2692 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 challenges the prevailing view that nonrelativistic effects in altermagnets are independent of spin-orbit coupling by predicting a giant, nonperturbative magnetic orbital Hall effect that is uniquely allowed in altermagnets, enabling field-free magnetization manipulation and strong room-temperature responses in materials like CrSb and FeSb2.
The paper introduces MetaDNS, a framework that integrates well-tempered metadynamics into discrete neural samplers to overcome mode collapse and enable efficient exploration of high-energy barriers for accurate free energy estimation in complex discrete distributions.
This first-principles study reveals that while Fe adsorption on biphenylene networks minimally affects in-plane mechanical properties, it dramatically enhances out-of-plane stiffness in bilayer structures and induces pronounced electrical conductivity anisotropy, highlighting its potential for tuning the material's functional properties.
This paper investigates an alternative path-finding approach utilizing the A* algorithm to compute the minimal-weight-matching centrosymmetry parameter, offering a potential solution to the flaws identified in existing molecular dynamics analysis methods.
This paper presents an automated deep learning framework utilizing an EfficientNetV1B0 Convolutional Neural Network to accurately classify nine distinct magnetic states, including complex antiferromagnetic textures, from RGB visualizations generated by atomistic spin dynamics simulations.
This paper introduces "Virp," a neural network-accelerated pipeline that combines permutation-based virtual cell generation, sampling, and thermodynamic post-processing to efficiently predict physical properties in site-disordered materials, overcoming the computational limitations of traditional methods by demonstrating that adequate configurational sampling can be achieved with just 400 virtual cells.
This study employs four simultaneous in situ techniques to systematically characterize Ga adsorption and desorption kinetics on GaN(0001) across various coverages, successfully validating a unified kinetic model and determining a Ga adlayer desorption activation energy of 2.87 ± 0.04 eV.
This study demonstrates that angle-resolved photoemission spectroscopy reveals an equilibrium-stabilized, hidden-phase-like metallic state in intermediate-thickness 1T-TaS2 flakes that persists up to room temperature while retaining characteristic hybridization gaps, offering a new platform for controlling competing electronic states in layered materials.
This paper reports the reproducible generation of an anomalous, spin-polarized linearly dispersing band with opposite helicity to the topological surface state in Bi-based topological insulator thin films, induced by soft Ar-ion bombardment and annealing.
This study employs first-principles calculations to demonstrate that hydrostatic pressure up to 40 GPa systematically tunes the electronic and optical properties of ferroelectric LaMoN, revealing an optimal regime near 15 GPa for enhanced photovoltaic efficiency through reduced exciton binding energy and maximized shift current density, thereby proposing a strategy for multi-junction solar devices.