4044 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 demonstrates a reversible method to dynamically tune charge transport in boron nitride-encapsulated graphene from a viscous hydrodynamic regime to an impurity-dominated regime at room temperature by using ultraviolet radiation to continuously modulate disorder levels in the hBN dielectric.
This paper introduces a noise-aware decision-making algorithm that leverages device-specific variability profiles to dynamically select between single-device and robust multi-device Bayesian optimization strategies, thereby enhancing reproducibility and resource efficiency in high-throughput parallel manufacturing workflows.
This paper introduces AGAPI, an open-access agentic AI platform that integrates multiple large language models with scientific tools to achieve numerical precision in materials property predictions and significantly outperform tool-free models on novel, memorization-resistant datasets by leveraging external databases and simulation workflows.
This study combines DFT and path-integral methods to construct a minimal moiré band model for twisted WSe homobilayers, revealing that layer antiferromagnetism and stripe spin-density-wave states compete with ferromagnetic Chern insulators at zero displacement field, while next-neighbor antiferromagnetic interactions can induce a time-reversal symmetry-breaking chiral superconducting state.
This paper presents a unified theoretical framework and practical guidelines for Bayesian calibration of complex, data-scarce models, accompanied by the open-source Python library ACBICI to facilitate reliable and extensible implementation in applied sciences.
This study investigates device-dependent variability in ultra-clean graphene field-effect transistors, attributing resistance fluctuations to competing scattering mechanisms and contact coupling, while proposing a phenomenological analysis method to effectively extract viscous electronic contributions in high-mobility graphene.
This study demonstrates that isovalent antimony substitution in PrFeAs(O,F) initially tunes superconductivity through lattice expansion and enhanced vortex pinning, but ultimately suppresses the superconducting transition temperature and degrades critical current density due to disorder and poor intergranular connectivity at higher concentrations.
BatteryMat is a hierarchical framework that combines machine learning and density functional theory to efficiently screen lithium-ion cathode materials by using an ALIGNN neural network for rapid initial voltage prediction, followed by force-field validation and automated DFT refinement to ensure thermodynamic consistency and accurate voltage estimation.
This paper proposes that the structural reconstruction of magic-angle twisted bilayer graphene from weak corrugation to large bending is driven by a twist-controlled mechanism called Moiré Phonon Condensation, where layer-symmetric flexural phonons soften and condense to capture the massive atomic displacements observed near the magic angle.
This paper employs oriented spin group theory and spin-orbit-coupling tensor expansion to reveal that altermagnets with fourfold rotation symmetry connecting opposite-spin sublattices exhibit distinct orbital and spin magnetization orders, leading to a coaxial Hall effect that enables deterministic switching of the Néel order for high-performance, stray-field-free spintronics.