2692 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 utilizes a first-principles-derived tight-binding model to demonstrate that while long-range hopping quantitatively refines the peak characteristics of shift current conductivity in monolayer SnS, a minimal short-range model successfully captures the essential low-energy nonlinear response features of the bulk photovoltaic effect.
This paper reports a counterintuitive negative temperature coefficient of Gilbert damping in Py/Nd bilayers, where damping decreases with rising temperature due to thermally induced dynamic separation of interfacial and bulk magnetization, a phenomenon that can be tuned via capping layer thickness to enhance spintronic device performance.
This study demonstrates that longitudinal magneto-optical Kerr effect (MOKE) is a sensitive tool for characterizing strain-controlled, single-crystal-like magnetic switching and domain dynamics in epitaxial antiferromagnetic LaFeO3 films, establishing a foundation for their application in antiferromagnetic spintronics.
This paper introduces a novel quantum annealing protocol based on path-integral molecular dynamics that efficiently finds global energy minima in materials by incorporating nuclear quantum effects without explicitly manipulating many-body wavefunctions, demonstrating strong performance across diverse atomic systems simulated with both empirical and machine-learning potentials.
This study demonstrates that epitaxial, L2₁-ordered Co₂MnSi waveguides with impeccable crystalline integrity exhibit intrinsic magnetocrystalline anisotropy that stabilizes magnetization, suppresses nonlinear spin-wave instabilities over a wide frequency range, and enables bias-field-free nonlinear magnonics with high group velocities and ultralow damping.
The paper introduces RamanGPT, a deep-learning framework that utilizes an Atomistic Line Graph Neural Network for predicting Raman spectra from crystal structures and a fine-tuned large language model for inferring crystal structures from Raman spectra, thereby addressing both the forward and inverse problems in materials characterization.
This paper demonstrates a quantitative method for detecting molecular oxygen in gas mixtures using optically detected magnetic resonance (ODMR) from nitrogen-vacancy centers in fluorescent nanodiamonds, achieving a sensitivity of approximately 1% O2 concentration with a linear response that is limited by surface physisorption dynamics.
This paper presents a first-principles Z+1 method to predict core-level X-ray photoemission spectra of various SnO(110) surface terminations and defect states, demonstrating that the calculated spectra for reduced surfaces with adsorbates align well with experimental measurements and successfully distinguish between different surface chemical environments.
This paper establishes a predictive framework for the deterministic synthesis of specific borophene polymorphs on silver substrates by integrating reactive machine-learned interatomic potentials with grand-canonical Monte Carlo simulations to map growth pathways and identify conditions that suppress competing motifs.
This paper demonstrates that the classical Bernoulli principle can be extended to ferroelectric materials, revealing that geometric variations in nanorods govern polarization flux conservation to induce polarization acceleration in constrictions and the formation of complex topological structures like bubbles and Hopfions in expansions.