2832 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 proposes a mechanism for nonvolatile electrical manipulation of spin and layer degrees of freedom in altermagnetic bilayers, such as CuF2, by utilizing sliding ferroelectricity to reversibly switch d-wave altermagnetic spin splitting, thereby enabling multifunctional spin-layertronic devices with potential multi-state logic applications.
This study demonstrates that Path Integral Molecular Dynamics simulations reveal nuclear quantum effects significantly accelerate the thermal decomposition of the TATB crystal and lower its activation energy by approximately 8% compared to classical methods, while highlighting that the Quantum Thermal Bath approximation substantially overestimates these quantum acceleration effects.
This paper presents a computationally efficient microscopic screening theory for excitons in two-dimensional materials that bridges the gap between effective models and first-principles methods by employing an atomistic description with quantum-screened interactions to accurately estimate binding energies and address discrepancies in existing literature.
This paper utilizes first-principles calculations to demonstrate that the sliding barrier of small islands on a graphene-covered substrate, rather than electrostatic potential, serves as the most rigorous metric for predicting the viability of remote epitaxy, suggesting the phenomenon is governed by island migration kinetics.
High-precision heat-capacity measurements of submonolayer He on graphite reveal a second-order transition between two striped domain-wall phases below 1 K, where the melting of the fixed-spacing phase into the variable-spacing phase supports the existence of a quantum nematic state characterized by one-dimensional phonons.
By combining THz-range Raman scattering, single-crystal X-ray diffraction, and first-principles calculations, this study reveals that formamidinium lead bromide possesses a unique coexistence of intrinsic local static disorder and a well-defined average crystal structure, where the former significantly influences the material's structural dynamics and phase transitions across the 10–300 K temperature range.
This study experimentally identifies the 3R polytypes of TaS and NbS as Kramers nodal line metals featuring tunable Octdong and Spindle-torus Fermi surfaces, respectively, and proposes a strain-induced phase transition to conventional metals alongside potential size quantization effects in natural inclusions.
Using angle-resolved photoemission spectroscopy, researchers successfully created, detected, and controlled quasi-steady dark excitons in doped SnSe2, revealing a novel anisotropic excitonic gap phase that extends the study of dark excitons from ultrafast timescales to quasi-equilibrium conditions.
This study reports the observation of electrostatic gate-controlled Altshuler-Aronov-Spivak quantum interference oscillations in a high-mobility two-dimensional electron gas at the (LaSr)(AlTa)O/SrTiO interface, attributed to closed-loop paths along SrTiO domain walls and demonstrating a long phase coherence length that highlights the potential of complex oxide interfaces for quantum technologies.
This paper presents a novel methodology using -learning with a dispersion-corrected tight-binding baseline to train machine-learning interatomic potentials that achieve CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions, enabling large-scale, chemically accurate simulations of materials like covalent organic frameworks.