Projektdatenbank (ab 2004)

Projektnummer

0067327

Zusammenfassung

In the last years, machine learning (ML) has been introduced as new tool in many fields in chemistry, e.g. to optimize catalysts and develop new drugs. All previous chemical databases rely on the usage of SMILES codes which work fine in organic chemistry with the majority of covalent bonds but totally fail in inorganic chemistry. Data-driven ML methods use the information from data bases to plan new syntheses, optimize reaction conditions and identify substances. Here is the largest hurdle for structure-based ML applications in inorganic chemistry. Most inorganic ML studies thus used a...