4119 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.
Drawing from a May 2023 workshop, this paper calls for resource-aware research in the fields of Universe and Matter by outlining a portfolio of digital transformation measures designed to simultaneously advance scientific progress and mitigate climate change through reduced fossil fuel reliance.
This study employs machine-learning force fields to conduct large-scale molecular dynamics simulations, revealing that optimal Li-ion transport and channel stability in amorphous Ti-doped lithium phosphorus sulfide electrolytes occur at 10% and 20% Ti concentrations via free-volume diffusion facilitated by disordered Li-S polyhedra.
This paper reports the discovery of high-field-stabilized reentrant superconductivity in infinite-layer nickelate thin films with transition temperatures up to 40 K, where both low- and high-field superconducting states are attributed to a Jaccarino-Peter-like compensation mechanism that significantly enhances the upper critical field.
This review explores the emerging interdisciplinary field of fluid-structure interaction enhanced by metamaterials, surveying theoretical frameworks and discussing how rationally designed composites can precisely control coupled fluidic, acoustic, and elastodynamic responses to improve performance in diverse technologies ranging from aerospace engineering to biomedical devices.
This paper introduces AtomWorld, a benchmark evaluating large language models on crystalline material structure modifications, which reveals that while models like Claude Opus 4.6 perform well on basic tasks, their success drops significantly with complex spatial reasoning, suggesting they are better suited as scientific copilots than autonomous agents.
This paper demonstrates that anisotropic local strains, induced by structural domains in an epitaxial La0.7Sr0.3MnO3/SrTiO3 heterostructure, deterministically lock split magnon branches to crystalline axes to enable robust, multimode magnon-phonon hybridization and transduction despite spatial inhomogeneity.
This paper introduces MiAD, an equivariant joint diffusion model that utilizes a novel "mirage infusion" technique to dynamically alter the number of atoms during generation, thereby significantly improving the discovery of stable, unique, and novel crystalline materials compared to existing state-of-the-art approaches.
This paper introduces CrystaLLM-{\pi}, a conditional autoregressive framework that integrates continuous property representations directly into transformer attention mechanisms to enable robust inverse design of crystalline materials, successfully demonstrating capabilities in both recovering structures from X-ray diffraction patterns and generating novel, stable photovoltaic candidates with targeted band gaps.
This study utilizes a peridynamic approach with an incubation time fracture criterion to model Ravi-Chandar and Knauss's experiments on Homalite-100, revealing that variations in the Mode-I stress intensity factor at constant crack velocities and the onset of micro-branching at higher velocities provide new insights into the nature of crack-velocity dependence in dynamic fracture.
By combining finite-temperature dynamical mean field theory with DFT+ and nudged-elastic-band calculations, this study reveals that dynamical correlations significantly lower Li-ion migration barriers in paramagnetic LiMnO, providing a unified explanation for both short-range and long-range transport activation energies without requiring extrinsic disorder or clustered vacancies.