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We analyze deficiencies of commonly used Coulomb approximations in Generalized Born solvation energy calculation models and report a development of a new fast surface-based method (FSBE) for numerical calculations of the solvation energy of…

Quantitative Methods · Quantitative Biology 2009-10-14 P. O. Fedichev , G. N. Getmantsev , L. I. Menshikov

A multi-scale framework was recently proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent, where we…

Biological Physics · Physics 2018-01-17 Li Xiao , Ray Luo

Several different approaches are proposed for solving fully implicit discretizations of a simplified Boltzmann-Poisson system with a linear relaxation-type collision kernel. This system models the evolution of free electrons in…

Computational Physics · Physics 2020-07-15 M. Paul Laiu , Zheng Chen , Cory D. Hauck

We present a scalable implementation of the $GW$ approximation using Gaussian atomic orbitals to study the valence and core ionization spectroscopies of molecules. The implementation of the standard spectral decomposition approach to the…

Chemical Physics · Physics 2021-12-06 Daniel Mejia-Rodriguez , Alexander Kunitsa , Edoardo Aprà , Niranjan Govind

We present an efficient approach for simulating Coulomb systems confined by planar polarizable surfaces. The method is based on the solution of Poisson equation using periodic Green functions. It is shown that the electrostatic energy…

Soft Condensed Matter · Physics 2017-12-12 Alexandre P. dos Santos , Matheus Girotto , Yan Levin

The implicit solvent approach offers a computationally efficient framework to model solvation effects in molecular simulations. However, its accuracy often falls short compared to explicit solvent models, limiting its use in precise…

Coarse graining is an important ingredient in many multi-scale continuum-discrete solvers such as CFD--DEM (computational fluid dynamics--discrete element method) solvers for dense particle-laden flows. Although CFD--DEM solvers have become…

Computational Physics · Physics 2015-08-14 Rui Sun , Heng Xiao

Determining the aqueous solubility of molecules is a vital step in many pharmaceutical, environmental, and energy storage applications. Despite efforts made over decades, there are still challenges associated with developing a solubility…

Materials Science · Physics 2022-09-05 Gihan Panapitiya , Michael Girard , Aaron Hollas , Vijay Murugesan , Wei Wang , Emily Saldanha

Atomistic or ab-initio molecular dynamics simulations are widely used to predict thermodynamics and kinetics and relate them to molecular structure. A common approach to go beyond the time- and length-scales accessible with such…

The ensemble average of physical properties of molecules is closely related to the distribution of molecular conformations, and sampling such distributions is a fundamental challenge in physics and chemistry. Traditional methods like…

Machine Learning · Computer Science 2025-08-06 Liya Guo , Zun Wang , Chang Liu , Junzhe Li , Pipi Hu , Yi Zhu

The conjugate gradient (CG) method is a classic Krylov subspace method for solving symmetric positive definite linear systems. We introduce an analogous semi-conjugate gradient (SCG) method for unsymmetric positive definite linear systems.…

Numerical Analysis · Mathematics 2022-06-09 Na Huang , Yu-Hong Dai , Dominique Orban , Michael A Saunders

High-precision scientific simulation faces a long-standing trade-off between computational efficiency and physical fidelity. To address this challenge, we propose NeuralOGCM, an ocean modeling framework that fuses differentiable programming…

Machine Learning · Computer Science 2025-12-15 Hao Wu , Yuan Gao , Fan Xu , Fan Zhang , Guangliang Liu , Yuxuan Liang , Xiaomeng Huang

We introduce a general framework for constructing coarse-grained potential models without ad hoc approximations such as limiting the potential to two- and/or three-body contributions. The scheme, called Deep Coarse-Grained Potential…

Chemical Physics · Physics 2018-08-15 Linfeng Zhang , Jiequn Han , Han Wang , Roberto Car , Weinan E

Continuum solvation models enable electronic structure calculations of systems in liquid environments, but because of the large number of empirical parameters, they are limited to the class of systems in their fit set (typically organic…

In this work, a coarse-graining method previously proposed by the authors in a companion paper based on solving diffusion equations is applied to CFD-DEM simulations, where coarse graining is used to obtain solid volume fraction, particle…

Computational Physics · Physics 2015-01-07 Rui Sun , Heng Xiao

ParticLS (\emph{Partic}le \emph{L}evel \emph{S}ets) is a software library that implements the discrete element method (DEM) and meshfree methods. ParticLS tracks the interaction between individual particles whose geometries are defined by…

Mathematical Software · Computer Science 2022-04-26 Andrew D. Davis , Brendan A. West , Nathanael J. Frisch , Devin T. O'Connor , Matthew D. Parno

This study investigates different Scientific Machine Learning (SciML) approaches for the analysis of functionally graded (FG) porous beams and compares them under a new framework. The beam material properties are assumed to vary as an…

Machine Learning · Computer Science 2024-12-25 Mohammad Sadegh Eshaghi , Mostafa Bamdad , Cosmin Anitescu , Yizheng Wang , Xiaoying Zhuang , Timon Rabczuk

Using the specific model of a system of like charged ions confined between two planar like charged surfaces, we compare the predictions for the energy and density profile of four simulation methods available to treat the long range Coulomb…

Statistical Mechanics · Physics 2007-05-23 M. Mazars , J-M. Caillol , J. -J. Weis , D. Levesque

In this paper we combine a flexible covariant formulation of the shallow water equations with the semi-implicit numerical scheme developed over the years by Casulli and collaborators. After adopting an orthogonal, but non-orthonormal,…

Fluid Dynamics · Physics 2026-05-26 Maurizio Tavelli , Olindo Zanotti

Super-Droplet Method (SDM) is a probabilistic Monte-Carlo-type model of particle coagulation process, an alternative to the mean-field formulation of Smoluchowski. SDM as an algorithm has linear computational complexity with respect to the…

Computational Physics · Physics 2021-07-27 Piotr Bartman , Sylwester Arabas