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.
This study investigates the spin-phonon behavior and magnetocaloric potential of FeP and FeMnPSi using magnetometry, neutron scattering, and theoretical modeling, revealing that the magnetic transitions are driven by distinct site-specific behaviors and uncorrelated magnetic processes at two length scales, which are well-supported by first-principles calculations.
This study demonstrates that the double half-Heusler compounds and exhibit significantly reduced lattice thermal conductivity compared to the parent NbCoSn system due to mass disorder, positioning them as promising candidates for high-temperature thermoelectric applications.
This study demonstrates that laser ablation in liquid kinetically stabilizes metastable, compositionally homogeneous CuPdAgPtAu high-entropy alloy nanoparticles that resist thermodynamically driven phase segregation until subsequent thermal treatment overcomes kinetic barriers to induce equilibrium Cu-Ag separation.
This paper introduces fractal-inspired lattices that combine long-range periodic order with self-similar hierarchy to enable the exponential scaling of topological boundary states and minigaps, a phenomenon theoretically explained by multi-topological-phase theory and experimentally verified in photonic lattices.
This paper reports the discovery of superconductivity at a transition temperature of approximately 16.3 K in the newly synthesized, non-centrosymmetric layered compound NaVSeO, marking the first realization of superconductivity in an altermagnetic candidate and offering a promising platform for exploring exotic superconducting states and bridging high-temperature superconductor families.
This study demonstrates that dense, non-porous cubic ice can reversibly stabilize and retain molecular hydrogen as interstitial guests at near-ambient pressures and cryogenic temperatures, offering a new class of materials for hydrogen storage with densities comparable to metal hydrides.
This paper reports the experimental observation of acoustic magneto-chiral anisotropy in -quartz using a high-resolution ultrasound spectrometer, supported by a macroscopic analytical model that explains the effect's magnitude and frequency dependence.
This paper introduces Equitrain, a LoRA-based fine-tuning framework that significantly enhances the accuracy of machine-learning interatomic potentials for predicting phonon and thermal properties across diverse materials using minimal additional training data, outperforming both pretrained and scratch-trained models.
This paper presents a multiphysics finite element framework that integrates exact surface roughness representations with mechanical contact and electrostatic simulations to accurately predict the performance of triboelectric nanogenerators, offering superior agreement with experimental data compared to traditional analytical models.
This paper proposes Adversarial Distribution Alignment (ADA), a domain-agnostic framework that bridges the simulation-to-experiment gap by pre-training a generative model on fully observed simulation data and then aligning it with partial experimental observations to recover the target observable distribution.