🔬 Category

cond-mat.mtrl-sci

4119 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

Short time-to-solution Quantum Monte Carlo for catalysed hydrogen synthesis. Tools give CO hydrolysis activation barriers to 1kJ/mol on Pt(111)

This paper demonstrates that a short time-to-solution Quantum Monte Carlo methodology, utilizing an embedded active site approach on a Pt(111) surface, accurately calculates CO hydrolysis activation barriers for hydrogen synthesis with a precision of approximately 1 kJ/mol, closely matching high-level configuration interaction benchmarks.

Ali Bagci, Philip E Hoggan2026-05-12
🔬 mesoscale physics

Super Moiré Domain Tessellations, Sliding Ferroelectricity, and Reconfigurable Quantum Dot Arrays in Twisted Trilayer Hexagonal Boron Nitride

This paper demonstrates that twisted trilayer hexagonal boron nitride exhibits unique super Moiré domain tessellations and sliding ferroelectricity, enabling electric-field reconfigurable arrays of localized quantum dots that facilitate tunable long-range quantum state transfer for quantum technologies.

Kunihiro Yananose, Changwon Park, Young-Woo Son2026-05-12
🔬 materials science

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 (…)2026-05-12
🔬 mesoscale physics

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 (…)2026-05-12
🔬 materials science

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
🔬 applied physics

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, Ro (…)2026-05-12
🔬 materials science

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
🔬 physics

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