@NYU Shanghai
Congratulations to Amiel on his recent paper on diabatic gradients making the cover of The Journal of Chemical Physics. We expect this technology to find broad use in Machine-learned potentials Continue Reading →
Amiel’s paper on diabatic gradients has just been accepted by J. Chem. Phys.. Preprint: doi.org/10.26434/chemrxiv-2023-rbv43 This opens the door to some interesting developments, including towards the ability to solve the Continue Reading →
Just out in Nature Communications: In collaboration with Mark Tuckerman’s group, we show how to machine learn a general Hohenberg-Kohn theorem for excited states. Congrats to Yuanming on his first Continue Reading →
Xingpin’s paper on the X-ray absorption spectrum of the hydrated electron has just been published in JACS! Read it here: doi.org/10.1021/jacs.2c07572
Xiao and Alexander’s paper on polarizable embedding methods for describing conical intersections in solution is now published in JCTC: doi.org/10.1021/acs.jctc.2c00662. Congrats to them both!
Zhuofan’s papers on our new FlexiBLE QM/MM method were just published in J. Chem. Phys. FlexiBLE solves the boundary issue in QM/MM simulations when diffusible particles (e.g. solvent) are included Continue Reading →
Amiel’s paper on Active Orbital Preservation for Multiconfigurational Self-Consistent Field was just published in J. Chem. Phys. This method allows a close-to automated approach to performing multiconfigurational calculations in condensed-phase Continue Reading →