4797 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 novel synthesis method for polycrystalline vanadium dioxide thin films using reactive pulsed laser deposition at room temperature followed by vacuum annealing, which overcomes traditional high-temperature constraints to enable CMOS-compatible integration for neuromorphic hardware.
This paper introduces KGE2, a parameter-free, semilocal kinetic energy density functional at the Generalized Gradient Approximation level that revives the Thomas-Fermi-von Weizsäcker framework by preserving the exact second-order gradient expansion, achieving state-of-the-art accuracy across both extended and finite systems while enabling efficient, large-scale Orbital-Free DFT simulations.
This paper presents a schema-first alignment framework that synthesizes large-scale domain knowledge and leverages an IR-driven Direct Preference Optimization workflow to build compact, executable domain-specific LLMs that outperform general models in data-scarce scientific fields like semiconductor TCAD and FEM simulation.
This study combines semiempirical atomistic thermodynamics with interpretable machine learning and symbolic regression to map the thermodynamic stability of graphene with atomic vacancies, successfully condensing the complex structure-stability relationship into a compact, high-accuracy analytical law that identifies defect concentration and inter-vacancy distance as the dominant factors.
This study employs first-principles calculations to demonstrate that the tetragonal T-GaN monolayer is a dynamically stable, nonmagnetic semiconductor with pronounced mechanical, electronic, and optical anisotropy, making it a promising candidate for anisotropic nanoelectronic and optoelectronic applications.
This study investigates how silicon and carbon doping influence the structural, morphological, and optical properties of catalyst-free InGaAs nanowires, revealing that while carbon doping significantly enhances crystal quality and aspect ratio, it simultaneously introduces point defects and surface recombination that diminish photoluminescence efficiency.
This study employs neural-network molecular dynamics with a Deep Potential model to establish a thermodynamically consistent pressure-dependent melting curve for B2-NiAl, revealing a steeper increase in melting temperature at high pressures and confirming that the melting process remains congruent with an essentially equiatomic liquid phase.
ALIGNN 2.0 is a unified, dependency-free PyTorch framework that reimagines the Atomistic Line Graph Neural Network to simultaneously handle diverse materials tasks—including property prediction, force fields, inverse design, and spectroscopy—while achieving state-of-the-art performance on benchmarks and enabling efficient large-scale simulations.
This paper demonstrates the creation and characterization of a quasi-one-dimensional, positionally disordered spin chain in diamond by leveraging nitrogen incorporation along CVD step bunches, enabling the use of nanoscale quantum sensing to probe local spin autocorrelations and dipolar transport within this engineered low-dimensional quantum system.
This study reveals that grain boundary distortion in Nd2Fe14B induces a crossover in crystal field strength between light and heavy lanthanides, reorienting the local easy axis toward the basal plane to facilitate magnetization reversal and providing an atomistic basis for optimizing heavy rare-earth grain-boundary diffusion.