M.& Behler, J.​ (2020)
  In:​Schütt, Kristof T.; Chmiela, Stefan; von Lilienfeld, O. Anatole; Tkatchenko, Alexandre; Tsuda, Koji; Müller, Klaus-Robert​ (Eds.), Machine Learning Meets Quantum Physics pp. 253​-275. ​Cham: ​Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-40245-7_13 
  ​Details  DOI 

• 2021 | Journal Article | Research Paper
  ​ ​Insights into lithium manganese oxide–water interfaces using machine learning potentials​
  Eckhoff, M. & Behler, J.​ (2021) 
  The Journal of Chemical Physics, 155(24) pp. 244703​.​ DOI: https://doi.org/10.1063/5.0073449 
  ​Details  DOI  PMID  PMC 

• 2021 | Journal Article | Research Paper | 
  ​ ​A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer​
  Ko, T. W.; Finkler, J. A.; Goedecker, S. & Behler, J.​ (2021) 
  Nature Communications, 12(1).​ DOI: https://doi.org/10.1038/s41467-020-20427-2 
  ​Details  DOI 

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