Replacing fossil fuels with energy sources and carriers that are sustainable, environmentally
benign, and affordable is amongst the most pressing challenges for future socio-economic …

Photoinduced chemical transformations have received in recent years a tremendous amount
of attention, providing a plethora of opportunities to synthetic organic chemists. However …

Reaction optimization is fundamental to synthetic chemistry, from optimizing the yield of
industrial processes to selecting conditions for the preparation of medicinal candidates …

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

Accelerating the discovery of new molecules and materials, as well as develo** green
and sustainable ways to synthesize them, will help to address global challenges in energy …

This is a critical review of artificial intelligence/machine learning (AI/ML) methods applied to
battery research. It aims at providing a comprehensive, authoritative, and critical, yet easily …

Self-driving laboratories (SDLs) promise an accelerated application of the scientific method.
Through the automation of experimental workflows, along with autonomous experimental …

Prediction of chemical bioactivity and physical properties has been one of the most
important applications of statistical and more recently, machine learning and artificial …

Conspectus We must accelerate the pace at which we make technological advancements to
address climate change and disease risks worldwide. This swifter pace of discovery requires …

Conspectus The ongoing revolution of the natural sciences by the advent of machine
learning and artificial intelligence sparked significant interest in the material science …