cond-mat.mtrl-sci 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

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

🔬 materials science

Reinforcement Learning for Chemical Ordering in Alloy Nanoparticles

This paper presents a reinforcement learning agent utilizing geometric graph representations to efficiently optimize atomic ordering in bimetallic alloy nanoparticles, successfully identifying ground-state structures and demonstrating transferability across compositions and sizes, though with limitations in multi-element systems.

Jonas Elsborg, Emma L. Hovmand, Arghya Bhowmik2026-03-24

🔬 materials science

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

🔬 materials science

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 $ABO_3$ 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

🔬 materials science

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 (…)2026-03-24

🔬 applied physics

Active learning for photonic crystals

This paper demonstrates that integrating analytic approximate Bayesian last-layer neural networks with uncertainty-driven active learning significantly accelerates photonic band gap prediction by reducing the required training data by up to 2.6 times compared to random sampling, thereby enabling more efficient surrogate modeling and inverse design for photonic crystals.

Ryan Lopez, Charlotte Loh, Rumen Dangovski, Marin Soljačić2026-03-24

🔬 materials science

Stripe antiferromagnetism in van der Waals metal HoTe3 decoupled from charge density wave order

Neutron diffraction studies on single-crystal HoTe3 reveal two distinct antiferromagnetic phases with specific stripe motifs and stacking orders that are decoupled from the charge density wave order, suggesting that the alignment of propagation vectors and single-ion anisotropy are critical for spin-charge coupling in van der Waals systems.

Weiyi Yun, Ryota Nakano, Ryo Misawa, Rinsuke Yamada, Shun Akatsuka, Yoshichika Onuki, Priya Ranjan Baral, Hiraku Saitoh (…)2026-03-24

🔬 applied physics

Theoretical Ion Sputtering Yields from Loose Powders using a Multiscale Monte Carlo Approach

This paper presents a multiscale Monte Carlo model demonstrating that ion sputtering yields from loose powders differ significantly from flat surfaces, being dominated by backward-directed ejecta at non-zero incident angles and exhibiting a universal energy dependence for normal incidence.

Sebastien Verkercke, Deborah Berhanu, Caixia Bu, Benjamin Clouter-Gergen, Francois Leblanc, Jesse R. Lewis, Liam S. Morr (…)2026-03-24

🧬 biology

Broad presence of ferromagnetism in bees and relationship to phylogeny, natural history, and sociality

This study reveals that ferromagnetic-based magnetoreception is widespread across diverse bee species and non-bee outgroups without phylogenetic signal, while its strength correlates with increased body size and social behavior.

Laura Russo, Caleb Allen, Cameron S. Jorgensen, Lizabeth Quigley, C. Charlotte Buchanan, Michael Winklhofer, Seán G. Bra (…)2026-03-24

🔬 mesoscale physics

Competing skin effect and quasiperiodic localization in the non-Hermitian Su-Schrieffer-Heeger chain: Reentrant delocalization, spectral topology destruction, and entanglement suppression

This study reveals that in a non-Hermitian Su-Schrieffer-Heeger chain, the competition between the skin effect and Aubry-André-Harper quasiperiodic disorder generates a unique reentrant delocalization regime and distinct five-phase landscape, while simultaneously destroying point-gap topology and suppressing entanglement entropy.

Souvik Ghosh2026-03-24

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