539 citations · 2.2k across the 35 of their papers we have counts for
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Utilizing Machine Learning to Greatly Expand the Range and Accuracy of Bottom-Up Coarse-Grained Models Through Virtual Particles
Patrick G. Sahrmann, Timothy D. Loose, Aleksander E. P. Durumeric +1
Coarse-grained (CG) models parameterized using atomistic reference data, i.e., 'bottom up' CG models, have proven useful in the study of biomolecules and other soft matter. However…
Centroid Molecular Dynamics Can Be Greatly Accelerated Through Neural Network Learned Centroid Forces Derived from Path Integral Molecular Dynamics
Timothy D. Loose, Patrick G. Sahrmann, Gregory A. Voth
For nearly the past 30 years, Centroid Molecular Dynamics (CMD) has proven to be a viable classical-like phase space formulation for the calculation of quantum dynamical properties…
Understanding Dynamics in Coarse-Grained Models: II. Coarse-Grained Diffusion Modeled Using Hard Sphere Theory
Jaehyeok Jin, Kenneth S. Schweizer, Gregory A. Voth
The first paper of this series [J. Chem. Phys. 158, 034103 (2023)] demonstrated that excess entropy scaling holds for both fine-grained and corresponding coarse-grained (CG) system…
Understanding Dynamics in Coarse-Grained Models: I. Universal Excess Entropy Scaling Relationship
Jaehyeok Jin, Kenneth S. Schweizer, Gregory A. Voth
Coarse-grained (CG) models facilitate an efficient exploration of complex systems by reducing the unnecessary degrees of freedom of the fine-grained (FG) system while recapitulatin…