3572 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 demonstrates that fabricating dense and graded trilayer Al-LLZO solid electrolytes significantly enhances lithium utilization and cycling stability in all-solid-state batteries by reducing interfacial resistance and improving near-surface lithium distribution compared to conventional dense electrolytes.
This paper utilizes a virtual spectral conductivity model to establish quantitative design principles for high-performance thermoelectric materials, demonstrating that optimal band convergence requires a band gap and energy separation exceeding approximately 5k_BT to suppress bipolar effects and maximize spectral conductivity through high band degeneracy, effective mass, and relaxation time.
This study demonstrates that thermal-evaporated self-assembled monolayers (eSAMs) with a unique vertical-to-horizontal molecular orientation gradient overcome the scalability and uniformity limitations of solution-processed SAMs, enabling high-efficiency perovskite photovoltaics with power conversion efficiencies up to 23.67%.
This paper advocates for a paradigm shift from optimization-driven to exploration-driven self-driving laboratories in materials science, proposing a defect-aware framework specifically for inorganic optoelectronic materials that prioritizes generating structured, physics-informed datasets to enable mechanistic inference and deeper scientific understanding.
This paper proposes a novel spintronic-magneto-impedictive effect in antiferromagnetic materials modeled by a spin-Rice-Mele Hamiltonian under a magnetic field gradient, offering a theoretical foundation for low-power, pure spin-current memory devices that operate without net charge transport.
This study demonstrates that Raman optical activity serves as a sensitive probe for electric toroidal octupolar symmetry in pyrite FeS, evidenced by reproducible sign reversals of circular intensity differences on neighboring {111} faces that are uniquely associated with the doubly degenerate phonon mode and confirmed by first-principles calculations.
This paper proposes a new paradigm for material design that leverages intrinsic quantum measurement to drive unitary-projective electron dynamics, thereby enabling novel functionalities such as nonreciprocal transport, new forms of magnetism, and energy conversion efficiencies exceeding the Carnot limit.
This study employs an interpretable small-data machine learning framework to optimize pulsed laser deposition of -Ga2O3 on sapphire, achieving record-breaking crystallinity while revealing that temperature and oxygen pressure independently govern bulk crystallinity and surface morphology, respectively.
This paper presents a unified heterogeneous computing framework within the ABACUS package that accelerates real-time time-dependent density functional theory simulations based on numerical atomic orbitals through co-designed abstraction layers, demonstrating significant speedups on single GPUs and high parallel efficiency across multiple GPUs for large-scale electron dynamics studies.
The paper introduces olLOSC, a unified and computationally efficient orbital-free density functional approximation that corrects delocalization errors in both molecules and periodic materials by calculating curvature via orbital-free electronic linear response, thereby enabling robust predictions of total energy, charge density, and band structure without the high cost of existing methods.