🔬 Category

cond-mat.mtrl-sci

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.

🔬 materials science

Pre-registered tests of solid-state-physics-inspired LLM compression: a cluster-level negative result at small-language-model scale

This pre-registered study employing autonomous research agents and a strict 3-sigma decision gate found that solid-state-physics-inspired compression mappings, including those based on Kohn-nearsightedness and tensor-train embeddings, failed to compress small-scale language models, instead revealing that their attention mechanisms exhibit critical or glassy behaviors rather than the predicted insulator-like properties.

Jun-qiang Lu2026-09-29
🔬 materials science

Electronic and topological properties of Ce-based honeycomb ferromagnet Ce2_2Zn6_6Ge3_3

This study establishes Ce2_2Zn6_6Ge3_3 as a rare Ce-based honeycomb ferromagnet with localized 4ff-electrons and nontrivial topological features, including Weyl points and a non-zero Berry phase, making it a unique platform for investigating the interplay between magnetism and topology.

Yanen Huang, Zihan Yang, Jiawen Zhang, Yuwei Zhou, Lubin Wang, Gang Li, Michael Smidman, Chao Cao, Yu Liu, Huiqiu Yuan2026-09-29
🔬 materials science

Magneto-optical Kerr spectroscopy of exciton Rydberg states in a magnetic van der Waals heterostructure

This study demonstrates that wavelength-resolved magneto-optical Kerr spectroscopy of a MoSe2_2/Fe3_3GaTe2_2 van der Waals heterostructure reveals proximity-induced magnetic symmetry breaking across both A- and B-exciton manifolds, specifically identifying enhanced resonances in the ground and 2s Rydberg states through combined experimental and theoretical analysis.

Astha Khandelwal, Benran Zhang, Madhusmita Jena, Zhenchao Wen, Kenji Watanabe, Takashi Taniguchi, Saroj P. Dash, Zhenglu (…)2026-09-29
🔬 materials science

High-Throughput Imaging of Degradation-Inducing Microscopic Impurities in Perovskite Solar Cells

This study establishes a practical, high-throughput diagnostic framework that combines nano-Fourier transform infrared spectroscopy with machine learning-enhanced optical imaging to rapidly identify and quantify microscopic impurities in perovskite solar cells, revealing these defects as critical nucleation sites for degradation and enabling early stability screening for scalable device fabrication.

Sofiia Kosar, Anil R. Pininti, Vladyslav Hnapovskyi, José P. Jurado, Subhashri Mannar, Lorenzo Mardegan, Anand S. Subbia (…)2026-09-29
🔬 materials science

Ultra-high vacuum Raman platform for in situ characterization of graphene nanoribbons

This paper presents a home-built ultra-high vacuum Raman suitcase (RVS) that enables the *in situ* characterization of air-sensitive, atomically precise graphene nanoribbons by preventing oxidation and allowing real-time monitoring of their growth kinetics, lattice dynamics, and edge-specific chemical reactivity under controlled thermal and gas environments.

Jeong Ha Hwang, Amogh Kinikar, Lukas Rotach, Andres Ortega-Guerrero, Carlo A. Pignedoli, Klaus Muellen, Thorsten G. Engl (…)2026-09-29
🔬 materials science

Density functional perturbation theory of meta-generalized gradient approximations using algorithmic differentiation

This paper presents an algorithmic differentiation-based implementation of density functional perturbation theory for meta-generalized gradient approximations, enabling efficient computation of arbitrary response properties and facilitating the gradient-based optimization of novel exchange-correlation functionals.

Bruno Ploumhans, Niklas Frederik Schmitz, Michael F. Herbst2026-09-29
🔬 materials science

Bounding Retraining Equivalence and the Deletion Floor in Materials Machine Unlearning

This paper addresses the ambiguity of post-deletion accuracy in materials machine learning by defining a "deletion floor" based on retraining equivalence, establishing theoretical bounds that link low deletion floors to retained data redundancy, and demonstrating empirically that request-level unlearning evaluations must jointly report reference loss, prediction change, and retained utility to distinguish between effective unlearning and mere data suppression.

Can Polat, Mustafa Kurban, Erchin Serpedin, Hasan Kurban2026-09-29
🔬 materials science

Catalogue of Collinear Magnetic Structures in Stoichiometric Materials

This paper presents a comprehensive computational catalogue of 365,639 symmetry-allowed collinear magnetic structures for over 72,000 stoichiometric materials by leveraging spin space groups and maximal subgroups, ultimately identifying thousands of new magnetic topological materials to guide experimental characterization and spintronics applications.

Liangliang Huang, Houhao Wang, Yuanze Song, Ruixi Pu, Xiangang Wan, Feng Tang2026-09-29