A mechanistic understanding of catalytic organic reactions is crucial for the design of new
catalysts, modes of reactivity and the development of greener and more sustainable …

As more data are introduced in the building of models of chemical reactivity, the mechanistic
component can be reduced until 'big data'applications are reached. These methods no …

Conspectus In the domain of reaction development, one aims to obtain higher efficacies as
measured in terms of yield and/or selectivities. During the empirical cycles, an admixture of …

Accurate prediction of chemical reactions in solution is challenging for current state-of-the-
art approaches based on transition state modelling with density functional theory. Models …

Quantitative predictions of reaction properties, such as activation energy, have been limited
due to a lack of available training data. Such predictions would be useful for computer …

Chemical reaction networks form the heart of microkinetic models, which are one of the key
tools available for gaining detailed mechanistic insight into heterogeneous catalytic …

Despite tremendous progress in understanding and engineering enzymes, knowledge of
how enzyme structures and their dynamics induce observed catalytic properties is …

Being able to predict the course of arbitrary chemical reactions is essential to the theory and
applications of organic chemistry. Approaches to the reaction prediction problems can be …

Reaction condition recommendation is an essential element for the realization of computer-
assisted synthetic planning. Accurate suggestions of reaction conditions are required for …

Proposing reasonable mechanisms and predicting the course of chemical reactions is
important to the practice of organic chemistry. Approaches to reaction prediction have …