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

Suppression of ferromagnetism in van der Waals insulator due to pressure-induced layer stacking variation

This study demonstrates that applying pressure to the van der Waals insulator CrBr3 induces a structural transition from a rhombohedral to an AA-stacked trigonal phase, which directly causes the suppression of ferromagnetism due to the emergence of antiferromagnetically coupled chromium moments.

M. Misek, U. Dutta, P. Kral, D. Hovancik, J. Kastil, K. Pokhrel, S. Ray, J. Valenta, J. Prchal, J. Kamarad, F. Borodavka (…)2026-07-08
🔬 mesoscale physics

Spontaneous Breaking of the SU(3) Flavor Symmetry in a Quantum Hall Valley Nematic

This paper reports experimental evidence of a quantum Hall valley nematic phase in Pb1-xSnxSe quantum wells, demonstrating both spontaneous and explicit SU(3) flavor symmetry breaking that offers fundamental insights into many-body physics within an SU(3) system.

G. Krizman, A. Kazakov, C. -W. Cho, V. V. Volobuev, A. Majou, E. Ben Achour, T. Wojtowicz, G. Bauer, Y. Guldner, B. A. P (…)2026-07-08
🔬 materials science

VASP Agent: An Agentic Framework for Autonomous First-principles Calculations

This paper introduces VASP Agent, a coding-agent framework that integrates domain skills, deterministic tools, and scientific guardrails to autonomously execute complex, multi-step first-principles VASP calculations with superior parameter accuracy and error recovery compared to existing LLM-based workflows.

Zeyu Xia, Jinzhe Ma, Congjie Zheng, Zhongyao Wang, Shufei Zhang, Yuqiang Li, Hang Su, P. Hu, Changshui Zhang, Xingao Gon (…)2026-07-08
🔬 materials science

High-Temperature Deformation Behavior of Co-Free Non-Equiatomic CrMnFeNi Alloy

This study investigates the high-temperature deformation behavior of a Co-free non-equiatomic CrMnFeNi alloy through combined experimental and computational methods, revealing that the absence of Cobalt enhances high-temperature strength while maintaining a stable FCC phase and balanced stacking fault energies to promote strain hardening and ductility.

F. J. Dominguez-Gutierrez, M. Frelek-Kozak, G. Markovic, M. A. Strozyk, A. Daramola, M. Traversier, A. Fraczkiewicz, A. (…)2026-07-08
🔬 materials science

Charge disproportionation as a possible mechanism towards polar antiferromagnetic metal in molecular orbital crystal

This paper proposes that charge disproportionation driven by Hund's physics in the negative charge transfer gap regime of the molecular orbital crystal Sr3_3Co2_2O7_7 enables the coexistence of metallicity, polarity, and antiferromagnetism, offering a unified framework for understanding polar antiferromagnetic metals in double-layer Ruddlesden-Popper perovskite oxides.

Yang Shen, Shuai Qu, Gang Li, Pu Yu, Guang-Ming Zhang2026-07-08
🔬 mesoscale physics

Generalized deformation potential and machine-learning approaches for electron-phonon coupling and thermoelectric transport in semiconductors

This paper introduces two computationally efficient methods, a generalized deformation potential model and a machine-learning interpolation approach, to accurately predict electron-phonon coupling and thermoelectric transport properties in semiconductors using a minimal number of first-principles calculations, with the machine-learning method demonstrating superior accuracy and ease of implementation.

Ransell D'Souza, Ivana Savic2026-07-08
🤖 machine learning

EquiFiLM: Charge-Conditioned Equivariant Force Fields via Feature-wise Linear Modulation

The paper introduces EquiFiLM, a lightweight, E(3)-equivariant extension that enables foundation machine learning force fields to accurately model charge-conditioned potential energy surfaces and driven processes with minimal training data by integrating Feature-wise Linear Modulation blocks.

Samuel Sahel-Schackis, Ken-ichi Nomura, Aiichiro Nakano, Matthias F. Kling, Thomas Linker2026-07-08
🔬 materials science

Raman spectroscopy of the van der Waals altermagnet Co1/4_{1/4}NbSe2_2

This study utilizes polarization-resolved Raman spectroscopy and density-functional theory to demonstrate that cobalt intercalation in Co1/4_{1/4}NbSe2_2 reconstructs the vibrational spectrum through zone folding without contributing Raman-active modes, while revealing spin-phonon coupling in A1g_{1g} modes despite the absence of discontinuities at the altermagnetic transition.

Dushyanthini Balasundaram, Bishal Thapa, Resham Regmi, Nirmal J. Ghimire, Igor I. Mazin, Patrick M. Vora2026-07-08