Thermodynamics of diamond formation from hydrocarbon mixtures in planets
B. Cheng, S. Hamel, M. Bethkenhagen, Nature Communications 14 (2023).

Physics-inspired machine learning of localized intensive properties
K. Chen, C. Kunkel, B. Cheng, K. Reuter, J.T. Margraf, Chemical Science (2023).

Computing chemical potentials of adsorbed or confined fluids
R. Schmid, B. Cheng, The Journal of Chemical Physics 158 (2023).

Reactivity of single-atom alloy nanoparticles: Modeling the dehydrogenation of propane
R. Bunting, F. Wodaczek, T. Torabi, B. Cheng, Journal of the American Chemical Society 145 (2023) 14894–14902.

Mechanistic insight on water dissociation on pristine low-index TiO2 surfaces from machine learning molecular dynamics simulations
Z. Zeng, F. Wodaczek, K. Liu, F. Stein, J. Hutter, J. Chen, B. Cheng, Nature Communications 14 (2023).

A streamlined molecular-dynamics workflow for computing solubilities of molecular and ionic crystals
A. Reinhardt, P.Y. Chew, B. Cheng, Journal of Chemical Physics 159 (2023).

BingqingCheng/solubility: .0
B. Cheng, (2023).

Computing chemical potentials of solutions from structure factors
B. Cheng, The Journal of Chemical Physics 157 (2022).

High-pressure phase behaviors of titanium dioxide revealed by a -learning potential
J.G. Lee, C.J. Pickard, B. Cheng, The Journal of Chemical Physics 156 (2022).

Thermodynamics of high-pressure ice phases explored with atomistic simulations
A. Reinhardt, M. Bethkenhagen, F. Coppari, M. Millot, S. Hamel, B. Cheng, Nature Communications 13 (2022).

BenchML: An extensible pipelining framework for benchmarking representations of materials and molecules at scale
C. Poelking, F.A. Faber, B. Cheng, Machine Learning: Science and Technology 3 (2022).

Quantum-mechanical exploration of the phase diagram of water
A. Reinhardt, B. Cheng, Nature Communications 12 (2021).

Ranking the information content of distance measures
A. Glielmo, C. Zeni, B. Cheng, G. Csanyi, A. Laio, ArXiv (n.d.).

Predicting the phase behaviors of superionic water at planetary conditions
B. Cheng, M. Bethkenhagen, C.J. Pickard, S. Hamel, ArXiv (n.d.).

Combining machine learning and computational chemistry for predictive insights into chemical systems
J.A. Keith, V. Valentin Vassilev-Galindo, B. Cheng, S. Chmiela, M. Gastegger, K.-R. Müller, A. Tkatchenko, Chemical Reviews 121 (2021) 9816–9872.

Classical nucleation theory predicts the shape of the nucleus in homogeneous solidification
B. Cheng, M. Ceriotti, G.A. Tribello, The Journal of Chemical Physics 152 (2020).

Computing the heat conductivity of fluids from density fluctuations
B. Cheng, D. Frenkel, Physical Review Letters 125 (2020).

Predicting the phase diagram of titanium dioxide with random search and pattern recognition
A. Reinhardt, C.J. Pickard, B. Cheng, Physical Chemistry Chemical Physics 22 (2020) 12697–12705.

Liquid water contains the building blocks of diverse ice phases
B. Monserrat, J.G. Brandenburg, E.A. Engel, B. Cheng, Nature Communications 11 (2020).

Mapping materials and molecules
B. Cheng, R.-R. Griffiths, S. Wengert, C. Kunkel, T. Stenczel, B. Zhu, V.L. Deringer, N. Bernstein, J.T. Margraf, K. Reuter, G. Csanyi, Accounts of Chemical Research 53 (2020) 1981–1991.