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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

A computer algorithm to search symmetries of crystal structures as implemented in the \texttt{spglib} code is described. An iterative algorithm is employed to robustly identify space group types tolerating a certain amount of distortion in…

Materials Science · Physics 2024-03-14 Atsushi Togo , Kohei Shinohara , Isao Tanaka

A novel method for crystal structure prediction, based on metadynamics and evolutionary algorithms, is presented here. This technique can be used to produce efficiently both the ground state and metastable states easily reachable from a…

Materials Science · Physics 2012-06-08 Qiang Zhu , Artem R. Oganov , Andriy O. Lyakhov

In this work we demonstrate the robustness of a real-space approach for the treatment of infinite systems described with periodic boundary conditions that we have recently proposed [J. Phys. Chem. Lett. 17, 7090]. In our approach we extract…

The complex arrangements of atoms near grain boundaries are difficult to understand theoretically. We propose a phenomenological (Ginzburg-Landau-like) description of crystalline phases based on symmetries and fairly general stability…

Materials Science · Physics 2015-06-25 Denis Boyer , David Romeu

Determining the atomic-level structure of crystalline solids is critically important across a wide array of scientific disciplines. The challenges associated with obtaining samples suitable for single-crystal diffraction, coupled with the…

We show using numerical simulations that a rich variety of novel colloidal crystalline states are realized on square and triangular two dimensional periodic substrates which can be experimentally created using crossed laser arrays. When…

Soft Condensed Matter · Physics 2016-08-31 C. Reichhardt , C. J. Olson

Materials discovery via high-throughput methods relies on the availability of structural prototypes, which are generally decorated with varying combinations of elements to produce potential new materials. To facilitate the automatic…

In this study, we present a novel approach along with the needed computational strategies for efficient and scalable feature engineering of the crystal structure in compounds of different chemical compositions. This approach utilizes a…

Materials Science · Physics 2021-05-25 Prathik R. Kaundinya , Kamal Choudhary , Surya R. Kalidindi

Assembly of colloidal particles on fluid interfaces is a promising technique for synthesizing two-dimensional micro-crystalline materials useful in fields as diverse as biomedicine1, materials science2, mineral flotation3 and food…

Soft Condensed Matter · Physics 2007-05-23 Anand Bala Subramaniam , Manouk Abkarian , Howard A. Stone

Polynomial machine learning potentials (MLPs) based on polynomial rotational invariants have been systematically developed for various systems and applied to efficiently predict crystal structures. In this study, we propose a robust…

Materials Science · Physics 2026-03-18 Hayato Wakai , Atsuto Seko , Isao Tanaka

We present a thermodynamically consistent theoretical framework for lyotropic liquid crystals (LCs) based on the GENERIC (General Equation for the Non-Equilibrium Reversible-Irreversible Coupling) formalism. This formalism ensures…

Soft Condensed Matter · Physics 2025-12-03 Jonathan Salmerón-Hernández , Pablo Zubieta-Rico , Juan de Pablo

This chapter provides a brief introduction to the theory and practice of spatial stochastic simulations. It begins with an overview of different methods available for biochemical simulations highlighting their strengths and limitations.…

Quantitative Methods · Quantitative Biology 2018-10-02 Sanjana Gupta , Jacob Czech , Robert Kuczewski , Thomas M. Bartol , Terrence J. Sejnowski , Robin E. C. Lee , James R. Faeder

Understanding the morphology formation process of solution-cast photoactive layers (PALs) is crucial to derive design rules for optimized and reliable third generation solar cell fabrication. For this purpose, a Phase-Field (PF)…

Materials Science · Physics 2023-10-19 Maxime Siber , Olivier J. J. Ronsin , Jens Harting

Crystalline films offer various physical properties based on the modulation of their thicknesses and atomic structures. The layer-by-layer assembly of atomically thin crystals provides powerful means to arbitrarily design films at the…

De novo crystal generation, a central task in materials discovery, aims to generate crystals that are simultaneously valid, stable, unique, and novel. Existing methods mainly rely on black-box stochastic sampling, providing limited control…

Crystal structure prediction (CSP) is now increasingly used in discovering novel materials with applications in diverse industries. However, despite decades of developments and significant progress in this area, there lacks a set of…

Detecting structures at the particle scale within plastically deformed crystalline materials allows a better understanding of the occurring phenomena. While previous approaches mostly relied on applying hand-chosen criteria on different…

Materials Science · Physics 2024-05-15 Armand Barbot , Riccardo Gatti

The ionic bonding across the lattice and ordered microscopic structures endow crystals with unique symmetry and determine their macroscopic properties. Unconventional crystals, in particular, exhibit non-traditional lattice structures or…

Materials Science · Physics 2024-11-04 Hongyi Wang , Ji Sun , Jinzhe Liang , Li Zhai , Zitian Tang , Zijian Li , Wei Zhai , Xusheng Wang , Weihao Gao , Sheng Gong

Particle-in-cell methods with stochastic collision models are commonly used to simulate collisional plasma dynamics, with applications ranging from hypersonic flight to semiconductor manufacturing. Code verification of such methods is…

Computational Physics · Physics 2026-05-26 Brian A. Freno , William J. McDoniel , Christopher H. Moore , Neil R. Matula