Rational catalyst design is typically achieved through a combination of experimental and theoretical techniques:
Computational Modeling: Techniques like density functional theory (DFT) and molecular dynamics simulations help predict the behavior of catalyst materials at the atomic level. High-throughput Screening: Automated systems can rapidly test a large number of catalyst candidates to identify promising leads. Machine Learning: Algorithms can analyze vast amounts of data to identify patterns and predict the performance of new catalyst designs.
