Chemists nowadays use model calculations to design molecules with specific properties, to assess the feasibility of synthesis, or to interpret complex experimental data. But simulation of a complex system by combining methods is difficult because of the diversity of data formats for specific molecular properties.
Rationally designing solar cells, reducing solvent losses in organic synthesis, tuning catalysts, or developing better LEDs
This project will design computational chemistry workflows allowing chemists to use massively parallel computing environments in an easy manner. This enables a single researcher to model and analyze thousands of compounds, yielding a wealth of detailed data to, for example, rationally design solar cells, reduce solvent losses in organic synthesis, tune catalysts, or develop better LEDs.