3501 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.
The EGMOF framework introduces a data-efficient, modular hybrid diffusion-transformer architecture that decomposes inverse design into property-to-descriptor mapping and descriptor-to-structure generation, achieving high validity and hit rates across diverse datasets with minimal training data and retraining requirements.
This paper presents the synthesis of soft, cell-stiffness-matched elastomer-based whispering gallery mode microlasers that enable robust, tunable, and stable biosensing of biological forces through force-dependent laser mode splitting.
This study extends the liquid-gas analogy to a frustrated spiral Ising antiferromagnet, NdBWO, by identifying a critical endpoint and a universal Ising supercritical regime that exhibits divergent magnetic cooling efficiency, thereby establishing a new pathway for exploring supercritical phenomena and magnetic refrigeration in rare-earth magnets.
This paper elucidates the microscopic mechanism of exciton-polariton relaxation following upper polariton excitation, revealing a two-step process involving vertical inter-band transition and phonon-induced Fröhlich scattering, while demonstrating that finite material thickness significantly suppresses intraband scattering due to phonon-fluctuation synchronization arising from polaritonic spatial delocalization.
This paper reports the high-pressure synthesis and characterization of a novel metallic CrS phase in the form of single-crystalline nanorods, which features a unique ladder-type structure bridging 2D and 3D dichalcogenide motifs and exhibits strong covalent bonding, metallic conductivity, and potential for ionic conduction.
This study demonstrates that combining laser-enhanced contact optimization (LECO) with optimized firing temperatures effectively mitigates the high contact resistance and limited performance of cavitated fine-line Ag paste in PERC solar cells, thereby recovering fill factor and enabling practical low-silver metallization.
This paper presents an active learning workflow that integrates density functional theory, thermochemical modeling, and machine learning to screen over 70 billion candidates, resulting in a generalizable predictive model and the largest public database of CHNO explosives to date, which reveals oxygen balance as the primary driver of detonation performance.
This study presents the first experimental characterization of 316plus (EN 1.4420) stainless steel, revealing that while hydrogen precharging causes a modest strength reduction and significant ductility loss (40–50%) at cryogenic temperatures (77 K and 20 K), the material retains notable ductility (~30% reduction in area), confirming its suitability for liquid hydrogen storage applications.
This study demonstrates that high-pressure compression can selectively transform the hexagonal phase of a ReNbTiZrHf high-entropy alloy into a metastable, Re-enriched body-centered cubic polymorph, resulting in a unique dual-BCC microstructure with enhanced stiffness that is inaccessible through conventional thermal processing.
This paper presents a formal proof demonstrating that average magnetization is the primary driver of shape effects in large magnetic samples, leading to a computationally efficient method for incorporating sample shape into micromagnetic simulations using 3D periodic boundary conditions.