Carbon Capture

1. Carbon Capture Berend Smit Berend-Smit@berkeley.edu

2. Carbon Emmisions Marland, G., T.A. Boden, and R. J. Andres (2003). "Global, Regional, and National CO2 Emissions" in Trends: A Compendium of Data on Global Change. Oak Ridge, Tenn., U.S.A.: Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy.

3. Carbon Capture EPRI (2008)

4. CCS addressable emissions McKinsey & Company (2008)

5. Carbon Capture and Storage Successful CCS involves two aspects: capture and storage. Capture is currently considered to be the most expensive part of CCS. Geologic storage involves uncertainties and risks when considered at full scale.

6. Cost of Carbon Capture McKinsey & Company (2008) McKinsey & Co (2008)

7. What to do with a GIGATON of CO2? Abhoyjit S. Bhown (EPRI): Let’s convert CO2 into “Dreamium™” www.TwentyThousandMinusThreeAppsOfDreamium.com

8. Making Dreamium™

9. Absorption processes: Amine Solutions Proven technology Costs: regeneration of the solvent (70% water) 30% energy cost Research: Better solvents: Lower regeneration energy Stability

10. Minimum Parasitic Energy Composition flue gas: Requirements: 90% of the CO2 needs to be captured: What is the minimum energy required?

11. Parasitic Energy Cost EPRI (2008) The current technology has an parasitic energy cost of 30% Chemical industry works at 3-5 times this thermodynamics minimum

12. Capture: new concepts are lacking McKinsey & Company (2008)

13. Center for Gas Separations Relevant to Clean Energy TechnologiesBerend Smit and Jeff Long (UC Berkeley) The aim of this EFRC is to develop new strategies and materials that allow for energy efficient selective capture or separation of CO2 from gas mixturesbased on molecule-specific chemical interactions. RESEARCH PLAN AND DIRECTIONS Capture of CO2 from gas mixtures requires the molecular control offered by nanoscience to tailor-make those materials exhibiting exactly the right adsorption and diffusion selectivity to enable an economic separation process. Characterization methods and computational tools will be developed to guide and support this quest.

14. Approach Identify two important case studies: Separations in flue gasses CO2 from natural gas Options for separations New materials and concepts Inorganic materials Polymer membranes Crosscutting Characterization Computation:

15. Alternatives to absorption Adsorption Membrane

16. Possible technologies EPRI (2008)

17. Metal-Organic Frameworks for Gas Separations Jeffrey Long UC Berkeley Omar Yaghi UCLA Hong-Cai Zhou Texas A&M

18. Metal-Organic Frameworks BET surface areas up to 5200 m2/g Density as low as 0.4 g/cm3 Adjustable pore sizes of up to 5 nm Channels connected in 1-, 2-, or 3-D Internal surface can be functionalized Can these porous, high-surface area materials be used for gas separations? Zn4O(1,4-benzenedicarboxylate)3 (MOF-5) Yaghi et al. Nature2003, 423, 705

19. Zeolitic Imidazolate Frameworks (ZIFs) Banerjee, Phan, Wang, Knobler, Furukawa, O’Keeffe, Yaghi Science2008, 319, 939

20. Mesh-Adjustable Molecular Sieves Zn(BBPDC) Ma, Sun, Wang, Zhou Angew. Chem., Int. Ed.2007, 46, 2458

21. Alkylamine-Functionalized MOF Surfaces H3[(Cu4Cl)3(BTTri)8]12en Co(BDP) Initial isosteric heat of CO2 adsorption of -90 kJ/mol observed Methods for directly functionalizing bridging ligands are under development Demmesence, D’Alessandro, Foo, Long J. Am. Chem. Soc.2009, 131, 8784

22. Polymer materials Frantisek Svec Jean Frechet Ting Xu Bret Helms

23. Controlling pore size and selectivity via crosslinker selection Pore size suitable for H2 only (submitted for publication) Larger pores (under study)

24. Thin Films from Cyclic Peptide-polymer Conjugates Cyclic Peptide Nanotube 0.7 - 0.8 nm

25. CP-PEO Conjugate/Asymmetric PS-b-PMMA Blends

26. Characterization Jeff Kortright Blandine Jerome • Jeff Reimer • Simon Teat • Characterize the materials • Determine the structure of loaded materials • Develop new experimental techniques to obtain understanding at the molecular level

27. Understanding separation Resonant Soft X-ray Scattering structure, composition length scale  1nm Nuclear Magnetic Resonance structure, diffusion Macroscopic transport length scale ≤ 1nm absorption, diffusion length scale  10nm

28. Computation Alice Koniges Jeff Neaton Berend Smit Juan Meza Maciej Haranczyk • In silico screening of materials • Theoretical understanding

29. Computations Every point takes about two weeks How to screen 5 million structures efficiently?

30. Structure Descriptors, Representations and Similarity Measures • Comparing “global” character of structures using Mapper – topology analysis tool Application to zeolites Comparing 3D objects using Mapper

31. In-silico Process Development Configurational- Bias Monte Carlo simulations Sorption isotherms Ideal Adsorbed Solution Theory Permeation fluxes across membranes; Breakthrough curves in packed bed adsorbers Equations of continuity of mass and momentum Molecular Dynamics Simulations; Transition State theory Maxwell-Stefan theory for Zeolite Diffusion Maxwell-Stefan diffusivities Kinetic Monte Carlo simulations Mixture diffusion

32. Connections to Other Initiatives at LBNL Climate modeling and economic evaluation People will make money out of CO2 but with zero impact on the environment Biological sequestration Chemical sequestration (e.g. through Helios) Integration with geological sequestration Integral solution: pressure as a driving force for separations Contaminations in the CO2