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.

Generalized deformation potential and machine-learning approaches for electron-phonon coupling and thermoelectric transport in semiconductors

This paper introduces two computationally efficient methods—a generalized acoustic deformation potential model and a machine-learning interpolation technique—that utilize a small number of first-principles electron-phonon matrix elements to accurately predict thermoelectric transport properties in semiconductors, with the machine-learning approach demonstrating superior accuracy and ease of implementation.

Ransell D'Souza, Ivana Savic2026-06-18🔬 cond-mat.mes-hall

Controllable Growth and Characterization of α- and β-phase MnSe by Chemical Vapor Deposition

This study demonstrates the controllable synthesis of phase-pure $\alpha$ - and $\beta$ -phase MnSe nanostructures via chemical vapor deposition, characterizing their structural, optical, and magnetic properties to establish MnSe as a tunable platform for 2D spintronic and optoelectronic applications.

Jennifer E. DeMell, Elias Kallon, Michael Pedowitz, Jimmy C. Kostakidis, Ihteyaz Aqaeed Avash, Kevin M. Daniels2026-06-18🔬 physics.app-ph

Spin point group symmetry and classification of non-relativistic spin splitting in non-collinear magnetic structures: Identification of high-order spin splitting types (l=5,7, and 9)

This paper establishes a comprehensive classification of non-relativistic spin splitting in coplanar and non-coplanar magnetic structures by tabulating 1,249 spin point groups and identifying previously overlooked high-order splitting types (l=5, 7, and 9), exemplified by the material LaMnAu5.

Luis Elcoro, Jesus Etxebarria, J. Manuel Perez-Mato, Emre S. Tasci2026-06-18🔬 cond-mat.mtrl-sci

Micromagnetic simulations for magnetic multipoles

This paper introduces a comprehensive micromagnetic framework for analyzing vector-like cluster magnetic multipoles, which is demonstrated through simulations of magnetic-octupole domain-wall dynamics in $\text{Mn}_3\text{Sn}$ to reveal key features like profile deformation and effective inertial mass, thereby providing a unified approach for investigating mesoscopic dynamics in advanced functional magnetic materials.

Myoung-Woo Yoo, Roland Winkler, Axel Hoffmann2026-06-17🔬 cond-mat.mes-hall

Extracting intrinsic superconducting properties in intercalated layered superconductors using an extended 2D Tinkham model

This study resolves the misclassification of certain intercalated layered superconductors as anisotropic 3D systems by developing an extended 2D Tinkham model that accounts for interlayer misalignment, thereby enabling the accurate extraction of intrinsic bulk 2D superconducting properties and BKT transitions in materials like (Li,Fe)OHFeSe and (CTA)0.5SnSe2.

Yue Liu, Yuhang Zhang, Zouyouwei Lu, Dong Li, Yuki M. Itahashi, Zhanyi Zhao, Jiali Liu, Jihu Lu, Feng Wu, Kui Jin, Hua Zhang, Ziyi Liu, Xiaoli Dong, Zhongxian Zhao2026-06-17🔬 cond-mat.mtrl-sci

Optical spin pumping in silicon

This study demonstrates an all-optical spin pumping method in a Ge-on-Si heterostructure that overcomes silicon's inherent limitations to achieve a record-high 9% spin polarization degree, thereby enabling the optical exploitation of silicon's spin-dependent properties for quantum and spintronic applications.

Stefano Achilli, Damiano Marian, Mario Lodari, Emiliano Bonera, Giordano Scappucci, Jacopo Pedrini, Michele Virgilio, Fabio Pezzoli2026-06-17🔬 cond-mat.mes-hall

Laser-Induced Topological Toggle Switching at Room Temperature in the van der Waals Ferromagnet Fe3GaTe2

This study demonstrates room-temperature, laser-controlled toggle switching between skyrmion/bubble and labyrinth topological spin textures in the van der Waals ferromagnet Fe3GaTe2 via thermal cycling, highlighting its potential for non-volatile memory applications.

Charlie W. F. Freeman, Woohyun Cho, Paul S. Keatley, PeiYu Cai, Elton J. G. Santos, Robert J. Hicken, H. Yang, Hidekazu Kurebayashi, Murat Cubukcu, Maciej Dabrowski2026-06-17🔬 cond-mat.mtrl-sci

Time-resolved observation of magnon splitting into vortex gyration and Floquet spin waves

This study utilizes time-resolved microwave measurements to demonstrate that the scattering of first-order azimuthal spin waves into vortex gyration and Floquet spin waves occurs via a three-wave splitting mechanism, characterized by a synchronous emergence of these modes after a power-dependent incubation delay that diverges at the scattering threshold.

T. Devolder, R. Lopes Seeger, C. Heins, A. Jenkins, L. C. Benetti, A. Schulman, R. Ferreira, G. Philippe, C. Chappert, H. Schultheiss, K. Schultheiss, J. -V. Kim2026-06-17🔬 cond-mat.mtrl-sci

Score-based diffusion models for accurate crystal-structure inpainting and reconstruction of hydrogen positions

This paper presents a score-based diffusion model that combines materials science and computer vision techniques to accurately and efficiently reconstruct missing hydrogen atom positions in crystal structures, achieving a success rate exceeding 97% compared to traditional DFT or unconditioned approaches.

Timo Reents, Arianna Cantarella, Marnik Bercx, Pietro Bonfà, Giovanni Pizzi2026-06-17🔬 cond-mat.mtrl-sci

Impulsive Hydrodynamic Exfoliation into Monolayer Graphene and Nanofragments by Transonic Flow Focusing

This paper demonstrates that Transonic Flow Focusing (TFF) is a purely mechanical, surfactant-free method capable of efficiently exfoliating graphene nanoplatelets into high-purity monolayer graphene and nanofragments by leveraging extreme shear and elongational stresses in a contact-free zone.

A. Ponce-Torres, A. Rubio-González, J. M. Montanero, M. A. Herrada, F. J. Galindo-Rosales2026-06-17🔬 physics

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