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The modification of electronic band structures and the subsequent tuning of electrical, optical, and thermal material properties is a central theme in the engineering and fundamental understanding of solid-state systems. In this scenario,…

Materials Science · Physics 2022-09-12 Valerio Di Giulio , P. A. D. Gonçalves , F. Javier García de Abajo

Electrode morphology critically determines the stability and efficiency of lithium metal anodes, yet no predictive framework has explained how measurable parameters control deposition. Here we introduce the first theoretical model of…

Materials Science · Physics 2025-10-21 Hanning Zhang , Oleg V. Yazyev , Ruslan Yamaletdinov

We present an overdamped continuum description of oriented active solids in which interactions respect the symmetries of space but do not obey the principle of action and reaction. Taking position and orientation as kinematic variables, we…

Soft Condensed Matter · Physics 2025-09-16 Balázs Németh , Takuya Kobayashi , Ronojoy Adhikari

The mathematical formulation of constitutive models to describe the path-dependent, i.e., inelastic, behavior of materials is a challenging task and has been a focus in mechanics research for several decades. There have been increased…

Computational Engineering, Finance, and Science · Computer Science 2023-09-06 Max Rosenkranz , Karl A. Kalina , Jörg Brummund , Markus Kästner

Absorption losses and laser-induced damage threshold (LIDT) are considered as the major constraint for the development of optical coatings for high-power laser optics. Such coatings require paramount properties like low losses due to…

Constitutive equations are developed for a polymer fluid, which is treated as a permanent network of strands bridged by junctions. The junctions are assumed to slide with respect to their reference positions under loading. Governing…

Materials Science · Physics 2007-05-23 A. D. Drozdov , R. K. Gupta

Two-dimensional (2D) materials have received considerable attention as possible electrodes in Li-ion batteries (LIBs), although a deeper understanding of the Li adsorption behavior as well as broad screening of the materials space is still…

Materials Science · Physics 2022-03-22 Sheng Gong , Shuo Wang , Taishan Zhu , Xi Chen , Jeffrey C. Grossman

A method for homogenization of a heterogeneous (finite or periodic) elastic composite is presented. It allows direct, consistent, and accurate evaluation of the averaged overall frequency-dependent dynamic material constitutive relations.…

Mathematical Physics · Physics 2015-05-28 Sia Nemat-Nasser , Ankit Srivastava

Understanding structure-property relationships in complex materials requires integrating complementary measurements across multiple length scales. Here we propose an interpretable "multimodal" machine learning framework that unifies…

Materials Science · Physics 2026-02-03 Shun Muroga , Hideaki Nakajima , Taiyo Shimizu , Kazufumi Kobashi , Kenji Hata

Image-text representation learning forms a cornerstone in vision-language models, where pairs of images and textual descriptions are contrastively aligned in a shared embedding space. Since visual and textual concepts are naturally…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Avik Pal , Max van Spengler , Guido Maria D'Amely di Melendugno , Alessandro Flaborea , Fabio Galasso , Pascal Mettes

Oxidation states are the charges of atoms after their ionic approximation of their bonds, which have been widely used in charge-neutrality verification, crystal structure determination, and reaction estimation. Currently only heuristic…

Materials Science · Physics 2022-11-30 Nihang Fu , Jeffrey Hu , Ying Feng , Gregory Morrison , Hans-Conrad zur Loye , Jianjun Hu

The calibration of solid constitutive models with full-field experimental data is a long-standing challenge, especially in materials which undergo large deformation. In this paper, we propose a physics-informed deep-learning framework for…

Machine Learning · Computer Science 2022-04-01 Craig M. Hamel , Kevin N. Long , Sharlotte L. B. Kramer

The design of physics-augmented neural networks (PANNs) for the purposes of constitutive modeling has received considerable attention as of late for a variety of material behaviors. Here, we revisit the classical framework of isotropic…

Mathematical Physics · Physics 2026-05-20 Maximilian P. Wollner , Dominik K. Klein , Herbert Baaser , Gerhard A. Holzapfel , Patrizio Neff

X-ray absorption spectroscopy is a premier element-specific technique for materials characterization. Specifically, the x-ray absorption near-edge structure (XANES) encodes important information about the local chemical environment of an…

Materials Science · Physics 2019-03-27 Matthew R. Carbone , Shinjae Yoo , Mehmet Topsakal , Deyu Lu

The determination of the chemical content is crucial for the quality control in high-precision device fabrication and advanced process development. For reliable chemical composition characterization, certain interaction volume of the target…

A multiscale (micro-to-macro) analysis is proposed for the prediction of the finite strain behavior of composites with hyperelastic constituents and embedded localized damage. The composites are assumed to possess periodic microstructure…

Materials Science · Physics 2020-10-20 Nathan Perchikov , Jacob Aboudi

In electrochemical systems, the structure of electrical double layers (EDLs) near electrode surfaces is crucial for energy conversion and storage functions. While the electrodes in real-world systems are usually heterogeneous, to date the…

High-fidelity electron microscopy simulations required for quantitative crystal structure refinements face a fundamental challenge: while physical interactions are well-described theoretically, real-world experimental effects are…

Computing atomic-scale properties of chemically disordered materials requires an efficient exploration of their vast configuration space. Traditional approaches such as Monte Carlo or Special Quasirandom Structures either entail sampling an…

Materials Science · Physics 2026-03-17 Maciej J. Karcz , Luca Messina , Eiji Kawasaki , Emeric Bourasseau

Damage gradient models approximate fracture mechanics using a modulation of the material stiffness. To this aim a single scalar field, the damage, is used to degrade as a whole the elastic energy. If applied to the structural models of…

Classical Physics · Physics 2022-11-30 Giovanni Corsi , Antonino Favata , Stefano Vidoli