2898 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 explores the landscape of "super-Mossian" dielectric materials that defy the empirical Moss rule by combining high refractive indices with wide optical transparency, explaining their electronic origins and computational discovery while highlighting their potential to overcome performance limits in advanced photonic devices.
This study demonstrates the synthesis of large-area, high-quality quasi-free-standing monolayer graphene via the intercalation of two-dimensional tin at the graphene/SiC interface, revealing a diffusion-driven growth mechanism and dynamic structural coupling that enables tunable strain engineering for next-generation quantum materials.
This study demonstrates that load-independent structural lubricity is strictly maintained in infinite contacts but persists in finite contacts only until elastic out-of-plane deformation at the boundaries exceeds a critical threshold, revealing that contact geometry and local compliance, rather than normal load, govern the onset of frictional load dependence.
This paper establishes a rigorous quantum-to-classical mapping for interacting spins at finite temperatures, demonstrating that the partition function asymptotically matches a classical model with effective spin length in the large- limit, a framework that successfully predicts transition temperatures for various magnetic materials in good agreement with experimental data.
This study develops a machine-learned interatomic potential for cerium hydride using active learning to investigate how increasing hydrogen content (H/Ce ratios from 2.0 to 3.0) drives lattice contraction and densification through stronger binding induced by octahedral atoms, enabling the simulation of properties like melting and diffusion that are inaccessible to ab initio methods.
This study combines experimental characterization and crystal plasticity modeling to demonstrate that increasing yttrium content in extruded Mg alloys suppresses common TT1 tension twins while promoting rare TT2 twins, alters critical resolved shear stress ratios, and induces higher local strain accumulation at TT2 sites, thereby offering new insights for alloy design.
This paper introduces a universal computational framework that decomposes macroscopic ion transport coefficients from molecular dynamics simulations into quantitatively additive, spatiotemporally resolved contributions from specific microscopic mechanisms, thereby enabling the identification of dominant transport modes and design rules across diverse electrolyte materials.
Through the synthesis of forty-five molecules and large-scale simulations, this study establishes that subtle hydrogen-fluorine substitution tunes molecular pairing motifs to predictably engineer either smectic or nematic fluid molecular ferroelectrics, providing a validated framework for designing functional polar fluids.
This paper introduces a scanning-probe-based manipulation scheme using nanostructured metal rotors to enable in situ, continuous post-fabrication twist control and direct imaging of moiré crystals, overcoming the fixed-angle limitations of conventional assembly methods while preserving sample quality for comprehensive multi-modal characterization.
This paper demonstrates that combining density-functional theory with dynamical mean-field theory provides a precise framework for analyzing Fermi-liquid behavior in SrVO and SrMoO, showing strong agreement between calculated and experimental low-temperature resistivity in high-quality samples while highlighting the need for further advancements in theory and material synthesis.