Advances within computational chemistry, particularly generative models, have opened new frontiers in designing catalytic systems. Generative models such as Genetic Algorithms(GAs) have been shown efficient at screening chemical space for various chemical tasks . Using either ML methods or fast quantum methods, one can quickly screen chemical space for any desired property for a wide range of chemical challenges. Recent years has seen some highly promising work withing GAs for catalyst design that also highlights the challenges related to the problem .