3396 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 study demonstrates that applying in-plane equibiaxial tensile strain to the room-temperature altermagnet KVSeO eliminates parasitic Fermi pockets, thereby restoring flat-band geometry and achieving a record charge-to-spin conversion efficiency of approximately 96%, which establishes strain engineering as a practical route for high-efficiency spintronic devices.
This study utilizes ARPES and DFT calculations to demonstrate that UV-induced electron doping in SrTiO3 causes a significant surface bandgap shrinkage and a counterintuitive valence band shift indicative of negative electronic compressibility, distinguishing it from KTaO3 and highlighting its potential for advanced oxide electronic and energy storage applications.
This paper reports the successful on-surface synthesis and comprehensive characterization of a novel gulf-edged chiral graphene nanoribbon, establishing a new design motif that yields a 1.8 eV bandgap semiconductor while revealing distinctive vibrational fingerprints and ambient instability linked to edge features.
This paper reports the first experimental observation of the optical nonlinear anomalous Hall effect in the antiferromagnet CuMnAs, demonstrating its ability to distinguish 180°-reversed magnetic states and enabling nanoscale imaging of hidden antiferromagnetic order for advanced spintronic applications.
This study demonstrates that natural language-derived descriptors generated from transformer embeddings of alloy processing treatments can effectively reconstruct processing parameters and significantly improve the prediction accuracy of high-entropy alloy hardness by 20%.
This study establishes a multiscale, data-driven framework using an Allegro neural network potential to reveal that phase-dependent thermophysical properties, particularly the strong absorption and distinct thermal conductivity of amorphous LiCoO2, are critical for accurately modeling photothermal sintering and preventing the overestimation of safe operating windows inherent in traditional constant-property models.
OptiMat Alloys is a large language model-powered conversational agent that transforms computational alloy exploration by integrating a living database, zero-code web accessibility, and built-in uncertainty quantification to enable on-demand, targeted multi-principal element alloy screening guided by user domain knowledge.
This study experimentally demonstrates that epitaxial bismuth films grown on ferromagnetic EuO(111) substrates form a stable, room-temperature quantum spin Hall insulator with edge-localized states, establishing a viable platform for realizing magnetically tunable higher-order topological phases.
This paper presents an updated LAMMPS implementation of the Hamiltonian-Adaptive Resolution Simulation (H-AdResS) method that supports diverse potentials and fluctuating densities, demonstrating its efficiency and accuracy in modeling gas adsorption and transport in porous metal-organic frameworks while preserving atomistic-level properties.
This paper introduces a "cryogenic shock exfoliation" method combined with low-pressure van der Waals assembly to produce large-area, high-yield rhombohedral multilayer graphene devices exhibiting ultrahigh mobility and uniform correlated electron phases, thereby overcoming previous material abundance and fabrication limitations.