🔬 Category

cond-mat.mtrl-sci

4007 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

A flexible kinetic Monte Carlo framework for GaN molecular beam epitaxy with adaptive on-the-fly barrier evaluation

This paper presents a flexible, scalable lattice-based kinetic Monte Carlo framework for simulating GaN molecular beam epitaxy that integrates predefined activation-energy catalogs with adaptive, machine-learned on-the-fly barrier evaluations to accurately model complex growth phenomena such as island formation, Ostwald ripening, and temperature-driven island walking.

Sajid Ali, Norbert Krause, Carla Verdi2026-07-29
🔬 materials science

MANDALA: An E(3)-Equivariant Graph Neural Network Framework for Learning Electronic-Structure Operators with Observable Guidance

Mandala is a modular, E(3)-equivariant graph neural network framework that bridges the gap between machine learning and electronic structure calculations by learning block-sparse quantum operators to directly predict electronic observables like band structures and densities of states, thereby complementing traditional machine learning interatomic potentials.

Bartosz Brzoza, Wiktoria Szopa, Zakaria Elabid, Vincent Martinetto, Varadarajan Rengaraj, Mani Lokamani, Thomas D. Kühne (…)2026-07-29
🔬 materials science

First-Principles Origins of Charge Transport in Molecular Semiconductors

This paper introduces a parameter-free, first-principles framework based on nonperturbative Green-Kubo dynamics that accurately predicts charge transport in molecular semiconductors across diverse regimes, overturns the prevailing microscopic mechanism for DNTT by attributing transient localization to correlated on-site disorder, and identifies the phenacene family as a promising direction for high-mobility materials.

Tong Jiang, Joonho Lee2026-07-29
🔬 materials science

Identifying Contact Barrier Types in Few-Layer MoS2 Devices Using Correlative IV, LBIC, and Bias-Dependent KPFM

This paper presents an integrated experimental framework combining IV, LBIC, and bias-dependent KPFM to unambiguously identify and characterize Schottky versus tunnel contact barriers in few-layer MoS2 devices, demonstrating that while thermal annealing reduces total resistance, contact barriers remain the dominant limiting factor.

Ariane Ufer, Zeinab Eftekhari, Benjamin Mayer, Hendrik Lambers, Hubert J. Krenner, Rebecca Saive, Ursula Wurstbauer2026-07-29
🔬 mesoscale physics

Anisotropic domain wall velocity profiles in the creep regime: the interplay of chiral damping, stiffness and Dzyaloshinskii-Moriya interaction

This paper presents an extended angular creep model that incorporates dispersive domain wall stiffness and chiral damping to accurately describe the anisotropic expansion of magnetic bubble domains, thereby enhancing the quantitative extraction of Dzyaloshinskii-Moriya interaction and chiral dynamical effects.

Adriano Di Pietro, Alessandro Magni, Stefania Pizzini, Frowin Dörr, Yasser Shokr, Gianfranco Durin, Silvia Tacchi, Marco (…)2026-07-29
🔬 materials science

Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility

This paper presents a physics-guided interpretable machine learning framework that combines Brownian Cluster Dynamics simulations with SHAP analysis to quantitatively disentangle the individual and coupled effects of crowding, composition, and tunable bond flexibility on particle transport in crowded media, revealing bond flexibility as a distinct regulator of relaxation in heterogeneous colloidal networks.

Zakiya Shireen, Sujin B. Babu2026-07-29
🔬 materials science

Stacking Polarity-Controlled Interlayer Photocarrier Dynamics in MoSe2/MoS2 Heterostructures

This study demonstrates that stacking polarity serves as a global control parameter for interlayer photocarrier dynamics in MoSe2_2/MoS2_2 heterostructures, where engineering the interface termination in 3R stacking enables deterministic tuning of charge-transfer rates and interlayer exciton lifetimes by modulating interfacial wavefunction overlap.

Gbenga S. Agunbiade, Ting Zheng, Hui Zhao2026-07-29
🔬 materials science

Singular geometry and eigenframe topology in local rank-2 tensor observables

This paper reveals that while symmetric second-rank tensors like the electric-field-gradient appear smooth, their magnitude-ordered principal value representations conceal a global topological effect where continuous transport around degeneracies induces a binary orientation reversal of the eigenframe, a phenomenon demonstrated through strain-controlled first-principles calculations in rutile TiO2, SnO2, and cubic MgO.

I. C. J. Yap, B. Doerschel, S. Q. Jin, T. T. Dang, P. M. Scott, H. C. Hofsaess, D. C. Lupascu, A. Krawczuk, J. H. Schell2026-07-29