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.

Ultra-long-living magnons in the quantum limit

This paper demonstrates that cooling single-crystal yttrium iron garnet spheres to 30 mK enables short-wavelength magnons to achieve lifetimes exceeding 18 μs, overturning previous limits and establishing them as viable, long-lived carriers for solid-state quantum information technologies.

Rostyslav O. Serha, Kaitlin H. McAllister, Fabian Majcen, Sebastian Knauer, Timmy Reimann, Carsten Dubs, Gennadii A. Melkov, Alexander A. Serga, Vasyl S. Tyberkevych, Andrii V. Chumak, Dmytro A. Bozhk (…)2026-05-12🔬 cond-mat.mtrl-sci

Opposite pressure effects on magnetic phase transitions in NiBr2

This study reveals that hydrostatic pressure exerts opposite effects on the magnetic phases of NiBr2 compared to NiI2, where pressure suppresses the helimagnetic order while steeply enhancing the collinear antiferromagnetic order due to the dominant role of interlayer exchange interactions.

Parvez Ahmed Qureshi, Krishna Kumar Pokhrel, Jiri Prchal, Subhasmita Ray, Sergiu Arapan, Karel Carva, Vladimir Sechovsky, Jiri Pospisil2026-05-12🔬 cond-mat.mtrl-sci

Signatures of three-state Potts nematicity in spin excitations of the van der Waals antiferromagnet FePSe3_3

Neutron scattering experiments on the van der Waals antiferromagnet FePSe3_3 under uniaxial strain reveal that tensile strain induces a transition to C2C_2 symmetry in both magnetic order and spin excitations, providing direct evidence that the observed three-state Potts nematicity in the paramagnetic phase arises from vestigial order associated with the low-temperature zigzag antiferromagnetic state.

Weiliang Yao, Viviane Peçanha Antonio, Devashibhai Adroja, S. J. Gomez Alvarado, Bin Gao, Sijie Xu, Ruixian Liu, Xingye Lu, Pengcheng Dai2026-05-12🔬 cond-mat.mes-hall

An improved reliability factor for quantitative low-energy electron diffraction

This paper introduces a modified reliability factor, RSR_\mathrm{S}, to replace Pendry's RPR_\mathrm{P} in quantitative low-energy electron diffraction, addressing its sensitivity to noise and intensity offsets while demonstrating superior or comparable performance in optimizing surface structure determination.

Alexander M. Imre, Lutz Hammer, Ulrike Diebold, Michele Riva, Michael Schmid2026-05-12🔬 cond-mat.mtrl-sci

Low-Field Ferroelectricity in 10 nm AlBScN Thin Films

This study demonstrates that incorporating boron into 10 nm aluminum scandium nitride (AlBScN) thin films enables robust ferroelectric switching with significantly reduced leakage currents and coercive fields, establishing AlBScN as a promising candidate for low-voltage, CMOS-compatible nonvolatile memory applications.

Xiaolei Tong, Pedram Yousefian, Ziyi Wang, Meenakshi A. Saravanan, Rajeev Kumar Rai, Giovanni Esteves, Eric A. Stach, Roy H. Olsson2026-05-12🔬 physics.app-ph

A probabilistic framework for crystal structure denoising, phase classification, and order parameters

This paper introduces a unified, differentiable probabilistic framework that simultaneously denoises atomic configurations, classifies crystal phases, and constructs order parameters by training on synthetic perturbations of known prototypes to robustly analyze complex atomistic simulations under diverse conditions.

Hyuna Kwon, Babak Sadigh, Sebastien Hamel, Vincenzo Lordi, John Klepeis, Fei Zhou2026-05-12🔬 cond-mat.mtrl-sci

Crystal Fractional Graph Neural Network for Energy Prediction of High-Entropy Alloys

This paper proposes a Crystal Fractional Graph Neural Network that combines local atomic environment analysis via graph attention mechanisms with global compositional data to accurately predict the energy of high-entropy alloys, achieving first-principles-level precision on a dataset of over 1,000 structures while acknowledging current limitations with large crystal cells.

Takanori Kotama, Yang Huang2026-05-12🔬 physics

Rashba engineering at van der Waals interfaces

This paper demonstrates that the interface between epitaxially grown transition metal dichalcogenide (TMD) monolayers can be engineered to control the intensity and sign of Rashba spin splitting, thereby enabling highly efficient and tunable THz spintronic emitters through enhanced spin-to-charge conversion.

Rahul Sharma, Soumya Mukherjee, Fatima Ibrahim, Gaétan Verdierre, Libor Vojáček, Martin Mičica, Sylvain Massabeau, Oliver Paull, Vincent Polewczyk, Nicola Marzari, Alain Marty, Isabelle Gomes de Morae (…)2026-05-12🔬 cond-mat.mes-hall