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Journal Articles

ORCID: 0000-0002-1220-1542

ResearcherID: C-8191-2014

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119.   Thumb-2024-3-100x  

M. Gubler, J. A. Finkler, M. R. Schäfer, J. Behler, S. Goedecker, "Accelerating fourth-generation machine learning potentials
by quasi-linear scaling particle mesh charge equilibration"
submitted (2024).

  
           
118.   Thumb-2024-2-100x  

S. Menon, Y. Lysogorskiy, A. L. M. Knoll, N. Leimeroth, M. Poul, M. Qamar, J. Janssen, M. Mrovec, J. Rohrer, K. Albe, J. Behler, R. Drautz, J. Neugebauer
"From electrons to phase diagrams with classical and machine learning potentials: automated workflows for materials science with pyiron"
submitted (2024).

  
           
117.   Thumb-2024-1-100x  

A. Omranpour, P. Montero De Hijes, J. Behler, C. Dellago
"Perspective: Atomistic Simulations of Water and Aqueous Systems with Machine Learning Potentials"
submitted (2024).
         
116.   Thumb-2023-5-100x   M. Liebetrau, Y. Dorenkamp, O. Bünermann, and J. Behler
"Hydrogen Atom Scattering at the Al2O3(0001) Surface: A Combined Experimental and Theoretical Study"
Phys. Chem. Chem. Phys. 26 (2024) 1696.
         
115.   Thumb-2023-4-100x  

M. Abedi, J. Behler, and C. F. Goldsmith
"High-Dimensional Neural Network Potentials for Accurate Prediction of Equation of State: A Case Study of Methane"
J. Chem. Theory Comput. 19 (2023) 7825.
         
114.   Thumb-2023-6-100x  

R. Herbst-Irmer, X. Wang, L. Haberstock, I. Köhne, R. Oswald, J. Behler, D. Stalke
"A new polymorph of white phosphorous at ambient conditions"
IUCrJ 10 (2023) 766.
         
113.   Thumb-2023-3-100x   A. M. Tokita and J. Behler
"Tutorial: How to Train a Neural Network Potential"
J. Chem. Phys. 159 (2023) 121501.
         
112.   Thumb-2023-2-100x  

H. Chikuma, G. Takasao, T. Wada, P. Chamninkwan, J. Behler, T. Taniike
"Accelerating Non-Empirical Structure Determination of Ziegler-Natta Catalysts with a High-Dimensional Neural Network Potential"
J. Phys. Chem. C 127 (2023) 11683.
         
111.     T.W. Ko, J.A. Finkler, S. Goedecker, J. Behler
"Accurate Fourth-Generation Machine Learning Potentials by Electrostatic Embedding"
J. Chem. Theory Comput. 19 (2023) 3567.
         
110.    

M. Herbold, J. Behler
"Machine learning transferable atomic forces for large systems from underconverged molecular fragments"
Phys. Chem. Chem. Phys. 25 (2023) 12979.
         
109.    

J. Daru, H. Forbert, J. Behler, D. Marx
"Coupled Cluster Molecular Dynamics of Condensed Phase Systems Enabled by Machine Learning Potentials: Liquid Water Benchmark"
Phys. Rev. Lett. 129 (2022) 226001.
         
108.     D. Shanavas Rasheeda, A. M. Santa Daria, B. Schröder, E. Matyus and J. Behler
"A High-dimensional neural network potentials for accurate vibrational frequencies: The formic acid dimer benchmark"
Phys. Chem. Chem. Phys. 24 (2022) 39281.
         
107.     M. Herbold, J. Behler
"A Hessian-Based Assessment of Atomic Forces for Training Machine Learning Interatomic Potentials"
J. Chem. Phys. 156 (2022) 114106.
         
106.       H. Kulik, T. Hammerschmidt, J. Schmidt, S. Botti, M. A. L. Marques, M. Boley, M. Scheffler, M. Todorovic, P. Rinke, C. Oses, A. Smolyanyuk, S. Curtarolo, A. Tkatchenko, A. Bartok, S. Manzhos, M. Ihara, T. Carrington, J. Behler, O. Isayev, M. Veit, A. Grisafi, J. Nigam, M. Ceriotti, K. T Schütt, J. Westermayr, M. Gastegger, R. Maurer, B, Kalita, K. Burke, R. Nagai, R. Akashi, O. Sugino, J. Hermann, F. Noe, S. Pilati, C. Draxl, M. Kuban, S. Rigamonti, M. Scheidgen, M. Esters, D. Hicks, C. Toher, P. Balachandran, I. Tamblyn, S. Whitelam, C. Bellinger and L. M. Ghiringhelli
"Roadmap on Machine Learning in Electronic Structures"
Electronic Structure 4 (2022) 023004.
         
105.     E. Kocer, T. W. Ko, J. Behler
"Neural Network Potentials: A Concise Overview of Methods"
Ann. Rev. Phys. Chem. 73 (2021) 163.
         
104.     M. Eckhoff, J. Behler
"High-Dimensional Neural Network Potentials for Magnetic Systems Using Spin-Dependent Atom-Centered Symmetry Functions"
npj Comput. Mater. 7 (2021) 170.
         
103.     M. Eckhoff, J. Behler
"Insights into lithium manganese oxide-water interfaces using machine learning potentials"
J. Chem. Phys. 155 (2021) 244703.
         
102.     D. Dragoni, J. Behler, M. Bernasconi
"Mechanism of amorphous phase stabilization in ultrathin films of monoatomic phase change material"
Nanoscale, 13 (2021) 16146.
         
101.     J. Behler, G. Csanyi
"Machine Learning Potentials for Extended Systems - A Perspective"
Eur. Phys. J. B 94 (2021) 142.
         
100.     J. Weinreich, M. L. Paleico, J. Behler
"Properties of alpha-Brass Nanoparticles II: Structure and Composition"
J. Phys. Chem. C 125 (2021) 14897.
         
99.     J. Behler
"Four Generations of High-Dimensional Neural Network Potentials"
Chem. Rev. 121 (2021) 10037.
         
98.     M.L. Paleico and J. Behler
"A Bin and Hash Method for Analyzing Reference Data and Descriptors in Machine Learning Potentials"
Mach. Learn. Sci. Techn. 2 (2021) 037001.
         
97.     B. Parsaeifard, D. Sankar De, A. S. Christensen, F. A. Faber, E. Kocer, S. De, J. Behler, O. A. von Lilienfeld, and S. Goedecker
"An assessment of the structural resolution of various fingerprints commonly used in machine learning"
Mach. Learn. Sci. Techn. 2 (2021) 015018.
         
96.     T.W. Ko, J.A. Finkler, S. Goedecker, J. Behler
"General-Purpose Machine Learning Potentials Capturing Non-local Charge Transfer"
Acc. Chem. Res. 54 (2021) 808.
         
95.     T.W. Ko, J.A. Finkler, S. Goedecker, J. Behler
"A Fourth-Generation High-Dimensional Neural Network Potential with Accurate Electrostatics Including Non-local Charge Transfer"
Nat. Commun. 12 (2021) 398.
         
94.     M. Eckhoff, F. Schönewald, M. Risch, C. A. Volkert, P. E. Blöchl, and J. Behler
"Closing the Gap between Theory and Experiment for Lithium Manganese Oxide Spinels Using a High-Dimensional Neural Network Potential"
Phys. Rev. B 102 (2020) 174102.
         
93.     M. Eckhoff, K. N. Lausch, P. E. Blöchl, and J. Behler
"Predicting Oxidation and Spin States by High-Dimensional Neural Networks: Applications to Lithium Manganese Oxide Spinels"
J. Chem. Phys. 153 (2020) 164107.
         
92.     S. Wille, H. Jiang, O. Bünermann, A. M. Wodtke, J. Behler, and A. Kandratsenka
"An experimentally validated neural-network potential energy surface for H atoms on free-standing graphene in full dimensionality"
Phys. Chem. Chem. Phys. 22 (2020) 26113.
         
91.     H. Ghorbanfekr, J. Behler, and F. M. Peeters
"Insights into water permeation through hBN nanocapillaries by ab initio machine learning molecular dynamics simulations"
J. Phys. Chem. Lett. 11 (2020) 7363.
         
90.     M L. Paleico and J. Behler
"Global Optimization of Copper Clusters at the ZnO(10-10) Surface Using a DFT-based Neural Network Potential and Genetic Algorithms"
J. Chem. Phys. 153 (2020) 054704.
         
89.     D. Lu, J. Behler, and J. Li
"Accurate Global Potential Energy Surfaces for the H + CH3OH Reaction by Neural Network Fitting with Permutation Invariance"
J. Phys. Chem. A 124 (2020) 5737.
         
88.     M. Eckhoff, P. E. Blöchl and J. Behler
"Hybrid Density Functional Theory Benchmark Study on Lithium Manganese Oxides"
Phys. Rev. B 101 (2020) 205113.
         
87.     C. Mangold, S. Chen, G. Barbalinardo, J. Behler, P. Pochet, K. Termentzidis, Y. Han, L. Chaput, D. Lacroix, and D. Donadio
"Transferability of neural network potentials for varying stoichiometry: phonons and thermal conductivity of MnxGey compounds"
J. Appl. Phys. 127 (2020) 244901.
         
86.     J. Weinreich, A. Römer, M.L. Paleico and J. Behler
"Properties of alpha-Brass Nanoparticles I: Neural Network Potential Energy Surface"
J. Phys. Chem. C 124 (2020) 12682.
         
85.     M.L. Paleico and J. Behler
"A flexible and adaptive grid algorithm for global optimization utilizing basin hopping Monte Carlo"
J. Chem. Phys. 152 (2020) 094109.
         
84.     Y. Shao, M. Hellström, A. Yllö, J. Mindemark, K. Hermansson, J. Behler, and C. Zhang
"Temperature effects on the ionic conductivity in concentrated alkaline electrolyte solutions"
Phys. Chem. Chem. Phys. 22 (2020) 10426.
         
83.     C. Schran, J. Behler, and D. Marx
"Automated Fitting of Neural Network Potentials at Coupled Cluster Accuracy: Protonated Water Clusters as Testing Ground"
J. Chem. Theory Comput. 16 (2020) 88.
         
82.     E. Bosoni, D. Campi, D. Donadio, G. C. Sosso, J. Behler, and M. Bernasconi
"Atomistic Simulations of Thermal Conductivity in GeTe Nanowires"
J. Phys. D: Appl. Phys. 53 (2020) 054001.
         
81.     Y. Zuo, C. Chen, X. Li, Z. Deng, Y. Chen, J. Behler, G. Csanyi, A. V. Shapeev, A. P. Thompson, M. A. Wood, and S. P. Ong
"A Performance and Cost Assessment of Machine Learning Interatomic Potentials"
J. Phys. Chem. A 124 (2020) 731.
         
80.     Y. Litman, J. Behler, and M. Rossi
"Temperature Dependence of the Vibrational Spectrum of Porphycene: A Qualitative Failure of Classical-Nuclei Molecular Dynamics"
Faraday Disc. 221 (2020) 526.
         
79.     H. Keil, M. Hellström, C. Stückl, R. Herbst-Irmer, J. Behler, and D. Stalke
"New insights in the catalytic activity of cobalt orthophos-phate Co3(PO4)2 from charge density analysis"
Chem. Eur. J. 25 (2019) 15786.
         
78.     P. Spiering, K. Shakouri, J. Behler, G.-J. Kroes and J. Meyer
"Orbital-Dependent Electronic Friction Signicantly Improves the Description of Reactive Scattering of N2 from Ru(0001)"
J. Phys. Chem. Lett. 10 (2019) 2957.
         
77.     M. Eckhoff and J. Behler
"From Molecular Fragments to the Bulk: Development of a Neural Network Potential for MOF-5"
J. Chem. Theory Comput. 15 (2019) 3793.
         
76.     V. Quaranta, J. Behler, and M. Hellström
"Structure and dynamics of the liquid-water/zinc-oxide interface from machine learning potential simulations"
J. Phys. Chem. C 123 (2019) 1293.
         
75.     A. Singraber, T. Morawietz, J. Behler and C. Dellago
"Parallel multi-stream training of high-dimensional neural network potentials"
J. Chem. Theory Comput. 15 (2019) 3075.
         
74.     J. Li, K. Song and J. Behler
"A critical comparison of neural network potentials for molecular reaction dynamics with exact permutation symmetry"
Phys. Chem. Chem. Phys. 21 (2019) 9672.
         
73.     B. Cheng, E. A. Engel, J. Behler, C. Dellago, and M. Ceriotti
"Ab initio thermodynamics of liquid and solid water"
PNAS 116 (2019) 1110.
         
72.     A. Singraber, J. Behler, and C. Dellago
"A library-based LAMMPS implementation of high-dimensional neural network potentials"
J. Chem. Theory Comput. 15 (2019) 1827.
         
71.     N. Gerrits, K. Shakouri, J. Behler, and G.-J. Kroes
"Accurate Probabilities for Highly Activated Reaction of Polyatomic Molecules on Surfaces Using a High-Dimensional Neural Network Potential: CHD3 + Cu(111)"
J. Phys. Chem. Lett. 10 (2019) 1763.
         
70.     M. Hellström, V. Quaranta, and J. Behler
"One-dimensional vs. two-dimensional proton transport processes at solid-liquid zinc-oxide-water interfaces"
Chem. Sci. 10 (2019) 1232.
         
69.     S. Gabardi, G. C. Sosso, J. Behler and M. Bernasconi
"Priming effects in the crystallization of the phase change compound GeTe from atomistic simulations"
Faraday Discuss. 213 (2019) 287.
         
68.     K. Shakouri, J. Behler, J. Meyer, and G.-J. Kroes
"Role of electronically non-adiabatic effects in the dissociative chemisorption of N2 on Ru(0001)"
J. Phys. Chem. C 122 (2018) 23470.
         
67.     M. Hellström, M. Ceriotti, and J. Behler
"Nuclear quantum effects in sodium hydroxide solutions from neural network molecular dynamics simulations"
J. Phys. Chem. B 122 (2018) 10158.
         
66.     A. Singraber, T. Morawietz, J. Behler and C. Dellago
"Density anomaly of water at negative pressures from first principles"
J. Phys.: Condens. Matter 30 (2018) 254005.
         
65.     G. Imbalzano, A. Anelli, D. Giofre, S. Klees, J. Behler, and M. Ceriotti
"Automatic Selection of Atomic Fingerprints and Reference Configurations for Machine-Learning Potentials"
J. Chem. Phys. 148 (2018) 241730.
         
64.     T. T. Nguyen, E. Szekely, G. Imbalzano, J. Behler, G. Csanyi, M. Ceriotti, A. W. Götz and F. Paesani
"Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions"
J. Chem. Phys. 148 (2018) 241725.
         
63.     V. Quaranta, M. Hellström, J. Behler, J. Kullgren, P. Mitev and K. Hermansson
"Maximally Resolved Anharmonic OH Vibrational Spectrum of the Water/ZnO(10-10) Interface from a High-Dimensional Neural Network Potential"
J. Chem. Phys. 148 (2018) 241720.
         
62.     C. Schran, F. Uhl, J. Behler, and D. Marx
"High-dimensional neural network potentials for solvation: The case of protonated water clusters in helium"
J. Chem. Phys. 148 (2018) 102310.
         
61.     M. Hellström and J. Behler
"Surface Phase Diagram Prediction from a Minimal Number of DFT Calculations: Redox-Active Adsorbates on Zinc Oxide"
Phys. Chem. Chem. Phys. 19 (2017) 28731.
         
60.     S. Gabardi, E. Baldi, E. Bosoni, D. Campi, S. Caravati, G. C. Sosso, J. Behler, and M. Bernasconi
"Atomistic Simulations of Crystallization Kinetics and Aging of GeTe nanowires"
J. Phys. Chem. C 121 (2017) 23827.
         
59.     M. Gastegger, J. Behler, P. Marquetand
"Machine Learning Molecular Dynamics for the Simulation of Infrared Spectra"
Chem. Sci. 8 (2017) 6924.
         
58.     J. Behler
"First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems"
Angewandte Chemie Int. Ed. 56 (2017) 12828.
and
"Hochdimensionale neuronale Netze für Potentialhyperflächen großer molekularer und kondensierter Systeme"
Angewandte Chemie 129 (2017) 13006.
         
57.     K. Shakouri, J. Behler, J. Meyer and G.-J. Kroes
"Accurate Neural Network Description of Surface Phonons in Reactive Gas-Surface Dynamics: N2+Ru(0001)"
J. Phys. Chem. Lett. 8 (2017) 2131.
         
56.     M. Hellström and J. Behler
"Proton-Transfer-Driven Water Exchange Mechanism in the Na+ Solvation Shell"
J. Phys. Chem. B 121 (2017) 4184.
         
55.     V. Quaranta, M. Hellström and J. Behler
"Proton Transfer Mechanisms at the Water-ZnO Interface: The Role of Presolvation"
J. Phys. Chem. Lett. 8 (2017) 1476.
         
54.     S. Kondati Natarajan and J. Behler
"Self-diffusion of Surface Defects at Copper-Water Interfaces"
J. Phys. Chem. C 121 (2017) 4368.
         
53.     M. Hellström and J. Behler
"Structure of aqueous NaOH solutions: Insights from neural-network-based molecular dynamics simulations"
Phys. Chem. Chem. Phys. 19 (2017) 82.
(Inside Front Cover).
         
52.     V. Kapil, J. Behler and M. Ceriotti
"High Order Path Integrals Made Easy"
J. Chem. Phys. 145 (2016) 234103.
         
51.     J. Behler
"Perspective: Machine Learning Potentials for Atomistic Simulations"
J. Chem. Phys. 145 (2016) 170901.
         
50.     D. Lu, J. Qi, M. Yang, J. Behler, H. Song and J. Li
"Mode specific dynamics in the H2 + SH → H + H2S reaction"
Phys. Chem. Chem. Phys. 18 (2016) 29113.
         
49.     S. Kondati Natarajan and J. Behler
"Neural Network Molecular Dynamics Simulations of Solid-Liquid Interfaces: Water at Low-Index Copper Surfaces"
Phys. Chem. Chem. Phys. 18 (2016) 28704.
         
48.     M. Hellström and J. Behler
"Concentration-dependent proton transfer mechanisms in aqueous NaOH solutions: From acceptor-driven to donor-driven and back"
J. Phys. Chem. Lett. 7 (2016) 3302.
         
47.     T. Morawietz, A. Singraber, C. Dellago and J. Behler
"How Van der Waals Interactions Determine the Unique Properties of Water"
PNAS 113 (2016) 8368.
         
46.     M. Gastegger, C. Kauffmann, J. Behler and P. Marquetand
"Comparing the Accuracy of High-Dimensional Neural Network Potentials and the Systematic Molecular Fragmentation Method: A Benchmark Study for all-trans Alkanes"
J. Chem. Phys. 144 (2016) 194110.
         
45.     B. Cheng, J. Behler and M. Ceriotti
"Nuclear Quantum Effects in Water at the Triple Point: Using Theory to Validate Experiments"
J. Phys. Chem. Lett. 7 (2016) 2210.
         
44.       G.C. Sosso, J. Behler and M. Bernasconi
"Atomic Mobility in the Overheated Amorphous GeTe Compound for Phase Change Memories"
Phys. Status Solidi A 213 (2016) 329.
         
43.     S. Gabardi, S. Caravati, G.C. Sosso, J. Behler and M. Bernasconi
"Microscopic Origin of Resistance Drift in the Amorphous State of the Phase-Change Compound GeTe"
Phys. Rev. B 92 (2015) 054201.
         
42.     P. Seema, J. Behler and D. Marx
"Peeling by Nanomechanical Forces: A Route to Selective Creation of Surface Structures"
Phys. Rev. Lett. 115 (2015) 036102.
         
41.     G. C. Sosso, M. Salvalaglio, J. Behler, M. Bernasconi and M. Parrinello
"Heterogeneous crystallization of phase change materials via atomistic simulations"
J. Phys. Chem. C 119 (2015) 6428.
         
40.     J. Behler
"Constructing High-Dimensional Neural Network Potentials: A Tutorial Review"
Int. J. Quantum Chem. 115 (2015) 1032. (invited review)
         
39.     D. Campi, D. Donadio, G. C. Sosso, J. Behler and M. Bernasconi
"Electron-phonon interaction and thermal boundary resistance at the crystal-amorphous interface of the phase change compound GeTe"
J. Appl. Phys. 117 (2015) 015304.
         
38.     S. Kondati Natarajan, T. Morawietz, and J. Behler
"Representing the potential-energy surface of protonated water clusters by high-dimensional neural network potentials"
Phys. Chem. Chem. Phys. 17 (2015) 8356. (invited paper)
         
37.     G. C. Sosso, J. Colombo, J. Behler, E. Del Gado, and M. Bernasconi
"Dynamical heterogeneity in the supercooled liquid state of the phase change material GeTe"
J. Phys. Chem. B 118 (2014) 13621.
         
36.     C. M. Handley and J. Behler
"Next-Generation Interatomic Potentials for Condensed Systems"
Eur. Phys. J. B 87 (2014) 152. (Invited Colloquium Paper).
         
35.     J. Behler
"Representing Potential-Energy Surfaces by High-Dimensional Neural Network Potentials"
J. Phys.: Condens. Matter 26 (2014) 183001. (Invited Topical Review).
         
34.     G.C. Sosso, G. Miceli, S. Caravati, F. Gilberti, J. Behler, and M. Bernasconi
"Fast Crystallization of the Phase Change Compound GeTe by Large Scale Molecular Dynamics Simulations"
J. Phys. Chem. Lett. 4 (2013) 4241.
         
33.     T. Morawietz and J. Behler
"A Full-Dimensional Neural Network Potential-Energy Surface for Water Clusters up to the Hexamer"
Z. Phys. Chem. 227 (2013) 1559 (invited article).
         
32.     P. Seema, J. Behler, and D. Marx
"Force-Induced Mechanical Response of Molecule-Metal Interfaces: Molecular Nanomechanics of Propanethiolate Self-Assembled Monolayers on Au(111)"
Phys. Chem. Chem. Phys. 15 (2013) 16001.
         
31.     T. Morawietz and J. Behler
"A Density-Functional Theory Based Neural Network Potential for Water Clusters Including van der Waals Corrections"
J. Phys. Chem. A 117 (2013) 7356 (invited article).
         
30.     N. Artrith, B. Hiller, and J. Behler
"Neural Network Potentials for Metals and Oxides - First Applications to Copper Clusters at Zinc Oxide"
Phys. Stat. Sol. B 250 (2013) 1191 (invited feature article).
Journal Cover
         
29.     P. Seema, J. Behler, and D. Marx
"Adsorption of Methanethiolate and Atomic Sulfur at the Cu(111) Surface: A Computational Study"
J. Phys. Chem. C 117 (2013) 337.
         
28.     G.C. Sosso, J. Behler and M. Bernasconi
"Breakdown of Stokes-Einstein relation in the supercooled liquid state of phase change materials"
Phys. Stat. Sol. B 249 (2012) 1880.
         
27.     G.C. Sosso, D. Donadio, S. Caravati, J. Behler, and M. Bernasconi
"Thermal Transport in Phase Change Materials from Atomistic Simulations"
Phys. Rev. B 86 (2012) 104301.
         
26.     Jovan Jose K.V., N. Artrith, and J. Behler
"Construction of High-Dimensional Neural Network Potentials Using Environment-Dependent Atom Pairs"
J. Chem. Phys. 136 (2012) 194111.
         
25.     G.C. Sosso, G. Miceli, S. Caravati, J. Behler, and M. Bernasconi
"A Neural Network Interatomic Potential for the Phase Change Material GeTe"
Phys. Rev. B 85 (2012) 174103.
         
24.     H. Eshet, R.Z. Khaliullin, T.D. Kühne, J. Behler, and M. Parrinello
"Microscopic Origin of the anomalous melting behavior of high-pressure sodium"
Phys. Rev. Lett. 108 (2012) 115701.
         
23.     T. Morawietz, V. Sharma, and J. Behler
"A Neural Network Potential-Energy Surface for the Water Dimer Based on Environment-Dependent Atomic Energies and Charges"
J. Chem. Phys. 136 (2012) 064103.
         
22.     N. Artrith and J. Behler
"High-Dimensional Neural Network Potentials For Metal Surfaces: A Prototype Study for Copper"
Phys. Rev. B 85 (2012) 045439.
         
21.     J. Behler
"Neural Network Potential-Energy Surfaces in Chemistry: A Tool for Large-Scale Simulations"
Phys. Chem. Chem. Phys. 13 (2011) 17930 (invited perspective).
Journal Cover
         
20.     R.Z. Khaliullin, H. Eshet, T.D. Kühne, J. Behler, and M. Parrinello
"Nucleation mechanism for the direct graphite-to-diamond phase transition"
Nature Materials 10 (2011) 693.
         
19.     N. Artrith, T. Morawietz, and J. Behler
"High-Dimensional Neural Network Potentials for Multicomponent Systems: Applications to Zinc Oxide"
Phys. Rev. B 83 (2011) 153101.
Erratum.
         
18.     J. Behler
"Atom-Centered Symmetry Functions for Constructing High-Dimensional Neural Network Potentials"
J. Chem. Phys. 134 (2011) 074106.
         
17.     H. Eshet, R.Z. Khaliullin, T.D. Kühne, J. Behler, and M. Parrinello
"Ab initio quality neural-network potential for sodium"
Phys. Rev. B 81 (2010) 184107.
         
16.     R.Z. Khaliullin, H. Eshet, T.D. Kühne, J. Behler, and M. Parrinello
"Ab initio quality study of the graphite-diamond phase coexistence"
Phys. Rev. B 81 (2010) 100103.
         
15.     C. Carbogno, J. Behler, K. Reuter, and A. Groß
"Signatures of nonadiabatic O2 dissociation at Al(111): First-principles fewest-switches study"
Phys. Rev. B 81 (2010) 035410.
         
14.     C. Carbogno, J. Behler, A. Groß, and K. Reuter
"Fingerprints for spin-selection rules in the interaction dynamics of O2 at Al(111)"
Phys. Rev. Lett. 101 (2008) 096104.
         
13.     J. Behler, R. Martonak, D. Donadio, and M. Parrinello
"Pressure-induced phase transitions in silicon studied by neural network-based metadynamics simulations"
Phys. Status Solidi (b) 245 (2008) 2618.
         
12.     J. Behler, R. Martonak, D. Donadio, and M. Parrinello
"Metadynamics simulations of the high-pressure phases of silicon employing a high-dimensional neural network potential"
Phys. Rev. Lett. 100 (2008) 185501.
         
11.     J. Behler, K. Reuter, and M. Scheffler
"Nonadiabatic effects in the dissociation of oxygen molecules at the Al(111) Surface"
Phys. Rev. B 77 (2008) 115421.
         
10.     J. Behler and M. Parrinello
"Generalized neural-network representation of high-dimensional potential-energy surfaces"
Phys. Rev. Lett. 98 (2007) 146401.
         
9.     J. Behler, S. Lorenz, and K. Reuter
"Representing molecule-surface interactions with symmetry-adapted neural networks"
J. Chem. Phys. 127 (2007) 014705.
         
8.     J. Behler, B. Delley, K. Reuter and M. Scheffler
"Nonadiabatic potential-energy surfaces by constrained density-functional theory"
Phys. Rev. B 75 (2007) 115409.
         
7.     L. Cano-Cortes, A. Dolfen, J. Merino, J. Behler, B. Delley, K. Reuter and E. Koch
"Spectral broadening due to long-range Coulomb interactions in the molecular metal TTF-TCNQ"
Eur. Phys. J. B 56 (2007) 173.
         
6.       J. Behler, K. Reuter and M. Scheffler
"Comment on "Dissociation of O2 at Al(111): The role of spin selection rules" Reply"
Phys. Rev. Lett. 96 (2006) 079802.
         
5.     C. Ratsch, A. Fielicke, A. Kirilyuk, J. Behler, G. von Helden, G. Meijer and M. Scheffler
"Structure determination of small vanadium clusters by density-functional theory in comparison with experimental far-infrared spectra"
J. Chem. Phys. 122 (2005) 124302.
         
4.     J. Behler, B. Delley, S. Lorenz, K. Reuter and M. Scheffler
"Dissociation of O2 at Al(111): The role of spin selection rules"
Phys. Rev. Lett. 94 (2005) 036104.
         
3.     A. Fielicke, A. Kirilyuk, C. Ratsch, J. Behler, M. Scheffler, G. von Helden and G. Meijer
"Structure determination of isolated metal clusters via far-infrared spectroscopy"
Phys. Rev. Lett. 93 (2004) 023401.
         
2.     R. Ludwig, J. Behler, B. Klink and E. Weinhold
"Molecular composition of liquid sulfur"
Angew. Chem. Int. Ed. 41 (2002) 3199.
         
1.     J.. Behler, D. W. Price and M. G. B. Drew
"Water structuring properties of carbohydrates, molecular dynamics studies on 1,5-anhydro-D-fructose"
Phys. Chem. Chem. Phys. 3 (2001) 588.