4853 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 atom-averaged features from pretrained Machine-Learning Interatomic Potentials (MLIPs), such as MACE, serve as effective coarse coordinates for both evaluating material generative models via a novel Coarse-Fine Transport Distance (CFTD) metric and guiding the generation process itself.
This paper introduces the first end-to-end differentiable forward model for High-Energy Diffraction Microscopy (HEDM) that covers far-field, near-field, and point-focused geometries, enabling gradient-based joint parameter refinement and uncertainty quantification while achieving pixel-exact agreement with established simulators.
This paper reports the molecular beam epitaxy synthesis of a novel ternary nitride, PrTaN, and details the determination of its orthorhombic crystal structure (space group ) using a specialized fitting procedure for thin-film diffraction data, thereby demonstrating MBE's potential to stabilize and characterize previously unexplored complex nitride materials.
This paper introduces a strength-degradation phase-field model for antiplane fracture that unifies limit analysis, plasticity, and various fracture regimes by decoupling strength, stiffness, and toughness, thereby allowing crack nucleation and propagation to be governed by an arbitrary convex strength surface and an elasto-cohesive length scale rather than being constrained by elastic energy.
This paper introduces machine-learning models and symbolic regression trained on over 12,000 micromagnetic simulations to accurately predict hard-magnet extrinsic properties and recover intrinsic parameters, offering a computationally efficient alternative to traditional analytical models and direct simulations.
This study resolves long-standing discrepancies between diffraction and Raman spectroscopy in Ca0.4Sr0.6TiO3 by combining X-ray and electron microscopy to reveal that the high-temperature tetragonal phase retains nanoscale orthorhombic platelets with distinct local symmetry due to a loss of coherence in octahedral tilting.
This study employs pulsed nanocalorimetry to map the layer- and field-dependent magnetic thermodynamics of 2D CrSBr, revealing a dimensional crossover from bulk-like antiferromagnetism to intralayer ferromagnetism, a distinct odd-even layer parity effect, and the suppression of magnetic order by in-plane fields.
This paper presents a versatile digital twin for transmission electron microscopy that simulates electron beam trajectories and provides automated calibration tools to simplify complex lens alignment, enabling predictive setup of new imaging modes and facilitating AI-driven automation.
This paper predicts and theoretically characterizes a boundary Kerr effect in weakly doped zinc-blende semiconductors where a longitudinal electric field converts optically induced interband coherence into an edge-localized, helicity-odd polarization, providing a direct probe of multiband quantum kinetics without requiring spin-orbit coupling or intra-band accumulation.
This study demonstrates that ordered-to-disordered transfer learning with graph neural networks effectively predicts formation energies in high-entropy perovskite oxides but requires supplementary HEPO-specific data and three-body geometric representations to accurately model HOMO-LUMO gaps due to their sensitivity to local chemical environments.