4173 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 the ability to drive antiferromagnetic NiO into a highly nonlinear regime using THz light and subsequently steer its dynamics out of this state with a 33-Tesla magnetic field, marking a significant step toward ultrafast resonant switching of antiferromagnetic order.
The paper presents a robust, fitting-free method based on identifying reflectance minima in spectroscopic measurements to accurately extract the in-plane dielectric permittivity of small-area van der Waals microcrystals, overcoming the limitations of conventional ellipsometry and near-field probes.
This study introduces the Northeast Materials Database (NEMAD), a comprehensive resource of 67,573 magnetic materials entries generated via Large Language Models, and demonstrates its utility in training machine learning models that achieve high accuracy in classifying magnetic types and predicting transition temperatures to accelerate the discovery of high-performance magnetic materials.
This paper proposes a minimal Hubbard model to explain the ferrimagnetic ground state of the metal-organic framework CrCl(pyz), demonstrating that delocalized electrons on pyrazine sites couple with localized chromium spins to yield a magnetic moment and exchange interactions consistent with experimental observations.
This study utilizes a calibrated Phase-Field Discrete Element Model to demonstrate that precipitation-induced slowdowns in pressure-solution creep are driven by chemical solute accumulation when precipitation is slow, but by mechanical stress reduction when precipitation is fast.
This study elucidates the mechanism of three-magnon splitting in synthetic antiferromagnet spin wave conduits, revealing that low-order optical spin waves decay into parallel channels of non-degenerate acoustic doublets with standing wave characteristics, a finding with significant implications for nonlinear microwave signal processing applications.
This perspective outlines how generative AI models, including variational autoencoders, diffusion models, and large language agents, are revolutionizing metal-organic framework (MOF) discovery by shifting from manual enumeration to autonomous design and synthesis, thereby accelerating the development of high-performance materials for clean air and energy applications while addressing challenges in synthetic feasibility and data diversity.
This paper proposes that the enigmatic pseudogap state in cuprates, characterized by Fermi arcs and reduced carrier density, originates from a structural reconstruction that introduces a symmetry-enforced sublattice degree of freedom, which, when combined with spin-orbit coupling, naturally explains these experimental signatures through Fermi surface reconstruction and matrix-element interference.
This study utilizes self-consistent field theory to characterize the anisotropic elastic response and equilibrium rigidity of ordered block copolymer melts, revealing distinct stiffness differences between morphologies and architectures, and demonstrating that columnar phases exhibit significantly higher bending stiffness than lamellar phases.
This paper presents an adapted Phase-Field model that resolves physical inconsistencies in cement hydration simulations to accurately predict evolving microstructures and, through computational homogenization, reliably link hydration chemistry to the material's mechanical properties.