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Solid state theory, density functional theory and its generalizations for correlated systems together with numerical simulations on supercomputers allow nowadays to model magnetic systems realistically and in detail and can be even used to…

Materials Science · Physics 2023-10-16 Vladislav Borisov

Robust local feature representations are essential for spatial intelligence tasks such as robot navigation and augmented reality. Establishing reliable correspondences requires descriptors that provide both high discriminative power and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Haodi Yao , Fenghua He , Ning Hao , Yao Su

Colloidal particles or nanoparticles, with equal affinity for two fluids, are known to adsorb irreversibly to the fluid-fluid interface. We present large-scale computer simulations of the demixing of a binary solvent containing such…

Soft Condensed Matter · Physics 2007-05-23 K. Stratford , R. Adhikari , I. Pagonabarraga , J. -C. Desplat , M. E. Cates

Multiparticle collision dynamics (MPCD) is a flexible and robust mesoscale computational technique for simulating solvent-mediated hydrodynamic interactions in soft materials. Here, we provide a critical overview of the MPCD method and…

Soft Condensed Matter · Physics 2019-02-28 Michael P. Howard , Arash Nikoubashman , Jeremy C. Palmer

Subsurface sequestration of CO2 has received attention from the global scientific community in response to climate change concerns due to higher concentrations of CO2 in the atmosphere. Mathematical models have thus been developed to aid…

Computational Physics · Physics 2020-04-28 Feyi Olalotiti-Lawal , Shusei Tanaka , Akhil Datta-Gupta

The chemical reaction network (CRN) is a widely used formalism to describe macroscopic behavior of chemical systems. Available tools for CRN modelling and simulation require local access, installation, and often involve local file storage,…

Computational Engineering, Finance, and Science · Computer Science 2015-12-07 Peter Banda , Drew Blount , Christof Teuscher

Experience in the physical sciences suggests that the only realistic means of understanding complex systems is through the use of mathematical models. Typically, this has come to mean the identification of quantitative models expressed as…

Artificial Intelligence · Computer Science 2011-11-02 George M. Coghill , Ross D. King , Ashwin Srinivasan

Sintering, as a thermal process at elevated temperature below the melting point, is widely used to bond contacting particles into engineering products such as ceramics, metals, polymers, and cemented carbides. Modelling and simulation as…

Materials Science · Physics 2023-02-13 Min Yi , Wenxuan Wang , Ming Xue , Qihua Gong , Bai-Xiang Xu

Attaining accurate average structural properties in a molecular simulation should be considered a prerequisite if one aims to elicit meaningful insights into a system's behavior. For charged surfaces in contact with an electrolyte solution,…

Materials Science · Physics 2021-03-25 Thomas Sayer , Stephen J. Cox

Linear kinetic Monte Carlo particle transport models are frequently employed in fusion plasma simulations to quantify atomic and surface effects on the main plasma flow dynamics. Separate codes are used for transport of neutral particles…

Plasma Physics · Physics 2015-06-03 J. Seebacher , A. Kendl

Tilt models offer intuitive and clean definitions of complex systems in which particles are influenced by global control commands. Despite a wide range of applications, there has been almost no theoretical investigation into the associated…

Computational Geometry · Computer Science 2025-04-24 Sándor P. Fekete , Peter Kramer , Jan-Marc Reinhardt , Christian Rieck , Christian Scheffer

One of the primary challenges in quantum chemistry is the accurate modeling of strong electron correlation. While multireference methods effectively capture such correlation, their steep scaling with system size prohibits their application…

Predicting the geometrical evolution of the pore space in geological formations due to fluid-solid interactions has applications in reservoir engineering, oil recovery, and geological storage of carbon dioxide. However, modeling frameworks…

In this mini-review we summarize the progress of modeling, simulation and analysis of shock responses of heterogeneous materials in our group in recent years. The basic methodology is as below. We first decompose the problem into different…

Soft Condensed Matter · Physics 2016-03-24 Aiguo Xu , Guangcai Zhang , Yangjun Ying , Cheng Wang

We study the properties of a polycarbonate melt near a nickel surface as a model system for the interaction of polymers with metal surfaces by employing a multiscale modeling approach. For bulk properties a suitably coarse grained bead…

Materials Science · Physics 2009-11-07 L. Delle Site , C. F. Abrams , A. Alavi , K. Kremer

Molten salts are crucial for clean energy applications, yet exploring their thermophysical properties across diverse chemical space remains challenging. We present the development of a machine learning interatomic potential (MLIP) called…

Materials Science · Physics 2024-12-30 Chen Shen , Siamak Attarian , Yixuan Zhang , Hongbin Zhang , Mark Asta , Izabela Szlufarska , Dane Morgan

Yamdb (Yet another materials data base) addresses the need to provide thermophysical properties of liquid metals and molten salts in an easily accessible manner. Mathematical relations describing material properties - usually determined by…

Materials Science · Physics 2024-02-20 Tom Weier , William Nash , Paolo Personnettaz , Norbert Weber

An elasto-plastic model for concrete, based on a recently-proposed yield surface and simple hardening laws, is formulated, implemented, numerically tested and validated against available test results. The yield surface is smooth and…

Materials Science · Physics 2014-04-28 F. Poltronieri , A. Piccolroaz , D. Bigoni

Quantum-mechanical molecular-dynamics simulations are carried out to explore possible precursor states of nano-polycrystalline diamond, a novel ultra-hard material produced directly from graphite. Large-scale simulation with 10^5 atoms is…

Materials Science · Physics 2015-05-14 Takeo Hoshi , Toshiaki Iitaka , Maria Fyta

MLMOD is a software package for incorporating machine learning approaches and models into simulations of microscale mechanics and molecular dynamics in LAMMPS. Recent machine learning approaches provide promising data-driven approaches for…

Machine Learning · Computer Science 2023-10-24 Paul J. Atzberger
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