🔬 Category

cond-mat.mtrl-sci

4940 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

Reaction-Network-Level Discovery of Ammonia Synthesis Catalysts via Ten-Million-Scale Generative Exploration

This paper presents a reaction-network-level discovery framework that leverages ten-million-scale generative exploration and machine learning potentials to identify 279 promising ammonia synthesis catalysts by mapping the complex compatibility of four critical intermediates, thereby uncovering both traditional motifs and novel material families like Fe-V and Al-Pd-Zr that conventional screening methods miss.

Ruili Li, Rui Qi, Shuoqi Zhang, Qingli Tang, Qingqing Mao, Ritankar Das, Beien Zhu, Yi Gao2026-06-23
🔬 materials science

Toward in-situ/operando X-ray absorption spectroscopy and electrochemical characterization of solid oxide fuel cells

This paper presents the development of specialized experimental instrumentation at the SIRIUS synchrotron facility to enable combined in-situ/operando X-ray absorption spectroscopy and electrochemical impedance spectroscopy studies of symmetric intermediate-temperature solid oxide fuel cells under varying atmospheres up to 800°C.

Renato A. N. de Oliveira, Rafael Galiza Yoshimura, Liliana Mogni, Maurico Arce, Diego G. Lamas, Lucia Toscani, Maria Bel (…)2026-06-23
🔬 applied physics

High Throughput Analysis of Nanobeam Electron Diffraction Datasets using Unsupervised Clustering

This paper demonstrates that unsupervised clustering algorithms can effectively automate the high-throughput analysis of nanobeam electron diffraction datasets by decomposing diffraction peak vectors to identify crystalline, amorphous, and minor components in both polycrystalline and single-crystal systems.

Ian MacLaren, Ala Al-Afeef, Trevor Almeida, Rantej Bali, Shriyar Tariq, Emily Wackan, Luke Daly, Joshua F. Einsle2026-06-23
🔬 materials science

Step-Edge Passivation and Quantitative Raman Mapping of Transfer Quality in Aligned Graphene Nanoribbons

This study investigates step-edge passivation of vicinal Au(788) by chevron-GNRs as a strategy to improve the transfer of aligned 9-armchair graphene nanoribbons and introduces an automated Raman mapping framework to quantitatively reveal that, despite locally altering growth configurations, the current approach fails to achieve reproducible, high-yield transfer of intact ribbons.

Dominik Lüthi, Rimah Darawish, Klaus Müllen, Roman Fasel, Gabriela Borin Barin2026-06-23
🔬 materials science

Atomic-scale theory of robust out-of-plane ferroelectricity in ultrathin films

This paper develops an atomic-scale theoretical framework explaining how robust out-of-plane ferroelectricity persists in ultrathin HfO2_2- and bismuth-based films through "self-polarizing" and "switchable role of the termination layer" effects driven by characteristic structures and electrode interactions, thereby guiding the design of next-generation nanoelectronic devices.

Fengbo Yuan, Yujia Teng, Karin M. Rabe, Yubo Qi2026-06-23
🔬 materials science

INCARBench: A Benchmark for Scientific Configuration in VASP INCAR by Large Language Models

This paper introduces INCARBench, a benchmark for evaluating large language models on generating and repairing scientific configurations for VASP simulations, revealing that while frontier models achieve high semantic accuracy, they still struggle with the task-critical correctness required for physically valid settings in complex materials science scenarios.

Bin Shao, Jixiang Li, Xinyue Zhang, Baishun Yang, Zhiyang Liu, Weichao Wang2026-06-23
🔬 applied physics

Data analysis methods for powder x-ray diffraction intensity under laser-driven dynamic compression at Omega and NIF laser facilities

This paper presents advanced data analysis methods to improve the fidelity of powder x-ray diffraction intensity measurements under laser-driven dynamic compression at the Omega and NIF facilities, utilizing in-situ references and accounting for thermal damping to accurately characterize materials like diamond near 1 TPa.

Marius Millot, Federica Coppari, Amy Lazicki, Jon H. Eggert2026-06-23
🔬 materials science

Overcoming Labelled Data Scarcity for Defect Classification in Scanning Tunneling Microscopy

This paper proposes an automated, flexible approach for segmenting Scanning Tunneling Microscopy (STM) images that combines few-shot and unsupervised learning to overcome labelled data scarcity, enabling high-accuracy defect classification on diverse surfaces with minimal manual annotation.

Nikola L. Kolev, Max Trouton, Filippo Federici Canova, Geoff Thornton, David Z. Gao, Neil J. Curson, Taylor J. Z. Stock2026-06-19
🔬 materials science

Evaluating Universal Machine Learning Force Fields Against Experimental Measurements

This paper introduces UniFFBench, a comprehensive evaluation framework featuring the MinX dataset of over 1,500 mineral systems with experimental references, to reveal a significant "reality gap" where state-of-the-art universal machine learning force fields, despite strong computational benchmark performance, fail to achieve the accuracy required for practical applications when tested against real-world experimental conditions.

Sajid Mannan, Vaibhav Bihani, Carmelo Gonzales, Kin Long Kelvin Lee, Nitya Nand Gosvami, Sayan Ranu, Santiago Miret, N M (…)2026-06-19