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.

β\beta-Ga2_2O3_3(001) surface reconstructions from first principles and experiment

This study combines first-principles calculations and experimental imaging to identify a stable, previously unreported 1×\times2 surface reconstruction on β\beta-Ga2_2O3_3(001) composed of paired GaO4_4 tetrahedra, while also revealing cooperative indium incorporation effects that offer new insights for controlling epitaxial growth.

Konstantin Lion, Piero Mazzolini, Kingsley Egbo, Toni Markurt, Oliver Bierwagen, Martin Albrecht, Claudia Draxl2026-03-24🔬 cond-mat.mtrl-sci

Tailoring dispersion and evanescent modes in multimodal nonlocal lattices using positive-only interactions

This paper presents a general interpolation-based framework for tailoring dispersion relations and evanescent modes in multimodal nonlocal lattices by enforcing prescribed frequency-wavenumber constraints, enabling the design of complex wave behaviors like rotons and controlled band-gap localization while ensuring physically consistent, positive-only stiffness parameters.

Lucas Rouhi, Christophe Droz2026-03-24🔬 cond-mat.mtrl-sci

Scaling Kinetic Monte-Carlo Simulations of Grain Growth with Combined Convolutional and Graph Neural Networks

This paper proposes a hybrid architecture combining a CNN-based bijective autoencoder with a graph neural network to compress spatial dimensions and evolve grain growth in latent space, achieving significantly improved scalability, reduced computational costs, and enhanced long-term accuracy compared to GNN-only baselines for simulating realistic material microstructures.

Zhihui Tian, Ethan Suwandi, Tomas Oppelstrup, Vasily V. Bulatov, Joel B. Harley, Fei Zhou2026-03-24🔬 cond-mat.mtrl-sci

Extreme disorder in crystalline perovskite oxide: a new paradigm in quantum materials research

This review examines the emerging paradigm of high-entropy perovskite oxides, highlighting how embedding extreme chemical disorder into the ABO3ABO_3 framework enables the discovery of novel electronic and magnetic phenomena through advances in synthesis, characterization, and theoretical understanding.

Srimanta Middey, Nandana Bhattacharya, Rukma Nevgi, Suresh Chandra Joshi, Subha Dey2026-03-24🔬 cond-mat.mtrl-sci

ZnO/ZnS heterostructures as hole reservoir to boost Ni foam energy storage performance

This study demonstrates that hydrothermally grown ZnO/ZnS heterostructures on nickel foam significantly enhance energy storage performance through a predominant pseudocapacitive mechanism, where the ZnS component acts as a crucial hole reservoir to boost charge storage capabilities.

Alessia Fischetti, Giacometta Mineo, Daniela Russo, Francesco Salutari, Claudio Lentini Campallegio, Elena Bruno, Jordi Arbiol, Giorgia Franzò, Salvatore Mirabella, Vincenzina Strano, M. Chiara Spadar (…)2026-03-24🔬 cond-mat.mtrl-sci