Kaihang Shi

Machine Learning Interatomic Potentials for Modeling Framework Flexibility and Water Uptake in NbOFFIVE-1-Ni Metal–Organic Framework http://dx.doi.org/10.1021/acs.jpcc.6c00023

Comparing the Mechanical and Thermodynamic Definitions of Pressure in Ice Nucleation Crystal nucleation studies using hard-sphere and Lennard-Jones models have shown that the actual (mechanical) pressure within the nucleus is lower than that in the surrounding liquid. Here, we use the...

Check out our recent work on elucidating the mechanical and thermodynamic pressures, interfacial stress and interfacial free energy in ice nucleus.

How to harmonize the thermodynamic and mechanical pictures of solid-liquid interfaces is still an open question.

pubs.acs.org/doi/10.1021/...

Computational Chemistry and Machine Learning-Assisted Screening of Supported Amorphous Metal Oxide Nanoclusters for Methane Activation Activating the C–H bond in methane represents a cornerstone challenge in catalytic research. While several supported metal oxide nanoclusters (MeO-NCs) have shown promise for this reaction, their opti...

In this new paper in ACS Catalysis, XijunWang, @kaihangs.bsky.social, and Anyang Peng tackle some of the challenges in modeling supported amorphous metal oxide nanoclusters for methane activation. pubs.acs.org/doi/abs/10.1...

As my first post on @bsky.app, I'm happy to announce the publication of a paper describing the new (very fast!) GPU version of our RASPA simulation code, gRASPA. Congratulations to Zhao Li and the team!