4213 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 review comprehensively introduces the geometrical formalism of strained moiré superlattices derived from linear elasticity theory, explores their application in various twisted 2D materials to predict special patterns, and summarizes recent experimental techniques for realizing and engineering these strain-induced geometries.
This study presents a glucose oxidase-embedded hydrogel that utilizes enzymatic pH waves to drive autonomous, energy-dependent spatiotemporal stiffening, revealing that mechanical transduction lags behind chemical propagation and establishing design principles for adaptive soft materials.
This study refutes previous claims that (Ca₀.₅Mn₁.₅)MnWO₆ is a hybrid multiferroic by demonstrating through comprehensive dielectric, magnetic, and structural analyses that observed anomalies are attributable to spin-phonon coupling and chemical impurities rather than intrinsic ferroelectric or antiferroelectric ordering, thereby reclassifying the material as a paraelectric antiferromagnet.
This paper introduces PAIPAI, an efficient Monte Carlo framework coupled with machine-learning potentials and a dual-worker architecture, to successfully predict the ground-state atomic configurations of defective high-entropy alloys containing interstitials, as validated by density functional theory across multiple case studies.
This study utilizes density functional theory to investigate the structural, electronic, mechanical, and thermodynamic properties of the half-metallic N2CaNa full-Heusler alloy, revealing its mechanical stability, ductility, and potential for applications in spintronics and structural engineering.
This paper demonstrates the experimental creation, steering, and parking of individual topological torons in chiral nematic liquid crystals using tailored alternating-current electric fields, enabling deterministic submicrometre control over their trajectories for applications in reconfigurable patterning, micromanipulation, and optical memory.
This paper demonstrates that gallium-based liquid-metal interconnects enable high-performance, non-destructive, and reconfigurable modular superconducting quantum circuits by maintaining microwave quality across thermal cycles and module replacements while revealing specific kinetic inductance and power-dependent loss characteristics.
This study introduces ultralight, three-dimensional "bird's-nest" scaffolds made from FeCoNiCrCu high-entropy alloy nanowires that achieve metal-like thermal and magnetic functionality at less than 1% of bulk density by co-engineering configurational entropy with structural porosity.
This paper introduces mPFDNN, an analytically tractable deep neural network framework that integrates Material Property Fields with Hopfield network dynamics to overcome the interpretability limitations of traditional DNNs by rigorously respecting physical symmetries and enabling principled structure-property mapping across diverse material systems.
This paper demonstrates that the fully relativistic fixed spin moment (FR-FSM) method reconciles discrepancies in magnetocrystalline anisotropy energy (MAE) calculations arising from different exchange-correlation potentials and provides a framework for estimating maximum MAE values to guide the design of new-generation permanent magnets.