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 …

The discovery and development of catalysts and catalytic processes are essential
components to maintaining an ecological balance in the future. Recent revolutions made in …

Scientists have long benefitted from and contributed to the development of quantitative
methods to reveal patterns in structure− property relationships across all branches of …

The recent synergy of machine learning (ML) with molecular synthesis has emerged as an
increasingly powerful platform in organic synthesis and catalysis. This merger has set the …

Burgeoning developments in machine learning (ML) and its rapidly growing adaptations in
chemistry are noteworthy. Motivated by the successful deployments of ML in the realm of …

Minimizing the time and material investments in discovering molecular catalysis would be
immensely beneficial. Given the high contemporary importance of homogeneous catalysis in …

Conspectus Numerous disciplines, such as image recognition and language translation,
have been revolutionized by using machine learning (ML) to leverage big data. In organic …

The past decade has seen a sharp increase in machine learning (ML) applications in
scientific research. This review introduces the basic constituents of ML, including databases …

The benefits of using machine learning approaches in the design, optimisation and
understanding of homogeneous catalytic processes are being increasingly realised. We …

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 …