The future of RL in catalysis looks promising, with ongoing research focusing on improving the accuracy and efficiency of RL algorithms. Advances in computational chemistry and quantum computing are expected to enhance the capabilities of RL in simulating and optimizing catalytic processes. Additionally, the integration of RL with other machine learning techniques, such as neural networks and genetic algorithms, could further accelerate the discovery and optimization of new catalysts.
