4797 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 develops a comparative analytical framework using compact electro-thermal models to elucidate the fundamental physical mechanisms behind the enhanced performance and scalability of disc-type phase-change memory for analog in-memory computing applications.
This paper presents a fabrication process combining anisotropic wet etching with a digital etching technique of repeated rapid thermal annealing oxidation and vapor-phase hydrofluoric acid etching to produce high-aspect-ratio, sub-10 nm-thick single-crystalline silicon fins, thereby establishing a scalable pathway for creating superconducting qubits with single-crystal Si dielectric barriers.
This study demonstrates that substituting boron with carbon in barium clathrates simultaneously drives a metal-to-semiconductor transition by opening a bandgap and significantly enhances lattice thermal conductivity through phonon hardening and increased group velocities, offering a unified chemical design strategy for advanced heat-management materials.
The paper introduces ANCHOR, a framework that decouples crystal structure generation from composition search by employing a frozen Crystal Structure Prediction (CSP) model as a fixed physical prior while using a GRPO-trained policy with adaptive novelty rewards to optimize composition selection, thereby significantly improving the discovery of unique, stable, and novel crystal structures compared to traditional end-to-end de novo generation approaches.
This paper presents a resilient, strain-mediated antiferromagnetic MnIr/PMN-PT bare-die processor that enables high-accuracy, ultra-low-energy analog computing for autonomous intelligence in extreme environments characterized by high temperatures, intense magnetic fields, and radiation.
This paper establishes a computational symmetry framework that separates the spin Hall conductivity in altermagnets into time-reversal-even and -odd channels, deriving magnetic-point-group tensor constraints and a design atlas to predict and prescreen symmetry-allowed responses across diverse magnetic crystals.
This study establishes a robust first-principles workflow for simulating Ti K-edge X-ray absorption spectra by systematically incorporating quadrupole excitations, thermal disorder, and many-body shake-up effects, achieving high agreement with experimental data for most titanium oxides while identifying the need for advanced electronic structure theories to resolve specific correlation-driven features in materials like BaTiO.
The paper introduces QuAcc, an open-source Python library that democratizes atomistic simulation workflows for the AI era by decoupling scientific logic from execution engines to enable flexible, engine-agnostic orchestration of diverse quantum-mechanical methods and foundation machine-learned interatomic potentials.
Using Zr-doped ErMnO3 as a model system, this study demonstrates that preferential retention of atoms during atom probe tomography, driven by evaporation field differences and analysis temperature, can significantly distort measured dopant site preferences and lead to incorrect interpretations of atomic positions.
This study presents a correlative STEM-EBIC and 4D-STEM approach to quantitatively map nanometer-scale electric fields in operating oxide Schottky junctions, revealing non-classical interfacial electrostatics that deviate from ideal depletion models.