Molecular discovery is a multi-objective optimization problem that requires identifying a
molecule or set of molecules that balance multiple, often competing, properties. Multi …

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

Designing protein sequences towards desired properties is a fundamental goal of protein
engineering, with applications in drug discovery and enzymatic engineering. Machine …

Rapid advancements in artificial intelligence (AI) have enabled breakthroughs across many
scientific disciplines. In organic chemistry, the challenge of planning complex multistep …

In the rapidly evolving landscape of electrochemical energy storage (EES), the advent of
artificial intelligence (AI) has emerged as a keystone for innovation in material design …

A necessary transformation for a sustainable economy is the transition from fossil-derived
plastics to polymers derived from biomass and waste resources. While renewable …

Machine learning can make a strong contribution to accelerating the discovery of transition
metal complexes (TMC). These compounds will play a key role in the development of new …

The development of post-vanadium electrolytes using abundant materials with versatile
redox chemistries will enable cost-effective energy storage and widespread implementation …

The discovery of new materials in unexplored chemical spaces necessitates quick and
accurate prediction of thermodynamic stability, often assessed using density functional …

Persistent and stable nitrogen‐centered organic radicals, including non‐heterocyclic/
heterocyclic nitrogen‐centered radicals and nitrogen‐centered radical complexes, have …