Abstract Machine learning plays an increasingly important role in many areas of chemistry
and materials science, being used to predict materials properties, accelerate simulations …

C–H functionalization reactions are playing an increasing role in the preparation and
modification of complex organic molecules, including pharmaceuticals, agrochemicals and …

Depolymerization is a promising strategy for recycling waste plastic into constituent
monomers for subsequent repolymerization. However, many commodity plastics cannot be …

Artificial intelligence for graphs has achieved remarkable success in modelling complex
systems, ranging from dynamic networks in biology to interacting particle systems in physics …

The design of molecular catalysts typically involves reconciling multiple conflicting property
requirements, largely relying on human intuition and local structural searches. However, the …

Chemical reaction networks (CRNs), defined by sets of species and possible reactions
between them, are widely used to interrogate chemical systems. To capture increasingly …

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 …

Site-and enantioselective cross-coupling of saturated N-heterocycles and carboxylic acids—
two of the most abundant and versatile functionalities—to form pharmaceutically relevant α …

Accurate and rapid evaluation of whether substrates can undergo the desired the
transformation is crucial and challenging for both human knowledge and computer …

Boron neutron capture therapy (BNCT) was clinically approved in 2020 and exhibits
remarkable tumour rejection in preclinical and clinical studies. It is binary radiotherapy that …