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Short range attractive colloids: Dynamics and energy landscape properties

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Short range attractive colloids: Dynamics and energy landscape properties

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Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Inferring free-energy barriers and kinetic rates from molecular dynamics via underdamped Langevin models

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

Low-Temperature Dynamics of Water Confined in Unidirectional Hydrophilic Zeolite Nanopores

Transferable machine-learning models of complex materials: the case of GaAs

Hamiltonian-Reservoir Replica Exchange and Machine Learning Potentials for Computational Organic Chemistry

Atomistic modeling of the solid-liquid interface of metals and alloys

Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems

Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems

Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

Atomistic modeling of the solid-liquid interface of metals and alloys

Transferable machine-learning models of complex materials: the case of GaAs

Low-Temperature Dynamics of Water Confined in Unidirectional Hydrophilic Zeolite Nanopores

Inferring free-energy barriers and kinetic rates from molecular dynamics via underdamped Langevin models

Hamiltonian-Reservoir Replica Exchange and Machine Learning Potentials for Computational Organic Chemistry

Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems

Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems