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Catalysts informatics: paradigm shift towards data-driven catalyst design.

Keisuke TakahashiJunya OhyamaShun NishimuraJun FujimaLauren TakahashiTakeaki UnoToshiaki Taniike
Published in: Chemical communications (Cambridge, England) (2023)
Designing catalysts is a challenging matter as catalysts are involved with various factors that impact synthesis, catalysts, reactor and reaction. In order to overcome these difficulties, catalysts informatics is proposed as an alternative way to design and understand catalysts. The underlying concept of catalysts informatics is to design the catalysts from trends and patterns found in catalysts data. Here, three key concepts are introduced: experimental catalysts database, knowledge extraction from catalyst data via data science, and a catalysts informatics platform. Methane oxidation is chosen as a prototype reaction for demonstrating various aspects of catalysts informatics. This work summarizes how catalysts informatics plays a role in catalyst design. The work covers big data generation via high throughput experiments, machine learning, catalysts network method, catalyst design from small data, catalysts informatics platform, and the future of catalysts informatics via ontology. Thus, the proposed catalysts informatics would help innovate how catalysts can be designed and understood.
Keyphrases
  • highly efficient
  • big data
  • metal organic framework
  • transition metal
  • machine learning
  • electronic health record
  • artificial intelligence
  • high throughput
  • healthcare
  • emergency department
  • ionic liquid
  • room temperature