Machine learning (ML) is a field of computer science that uses algorithms and techniques for
automating solutions to complex problems that are hard to program using conventional …

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 …

Organic solar cells are the most promising candidates for future commercialization. This goal
can be quickly achieved by designing new materials and predicting their performance …

The power conversion efficiency (PCE) of organic solar cells (OSCs) is increasing
continuously, however, commercialization is far from being achieved due to the very high …

Theoretical simulations of electronic excitations and associated processes in molecules are
indispensable for fundamental research and technological innovations. However, such …

Nonfullerene, a small molecular electron acceptor, has substantially improved the power
conversion efficiency of organic photovoltaics (OPVs). However, the large structural freedom …

Integrating artificial intelligence (AI) and computer science together with current approaches
in material synthesis and optimization will act as an effective approach for speeding up the …

Despite the capacity of conjugated materials for enhanced power conversion efficiency
(PCE) of organic photovoltaics (OPV), a comprehensive survey of unexplored materials is …

The discovery of novel high-performing materials such as non-fullerene acceptors and low
band gap donor polymers underlines the steady increase of record efficiencies in organic …

In this work, we analyzed a data set formed by 566 donor/acceptor pairs, which are part of
organic solar cells recently reported. We explored the effect of different descriptors in …