Graphene Membrane for Gas Separation - PowerPoint PPT Presentation

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group 3 krista melish phillip keller james kancewick micheal jones l.
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Graphene Membrane for Gas Separation

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  1. Group 3: Krista Melish, Phillip Keller, James Kancewick, Micheal Jones Graphene Membrane for Gas Separation

  2. Gas Separation in Industry • Hydrogen separation • From Nitrogen in ammonia plants • From hydrocarbons in petrochemical applications • CO2 and water removal from natural gas • Nitrogen separation from air • Hydrogen Recovery From Tail Gases • Air & natural  gas drying • Vapor removal • Hydrocarbon Separations • Helium recovery from natural gas Food processing, packaging, and storing Pharmaceuticals

  3. Membranes for Gas Separation • Less waste produced • Less harm on environment • Lower industrial cost • Lower energy consumption

  4. Limitations of Common Membranes • Energy intensive • Expensive • Lack efficiency and productivity • Break easily • The material plugs too easily and becomes resistant to flow

  5. Properties of a Good Membrane • High flux rate (permeability) • High selectivity • Ideal pore size • High surface area • Low manufacturing cost • Small thickness • Mechanically Stable

  6. Flux Rate of Different Gases • Affected by: • molecule size • gas concentration • pressure difference across the membrane • the affinity of the gas for the membrane material

  7. Mechanisms for Gas Separation in Membranes

  8. Relationships Among Membranes Selectivity vs. Permeability of Membranes Fick’s Law The Flux rate (J) is inversely proportional to membrane thickness (x)

  9. Graphene • Single layer of carbon atoms • Densely packed • Hexagonal pattern • Sp2 bonded • Crystal lattice • One atom thick • 2-D structure

  10. Properties of Graphene • Tear-resistant • Thermal conductor • Very Thin • Very stiff, but also flexible • Mechanically Strong • Stronger than a diamond • Electronically conducting • 100 times faster than the silicon in computer chips • Ductile

  11. Graphene Becomes a Membrane • Graphene is impermeable to all gases due to the electron density of its Aromatic rings • In order to create a membrane, must create pores synthetically http://www.physics.upenn.edu/~drndic/group/research.html

  12. Two Methods for Creating Nanopores • Bottom-up synthesis • chemical building blocks of functionalized phenyl rings "grow" into a 2-D structure on a silver substrate • pore diameters of a single atom • pore-to-pore spacing of less than a nanometer

  13. TEM • Puncture holes by removing carbon rings by electric beam • The unsaturated carbons are passivated by nitrogen • Control pore size

  14. Graphene Membrane • Thinnest possible membrane (1 atom thick) • Over 20,000 x thinner than other membranes • Ideal pore size for separation • Improvement of 500x compared to other membranes • Large surface area • (Up to areas of 1 mm ^2) • Resistant to oxidation • (for temperature less than 450 celsius) • Very mechanically stable

  15. Research Article by the Chemical Sciences, Materials Science, and Technology Divisions of Oak ridge National Laboratory (De-en Jiang, Valentino R. Cooper, and Sheng Dai) Porous Graphene as the Ultimate membrane for Gas Separation Article taken from: Nano Letters 2009 Volume 9 No. 12 Pages 4019-4024 • All pictures not cited on slide are from this article and belong to the authors

  16. Article Overview • Inspiration for Research • No prior research on graphene as a separation membrane • Massive possible efficiency gains in the gas separation field • Goals • Use first principles models to mathematically prove the viability of graphene as the ultimate membrane for gas separation • Encourage future research and experimentation • Method • Density Functional Theory • Simulation Results • Further Research and Experimentation Ideas

  17. Research Inspiration • Graphene first isolated in 2004 • Although there has been a boom of graphene research lately, no efforts have been put into analyzing its usefulness as a gas separation membrane. • Gas separation is very energy intensive currently • Huge opportunities to increase efficiency • Application to other fields • Proton Exchange Membranes for fuel cells • Carbon sequestration from flue gases • Gas sensors in instrumentation

  18. Research Goals • Show Viability of graphene as a gas separation membrane • Mathematical modeling from first principles • Inspire future research and experimentation • New nano-pore designs • New nano-pore construction methods • Innovative applications to new fields

  19. Research Method • Density Functional Theory based modeling using • Plane wave base • 300 and 680 eV kinetic energy cutoffs • Periodic boundary conditions • Initial Static Calculations • 2 methods used • Perdew, Burke, and Erzenhoff functional form of the generalized gradient approximation (PBE) • Rutgers-Chalmers van der Waals density function for exchange and correlation (vdW-DF) • Good at evaluating strength of dispersion interactions between neutral non polar molecules

  20. Model: Nitrogen Functionalized • Hexagonal cell made of graphene • 15 H2 or CH4 molecules placed inside the cell for dispersion calculations • One face of the cell contains the nano-pore • Nano-pore created by removing two cells (a), leaving 8 dangling carbons • Functionalized with 4 hydrogens and 4 nitrogens (b)

  21. Model: Nitrogen Functionalized • Resulting pore electron density isosurface (red) leaves a rectangular pore • 3.0 Angstroms by 3.5 Angstroms • Nitrogen slightly attractive • Hydrogen slightly repulsive • 0.05 eV Barrier to H2 versus 0.33-0.41 eV for CH4 • Nitrogen yellow, Hydrogen blue

  22. Model: Nitrogen Functionalized • Graph shows the interaction energy between H2 and the nitrogen functionalized pore as a function of adsorption height and orientation of the molecule within the pore. • Red line and squares are calculated using vdW-DF method. • Black line and dots are calculated using PBE method. • Relatively flat curve shows little repulsion as molecule approaches the pore.

  23. Model: Nitrogen Functionalized • Graph shows the interaction energy between CH4 and the nitrogen functionalized pore as a function of adsorption height and orientation of the molecule within the pore. • Red line and squares are calculated using vdW-DF method. • Black line and dots are calculated using PBE method. • Curvature shows the repulsion of the molecule as it approaches the pore

  24. Model: Nitrogen Functionalized • Results • Selectivity for H2 / CH4 with the nitrogen functionalized pore is 108 (Arrhenius) • Selectivity is high compared to traditional polymer membranes and silica membranes with selectivities ranging from 10-103 • Graphene is also much more resilient than other membrane materials that are more susceptible to Hydrogen damage • Difficulties • Such functionality will be hard to specify during manufacture • i.e. The placement of the Nitrogens and Hydrogens will be random around the edge of the pore • Much easier to functionalize the poor using only Hydrogen • Next calculations are for a Hydrogen only functionalized pore

  25. Model: Hydrogen Functionalized • (a) Face of Hexagonal cell with nano-pore functionalized with only Hydrogen (blue) • Created by removing 2 neighboring rings from the graphene sheet like before. • (b) Pore-electron density isosurface showing effective pore size • Dimensions are now 2.5 Angstroms by 3.5 Angstroms • Now it will be harder for both species to pass through

  26. Model: Hydrogen Functionalized • Graph shows the interaction energy between H2 and the hydrogen functionalized pore as a function of adsorption height and orientation of the molecule within the pore. • Red line and squares are calculated using vdW-DF method. • Black line and dots are calculated using PBE method. • Relatively flat curve shows little repulsion as molecule approaches the pore just like before.

  27. Model: Hydrogen Functionalized • Graph shows the interaction energy between CH4 and the hydrogen functionalized pore as a function of adsorption height and orientation of the molecule within the pore. • Red line and squares are calculated using vdW-DF method. • Black line and dots are calculated using PBE method. • Curvature shows the repulsion of the molecule as it approaches the pore with values significantly higher than before.

  28. Model: Hydrogen Functionalized • Results • Selectivity for Hydrogen over methane raised to 1023 • New barriers were 0.22 eV for H2 and 1.6 eV for CH4 which translates to a pass through frequency of 109 atoms of H2 per second at room temperature. • Conducted further research to judge the effect of inevitable errors in future manufacture such as removing three neighboring rings versus just 2 resulting in a width of 3.8 Angstroms. • Found that this small error resulted in the pore becoming useless (neither species impeded) • Demands absolute precision in manufacture

  29. Conclusions • Although these are just mathematical models, they show the viability of graphene as a new generation super membrane material. • This research applies universally to the separation of gaseous molecules based on size. • If findings can be reproduced in real life, this will seriously advance many industries including “green technologies” like fuel cells and carbon capture projects. • Next efforts should be focused into two main areas: • 1. Further modeling to test new pores for more systems of gases • 2. Experimentation to physically construct the pores being modeled.

  30. Further Research • As mentioned previously, further modeling and manufacture processes need to be investigated. • Interesting Systems to model would be exhaust gases of common combustion engines, air separation, ethylene/ethane, and any other difficult distillation systems • Future manufacturing techniques using electron beams to punch holes into graphene need experiments focused on reducing the diameter of the beam to widths capable of targeting groups of 2-3 carbon atoms. • New functionalizing groups for liquids • Desalination of sea water • Wastewater treatment: community and industrial • Biological screening • This would require functional group modeling that accounts for both mechanical and electrical interactions. • Require many different equations for modeling, which will increase the time and computing power needed.

  31. Literature Cited • Article taken from: • Nano Letters 2009 Volume 9 No. 12 Pages 4019-4024 • All pictures not cited on slide are from this article and belong to the authors.

  32. References • Graphene Source • Sciencedirect • Graphene Website