4940 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 score-based diffusion model that combines materials science and computer vision techniques to accurately and efficiently reconstruct missing hydrogen atom positions in crystal structures, achieving a success rate exceeding 97% compared to traditional DFT or unconditioned approaches.
This paper demonstrates that Transonic Flow Focusing (TFF) is a purely mechanical, surfactant-free method capable of efficiently exfoliating graphene nanoplatelets into high-purity monolayer graphene and nanofragments by leveraging extreme shear and elongational stresses in a contact-free zone.
This study establishes KNdTeO as a structurally perfect frustrated triangular-lattice antiferromagnet with moments that exhibits exotic magnetism and persistent spin dynamics down to 50 mK, characterized by the absence of long-range magnetic ordering and the presence of fluctuating ground-state moments.
This study demonstrates that a deep learning model for grain growth prediction, enhanced by a physics-informed boundary-masked attention mechanism, achieves robust out-of-distribution generalization across diverse microstructural conditions without retraining, significantly improving prediction accuracy and aligning with curvature-driven physical principles.
This paper presents an exact method that exploits mirror symmetries in periodic unit cells to decompose eigenproblems into four independent sub-problems on a quarter-cell, enabling the efficient calculation of stop-band intervals via explicit formulas derived from just three discrete wavevectors without computing the full dispersion diagram.
Using hard x-ray photoemission spectroscopy, this study demonstrates that hydrogen in n-type InN exhibits amphoteric behavior by coexisting as both donor (H+) and acceptor (H-) states, providing a microscopic explanation for hydrogen-driven compensation in this semiconductor.
This paper introduces a large-scale autoregressive generative model pretrained on 133 million catalyst structures that enables controllable inverse design by generating valid catalysts with specific categorical and continuous properties, thereby significantly improving screening efficiency for reaction-targeted discovery.
The Lifetime Sample Tracking (LiST) platform is a comprehensive data management system developed by the 2DCC-MIP to automate the curation, analysis, and dissemination of diverse materials science data, thereby enabling closed-loop synthesis-design iterations and supporting machine learning research for approximately twenty thousand samples.
Using spin-polarized scanning tunneling spectroscopy, this study demonstrates that near-zero-energy localized states observed on the surface of the iron-based superconductor Fe(Te,Se) are topologically trivial Yu-Shiba-Rusinov states rather than Majorana zero modes, highlighting the critical role of spin-dependent analysis in distinguishing true topological signatures from trivial defect states.
This paper reveals that superlubric sliding ferroelectrics (SL-sFEs) exhibit a unique hybrid electronic-ionic polarization driven by the coupling between interlayer sliding and spacer layer buckling, resulting in diverse hysteresis behaviors that distinguish them from conventional sliding ferroelectrics.