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.
First-principles calculations reveal that oxygen vacancies in multiferroic V-doped HfO donate electrons to V centers, reducing them to V and altering local magnetization and core-level shifts in a manner consistent with experimental XPS data, while suggesting that additional electron reservoirs are required to fully explain the valency ratios observed under ALD growth conditions.
This paper presents a custom-designed ultrahigh vacuum cluster tool that integrates in situ diamond surface preparation and characterization with cryogenic single nitrogen-vacancy center measurements to directly correlate surface chemistry with spin and charge properties for quantum sensing applications.
This study employs equivariant graph-based machine learning potentials, specifically the MACE architecture, to overcome computational limitations in simulating molten lithium carbonate, revealing that lithium transport is dominated by concerted motion and undergoes a temperature-driven transition from anisotropic to isotropic diffusion while accurately reproducing experimental structural and viscous properties.
This paper demonstrates that physical vapor deposition on aligned substrates can produce biaxially aligned organic glasses from both disk-like and rod-like mesogens at temperatures significantly below their clearing and glass transition points, thereby enabling new structural control for polarized emission and in-plane charge mobility in organic semiconductors.
This perspective paper outlines the necessity of integrating classical simulations, experimental measurements, machine learning, and quantum computing within reproducible, standardized workflows to overcome current limitations and accelerate the reliable discovery of advanced materials.
This paper demonstrates that incorporating gold nanoparticles with specific surface modifications at an electrode interface serves as a versatile, non-invasive control parameter to reshape the electrochemical doping profile and emission zone of light-emitting electrochemical cells, thereby enabling the optimization of device efficiency through constructive or destructive optical interference without altering the active material's chemistry.
This paper introduces a predictive first-principles framework that combines multi-configurational TDDFT and analytical non-adiabatic couplings to accurately compute internal conversion rates in optically active spin defects, successfully resolving long-standing discrepancies with experimental data for diamond NV centers and SiC divacancies.
This study establishes quantitative fluence thresholds and a practical operational window for 30 keV He ion irradiation of YBaCuO thin films, demonstrating that controlled defect engineering via Frenkel pair generation—rather than oxygen depletion—enables precise superconducting property suppression and nanopatterning while maintaining structural integrity within a specific fluence range.
This paper introduces Magnon Momentum Microscopy (MMM), a highly sensitive soft-X-ray technique that successfully images previously unobserved nonlinear magnon interactions at nanometre wavelengths in yttrium iron garnet, thereby establishing a versatile platform for exploring short-wavelength magnonics.
PLaID++ is a preference-aligned language model that leverages a novel symmetry-informed Wyckoff text representation and temperature scaling to efficiently generate diverse, thermodynamically stable, and target-constrained inorganic crystal structures, outperforming prior methods by approximately 50%.