Extracting kinetic information in catalysis: an automated tool for the exploration of small data

January 1, 2022

For numerous reactions in catalysis{,} the lack of (big) data in kinetics is compensated for by the availability of numerous small{,} scattered datasets as typically found in the literature. To exploit the potential of such peculiar{,} small data{,} incorporation of fundamental knowledge into data-driven approaches is essential. In this work{,} a novel tool was developed to automatically extract kinetically relevant information from small datasets of steady-state kinetic data for heterogeneously catalysed reactions. The developed tool{,} based on the principles of qualitative trend analysis{,} was tailored to the needs of catalysis and enriched with chemical knowledge{,} balancing thereby the limited amount of data and ensuring that meaningful information is extracted. A detailed account of the development steps discloses how the chemical knowledge was incorporated{,} such that this approach can inspire new tools and applications. As demonstrated for a hydrodeoxygenation case study{,} such a tool is the first step into automatic construction of kinetic models{,} which will ultimately lead to a more rational design of novel catalysts.

Authors in the community:

• 

  P

  Pedro Simão Freitas Mendes

  ist163499

  Affiliations and sources

  In: orcid

  ID: 101663018

  In: scopus

  ID: 2-s2.0-85121719940

Reaction Chemistry & Engineering

142

155

7

1

10.1039/D1RE00215E

chemical-engineering - Chemical engineering

eng - English

Financing entity

Universiteit Gent

Identifier for the funding entity: BOF/PDO/2018/001901