ABSTRACT
The wide spectrum of machine learning applications ranging from predictive analysis to classification techniques, feature engineering and deep learning analysis in transforming the synthesis and development of materials for enhancing thin film deposition process have been investigated. Critical challenges in providing machine learning-based solutions to ALD problems were discussed under several chapters in the second and last section of the book. Since industrial-scale applications involves more sophisticated processes, bigger materials and substrates in a single process, substantial scaling up of machine learning-based ALD research to an industrial scale has been necessitated. Some of these future prospects in machine learning-based ALD modeling research space are briefly discussed as follows. Approaches for developing an explainable AI include model interpretation techniques which function based on the underlying workings of machine learning to acquire knowledge of how it generates predictions, visualization technique which assists researchers to visualize and observe connections between various dataset properties and prediction provided by the models.
