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In this study, we develop a conditional diffusion model that proposes the optimal process parameters and predicts the microstructure for the desired mechanical properties. In materials development, it is costly to try many samples with…

Computational Engineering, Finance, and Science · Computer Science 2025-10-27 Arisa Ikeda , Ryo Higuchi , Tomohiro Yokozeki , Katsuhiro Endo , Yuta Kojima , Misato Suzuki , Mayu Muramatsu

This article reviews recent inverse statistical-mechanical methodologies that we have devised to optimize interaction potentials in soft matter systems that correspond to stable "target" structures. We are interested in finding the…

Soft Condensed Matter · Physics 2008-11-05 Salvatore Torquato

Optical and acoustic metasurfaces are two-dimensional arrays of subwavelength elements that locally modulate or phase shift incident waves. Acoustoplasmonic metasurfaces combine the physics of light and sound, producing acoustic wavefronts…

Applied Physics · Physics 2025-04-11 Julia E. Holland , Nicholas Boechler , Lisa V. Poulikakos

Amorphous solids, i.e., systems which feature well-defined short-range properties but lack long-range order, constitute an important research topic in condensed matter. While their microscopic structure is known to differ from their…

Quantum Gases · Physics 2024-08-23 Sergi Julià-Farré , Joseph Vovrosh , Alexandre Dauphin

Adjoint-based design optimizations are usually computationally expensive and those costs scale with resolution. To address this, researchers have proposed machine learning approaches for inverse design that can predict higher-resolution…

Machine Learning · Computer Science 2024-08-19 Milad Habibi , Mark Fuge

The ability to readily design novel materials with chosen functional properties on-demand represents a next frontier in materials discovery. However, thoroughly and efficiently sampling the entire design space in a computationally tractable…

Materials Science · Physics 2021-06-08 Victor Fung , Jiaxin Zhang , Guoxiang Hu , P. Ganesh , Bobby G. Sumpter

The atomic-level structure of bulk metallic glasses is a key determinant of their properties. An accurate representation of amorphous systems in computational studies has traditionally required large supercells that are unfortunately…

Materials Science · Physics 2024-01-17 Siya Zhu , Jan Schroers , Stefano Curtarolo , Hagen Eckert , Axel van de Walle

Creating amorphous solid states by randomly bonding an ensemble of dense liquid monomers is a common procedure which is applied to create a variety of materials such as epoxy resins, colloidal gels, and vitrimers. The properties of the…

Soft Condensed Matter · Physics 2024-01-26 Misaki Ozawa , Jean-Louis Barrat , Walter Kob , Francesco Zamponi

There is growing interest in engineering unconventional computing devices that leverage the intrinsic dynamics of physical substrates to perform fast and energy-efficient computations. Granular metamaterials are one such substrate that has…

Machine Learning · Computer Science 2024-04-09 Atoosa Parsa , Corey S. O'Hern , Rebecca Kramer-Bottiglio , Josh Bongard

A novel approach to predict the atomic densities of amorphous materials is explored on the basis of Car-Parrinello molecular dynamics (CPMD) in density functional theory. Despite that determination of the atomic density of matter is crucial…

Disordered Systems and Neural Networks · Physics 2018-01-17 Yoritaka Furukawa , Yu-ichiro Matsushita

Ambigrams are graphical letter designs that can be read not only from the original direction but also from a rotated direction (especially with 180 degrees). Designing ambigrams is difficult even for human experts because keeping their dual…

Computer Vision and Pattern Recognition · Computer Science 2023-06-22 Takahiro Shirakawa , Seiichi Uchida

We present a genetic algorithm for the atomistic design and global optimisation of substitutionally disordered bulk materials and surfaces. Premature convergence which hamper conventional genetic algorithms due to problems with…

Materials Science · Physics 2008-09-10 Chris E. Mohn , Walter Kob

Generative models hold the promise of significantly expediting the materials design process when compared to traditional human-guided or rule-based methodologies. However, effectively generating high-quality periodic structures of materials…

Materials Science · Physics 2024-08-15 Anshuman Sinha , Shuyi Jia , Victor Fung

Inverse design has enabled the systematic design of ultra-compact and high-performance nanophotonic components. Yet enforcing foundry design rules during inverse design remains a major challenge, as optimized devices frequently violate…

The fact that a disordered material is not constrained in its properties in the same way as a crystal presents significant and yet largely untapped potential for novel material design. However, unlike their crystalline counterparts,…

Soft Condensed Matter · Physics 2015-10-30 Carl P. Goodrich

Theoretical frameworks used to qualitatively and quantitatively describe nuclear dynamics in solids are often based on the harmonic approximation. However, this approximation is known to become inaccurate or to break down completely in many…

Materials Science · Physics 2020-09-02 Florian Knoop , Thomas A. R. Purcell , Matthias Scheffler , Christian Carbogno

The use of generative models to sample equilibrium distributions of many-body systems, as first demonstrated by Boltzmann Generators, has attracted substantial interest due to their ability to produce unbiased and uncorrelated samples in…

Statistical Mechanics · Physics 2025-10-23 Maximilian Schebek , Frank Noé , Jutta Rogal

Designing free-form photonic devices is fundamentally challenging due to the vast number of possible geometries and the complex requirements of fabrication constraints. Traditional inverse-design approaches--whether driven by human…

Optics · Physics 2025-04-25 Dongjin Seo , Soobin Um , Sangbin Lee , Jong Chul Ye , Haejun Chung

Many natural materials exhibit highly complex, nonlinear, anisotropic, and heterogeneous mechanical properties. Recently, it has been demonstrated that data-driven strain energy functions possess the flexibility to capture the behavior of…

Computational Engineering, Finance, and Science · Computer Science 2023-10-09 Vahidullah Tac , Manuel K Rausch , Ilias Bilionis , Francisco Sahli Costabal , Adrian Buganza Tepole

In this study, a new alternative model algorithm has been proposed for assembling amorphous structures, unifying the bosonic paradigm applicable at low temperatures with crystalline models relevant at room and higher temperatures. Physical…

Materials Science · Physics 2026-02-02 A. Berezner , M. Rybakov , M. Sidlyar , V. Fedorov
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