3525 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 proposes that correlation-driven spontaneous orbital order provides a general mechanism for realizing two-dimensional metallic altermagnets, identifying monolayer YbMnGe as a stable material with giant nonrelativistic spin splitting and large, gate-tunable transverse spin conductivity.
This paper presents a self-thermometry method using a standard PPMS instrument to accurately determine the adiabatic temperature change in first-order phase transition magnetocaloric materials like GdSiGe, enabling full characterization of both first- and second-order materials with a single device and achieving results within 1% of direct measurements.
This study demonstrates that the prototypical discotic organic semiconductor HAT6 undergoes a rapid, reversible, and orientationally correlated Martensitic-like transition between its liquid crystalline and crystalline phases when biaxially aligned in microchannels, challenging the conventional view that such transformations occur only between crystalline solids and offering a pathway for growing large-area aligned organic crystals for electronic devices.
This study reports the synthesis and characterization of the layered kagome antiferromagnet GdTi3Bi4, revealing a colossal anomalous Hall effect driven by Berry curvature and f-electron contributions, alongside a spin-cluster-like glassy phase that generates spin-texture-driven Hall responses.
This study establishes electronegativity mismatch as a predictive design principle for interfacial charge transfer in 3d/5d oxide heterostructures, demonstrating how this mechanism enables quantitative control over band filling and induces spin-state conversions without chemical substitution.
This study utilizes first-principles calculations to demonstrate that the p-wave magnet NiI2 exhibits distinct, large photogalvanic shift and injection currents under linear and circular polarization, respectively, enabling the direct probing of its nonrelativistic p-wave spin texture and the generation of pure spin currents for all-optical spin injection applications.
Using ultrafast electron diffraction, this study reveals that ferroelectric BaTiO exhibits polarization-dependent electron-phonon coupling and ultrafast carrier separation, where excited electrons relax more rapidly when the optical electric field aligns with the material's intrinsic ferroelectric polarization.
This study introduces a novel microcorrosion cell fabricated via localized electrodeposition in liquid and analyzed using cryogenic atom probe tomography to achieve unprecedented 3D atomic-scale mapping of transient copper corrosion reactions in acidic environments, revealing temperature-dependent interfacial evolution and transient complexes previously inaccessible to conventional characterization.
This study demonstrates that single Dysprosium atoms on NaCl(100) films, particularly those substituting surface sodium ions, exhibit thermally stable magnetic bistability up to 300 K and long spin relaxation times, establishing NaCl as a viable platform for single-atom magnets.
This paper presents a general-purpose, machine-learned interatomic potential for CrCoNi alloys based on the neuroevolution potential framework that achieves near first-principles accuracy across the full compositional range, enabling efficient large-scale simulations of complex phenomena like short-range order and composition-dependent mechanical properties.