  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.
