Electrocatalytic water splitting driven by renewable electricity has attracted great interest in
recent years for producing hydrogen with high-purity. However, the practical applications of …

Machine learning models are poised to make a transformative impact on chemical sciences
by dramatically accelerating computational algorithms and amplifying insights available from …

In recent years, the use of machine learning (ML) in computational chemistry has enabled
numerous advances previously out of reach due to the computational complexity of …

The power of chemistry to prepare new molecules and materials has driven the quest for
new approaches to solve problems having global societal impact, such as in renewable …

The unprecedented ability of computations to probe atomic-level details of catalytic systems
holds immense promise for the fundamentals-based bottom-up design of novel …

One of the most promising suggested applications of quantum computing is solving
classically intractable chemistry problems. This may help to answer unresolved questions …

Electronically excited states of molecules are at the heart of photochemistry, photophysics,
as well as photobiology and also play a role in material science. Their theoretical description …

Luminescent small, all‐organic molecules are of tremendous interest in materials and life
science applications. Nevertheless, targeted design requires a basic understanding of the …

block2 is an open source framework to implement and perform density matrix
renormalization group and matrix product state algorithms. Out-of-the-box it supports the …

Optically active molecular materials, such as organic conjugated polymers and biological
systems, are characterized by strong coupling between electronic and vibrational degrees of …