Parallelization is crucial in catalysis for several reasons:
1. High Throughput Screening: It allows for the rapid evaluation of a large number of catalysts, substrates, and reaction conditions. 2. Optimization: Accelerates the optimization process for catalytic reactions by testing multiple variables simultaneously. 3. Resource Efficiency: Conserves time and resources by reducing the need for repetitive sequential experiments. 4. Data Generation: Generates vast amounts of data, which can be used for machine learning and other computational methods to predict catalyst performance.
