2832 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.
Through precise molecular beam epitaxy synthesis of MnBi2Te4 thin films, researchers demonstrated that controlling layer thickness induces a striking even-odd dependence in the anomalous Hall effect, where odd layers exhibit robust non-compensated antiferromagnetism and even layers show minimal response, offering a pathway toward realizing the zero-field quantum anomalous Hall effect.
The paper introduces MaterialFigBench, a benchmark dataset of 137 university-level materials science problems requiring figure interpretation, which reveals that despite improvements in multimodal large language models, they still struggle with genuine visual reasoning and quantitative analysis, often relying on memorized knowledge rather than accurately reading provided diagrams.
This study resolves the long-standing puzzle of ice's slipperiness by demonstrating that while nanoscale simulations alone fail to predict the correct friction behavior, incorporating frictional heating—which raises contact temperatures to the melting point even at modest speeds—accurately reproduces experimental data and confirms the 1939 hypothesis by Bowden and Hughes that frictional heating is the primary driver of ice's low friction.
This paper demonstrates that three-dimensional Bragg ptychography (3DBP) overcomes the phase retrieval limitations of traditional Bragg coherent diffraction imaging (BCDI) by successfully imaging micro-crystals with lattice distortions more than six times larger, thereby enabling reliable quantitative 3D imaging of strongly deformed systems.
This paper presents a high-fidelity level-set framework for simulating capillarity-driven polycrystalline grain growth with disorientation-dependent grain boundary energies, demonstrating superior energetic consistency and accuracy compared to existing models to enable advanced digital twins for annealing applications.
This molecular dynamics study compares the thermal stability of silicene and thin silicon films using SNAP and GAP machine learning potentials, revealing that while SNAP accurately models the thickness-dependent melting behavior up to the bulk limit, GAP fails to describe the gas phase, causing silicene to decompose into clusters.
This paper theoretically proposes that hole-doped reduced bilayer nickelate LaNiO can exhibit -wave superconductivity driven by interorbital interactions within an orbital-space bilayer model, where the absence of apical oxygens creates a large orbital energy offset analogous to interlayer hopping in bilayer systems.
This study investigates the advanced degradation and plasticiser exudation in Joseph Beuys's plasticised PVC artworks by combining multi-analytical techniques with DFT simulations to elucidate the thermodynamic mechanisms of phase separation and demonstrate the efficacy of NMR spectroscopy for developing non-destructive preventive conservation tools.
This paper proposes a novel cold source field-effect transistor (CSFET) utilizing a type-III aligned 2D WTe/HfS heterostructure to eliminate Schottky barriers, achieving a high on/off ratio of 10 and a sub-thermal subthreshold swing of 41.3 mV/dec through first-principles quantum transport modeling.
This review systematically analyzes 96 peer-reviewed articles from 2017 to early 2026 to categorize Generative Adversarial Network architectures for porous material reconstruction, highlighting significant advancements in accuracy and scale while identifying persistent challenges in computational efficiency and structural continuity.