🔬 Category

cond-mat.mtrl-sci

3396 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.

Electronic structure and oxidation states in high-pressure synthesized isostructural CeCN5_5 and TbCN5_5

This study employs DFT+U and DFT+DMFT calculations to reveal that despite being isostructural high-pressure synthesized compounds, CeCN5_5 and TbCN5_5 exhibit distinct electronic properties—CeCN5_5 being an insulator with Ce in a 4+ oxidation state and TbCN5_5 being a metal with Tb in a 3+ oxidation state—demonstrating how the polymeric C-N network accommodates different lanthanide oxidation states and modulates electronic behavior.

Amanda Ehn, Florian Trybel, Talha Bin Masood, Leonid V. Pourovskii, Igor A. Abrikosov2026-04-22🔬 cond-mat.mtrl-sci

Atomic-scale origin of charge density wave-driven metal-semiconductor transition in an incommensurately modulated metal-organic framework

This study provides the first direct atomic-scale evidence linking an incommensurate charge density wave to a reversible metal-semiconductor transition in the conductive metal-organic framework Pr3HHTP2, revealing how guest water molecules stabilize the modulated structure to drive this electronic phase change.

Ling Zhang, Zeyue Zhang, Liu He, Bin Jiang, Yingchao Wang, Jiaxiang Zhang, Huimin Qi, Chao Zhang, Jinkun Guo, Hao Chen, Yunlong Fan, Yanran Shen, Hongli Jia, Guobao Li, Yu-Qing Zheng, Julius J. Oppenh (…)2026-04-22🔬 cond-mat.mtrl-sci

Structural, optical and magnetic properties of nanostructured Cr-substituted Ni-Zn spinel ferrites synthesized by a microwave combustion method

Nanoparticles of Cr-substituted Ni-Zn spinel ferrites synthesized via microwave combustion exhibit a single-phase spinel structure with Cr³⁺ ions preferentially occupying B-sites, resulting in decreased lattice parameters and band gap energy, enhanced saturation magnetization at low doping levels, and improved photocatalytic degradation of methyl orange dye.

Abdulaziz Abu El-Fadl, Azza M. Hassan, Mohamed A. Kassem2026-04-21🔬 cond-mat.mtrl-sci

A Versatile Post-Doping Towards Two-Dimensional Semiconductors

This paper presents a versatile post-doping method using low-kinetic energy dopant beams and high-flux chalcogen beams to achieve controlled, substitutional doping in 2D transition metal dichalcogenides, resulting in significant electronic property enhancements and position-selective patterning for next-generation electronics.

Y. Murai, S. Zhang, T. Hotta, Z. Liu, Y. Miyata, T. Irisawa, Y. Gao, M. Maruyama, S. Okada, H. Mogi, T. Sato, S. Yoshida, H. Shigekawa, Takashi Taniguchi, Kenji Watanabe, R. Kitaura2026-04-21🔬 cond-mat.mes-hall

Temperature-dependent thermodynamic properties of CrNbO4 and CrTaO4 by first-principles calculations

This study employs first-principles calculations to predict the temperature-dependent thermodynamic properties and thermal stability of rutile-type CrNbO4 and CrTaO4 oxides, demonstrating their potential to reduce chromium volatilization and thereby enhance the oxidation resistance of refractory high-entropy alloys.

Shuang Lin, Shun-Li Shang, Allison M. Beese, Zi-Kui Liu2026-04-21🔬 cond-mat.mtrl-sci

Machine Learning Based Prediction of Proton Conductivity in Metal-Organic Frameworks

This paper addresses the limited understanding and scarcity of proton-conductive metal-organic frameworks (MOFs) by constructing a comprehensive database and developing a high-performing transformer-based machine learning model that predicts proton conductivity with a mean absolute error of 0.91, thereby facilitating the targeted design of new solid-state electrolytes for fuel cells.

Seunghee Han, Byeong Gwan Lee, Dae Woon Lim, Jihan Kim2026-04-21🔬 physics.app-ph

The Key Steps and Distinct Performance Trends of Pyrrolic vs. Pyridinic M-N-C Catalysts in Electrocatalytic Nitrate Reduction

Through combined theoretical modeling and experimental validation, this study elucidates the distinct performance trends and rate-determining mechanisms of pyrrolic versus pyridinic M-N-C catalysts in electrochemical nitrate reduction, revealing that adsorption and protonation of nitrate govern the reaction while demonstrating the limitations of classical thermodynamic models in accurately predicting catalytic performance.

Qiuling Jiang, Mingyao Gu, Tianyi Wang, Fangzhou Liu, Xin Yang, Di Zhang, Zhijian Wu, Ying Wang, Li Wei, Hao Li2026-04-21🔬 cond-mat.mtrl-sci