CDI currently offers a service model, where our experts develop reports for clients tackling domain-specific problems. Our solutions are based on a combination of Big Data analytics, machine learning, chemoinformatics, as well as conventional chemical knowledge.

Typical questions from clients may look like these:

Are there suitable routes to the target molecule starting from bio-renewable feedstocks, e.g. from CO2, from CH4, …?

Development of client-based ranking schemes for the possible routes based on a set of criteria, e.g. overall yield, a greenness metric, a safety metric, overall energy use, etc.

Are there routes to the target molecule that avoid the use of specific reagents or solvents?

“In a proof of concept, the CDI team demonstrated that the automated reaction network analysis workflow they are currently developing can accelerate and facilitate route scouting exercises by providing overviews of routes that are consistent with a set of user-defined criteria, such as avoiding halogenated solvents/reagents or preferred use of renewable raw materials. A distinguishing feature of this tool is the possibility to highlight/prefer routes that maximize the use of renewables and/or reagents that can be easily derived from renewables.”

DSM Nutritional Products