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

Ultrafast Terahertz Photoconductivity and Near-Field Imaging of Nanoscale Inhomogeneities in Multilayer Epitaxial Graphene Nanoribbons

This study investigates the broadband terahertz conductivity and ultrafast photoconductivity of multilayer epitaxial graphene nanoribbons, revealing that near-field imaging detects nanoscale inhomogeneities while far-field spectroscopy distinguishes doped substrate layers from quasi-neutral layers that exhibit high mobility and strong positive photoconductivity driven by carrier temperature-dependent scattering mechanisms.

Arvind Singh, Jan Kunc, Tinkara Troha, Hynek Němec, Petr Kužel2026-03-02
🔬 materials science

Implementation and application of a DFT+U+U+V+V approach within the all-electron FLAPW method

This paper presents a first-principles implementation of the DFT+U+U+V+V formalism within the all-electron FLAPW method using the FLEUR code, demonstrating improved accuracy for diverse materials ranging from covalent semiconductors to charge-transfer insulators by incorporating intersite Coulomb interactions derived via the constrained random-phase approximation.

Wejdan Beida, Gustav Bihlmayer, Christoph Friedrich, Gregor Michalicek, Daniel Wortmann, Stefan Blügel2026-03-02
🔬 materials science

Buried Stressor Engineering for Position-Controlled InGaAs Quantum Dots with Local Density Variation for Integrated Quantum Photonics

This paper demonstrates a monolithic, two-step epitaxial growth method using buried stressors to fabricate precisely positioned, site-controlled InGaAs quantum dots with tunable local densities, enabling the integration of single-photon sources and microlasers on a single photonic chip for advanced quantum technologies.

Martin Podhorský, Maximilian Klonz, Lux Böhmer, Sebastian Kulig, Chirag C. Palekar, Petr Klenovský, Sven Rodt, Stephan R (…)2026-03-02
🔬 materials science

Exploring the extremes: atomic basis for multi-elemental materials science under complex thermodynamic conditions

This paper introduces a chemistry-agnostic, information-entropy-maximization protocol for generating training data that overcomes the limitations of current machine-learning interatomic potentials in complex, multi-elemental systems, thereby enabling robust and unbiased simulation of materials under extreme thermodynamic conditions.

Anton Bochkarev, Yury Lysogorskiy, Aparna Subramanyam, Ralf Drautz, Danny Perez2026-03-02
🔬 materials science

Defect-Engineered h-BN as a Platform for Single-Atom HER Catalysts: Descriptor Screening Refined by Electrochemical Stability Analysis

This study utilizes a multi-step computational framework combining DFT-based descriptor screening with electrochemical stability analysis to identify Pd anchored at boron vacancies in defect-engineered h-BN as a robust, pH-tolerant single-atom catalyst for the hydrogen evolution reaction, while highlighting the necessity of stability filtering to eliminate initially promising but unstable candidates like Cu at nitrogen vacancies.

Ana S. Dobrota, Natalia V. Skorodumova, Igor A. Pašti2026-03-02
🔬 materials science

Performance of universal machine learning potentials in global optimization

This paper systematically benchmarks the latest generation of universal machine learning potentials in unconstrained global optimization tasks, revealing a wide performance spectrum from near ab initio accuracy to non-predictive results while demonstrating that several models can successfully capture subtle electronic structure features to identify complex crystal ground states.

Edan T. Marcial, Laxman Chaudhary, Olesya Gorbunova, Aleksey N. Kolmogorov2026-03-02
🔬 materials science

Photoluminescence Line Shapes of Nanocrystals: Contributions from First- and Second-Order Vibronic Couplings

This paper presents a parameter-free microscopic approach that successfully reproduces experimental photoluminescence spectra of CdSe/CdS nanocrystals by demonstrating that second-order diagonal vibronic couplings are the dominant source of homogeneous linewidth broadening at temperatures above 100–150 K, while off-diagonal couplings play a negligible role until near room temperature.

Kaiyue Peng, Bokang Hou, Kailai Lin, Caroline Chen, Hendrik Utzat, Eran Rabani2026-03-02
🔬 materials science

High sub-bandgap response and fast switching enabled by thermal quenching in carbon-doped semi-insulating GaN

This study demonstrates that semi-insulating carbon-doped GaN exhibits high sub-bandgap photoconductivity with an ON/OFF ratio exceeding 10^7, where thermal quenching above a crossover temperature accelerates photocurrent decay by a factor of five to enable fast optical switching via a thermally activated recombination mechanism likely involving carbon-hydrogen defect complexes.

Jiahao Dong, Sanam SaeidNahaei, Austin Fehr, Auditee Majumder Momo, Pramod Reddy, Ronny Kirste, Zlatko Sitar, Ramón Coll (…)2026-03-02