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 presents a non-Markovian open quantum system theory for muon spin relaxation using a Schwinger-Keldysh influence-functional formulation to derive a spin stochastic equation with colored fluctuations and memory effects, enabling a quantitative global analysis of SR spectra in materials like that goes beyond standard strong-collision approximations.
This study demonstrates that applying magnetic fields along the crystallographic c-axis in NdFeO3 induces a complex sequence of spin-reorientation, spin-flop, and spin-flip transitions across a broad temperature range, driven by anisotropic 4f-3d coupling and significantly modified by Nd-sublattice ordering below 8 K.
This paper demonstrates that -valley twisted square homobilayers offer a highly tunable platform for realizing the square-lattice Hubbard model, where an interlayer displacement field breaks emergent layer-exchange symmetry to enable wide-range experimental control over the effective hopping ratio .
The paper introduces GLASS, a generative framework that utilizes a score-based model to invert multi-modal spectroscopic data into realistic atomistic structures of amorphous materials without requiring potential energy surface knowledge, successfully resolving complex experimental challenges in silicon, sulfur, and ice.
This paper demonstrates a breakthrough in characterizing operating nanowire lasers by using synchronous electron and photon spectroscopies to overcome the diffraction limit, enabling the nanometer-scale, sub-picosecond mapping of near-field dynamics and the quantification of stimulated photon populations to reveal complex cavity modes and material heterogeneity effects.
This paper presents a virtual materials testing framework for all-solid-state battery cathodes that combines AI-based stochastic 3D modeling with numerical simulations to generate diverse microstructures, enabling the calibration of regression models that quantitatively link geometrical descriptors to macroscopic properties like ionic and electronic conductivity.
This paper comments on a 2025 study by Fujiwara et al. that provides clear evidence of charge density wave synchronization in NbSe3 nanowires through the observation of Shapiro steps on I-V curves when driven by resonant surface acoustic waves generated on a piezoelectric substrate.
This study identifies that the critical limiting mechanism for vacancy transport in sodium metal anodes of solid-state batteries is interfacial thermodynamics rather than bulk diffusion, as evidenced by activation energies significantly higher than bulk migration values and a reduction in these energies upon introducing a sodiophilic tin-sodium alloy interlayer.
This paper demonstrates a reliable, high-performance strategy for IGZO and In2O3 transistors compatible with a 400°C BEOL thermal budget, featuring a novel amorphous In2O3/SiO2 capping layer that achieves a high mobility of 33.1 cm²/V·s and minimal threshold voltage shift under stress.
This paper proposes a physics-informed AI framework that couples transient electrothermal modeling with reliability classification to optimize laser-enhanced contact (LECO) processes in silicon photovoltaics, enabling the differentiation between stable performance gains and latent damage while guiding the development of digital twins for industrial process control.