Description
Metal Organic Frameworks for Energy and Environmental Applications presents a comprehensive overview on the application of metal organic frameworks (MOFs) to energy and environmental areas. MOFs are a promising class of materials due to their tunable structures, high surface area, and versatile functionalities, and are capturing the attention of the global scientific community due to their intersection with environmental concerns. Chapters summarize recent research on MOFS and synthesis strategies for catalysis, including photocatalysis, electrocatalysis, and thermal catalysis, and how MOFs offer enhanced performance, selectivity, and efficiency.Additionally, the vital role MOFs play in energy storage, environmental purification, including degradation of harmful agents, and resource utilization is explored. The book also presents new research on machine learning and data mining, including how researchers can leverage datasets and algorithms to discover new, high-performance MOFs. Metal Organic Frameworks for Energy and Environmental Applications will be a valuable reference for those studying and working in the field of MOFs as they apply to energy, environmental technologies, catalysis, and materials science.- Presents a broad understanding of the diverse applications of MOFs in energy and environment-related areas- Summarizes recent research on MOFs, including synthesis strategies for catalysis, energy storage, environmental purification, etc.- Introduces machine learning and data mining as techniques to discover high-performance MOFs
Table of Contents
1. Introduction to MOFs2. Synthetic strategies for MOFs3. Characterization techniques for MOFs4. Shaping of metal-organic framework5. MOFs for photocatalytic water splitting6. MOFs for photocatalytic CO2 reduction7. MOFs for HER and OER8. MOFs for CO2 electroreduction9. MOFs for oxidation and hydrogenation reaction10. MOFs for thermal energy storage11. MOFs for electrical energy storage12. MOFs for hydrogen storage13. MOFs for chemical warfare agent degradation14. MOFs for gas sensor15. MOFs for extraction of radionuclide/noble metals/lithium16. Machine learning accelerates the development of MOFs17. Conclusions and challenges
