Machine Learning and Hybrid Modelling for Reaction EngineeringTheory and Applications\nAuthor(s): Dongda Zhang, Ehecatl Antonio del Ro Chanona\nFormat: Hardback\nPublisher: Royal Society of Chemistry, United Kingdom\nImprint: Royal Society of Chemistry\nISBN-13: 9781839165634, 978-1839165634\nSynopsis\nOver the last decade, there has been a significant shift from traditional mechanistic and empirical modelling into statistical and data-driven modelling for applications in reaction engineering. In particular, the integration of machine learning and first-principle models has demonstrated significant potential and success in the discovery of (bio)chemical kinetics, prediction and optimisation of complex reactions, and scale-up of industrial reactors. \n\nSummarising the latest research and illustrating the current frontiers in applications of hybrid modelling for chemical and biochemical reaction engineering, Machine Learning and Hybrid Modelling for Reaction Engineering fills a gap in.