Advances of machine learning in molecular modeling and simulation

Publication date: March 2019Source: Current Opinion in Chemical Engineering, Volume 23Author(s): Mojtaba Haghighatlari, Johannes HachmannIn this review, we highlight recent developments in the application of machine learning for molecular modeling and simulation. After giving a brief overview of the foundations, components, and workflow of a typical supervised learning approach for chemical problems, we showcase areas and state-of-the-art examples of their deployment. In this context, we discuss how machine learning relates to, supports, and augments more traditional physics-based approaches in computational research. We conclude by outlining challenges and future research directions that need to be addressed in order to make machine learning a mainstream chemical engineering tool.Graphical abstract
Source: Current Opinion in Chemical Engineering - Category: Chemistry Source Type: research