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Faceted shapes, such as polyhedra, are commonly found in systems of nanoscale, colloidal, and granular particles. Many interesting physical phenomena, like crystal nucleation and growth, vacancy motion, and glassy dynamics are challenging…

Computational Physics · Physics 2017-03-08 Matthew Spellings , Ryan L. Marson , Joshua A. Anderson , Sharon C. Glotzer

The large time and length scales and, not least, the vast number of particles involved in industrial-scale simulations inflate the computational costs of the Discrete Element Method (DEM) excessively. Coarse grain models can help to lower…

Computational Physics · Physics 2017-05-11 Daniel Queteschiner , Thomas Lichtenegger , Simon Schneiderbauer , Stefan Pirker

A challenging topic in materials engineering is the development of numerical models that can accurately predict material properties with atomistic accuracy, matching the scale and level of detail achieved by experiments. In this regard,…

Soft Condensed Matter · Physics 2024-10-31 Francesco Maria Bellussi , Matteo Ricci , Matteo Fasano , Otello Maria Roscioni

Centroid molecular dynamics (CMD) incorporates nuclear quantum statistics into the calculation of vibrational spectra. However, when performed in Cartesian coordinates, CMD shows unphysical artifacts in certain vibrational bands, known as…

Chemical Physics · Physics 2025-11-04 Jorge Castro , George Trenins , Venkat Kapil , Mariana Rossi

Coarse-Graining (CG) models are low resolution approximation of high resolution models, such as all-atomic (AA) models. An effective CG model is expected to reproduce equilibrium values of sufficient physical quantities of its AA model,…

Statistical Mechanics · Physics 2015-02-10 Shijing Lu , Xin Zhou

In this paper, we consider the quasi-gas-dynamic (QGD) model in a multiscale environment. The model equations can be regarded as a hyperbolic regularization and are derived from kinetic equations. So far, the research on QGD models has been…

Numerical Analysis · Mathematics 2021-06-30 Boris Chetverushkin , Eric Chung , Yalchin Efendiev , Sai-Mang Pun , Zecheng Zhang

A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach…

The Generalized Method of Moments (GMM) is a partition of unity based technique for solving electromagnetic and acoustic boundary integral equations. Past work on the GMM for electromagnetics was confined to geometries modeled by piecewise…

Computational Physics · Physics 2015-06-18 Daniel Dault , Naveen V. Nair , Jie Li , Balasubramaniam Shanker

The integral equation coarse-graining (IECG) approach is a promising high-level coarse-graining (CG) method for polymer melts, with variable resolution from soft spheres to multi CG sites, which preserves the structural and thermodynamical…

Soft Condensed Matter · Physics 2018-07-24 Mohammadhasan Dinpajooh , Marina G. Guenza

Coarse grid projection (CGP) methodology is a novel multigrid method for systems involving decoupled nonlinear evolution equations and linear elliptic Poisson equations. The nonlinear equations are solved on a fine grid and the linear…

Computational Physics · Physics 2016-10-25 A. Kashefi , A. E. Staples

Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely…

Materials Science · Physics 2023-01-12 Huaiqian You , Xiao Xu , Yue Yu , Stewart Silling , Marta D'Elia , John Foster

We develop a new meshfree geometric multilevel (MGM) method for solving linear systems that arise from discretizing elliptic PDEs on surfaces represented by point clouds. The method uses a Poisson disk sampling-type technique for coarsening…

Numerical Analysis · Mathematics 2022-04-14 Grady B. Wright , Andrew M. Jones , Varun Shankar

We present a data-efficient, multiscale framework for predicting the density profiles of confined fluids at the nanoscale. While accurate density estimates require prohibitively long timescales that are inaccessible by ab initio molecular…

Computational Physics · Physics 2025-09-11 Bugra Yalcin , Ishan Nadkarni , Jinu Jeong , Chenxing Liang , Narayana R. Aluru

Field emission coupled with molecular dynamics simulation (FEcMD) software package is a computational tool for studying atomic structure evolution, structural deformation, phase transitions, recrystallization as well as electron emission…

Computational Physics · Physics 2026-01-22 Bing Xiao , Nan Li , Wenqian Kong , Rui Chu , Hongyu Zhang , Guodong Meng , Kai Wu , Yonghong Cheng

Coarse-grained (CG) force field methods for molecular systems are a crucial tool to simulate large biological macromolecules and are therefore essential for characterisations of biomolecular systems. While state-of-the-art deep learning…

Molecular dynamics (MD) simulations employing classical force fields constitute the cornerstone of contemporary atomistic modeling in chemistry, biology, and materials science. However, the predictive power of these simulations is only as…

Chemical Physics · Physics 2018-09-26 Stefan Chmiela , Huziel E. Sauceda , Klaus-Robert Müller , Alexandre Tkatchenko

Coarse-grained (CG) models play a crucial role in the study of protein structures, protein thermodynamic properties, and protein conformation dynamics. Due to the information loss in the coarse-graining process, backmapping from CG to…

Quantitative Methods · Quantitative Biology 2023-11-30 Yikai Liu , Ming Chen , Guang Lin

Many-body correlations developed in the constrained molecular dynamics approach in the frame-work of the CoMD model are analyzed in the case of a finite range effective interaction. The study is performed in the case of infinite nuclear…

Nuclear Theory · Physics 2021-12-01 Massimo Papa

We establish, through coarse-grained computation, a connection between traditional, continuum numerical algorithms (initial value problems as well as fixed point algorithms) and atomistic simulations of the Larson model of micelle…

Soft Condensed Matter · Physics 2009-11-10 Dmitry I. Kopelevich , Athanassios Z. Panagiotopoulos , Ioannis G. Kevrekidis

We propose a semi-partitioned Generalized Method of Moments (GMM) framework for analyzing longitudinal data with time-dependent covariates, within a marginal modeling paradigm. This approach addresses limitations of both aggregated and…

Methodology · Statistics 2026-03-04 Niloofar Ramezani , Jeffrey R. Wilson
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