activity
20142024
most citedCombining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems

876 citations · 2.5k across the 28 of their papers we have counts for

collaborators
Showing 2018Show all

5 papers · 1 filter

cond-mat.mtrl-sci2018★ 379 cited

Ab initio thermodynamics of liquid and solid water

Bingqing Cheng, Edgar A. Engel, Jörg Behler +2

Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously ta…

physics.chem-ph2018★ 382 cited

i-PI 2.0: A Universal Force Engine for Advanced Molecular Simulations

Venkat Kapil, Mariana Rossi, Ondrej Marsalek +23

Progress in the atomic-scale modelling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomi…

cond-mat.stat-mech2018★ 31 cited

Theoretical prediction of the homogeneous ice nucleation rate: disentangling thermodynamics and kinetics

Bingqing Cheng, Christoph Dellago, Michele Ceriotti

Estimating the homogeneous ice nucleation rate from undercooled liquid water is at the same time crucial for understanding many important physical phenomena and technological appli…

cond-mat.stat-mech2018★ 15 cited

Computing the Tolman length for solid-liquid interfaces

Bingqing Cheng, Michele Ceriotti

The curvature dependence of interfacial free energy, which is crucial in quantitatively predicting nucleation kinetics and the stability of bubbles and droplets, can be described i…

cond-mat.mtrl-sci2018★ 42 cited

Hydrogen Diffusion and Trapping in α-Iron: The Role of Quantum and Anharmonic Fluctuations

Bingqing Cheng, Anthony T. Paxton, Michele Ceriotti

We investigate the thermodynamics and kinetics of a hydrogen interstitial in magnetic α-iron, taking account of the quantum fluctuations of the proton as well as the anharmonicitie…