4091 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 develops an atomic-scale theoretical framework explaining how robust out-of-plane ferroelectricity persists in ultrathin HfO- and bismuth-based films through "self-polarizing" and "switchable role of the termination layer" effects driven by characteristic structures and electrode interactions, thereby guiding the design of next-generation nanoelectronic devices.
This paper introduces INCARBench, a benchmark for evaluating large language models on generating and repairing scientific configurations for VASP simulations, revealing that while frontier models achieve high semantic accuracy, they still struggle with the task-critical correctness required for physically valid settings in complex materials science scenarios.
This paper presents advanced data analysis methods to improve the fidelity of powder x-ray diffraction intensity measurements under laser-driven dynamic compression at the Omega and NIF facilities, utilizing in-situ references and accounting for thermal damping to accurately characterize materials like diamond near 1 TPa.
This paper proposes an automated, flexible approach for segmenting Scanning Tunneling Microscopy (STM) images that combines few-shot and unsupervised learning to overcome labelled data scarcity, enabling high-accuracy defect classification on diverse surfaces with minimal manual annotation.
This paper introduces UniFFBench, a comprehensive evaluation framework featuring the MinX dataset of over 1,500 mineral systems with experimental references, to reveal a significant "reality gap" where state-of-the-art universal machine learning force fields, despite strong computational benchmark performance, fail to achieve the accuracy required for practical applications when tested against real-world experimental conditions.
This paper presents a scalable, real-space first-principles method based on RS-LMTO-ASA and Chebyshev polynomial expansion to simulate orbital and spin transport phenomena in complex metallic multilayers, successfully demonstrating substantial orbital accumulation in centrosymmetric systems while naturally accounting for disorder and interface effects.
This study combines scanning tunneling microscopy and ab initio calculations to reveal that the Pt(111) surface catalyzes the thermal conversion of n-octane into benzene rings via intramolecular cyclization and into polycyclic species through a zipper-like intermolecular homocoupling mechanism at temperatures above 600 K.
This paper presents a comprehensive phase-field fracture model for brittle materials under thermal shock that independently specifies bulk properties, strength, and toughness, successfully unifying the prediction of diverse fracture scenarios—from crack propagation to nucleation and branching—across various experimental cases where classical approaches fall short.
By measuring the work functions of Li and Li metal nanoparticles, researchers discovered a significant isotope effect and non-trivial temperature dependence that challenge simple models and highlight lithium's nature as a quantum material where electronic and ionic degrees of freedom strongly interact.
This study demonstrates that topological antiferromagnet MnSn exhibits an unusually large near-infrared photoelastic effect driven by coherent acoustic phonons, revealing its exceptional sensitivity to lattice distortions and establishing a foundation for ultrafast straintronics applications.