183 citations · 355 across the 11 of their papers we have counts for
11 papers
Considerations in the use of ML interaction potentials for free energy calculations
Orlando A. Mendible, Jonathan K. Whitmer, Yamil J. Colón
Machine learning force fields (MLFFs) promise to accurately describe the potential energy surface of molecules at the ab initio level of theory with improved computational efficien…
Transfer Learning Facilitates the Prediction of Polymer-Surface Adhesion Strength
Jiale Shi, Fahed Albreiki, Yamil J. Colón +2
Machine learning (ML) accelerates the exploration of material properties and their links to the structure of the underlying molecules. In previous work [J. Shi, M. J. Quevillon, P.…
PySAGES: flexible, advanced sampling methods accelerated with GPUs
Pablo F. Zubieta Rico, Ludwig Schneider, Gustavo R. Pérez-Lemus +11
Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced…
Free Energy Landscape and Isomerization Rates of Au Clusters at Finite Temperature
Jiale Shi, Shanghui Huang, François Gygi +1
In metallic nanoparticles, the cluster geometric structures control the particle's electronic band structure, polarizability, and catalytic properties. Analyzing the structural pro…
Predicting Adhesive Free Energies of Polymer--Surface Interactions with Machine Learning
Jiale Shi, Michael J. Quevillon, Pedro H. Amorim Valença +1
Polymer-surface interactions are crucial to many biological processes and industrial applications. Here we propose a machine-learning method to connect a model polymer's sequence w…
Exploring the Potential of Parallel Biasing in Flat Histogram Methods
Shanghui Huang, Michael J. Quevillon, Ernesto C. Cortés-Morales +1
Metadynamics, a member of the `flat histogram' class of advanced sampling algorithms, has been widely used in molecular simulations to drive the exploration of states separated by…
Linking dynamics and structure in highly asymmetric ionic liquids
Mariana E. Farías-Anguiano, Ernesto C. Cortés-Morales, Jonathan K. Whitmer +1
We explore an idealized theoretical model for the transport of ions within highly asymmetric ionic liquid mixtures. A primitive model (PM)-inspired system serves as a representativ…
Automatic Determination of -Cyanobiphenyl Elastic Constants from Molecular Simulation
Hythem Sidky, Jonathan K. Whitmer
New applications of liquid crystalline materials have increased the need for precise engineering of elastic properties. Recently, Sidky et al. presented methods by which the elasti…
Learning Free Energy Landscapes Using Artificial Neural Networks
Hythem Sidky, Jonathan K. Whitmer
Existing adaptive bias techniques, which seek to estimate free energies and physical properties from molecular simulations, are limited by their reliance on fixed kernels or basis…
Orientationally Glassy Crystals of Janus Spheres
Shan Jiang, Jing Yan, Jonathan K. Whitmer +3
Colloidal Janus spheres in water (one hemisphere attractive and the other repulsive) assemble into two-dimensional hexagonal crystals with orientational order controlled by anisotr…
Coarse-grained Modeling of DNA Curvature
Gordon S. Freeman, Daniel M. Hinckley, Joshua P. Lequieu +2
Modeling of DNA-protein interactions is a complex process involving many important time and length scales. This can be facilitated through the use of coarse-grained models which re…