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 paper demonstrates that decoupled transfer learning, which separates pretrained graph neural network feature extractors from simple regressors, significantly outperforms end-to-end training in extrapolating materials properties by leveraging transferable structural knowledge to maintain learned trends beyond training distributions.
This paper proposes a stable deep learning framework using latent multiscale recurrent graph neural networks to accurately predict long-horizon spatiotemporal temperature fields on complex meshes, outperforming existing baselines in applications like additive manufacturing.
This study demonstrates that substituting Li+ with Na+ in the second coordination sphere of Eu3+ in LiYO2 effectively shifts the phase transition temperature to optimize the operating range of luminescent thermometers, albeit at the cost of reduced relative sensitivity due to weakened first-order transition characteristics.
This study demonstrates that integrating freestanding epitaxial BaTiO₃ membranes onto silicon substrates significantly reduces mechanical clamping, resulting in a massive enhancement of the pyroelectric coefficient (up to 34x) and establishing a promising lead-free platform for infrared detection and energy management.
This study demonstrates that in epitaxial V2O3 thin films, the metal-insulator transition temperature is directly controlled by the degree to which martensitic laminate geometries satisfy macroscopic strain compatibility, revealing that finely tuned layered mixtures of twin variants govern electronic phase transitions.
This paper presents a stochastic simulation model that successfully reproduces the complex "cascade" pore morphologies and chronoamperometry trends observed during the dislocation-mediated electrochemical etching of porous GaN distributed Bragg reflectors by correlating etching probabilities with applied bias.
By combining ultrafast reflectivity experiments and density functional theory calculations, this study reveals that the charge density wave order in the Kagome lattice superconductors RbVSb and KVSb corresponds to a shifted 2×2×2 inverted star pattern, thereby breaking the six-fold rotational symmetry.
This study reveals that monolayer ice confined within the mineral martyite undergoes a disorder-order transition below 200 K, forming hydrogen-bonded toroidal hexamers that establish a ferroaxial order, thereby elucidating the ground state of two-dimensional ice.
This study employs a high-throughput methodology combining automated annealing and lock-in thermography to screen 151 flexible Fe-based alloy ribbons, identifying seven candidates with record-breaking anomalous Nernst coefficients and revealing that short-range atomic order in the amorphous matrix, rather than specific nanoclusters, drives the enhanced thermoelectric performance near the first crystallization temperature.
This review examines how spatial and temporal beam shaping techniques enhance pulsed laser ablation in liquids to achieve superior control over nanoparticle size, morphology, and productivity, thereby advancing the method's potential for industrial-scale synthesis of high-purity colloids.