4796 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 demonstrates that by leveraging noncollinear magnetic configurations and nonrelativistic spin splitting, optically-induced spin torque can be generated without relying on spin-orbit coupling, resulting in significantly stronger effects and broader material applicability for contactless spin manipulation.
This paper demonstrates that a square-lattice model with a slowly modulated Dirac mass texture naturally hosts chirally pinned flat bands and bias-controlled topological Jackiw-Rebbi states, offering an experimentally accessible platform for correlated phases without requiring engineered geometries or long-range hoppings.
This study demonstrates that reversible tuning of the Al/Si ratio in PrAlSi single crystals acts as a chemical knob to drive a unique intrinsic-extrinsic-intrinsic crossover of the anomalous Hall effect, primarily by modulating the Fermi level and carrier mobility.
This paper presents a machine learning workflow using CatBoost to indirectly predict the magnetic frustration index by independently estimating Curie-Weiss and Neel temperatures, successfully screening over 67,000 compounds to identify 20 high-confidence frustrated magnetic candidates, including novel oxide systems.
This paper demonstrates that 2D altermagnets with spin-valley-layer coupling exhibit a hidden spin-valley Hall effect that can be unveiled into a gate-switchable electric Hall signal by an external field, offering a new symmetry-based route for all-electrical valley-spin control and magneto-optics.
The paper introduces EpNet-Si, an equivariant neural network-enhanced empirical pseudopotential method for silicon that learns atomic form factors from local environments to achieve fast, accurate band structure predictions with errors comparable to density functional theory across diverse crystal structures.
This first-principles study compares the pressure-dependent structural, elastic, electronic, and vibrational properties of layered Y2GaB and Y2InB MAB phases up to 20 GPa, revealing that Y2GaB remains mechanically stable with enhanced thermal and elastic performance under compression while Y2InB is unstable beyond ambient pressure, thereby clarifying the critical role of the M-site substitution in governing their pressure-driven evolution.
This paper introduces the WBM-MatPES benchmark dataset to systematically evaluate machine-learning potentials under high pressure and presents Tuga-FF, a graph transformer model that significantly outperforms existing methods by maintaining high accuracy across ambient and extreme pressure conditions up to 150 GPa.
This study combines experimental characterization and first-principles calculations to demonstrate that hexagonal boron nitride growth on a curved platinum substrate induces selective faceting into specific crystal planes by altering the relative stability of surface facets through varying overlayer-substrate interaction strengths.
This paper presents a graph-based inverse design framework that enables the architectural and modal programming of reconfigurable piezoelectric tensors, allowing a single structure to achieve programmable, frequency-selective sensing and actuation across multiple directions while significantly reducing volume compared to conventional assemblies.