Importance of First-Principles in Model-Based Scale-Up

The energy transition demands improvement to existing and development of new technologies. Both require extrapolation, either through optimization or scale-up. AI is becoming more prevalent and will play an important role in chemical engineering, but the generally poor extrapolation properties and general lack of data in the case of new technologies make a first-principles model-based approach critical for the energy transition. Two case studies are presented illustrating the importance of first-principles modeling. Our modular, ground-up, fundamentals-based model approach allows us to do targeted experiments at lab or pilot scales to reduce the cost compared to a purely experiment-based scale-up approach.