In catalysis, gradient descent can be used to optimize various parameters such as temperature, pressure, and catalyst composition. By defining an objective function, such as the rate of reaction or yield of a desired product, researchers can employ gradient descent to find the set of conditions that maximizes or minimizes this objective function.
