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Molecular Dynamics simulations can help scientists to gather valuable insights for physical processes on an atomic scale. This work explores various techniques for SIMD vectorization to improve the pairwise force calculation between…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-04 Luis Gall , Samuel James Newcome , Fabio Alexander Gratl , Markus Mühlhäußer , Manish Kumar Mishra , Hans-Joachim Bungartz

A method for adaptive model order reduction for nonsmooth discrete element simulation is developed and analysed in numerical experiments. Regions of the granular media that collectively move as rigid bodies are substituted with rigid bodies…

Computational Physics · Physics 2015-12-02 Martin Servin , Da Wang

We develop an efficient parallel multiscale method that bridges the atomistic and mesoscale regimes, from nanometer to micron and beyond, via concurrent coupling of atomistic simulation and mesoscopic dynamics. In particular, we combine an…

Computational Physics · Physics 2020-12-23 Yuying Wang , Zhen Li , Junbo Xu , Chao Yang , George Em Karniadakis

We present a three-dimensional model, based on cohesive spherical particles, of rain-induced landslides. The rainwater infiltration into the soil follow the either the fractional or the fractal diffusion equations. We solve analytically the…

Geophysics · Physics 2017-04-05 Gianluca Martelloni , Franco Bagnoli , Alessio Guarino

The central approximation made in classical molecular dynamics simulation of materials is the interatomic potential used to calculate the forces on the atoms. Great effort and ingenuity is required to construct viable functional forms and…

Computational Physics · Physics 2019-06-26 Mitchell A. Wood , Mary Alice Cusentino , Brian D. Wirth , Aidan P. Thompson

Machine learning interatomic potentials (MLPs) are a promising technique for atomic modeling. While high accuracy and small errors are widely reported for MLPs, an open concern is whether MLPs can accurately reproduce atomistic dynamics and…

Materials Science · Physics 2023-10-02 Yunsheng Liu , Xingfeng He , Yifei Mo

A solidification model based on the principle of maximum entropy production rate (MEPR) is considered for the study of pure metals. The approach leads to the development of a breakdown criterion which is able to account for the…

Materials Science · Physics 2017-03-17 Yaw Delali Bensah

Machine-learning models of atomic-scale interactions achieve the accuracy of the quantum mechanical calculations on which they are trained, but at a dramatically lower computational cost. Their predictions can be made trustworthy by…

The vibrational entropy of a solid at finite temperature is investigated from the perspective of information theory. Ab initio molecular dynamics (AIMD) simulations generate ensembles of atomic configurations at finite temperature from…

Statistical Mechanics · Physics 2022-05-11 Yang Huang , Michael Widom

Isothermal-isobaric molecular dynamics simulations are used to examine the microscopic structure and some properties of water-methanol liquid mixture. The TIP4P/2005 and SPC/E water models are combined with the united atom TraPPE and the…

Soft Condensed Matter · Physics 2019-03-28 M. Cruz Sanchez , H. Dominguez , O. Pizio

The two-phase thermodynamic (2PT) model {[}J. Chem. Phys., \textbf{119}, 11792 (2003){]} provides a promising paradigm to efficiently determine the ionic entropies of liquids from molecular dynamics (MD). In this model, the vibrational…

Chemical Physics · Physics 2017-11-20 Tao Sun , Jiawei Xian , Huai Zhang , Zhigang Zhang , Yigang Zhang

We present an active learning framework for efficiently generating training data for machine-learned interatomic potentials (MLIPs). The method combines local entropy-driven molecular dynamics with global dataset-aware filtering: a…

Materials Science · Physics 2026-05-21 Meiyan Wang , Rishi Rao , Li Zhu

We present a maximum entropy inverse reinforcement learning (IRL) approach for improving the sample quality of diffusion generative models, especially when the number of generation time steps is small. Similar to how IRL trains a policy…

Machine Learning · Computer Science 2024-11-01 Sangwoong Yoon , Himchan Hwang , Dohyun Kwon , Yung-Kyun Noh , Frank C. Park

We use molecular dynamics simulations to study the evaporation of particle-laden droplets on a heated surface. The droplets are composed of a Lennard-Jones fluid containing rigid particles which are spherical sections of an atomic lattice,…

Soft Condensed Matter · Physics 2015-06-04 Weikang Chen , Joel Koplik , Ilona Kretzschmar

We study the problem of efficient exploration in order to learn an accurate model of an environment, modeled as a Markov decision process (MDP). Efficient exploration in this problem requires the agent to identify the regions in which…

Considering turbulent clouds containing small inertial particles, we investigate the effect of particle collision, in particular collision-coagulation, on particle clustering and particle relative motion. We perform direct numerical…

Fluid Dynamics · Physics 2022-07-14 Ewe-Wei Saw , Xiaohui Meng

Phase change materials are exploited in several enabling technologies such as storage class memories, neuromorphic devices and memories embedded in microcontrollers. A key functional property for these applications is the fast crystal…

Materials Science · Physics 2025-01-14 Omar Abou El Kheir , Marco Bernasconi

We propose a hybrid deterministic and stochastic approach to achieve extended time scales in atomistic simulations that combines the strengths of molecular dynamics (MD) and Monte Carlo (MC) simulations in an easy-to-implement way. The…

Materials Science · Physics 2011-10-18 Pratyush Tiwary , Axel van de Walle

Molecular Dynamic (MD) approach is applied to study the converging cylindrical shock waves in a dense Lennard-Jones (LJ) fluid. MD method is based on tracking of the atom motions and hence it has an fundamental advantages over hydrodynamic…

Computational Physics · Physics 2009-04-23 V. Zhakhovskii , K. Nishihara , M. Abe

Diffusion in solids is a slow process that dictates rate-limiting processes in key chemical reactions. Unlike crystalline solids that offer well-defined diffusion pathways, the lack of similar structural motifs in amorphous or glassy…

Materials Science · Physics 2023-12-12 Ken-ichi Nomura , Ankit Mishra , Tian Sang , Rajiv K. Kalia , Aiichiro Nakano , Priya Vashishta