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This is an immensely useful book, and the source that I would turn to first when seeking virtually any information about solvent effects.

Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important

COSMO-RS, From Quantum Chemistry to Fluid Phase Thermodynamics and Drug Design is about this novel technology, which has recently proven to be the most reliable and efficient tool for the prediction of vapour-liquid equilibria.

This book embraces all physiochemical aspects of the structure and molecular dynamics of water, focusing on its role in biological objects, e.g. living cells and tissue, and in the formation of functionally active structures of biological ...

He also includes a concise review of the linear algebra needed for group theory, making the book ideal for self-study.

A universal, fast CFF would open the door to high-throughput virtual materials screening in the pursuit of novel materials with tailored properties.

In this thesis I examine the use of graph neural networks for prediction tasks in chemistry with an emphasis on interpretable and scalable methods.

This book sheds light on the molecular aspects of liquids and liquid-based materials such as organic or inorganic liquids, ionic liquids, proteins, biomaterials, and soft materials including gels.