cond-mat.mtrl-sci · 2026-07-28 · No. 67

Materials Science, 2026-07-28.

2 new papers in cond-mat.mtrl-sci. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Catalyst Diffusion Transformer: Generative Inverse Design of Heterogeneous Catalysts

    Hayoung Doo, Dong Hyeon Mok, Seoin Back, Jonggeol Na

    cond-mat.mtrl-sci · cs.LG

    The vast chemical design space and complex, interdependent design variables make catalyst discovery for targeted properties highly labor- and resource-intensive. Although generative models have emerged as a promising solution, existing approaches are generally limited to single-property conditioning or narrow chemical spaces. Here, we present Catalyst Diffusion Transformer (CatDiT), a unified framework for inverse catalyst design that...

    arxiv.org/abs/2607.24272 · PDF

  2. 02

    Harnessing X-ray Absorption Spectroscopy Data through Multimodal Mining of Battery Literature

    Tanjin He, Aikaterini Vriza, Logan Ward, Xu Huang, Yiming Chen, Anubhav Jain, Gerbrand Ceder, Rajeev S. Assary, Ian...

    cond-mat.mtrl-sci · cs.AI · cs.CL · cs.DL · cs.IR

    X-ray absorption spectroscopy (XAS) is central to understanding the local electronic and atomic structure of materials, yet most published spectra remain inaccessible to data-driven analysis because they are embedded in figures and described through fragmented textual context in the literature. Here, we use multimodal (image and text) literature mining to transform this dispersed knowledge into an AI-ready experimental data resource. We...

    arxiv.org/abs/2607.23886 · PDF

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