3992 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 employs ab initio calculations to demonstrate that metal-encapsulated biphenylene bilayers serve as efficient bifunctional catalysts for oxygen reduction and evolution reactions, with specific metals like Mn and Fe identified as optimal for ORR and OER respectively, driven primarily by the d-orbital charge population of the intercalated metal.
This paper demonstrates that a printable hexagonal boron nitride ionogel enables efficient low-voltage gating of epitaxial Bi (111) films, revealing a non-rigid band response with tunable Rashba spin-orbit coupling and multiband transport effects that cannot be explained by conventional Fermi level shifts.
This paper proposes a machine-learning charge density (MLCD) approach that, by optimizing training sets with mixed-size small supercells, achieves high-accuracy prediction of large-supercell defect formation energies with significantly greater data efficiency and lower error rates compared to traditional machine-learning interatomic potentials.
This study utilizes a mass-selected ion beam apparatus to measure the etching yields of Si, SiO2, and Si3N4 under irradiation by various silicon, halogen, and silicon halide ions, revealing that silicon tri-halide ions exhibit superior etching performance at high energies while mono-halide ions tend to deposit silicon at low energies, thereby providing critical data to enhance the precision of etching process simulations.
This study proposes a multimodal deep learning framework that integrates volume fractions, persistent diagrams, and spatial correlations derived from 3D microstructure images to accurately predict local strain localization in Mg/LPSO two-phase alloys, revealing that high strain concentrates in regions where the hard LPSO phase is elongated at a 45-degree angle to the loading direction.
High-pressure synthesis significantly enhances the superconducting transition temperature and phase purity of underdoped and optimally doped PrFeAsO1-xFx by improving fluorine incorporation and microstructure, but its effectiveness is strongly composition-dependent, leading to impurity segregation and suppressed superconductivity in overdoped samples.
This paper presents a physics-guided computational framework that combines Random Forest classification, Ising-model Monte Carlo simulations, and autoencoder analysis to screen and identify promising cerium-based Ising ferromagnets with uniaxial magnetic anisotropy for future experimental synthesis.
This study investigates magnetoelastic coupling in stripe-domain states of yttrium iron garnet thin films, revealing that while local coupling is strong, the overall interaction remains in the weak regime due to phase cancellation across the magnetic texture, thereby establishing magnetic domain patterns as a key control parameter for phonon-mediated magnon dynamics.
This study demonstrates that alloying Pt with Cr enhances spin-orbit torques via an orbital Hall effect mechanism, enabling low-power, coherent spin-orbital Hall nano-oscillators in simple PtCr/NiFe heterostructures without the need for engineered multilayers.
This paper presents a template for upgrading manually operated magnetron sputtering chambers to automated systems, demonstrating its application in the semi-autonomous optimization of coercive fields in wurtzite AlScBN ferroelectric thin films.