Current Outlooks on Machine Learning Methods for the Development of Industrial Homogeneous Catalytic Systems

• Type: Article in International Scientific Journal
• Date: 2022

Authors

Ferraz-Caetano, J (Author) FCUP

Journal

The Journal is awaiting validation by the Administrative Services.

Title: CURRENT ORGANOCATALYSIS

Vol. 9

Pages: 276-280

ISSN: 2213-3372

Indexing

ISI Web of Knowledge - 1 Citation

Scopus

Other information

Authenticus ID: P-00X-NA5

DOI: 10.2174/2213337209666220728094248

Abstract (EN): This brief perspective outlines the pivotal role of Machine Learning methods in the green, digital transition of industrial chemistry. The focus on homogenous catalysis highlights the recent methodologies in the development of industrial processes, including the design of new catalysts and the enhancement of sustainable reaction conditions to lower production costs. We report several examples of Machine Learning assisted methodologies through recent Data Science trends in the innovation of industrial homogeneous organocatalytic systems. We also stress the current benefits, drawbacks, and limitations of the mass implementation of these Data Science methodologies.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 5