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<p>The rationalization of catalytic processes relies on the fundamental understanding of competing reaction mechanisms driving reactants to products. The list of elementary steps composing the reaction networks is proposed based on chemical intuition and evaluated via density functional theory. This approach is limited by the size of the network and disregards alternative paths. Here we present the Catalytic Automated Reaction Evaluator (CARE), a flexible end-to-end framework for heterogeneous catalysis composed of (1) a rule-based reaction network generator, (2) a thermodynamic and kinetic parameter evaluator powered by state-of-the-art machine learning models and (3) a fast microkinetic solver. CARE reproduces the experimental activity trends in methanol decomposition, identifies the selectivity to C<sub>3</sub> products in CO<sub>2</sub> electroreduction and generates the Fischer–Tropsch synthesis mechanism including 370,000 reactions reaching C<sub>6</sub> products. This comprehensive framework enables the exploration of thermal and electrocatalytic reactions previously not amenable to atomistic simulations.</p><p></p>

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An end-to-end framework for reactivity in heterogeneous catalysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月19日

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  • Santiago Morandi,
  • Oliver Loveday,
  • Tim Renningholtz,
  • Sergio Pablo-García,
  • Rodrigo A. Vargas-Hernández,
  • Ranga Rohit Seemakurthi,
  • Pol Sanz Berman,
  • Rodrigo García-Muelas,
  • Alán Aspuru-Guzik,
  • Núria López

摘要

The rationalization of catalytic processes relies on the fundamental understanding of competing reaction mechanisms driving reactants to products. The list of elementary steps composing the reaction networks is proposed based on chemical intuition and evaluated via density functional theory. This approach is limited by the size of the network and disregards alternative paths. Here we present the Catalytic Automated Reaction Evaluator (CARE), a flexible end-to-end framework for heterogeneous catalysis composed of (1) a rule-based reaction network generator, (2) a thermodynamic and kinetic parameter evaluator powered by state-of-the-art machine learning models and (3) a fast microkinetic solver. CARE reproduces the experimental activity trends in methanol decomposition, identifies the selectivity to C3 products in CO2 electroreduction and generates the Fischer–Tropsch synthesis mechanism including 370,000 reactions reaching C6 products. This comprehensive framework enables the exploration of thermal and electrocatalytic reactions previously not amenable to atomistic simulations.