4119 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 introduces an efficient Epstein zeta function-based method that transforms the computation of many-body lattice sums from exponentially complex direct summation to linear-cost singular integrals, enabling high-precision studies of three-body interactions like the Axilrod-Teller-Muto potential and revealing pressure-induced structural transitions in condensed matter systems.
This paper identifies three anomalous cases—rotationless axial phonons, divergent gyromagnetic ratios, and anisotropic gyromagnetic ratios—that demonstrate phonon magnetic moments cannot be fully explained by conventional frameworks, thereby revealing new aspects of phonon magnetism and suggesting the existence of phononomagnetic hidden order.
This paper resolves the debate surrounding the nature of NiPS3's sharp photoluminescence by combining substitution experiments and theoretical calculations to demonstrate that the emission originates from a crystal-field-tuned spin-flip transition between a triplet ground state and a singlet excited state, thereby establishing a fundamental link between the material's optical properties and its magnetic order.
Ab initio calculations reveal that low-concentration vanadium doping in orthorhombic HfO yields a robust multiferroic insulator that maintains a significant band gap and intrinsic polarization while exhibiting linearly increasing ferromagnetism.
This paper derives generalized stochastic Landau-Lifshitz-Gilbert equations from first principles for spin-orbital coupled Mott insulators by incorporating electron-phonon interactions via a Keldysh path-integral formalism, thereby establishing a microscopic framework that accurately captures dissipative spin dynamics, thermal fluctuations, and non-equilibrium relaxation processes.
This paper introduces TEM Agent, a framework that leverages Large Language Models and the Model Context Protocol to enable text-based control of transmission electron microscopy subsystems, data management, and high-performance computing resources, thereby simplifying complex workflows without requiring additional model training.
This study demonstrates the quantum control of a strongly correlated Hubbard exciton in the one-dimensional Mott insulator SrCuO by using nonresonant midinfrared Floquet engineering to drive ultrafast rotations between bright and dark states, as quantified by resonant third-harmonic generation.
This paper develops a simple electrostatic two-equation model that accurately simulates dual-layer a-IGZO/a-IZO TFT operation by analyzing charge distribution and identifying an optimal top-layer thickness of 9 to 12 nm, while demonstrating the model's broader applicability to other dual-layer TFT systems.
This study uses ab initio calculations to demonstrate that framework materials, particularly the metal–organic compound Zn(NH)(formate), can generate significantly larger light-induced magnetic fields than traditional oxides by leveraging the circular motion of high-gyromagnetic-ratio hydrogen ions within their flexible structures.
This paper introduces a hybrid machine learning-accelerated solid-state nudged elastic band (SSNEB) framework that integrates EquiformerV2 and eSEN models with DFT to achieve up to a 7-fold speedup in calculating minimum energy pathways for solid-state materials while maintaining accuracy comparable to first-principles calculations.