Application of Artificial Neural Networks for Catalysis

TL;DR

This paper reviews how artificial neural networks are applied to catalyst optimization, significantly reducing resource consumption and accelerating progress in catalysis research.

Contribution

It provides a comprehensive overview of ANN applications in catalyst development, highlighting its advantages in solving complex problems in catalysis.

Findings

ANN reduces catalyst development time

ANN improves catalyst performance predictions

ANN accelerates catalysis research progress

Abstract

Catalyst, as an important material, plays a crucial role in the development of chemical industry. By improving the performance of the catalyst, the economic benefit can be greatly improved. Artificial neural network (ANN), as one of the most popular machine learning algorithms, relies on its good ability of nonlinear transformation, parallel processing, self-learning, self-adaptation and good associative memory, has been widely applied to various areas. Through the optimization of catalyst by ANN, the consumption of time and resources can be greatly reduced and greater economic benefits can be obtained. In this review, we show how this powerful technique helps people address the highly complicated problems and accelerate the progress of the catalysis community.