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 …

Carbon capture, utilization, and storage (CCUS) is a promising pathway to decarbonize
fossil-based power and industrial sectors and is a bridging technology for a sustainable …

Deep learning has become a powerful and frequently employed tool for the prediction of
molecular properties, thus creating a need for open-source and versatile software solutions …

The global spread of COVID-19 has raised the importance of pharmaceutical drug
development as intractable and hot research. Develo** new drug molecules to overcome …

Interest in green neoteric solvents, such as ionic liquids (ILs) and deep eutectic solvents
(DESs), has increased dramatically in recent years due to their highly tunable properties …

Artificial intelligence (AI) is gaining strength, and materials science can both contribute to
and profit from it. In a simultaneous progress race, new materials, systems, and processes …

In modern drug discovery, the combination of chemoinformatics and quantitative structure–
activity relationship (QSAR) modeling has emerged as a formidable alliance, enabling …

Modern therapeutic development often involves several stages that are interconnected, and
multiple iterations are usually required to bring a new drug to the market. Computational …

We report a new deep learning message passing network that takes inspiration from
Newton's equations of motion to learn interatomic potentials and forces. With the advantage …

With its extremely strong capability of data analysis, machine learning has shown versatile
potential in the revolution of the materials research paradigm. Here, taking dielectric …