Optimization in catalysis typically involves a combination of experimental and computational approaches:
Experimental Design: Techniques such as Design of Experiments (DOE) are used to systematically investigate the effects of multiple variables. DOE helps in identifying the most influential factors and their interactions. Computational Modeling: Computational chemistry and reactor modeling can predict the behavior of catalytic systems under different conditions, saving time and resources in the experimental phase. Optimization Algorithms: Algorithms such as genetic algorithms, simulated annealing, and gradient descent are employed to search for the optimal conditions in a multi-dimensional space.
