3499 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 employs density functional theory to reveal that CaMnBi exhibits narrow-gap antiferromagnetism describable by a modified Heisenberg model, where small strain can tune the easy-plane magnetic anisotropy through the interplay of spin-orbit coupling and lattice distortions, highlighting its potential for spintronic applications.
This paper demonstrates that high-quality bilayer graphene/WSe heterostructures exhibit gate-tunable transitions between weak anti-localization and weak localization, providing direct spectroscopic evidence of proximity-induced spin-split valence bands driven by Rashba-type spin-orbit coupling.
This paper introduces vectorial field-guided lithography, a novel approach that utilizes fully structured polarization fields to quantitatively predict and programmably reconfigure pre-patterned azopolymer microstructures into complex anisotropic, bent, and chiral architectures through stress-driven mechanisms, thereby establishing a comprehensive theoretical framework for designing functional polymer surfaces beyond conventional intensity-based photopatterning.
This study demonstrates that magnetic field oscillations can effectively tune the non-flat energy landscape to control the formation and evolution of skyrmion lattice domains, thereby overcoming pinning effects to enhance quasi-long-range order in magnetic thin films.
This paper develops a unified theory for nonadiabatic wave-packet dynamics of Bloch electrons by deriving leading-order corrections that introduce a nonadiabatic metric and modified Berry connections, thereby reformulating the dynamics as geodesic motion in phase space and revealing that magnitude variations of external fields, unlike in the adiabatic regime, critically influence nonadiabatic behavior.
The paper introduces AMaRaNTA, an automated computational package that streamlines the energy-mapping method within Density Functional Theory to efficiently extract exchange and anisotropy parameters for modeling magnetic interactions in two-dimensional materials.
This paper presents a resolution-dependent formulation for continuum dislocation dynamics that bridges the gap between fine and coarse scales by introducing a "line bundle" closure relation, which is demonstrated to be significantly more accurate than the standard maximum entropy closure for modeling orientation fluctuations in intermediate regimes.
This study demonstrates that fully dense (Cr,Mo,Ta,V,W)C high-entropy carbide ceramics, synthesized via carbothermal reduction and spark plasma sintering, exhibit tunable thermal and electrical properties—including thermal conductivity ranging from 7 to 12 W m⁻¹ K⁻¹ and a consistent Vickers hardness of ~29 GPa—that are significantly influenced by densification temperature and excess carbon content.
This paper extends a previously developed inverse problem framework for identifying viscoplastic constitutive behavior from full-field observations to dynamic indentation scenarios by incorporating contact constraints via Lagrange multipliers and slack variables, and validates the method using both synthetic data and experiments on rolled homogeneous armor steel and polycrystalline aluminum alloy.
The EGMOF framework introduces a data-efficient, modular hybrid diffusion-transformer architecture that decomposes inverse design into property-to-descriptor mapping and descriptor-to-structure generation, achieving high validity and hit rates across diverse datasets with minimal training data and retraining requirements.