4091 papers
Condensed matter physics and materials science form a dynamic partnership, exploring how the collective behavior of atoms gives rise to the unique properties of solids and liquids. This field bridges the gap between fundamental quantum mechanics and the practical engineering of everything from flexible electronics to superconductors, turning abstract theories into tangible innovations that shape our daily lives.
At Gist.Science, we process every new preprint in this category directly from arXiv to make these complex discoveries accessible to everyone. Our team generates both plain-language overviews and detailed technical summaries for each paper, ensuring that researchers, students, and curious minds alike can grasp the latest breakthroughs without getting lost in dense jargon.
Below are the latest papers in condensed matter and materials science, organized by their most recent publication dates.
This paper presents a computationally efficient, two-dimensional analytical model for characterizing toroidal magnetic rings with circular cross-sections under sinusoidal excitation, deriving explicit expressions for internal fields, impedance, and separated loss components to serve as an accurate alternative to finite element analysis for standardized material testing.
This paper demonstrates that equivariant graph neural networks, specifically an adapted GotenNet, significantly outperform existing state-of-the-art models in predicting optical spectra and static real permittivity for materials screening by leveraging geometric expressiveness and high-fidelity RPA-level training data.
AdsMind is a physics-grounded, closed-loop multi-agent framework that leverages machine-learning force field feedback to autonomously correct initial guesses and efficiently discover accurate adsorption configurations on heterogeneous catalyst surfaces, significantly outperforming open-loop methods and heuristic baselines in reliability and computational efficiency.
This study presents the first large-area observation of subsurface plastic activity in conditioned copper electrodes, demonstrating that high-field exposure induces significant intragrain misorientation consistent with evolving dislocation dynamics as the underlying physical mechanism for high-field conditioning.
This paper proposes a physics-informed framework that utilizes convex neural networks to discover anisotropic yield functions directly from full-field displacement and reaction force data, bypassing the need for direct stress observations or predefined parametric forms by embedding the yield function within a differentiable elastoplastic stress integration scheme.
This paper proposes a hybrid GNN-FEM framework that integrates a graph neural network surrogate for phase-field updates within a conventional finite element staggered scheme, enabling efficient, accurate, and generalizable simulations of history-dependent fracture evolution across diverse geometries and conditions while preserving physical consistency.
This paper establishes a theoretical and numerical framework for density-potential inversion in periodic systems using Moreau-Yosida-regularized density-functional theory, leveraging lower semicontinuity of the kinetic-energy functional and proximal mappings to recover exchange-correlation potentials for Kohn-Sham and Gross-Pitaevskii equations.
By combining photo-induced electron paramagnetic resonance, optical absorption spectroscopy, and hybrid functional calculations, this study identifies the neutral charge state of substitutional carbon on the nitrogen site (C) as the microscopic origin of the widely observed sub-bandgap optical absorption in AlN between 2 eV and 4 eV.
HEACalculator is an open-source Python tool that streamlines high-entropy alloy design by computing key thermodynamic descriptors and evaluating solid-solution formation rules through a unified command-line, graphical, and programmatic interface.
This study employs first-principles calculations to demonstrate that two-dimensional CsCr3Sb5 and Cr3Sb5 monolayers exhibit enhanced electronic correlations and an altermagnetic ground state, characterized by the simultaneous proximity of flat bands and van Hove singularities to the Fermi level, which can be further tuned via tensile strain.