Automated parameter tuning refers to the use of computational techniques to optimize various parameters in catalytic processes. This involves leveraging algorithms, machine learning, and high-throughput experimentation to identify the optimal conditions for catalytic reactions. Parameters such as temperature, pressure, catalyst composition, and reactant concentration can be fine-tuned to enhance catalytic performance, yield, and selectivity.
