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This lecture explores the use of machine-learning techniques in materials science, focusing on Metal Organic Frameworks (MOFs) and their potential in clean energy technologies. It delves into the computational challenges of MOFs, the growing field of MOFs, and the world energy consumption trends. The lecture discusses carbon capture and storage, post-combustion carbon capture, and the performance metrics involved. It also covers the synthesis of MOFs, the comparison of different structures, and the importance of chemical intuition in the process. The presentation concludes with the implications of the research and the future directions in the field.