4213 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 utilizes magneto-Raman scattering to reveal how magnetic field tuning and layer thickness modulate the complex magnetic phase diagram and spin-lattice coupling in two-dimensional chromium oxychloride (CrOCl), identifying commensurate magnetic orders and significant magneto-strictive effects down to the single-layer limit.
This paper introduces MAP-E, an autonomous, high-throughput robotic platform that automates parallel electrochemical experiments to generate reproducible, large-scale corrosion datasets and accelerate materials discovery through uncertainty-driven sampling strategies.
This study utilizes nano-spectroscopic X-ray magnetic circular dichroism to demonstrate that -FeO exhibits locally varying altermagnetic responses, including on-and-off switching across the Morin transition and finite signals within nanoscale domain walls and meron textures, thereby establishing a pathway for harnessing complex spin textures in earth-abundant altermagnets.
By utilizing a novel molecular beam epitaxy method to selectively stabilize metastable CrTe and CrTe monolayers, researchers demonstrate that controlling self-intercalation allows for the tunable switching between an antiferromagnetic metallic state and a ferromagnetic semiconducting state, establishing the Cr-Te system as a versatile platform for 2D spintronics.
This paper presents a unified classification of magnetic orders using oriented spin space groups, which distinguishes between ferromagnetism and antiferromagnetism based on net spin constraints and identifies a new phase called spin-orbit magnetism induced by spin-orbit coupling.
This study combines first-principles Density Functional Theory calculations with Reduced-Configuration-Space searches and Monte Carlo simulations to derive accurate exchange parameters for the HoAgGe twisted-Kagome spin ice, successfully resolving discrepancies in previous empirical models and providing a precise description of its complex field-dependent phase diagram.
This study demonstrates that in the van der Waals magnet Fe5GeTe2, strong electronic correlations drive the formation of a flat band at the Fermi level, which in turn induces a charge order, establishing a paradigm where interaction-driven flat bands promote large-scale electronic ordering.
This paper proposes an extended spin-phonon model that interpolates between bond- and site-phonon approaches to successfully reproduce the complex field-induced phase transitions and distinctive thermodynamic properties, such as negative thermal expansion and enhanced magnetocaloric effects, observed in the pyrochlore Heisenberg antiferromagnet.
This paper proposes CbLDM, a Condition-based Latent Diffusion Model that utilizes conditional priors and Laplacian matrices to effectively and stably recover the nanostructures of monometallic nanoparticles from their atomic pair distribution functions, addressing the highly ill-posed nature of the inverse problem.
This study presents an automated, cost-effective LLM-based agentic workflow that successfully extracts over 27,000 thermoelectric and structural property records from approximately 10,000 scientific articles, creating the largest LLM-curated dataset to date and establishing a scalable foundation for data-driven materials discovery.