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RESEARCH PAPER · Digital Discovery · 2026

Accelerating catalytic advancements through the precision of high-throughput experiments & calculations

Jenny G. Vitillo, Alán Aspuru‐Guzik, Eric J. Doskocil, Omar K. Farha, Timur İslamoğlu, Heather J. Kulik, Peter M. Margl, Stuart Miller, Jordan C. T. Reddel, Aayush R. Singh, Varinia Bernales

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Accelerating catalytic advancements through the precision of high-throughput experiments & calculationsOriginalAccelerating Sustainable Energy Catalysis through Machine Learning: High-Throughput Screening and Machine Learning-Based Potential Energy Surface2Taking Care of Complexity: A Pragmatic View on Computational Modeling in Catalysis and Materials Science0Uncovering the source of uncertainty0A critical review of industry 5.0-enabled nano-catalysts for synergistic air, water, and soil pollution abatement toward environmental sustainability0

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  1. Accelerating Sustainable Energy Catalysis through Machine Learning: High-Throughput Screening and Machine Learning-Based Potential Energy Surface

    ACS Materials Letters · 2026-04-21

    Junjie Ni, Chen Liu, Chao Yu, Huinan Che, Bin Liu, Yanhui Ao

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  2. Taking Care of Complexity: A Pragmatic View on Computational Modeling in Catalysis and Materials Science

    Journal of Chemical Theory and Computation · 2026-06-17

    Giacomo Melani, Bernardino Tirri, GiovanniMaria Piccini

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  3. Uncovering the source of uncertainty

    Nature Catalysis · 2026-07-31

    Lichen Liu

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  4. A critical review of industry 5.0-enabled nano-catalysts for synergistic air, water, and soil pollution abatement toward environmental sustainability

    Discover Catalysis. · 2026-10-01

    Nima Alizadeh Raef, Siamak Pedrammehr, Fatemeh Hamedi

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