To face climate change and create more resilient supply chains a transformation from fossil feedstocks to renewable raw materials is indispensable. However, renewable raw materials fluctuate seasonally and geologically in their availability and quality (also due to (geo)political crises). Therefore, society urgently requires processes and reactors that can flexibly respond to fluctuating characteristics of raw materials. To enable such adaptation very high level of process control is needed: pressures, temperatures, concentrations and dispersed phases must be monitored within the reactors continuously and in situ using appropriate sensors. Local process control and adjustment during operation must be realized. This requires a deep and fundamental understanding of all relevant transport processes and reaction steps to provide a fast and reliable modelling and simulation for an operando and in situ process optimisation. Fundamental research on these topics will enable technologies for SMART reactors, that convert renewable resources which are more Sustainable into different products (Multipurpose) and that are Autonomously (self-adaptive), which will lead to more Resilient processes that are better Transferable between scales and locations. In our vision the autonomous reactor can in situ measure the local conditions using integrated sensors, which transfer the chemical or electrical signal to the integrated responsive internal components of the reactor (actuators). These actuators self-adapt and therefore optimize the process on a local level. Therefore, this CRC will investigate how local process conditions in reactors can be detected, formulated in models and translated into actions to always ensure optimal process conditions with constant product quality and maximum yield despite fluctuating quality of the feed coming from renewable resources.
