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

Ghost-RISB for Correlated Electron-Phonon Systems: Application to the Hubbard-Holstein Model

This paper introduces an extended ghost-rotationally-invariant slave-boson (ghost-RISB) method that efficiently and accurately treats correlated electron-phonon systems by incorporating local phonon modes and dynamical self-energy effects, achieving DMFT-level accuracy at a fraction of the computational cost and revealing a Franck-Condon-like suppression of superconductivity in the strong-coupling bipolaronic regime.

Samuele Giuli, Ricardo J. Campos-Lopes, Emin Moghadas, Massimo Capone2026-08-06
🔬 materials science

CheMLFlow: An Open-Source Platform for Cheminformatics and Materials Informatics Applications

CheMLFlow is an open-source platform designed to streamline and automate end-to-end cheminformatics and materials informatics workflows by providing modular, reproducible, and agent-compatible components that address the common bottleneck of assembling complex scientific machine learning pipelines.

Brendan Smith, Susana Lopez-Moreno, Eric Dolores-Cuenca, Sangil Kim, Jose L. Mendoza-Cortes, Nijamudheen Abdulrahiman2026-08-06
🔬 materials science

Delocalized Coupled-Cluster Theory for Polaron Structure and Dynamics

This paper introduces delocalized coupled-cluster (dCC) theory, a translationally invariant variational framework that accurately and efficiently simulates polaron ground states and finite-temperature dynamics across model systems and real materials without phonon-number cutoffs, achieving results comparable to state-of-the-art benchmarks at a significantly lower computational cost.

Hamlin Wu, Moritz K. A. Baumgarten, Tong Jiang, Joonho Lee2026-08-06
🔬 materials science

X-ray Thermal diffuse scattering from real-space displacement correlations

This paper introduces an exact, harmonic-approximation method for calculating X-ray thermal diffuse scattering using the 3D-difference pair distribution function, which accurately reproduces experimental silicon data with minimal refinement and treats thermal and static disorder on equal footing.

Benjamin Fahl, Jonathan Bulled, Artem Korshunov, Dmitry Chernyshov, Yevheniia Kholina, Arkadiy Simonov2026-08-06
🔬 materials science

Direct Evidence for Robust Bulk Band Gap Across the Charge Density Wave Transition in TiSe2

Using high-resolution angle-resolved photoemission spectroscopy, this study demonstrates that the charge density wave transition in TiSe2 does not involve the opening of a bulk band gap, but rather a lattice-driven reconstruction that folds the electronic structure of a pre-existing band insulator.

Turgut Yilmaz, Anil Rajapitamahuni, Muhammad Awais Fiaz, Zhenxian Liu, Jerzy T. Sadowski, Abdullah Al-Mahboob, Asish K. (…)2026-08-06
🔬 materials science

Physics-Informed and Knowledge-Driven Generative AI for Autonomous Discovery of Porous Oxide Energy Materials: Opportunities and Challenges

This paper proposes a comprehensive roadmap for advancing generative AI in the autonomous discovery of porous oxide energy materials by introducing a seven-tier physics-informed inverse-design framework and an autonomous knowledge-generation system to overcome current limitations in application-awareness and data scarcity.

Dibakar Datta2026-08-05