4940 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 rigorous quantum theory of the exciton orbital magnetic moment that incorporates electron-hole interactions and quantum geometric effects, revealing three distinct contributions that resolve long-standing discrepancies between theoretical predictions and experimental observations in materials like biased bilayer graphene.
This study employs an active learning framework guided by machine learning and density functional theory to efficiently discover 2D materials with exceptionally high spin Hall conductivity, identifying a top candidate nearly 23 times more effective than initial benchmarks while elucidating key atomic and electronic features that govern spin-charge interconversion.
This paper presents an improved algorithm for precisely determining the microstructural scaling exponent of two-phase media by incorporating higher-order correction terms and analyticity properties into the long-time asymptotics of diffusion spreadability, while also introducing a two-point Padé approximant to model the spreadability behavior across all time scales.
This paper demonstrates that machine-learning screens for sodium-cathode voltages, which rely on computationally derived references with systematic errors, failed pre-registered validation against experimental data due to a dominant 0.54 V bias in the reference values rather than the model itself, leading the authors to retire the screen and commit to a new calibration audit.
This paper introduces Materials Spatial Intelligence (MSI), an interpretable machine learning framework that learns directly from multimodal spatial observations of material systems to predict macroscopic behavior, identify governing microstructural features, and enable mechanism-driven microstructure optimization.
This paper presents a comparative analysis of zero-field remanent magnetization and magnetic relaxation data in the BCS superconductor LuNi2B2C and various hard ferromagnets, highlighting similarities and differences across TRM, IRM, and zigzag temperature sweep measurements to discuss their relevance for magnetization studies in diamond anvil cells.
This paper demonstrates a stable, low-temperature thermal oscillator driven by a magnetic field rather than complex power control, which utilizes the sharp thermal conductivity change at the superconducting transition of a metal-superconductor (Cu-Pb) joint to generate flexible sine or square-wave temperature oscillations with large amplitudes.
This paper introduces a rigorous nonradiative multiphonon (NMP) model for Deep-Level Transient Spectroscopy (DLTS) that corrects the significant errors and incorrect temperature dependencies found in the traditional Henry-Lang model by accounting for lattice relaxation and effective phonon correlations, demonstrating discrepancies of up to six orders of magnitude across 21 defects in 12 semiconductors.
This paper proposes a comprehensive framework for accelerating solid electrolyte discovery by integrating large AI models, including machine learning interatomic potentials and large language models, into a closed-loop autonomous system that bridges simulation, literature mining, and experimental validation to overcome current data and efficiency bottlenecks.
This paper reports the first experimental demonstration of electrical readout for 180-degree Néel vector reversal in atomically thin van der Waals antiferromagnetic CrSBr films by utilizing spin-dependent tunneling magnetoresistance in a heterostructure coupled to a spin-polarized layer.