Developing a Hybrid Monte Carlo Algorithm for Peptides through Kernel Machine Learning Read more about Developing a Hybrid Monte Carlo Algorithm for Peptides through Kernel Machine Learning
Development of a semi-analytic thermodynamic model for the grand canonical potential of flexible MOFs Read more about Development of a semi-analytic thermodynamic model for the grand canonical potential of flexible MOFs
Improved force-field approximations of symmetry-adapted perturbation theory Read more about Improved force-field approximations of symmetry-adapted perturbation theory
Ranking molecular crystals with a many-body expansion Read more about Ranking molecular crystals with a many-body expansion
Machine learning of atomic polarizabilities for polarizable force field development Read more about Machine learning of atomic polarizabilities for polarizable force field development
Machine learning of the ground state density of molecules for force field development Read more about Machine learning of the ground state density of molecules for force field development
Constructing a new localization scheme to improve the electrostatic potential of explicit electron force fields Read more about Constructing a new localization scheme to improve the electrostatic potential of explicit electron force fields
Improved force-field approximations of symmetry-adapted perturbation theory Read more about Improved force-field approximations of symmetry-adapted perturbation theory
Ranking molecular crystals with a many-body expansion Read more about Ranking molecular crystals with a many-body expansion
Development of a semi-analytic thermodynamic model for the grand canonical potential of flexible MOFs Read more about Development of a semi-analytic thermodynamic model for the grand canonical potential of flexible MOFs