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New AI Model CatRetriever Links Catalyst Surfaces to Bulk Structures

By PulseAugur Editorial · [2 sources] ·

Researchers have developed CatRetriever, a novel contrastive representation learning model designed to bridge the gap between catalyst surface structures and their corresponding bulk materials. This model aligns slab and bulk crystal representations in a shared latent space, enabling accurate retrieval of plausible parent bulk candidates from slab queries. The framework has been extended into a pipeline for discovering bulk catalysts optimized for specific adsorption energies, considering both structural compatibility and target adsorption ranges. AI

IMPACT Enhances AI-driven materials discovery by enabling the connection of surface-level catalyst designs to bulk properties.

RANK_REASON The cluster contains a research paper detailing a new AI model for catalyst discovery.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New AI Model CatRetriever Links Catalyst Surfaces to Bulk Structures

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The cluster contains a research paper detailing a new AI model for catalyst discovery.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Jungho Oh, Woosung Kim, Dong Hyeon Mok, Jonggeol Na, Seoin Back ·

    CatRetriever: Contrastive Representation Learning for Slab-to-Bulk Retrieval in Generative Catalyst Discovery

    arXiv:2607.11712v1 Announce Type: new Abstract: Inverse design is an emerging data-driven paradigm for efficiently navigating vast chemical spaces to discover new materials with targeted properties, and in the context of heterogeneous catalysis, surface generative models have rec…

  2. arXiv cs.LG TIER_1 English(EN) · Seoin Back ·

    CatRetriever: Contrastive Representation Learning for Slab-to-Bulk Retrieval in Generative Catalyst Discovery

    Inverse design is an emerging data-driven paradigm for efficiently navigating vast chemical spaces to discover new materials with targeted properties, and in the context of heterogeneous catalysis, surface generative models have recently advanced this goal by directly generating …

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