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.

Competing incommensurability, electronic correlations, and superconductivity in a hybrid transition metal dichalcogenide

Using scanning tunneling microscopy and advanced theoretical modeling, this study reveals that a bulk hybrid transition-metal dichalcogenide (4Hb-TaS $_2$ ) hosts an emergent incommensurate potential arising from lattice mismatch between alternating 1T and 1H layers, which modulates interlayer charge transfer to drive the system toward a doped Mott regime and competes with bulk superconductivity.

Jean C. Souza, Moshe Haim, Lorenzo Crippa, Hyeonhu Bae, Edanel Fishbein, Jonathan Ruhman, Binghai Yan, Amit Kanigel, Roser Valentí, Nurit Avraham, Haim Beidenkopf2026-05-22🔬 cond-mat.mtrl-sci

Upscaling DFT-trained machine-learning interatomic potential toward Quantum Monte Carlo accuracy: Sulfur-vacancy migration in monolayer MoS $_2$ as a testbed

This paper presents a multi-fidelity machine learning approach that fine-tunes a DFT-trained interatomic potential using limited quantum Monte Carlo energies to achieve near-QMC accuracy for simulating sulfur vacancy migration in monolayer MoS $_2$ , enabling large-scale, high-precision simulations that are computationally prohibitive with direct QMC methods.

Adam Hložný, Ján Brndiar, Ye Luo, Ivan Štich2026-05-22🔬 cond-mat.mtrl-sci

Topological cell-openness index for porous materials

This paper proposes a topological cell-openness index ( $\tau$ ) based on Betti numbers as a complementary or alternative metric to gas pycnometry for characterizing the open versus closed cell proportions in porous materials, while also demonstrating its correlation with physical quantities and its utility in estimating feature sizes.

Michał Bogdan, Paweł Dłotko2026-05-22🔬 cond-mat.mtrl-sci

Crystal Symmetry Selected Pure Spin Photocurrent in Altermagnetic Insulators

This paper demonstrates that crystal symmetry enables the generation of pure spin photocurrents in altermagnetic insulators independent of spin-orbit coupling, a phenomenon validated through first-principles calculations on materials like MnTe and BiFeO3.

Ruizhi Dong, Ranquan Cao, Dian Tan, Ruixiang Fei2026-05-21🔬 cond-mat.mes-hall

Limited Diffusion of Silicon in GaN: A DFT Study Supported by Experimental Evidence

This study combines first-principles DFT calculations with ultra-high-pressure annealing experiments to demonstrate that silicon diffusion in gallium nitride is extremely limited due to prohibitively high activation barriers, thereby confirming the material's stability for precise doping in advanced electronic applications.

Karol Kawka, Pawel Kempisty, Akira Kusaba, Krzysztof Golyga, Karol Pozyczka, Michal Fijalkowski, Michal Bockowski2026-05-21🔬 cond-mat.mtrl-sci

Machine-Learned Force Fields for Lattice Dynamics at Coupled-Cluster Level Accuracy

This study demonstrates that machine-learned force fields trained on coupled-cluster data, enhanced by delta-learning and charge-aware approaches to address long-range effects and data limitations, achieve superior accuracy in predicting phonon dispersions and anharmonic vibrational properties for diamond and lithium hydride compared to traditional density functional theory.

Sita Schönbauer, Johanna P. Carbone, Fredrik V. Eriksson, Florian Libisch, Andreas Grüneis2026-05-21🔬 cond-mat.mtrl-sci

A new skyrmion topological transition driven by higher-order exchange interactions in Janus MnSeTe

This study reveals a novel "ferric" topological transition in single-layer Janus MnSeTe driven by higher-order exchange interactions that specifically modify the Bloch point while leaving skyrmion stability largely governed by Dzyaloshinskii-Moriya interaction, establishing the material as a robust platform for 2D skyrmionics with exceptionally high energy barriers.

Megha Arya, Moritz A. Goerzen, Lionel Calmels, Rémi Arras, Soumyajyoti Haldar, Stefan Heinze, Dongzhe Li2026-05-21🔬 cond-mat.mes-hall

Trigonal Distortion Driven Ground States in VX3 (X = Br and I)

This study utilizes high-resolution resonant inelastic x-ray scattering (RIXS) combined with ligand field multiplet calculations to comprehensively determine the ground state electronic structures of VBr $_3$ and VI $_3$ , revealing distinct high-spin V $^{3+}$ configurations driven by opposing trigonal distortions and increased covalency from bromine to iodine.

Chamini S. Pathiraja, Deniz Wong, Christian Schulz, Yi-De Chuang, Yu-Cheng Shao, Byron Freelon2026-05-21🔬 cond-mat.mtrl-sci

Electrostatic Screening in Nanotubes: A Tubular Response Function Framework

This paper introduces a general "tubular response function" framework to evaluate electrostatic screening in nanotubes with arbitrary electronic properties, demonstrating that metallic carbon nanotubes screen ion interactions almost identically to ideal metals due to quantum confinement and suppressed Friedel oscillations.

Peter Gispert, Nikita Kavokine2026-05-21🔬 cond-mat.mes-hall

Modeling phase separation in polymer-derived carbonitride ceramics through extended machine learning molecular dynamics

This study employs a machine learning interatomic potential trained on over 9,000 configurations to simulate large-scale molecular dynamics of silicon carbonitride systems, revealing that thermal treatment drives phase separation where defective carbon rings mediate the nucleation of graphene-like sheets within the amorphous matrix, thereby explaining the material's unique hybrid properties.

Fabien Mortier, Sylvian Cadars, Olivier Masson, Mauro Boero, Guido Ori, Yun Wang, Samuel Bernard, Assil Bouzid2026-05-21🔬 cond-mat.mtrl-sci

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