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A Combined Computational and Experimental Approach to Ultra-High Permeability Mixed Matrix Membranes for Post-Combustion CO 2 Capture Dave Hopkinson, Surendar Venna, Ali Sekizkardes, Sameh Elsaidi, Samir Budhathoki, and Jan Steckel Month 31,

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Solutions for Today | Options for Tomorrow

A Combined Computational and Experimental Approach to Ultra-High Permeability Mixed Matrix Membranes for Post-Combustion CO2 Capture Dave Hopkinson, Surendar Venna, Ali Sekizkardes, Sameh Elsaidi, Samir Budhathoki, and Jan Steckel

Month 31, 2016

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Robeson Upper Bound

Membranes need very high performance to be used in CO2 capture from fossil energy

Polymer Inorganic filler

Lloyd M.Robeson, Journal of Membrane Science, 320, 2008, 390-400 Performance vs cost plot, Courtesy: William Koros

Challenge: Need to process large amount of gases with low available driving force

Mixed Matrix Membrane

Potential Mixed Matrix Membranes

CO2 Permeability (Barrer) CO2/N2 Selectivity

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3 Two stage membrane process with air sweep

For a 10% reduction in COE over reference plant, CO2 permeance of 4000 GPU and CO2/N2 selectivity of 25 is needed

Keairns et al, A cost and performance analysis of polymeric membrane-based post- combustion carbon capture, In review

5 10 15 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

COE reduction (%)

CO2 Permeance (1000 GPU)

25 50 50 (advanced) 100 (advanced)

αCO2/N2

0.25 0.5 1 0.1

Flue Gas Secondary Air Retentate Gas To Stack

Flue Gas Membrane Module Array Air Sweep Membrane Module Array

Vent Gas CO2 Product

CPU Vacuum Pump

Secondary Air to Boiler

Air Booster ID-Fan FG Booster Fan Retentate Booster Fan FGD Vent Gas Membrane

Recycle Gas CW Water CW Water Raw CO2 Gas CPU Exhaust Gas

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MMMs can increase membrane performance beyond the Robeson Upper Bound

1 10 100 1 10 100 1000 10000 100000

CO2/N2 selectivity CO2 Permeability (Barrer)

Matrimid-UiO-66 polyphosphazene-SIFSIX PIM-BILP IXPE-Silica gel Robeson upper bound NETL Polymer 1 NETL Polymer 2 NETL Polymer 3 MMM performance

Assumptions of Robeson UB: pure polymers; 35 ⁰C; pure gas; solution-diffusion

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How do we choose the best pair of polymer and filler particle? By chemical intuition?

UiO-66 Polyphosphazenes SIFSIX POP Ionic XL Polyethers Microporous Polymers

Polyimide Silica

Polyphosphazene polymer development for mixed matrix membranes using SIFSIX-Cu-2i as performance enhancement filler particles, Journal of Membrane Science, 535 (2017) 103-112. Incorporation of benzimidazole linked polymers into Matrimid to yield mixed matrix membranes with enhanced CO2/N2 selectivity, Journal of Membrane Science, 554 (2018). Carbon Dioxide Separation from Flue Gas by Mixed Matrix Membranes with Dual Phase Microporous Polymeric Constituents, Chemical Communications, 52 (2016) 11768-11771.

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According to the Maxwell Model, properties of the polymer and filler must be complementary

5 10 15 20 25 30 35 40 45 1E+00 1E+01 1E+02 1E+03 1E+04 1E+05 1E+06 1E+07 Filler Particle Permeability (Barrer)

MMM CO2 Permeability (Barrer) MMM CO2/N2 Selectivity Matrimid CO2 Permeability = 10 Barrer Matrimid CO2/N2 selectivity = 30 Matrimid with 23% filler particle CO2/N2 Selectivity CO2 Permeability

Interface

Rpolymer Rseive

Assumptions of Maxwell Model:

Resistors in series
No particle agglomeration
Low particle loading, spherical
Ideal interface

𝑄𝑓𝑔𝑔 = 𝑄

𝑑

𝑄𝑒 + 2𝑄

𝑑 − 2∅𝑒 𝑄 𝑑 − 𝑄𝑒

𝑄𝑒 + 2𝑄

𝑑 + ∅𝑒 𝑄 𝑑 − 𝑄𝑒

For optimum selectivity, permeability of particle

should be < 100X greater than polymer

MMM permeability improvement has limitations

Journal of Molecular Structure 739 (2005) 87–98

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Computational modeling is used to predict MOF and MMM properties

Budhathoki et al, Energy Environ. Sci. 2019, 12, 1255

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Permeability of MOFs is calculated based on pore geometry

Grand Canonical Monte Carlo simulations are used to calculate CO2 and N2 solubility for rigid MOFs Molecular dynamics simulations are used to calculate CO2 and N2 diffusivity

Pore Limiting Diameter Solubility Diffusivity

MOF Permeability = Solubility X Diffusivity Mixed Matrix Membrane Permeability is from the Maxwell Model

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Predictions of MMM permeability are in good agreement with literature data

Blue markers = CO2 permeability; Green markers = N2 permeability

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CO2 permeability and CO2/N2 selectivity is calculated for MMMs with hypothetical MOFs

CO2 Permeability (Barrer) CO2/N2 Selectivity

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Cost Reduction from ~$61 to ~$46 per tonne CO2
Reduction of ~24%

Compared to pure polymer, MMMs can dramatically reduce the cost of capture

CO2 removal system: Two stage membrane with air sweep

NETL Polymer MMM

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There are many practical considerations for a high performance membrane

Support with

ptimum pore size

and density High performance polymer 1 4 3 2 Ultra-thin, defect- free selective layer Nano-size MOF with matched properties

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PIM-1/MEEP-Polyphosphazene polymers combine the best properties of each

J. Mat. Chem. A 2018,6, 22472

PIM-1: High Permeability Low Selectivity Brittle films Physical aging reduces permeability MEEP: Low Permeability High Selectivity Gummy films

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Thin film PIM-1/MEEP has reduced aging compared with neat PIM-1

PIM-1/MEEP: 150 nm Gutter layer: 250 nm PIM-MEEP suffers less aging than PIM-1 due to (1) chain-chain entanglement (2) MEEP chain/PIM-1 pore intercalations

500 nm

PIM-1 MEEP

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A hollow fiber support needs to be optimized for flux, pore size, and pore density

Our current hollow fiber membrane supports:

N2 permeance >100,000 GPU
CO2/N2 selectivity ~ 0.8

(Knudsen diffusion)

Surface pore size ~ 20 nm
Resistant to mild solvents

The support should have at least an order of magnitude higher gas flux compared to selective layer

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MOF A can now be synthesized in a variety

f particle sizes with the same structure

a b c d e f

TEM Images

(scale bars = 200 nm)

Diameter

(nm)

43±9 67±11 82±12 104±16 151±24 248±34 Surface area

(m2/g, N2 77 K)

1158±2 1353±3 1205±2 1393±3 1409±4 1410±4

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NETL MMMs are above the Robeson Upper Bound with high CO2 permeability

Neat PIM-1/MEEP Experimental MMMs Simulations Robeson Upper Bound Other reported MMMs

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Increasing MOF concentration improves PCO2 with little effect on aCO2/N2

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Kusuma et al.,Journal of Membrane Science, 533, 2017, 28–37

NETL’s membrane flue gas test unit at the National Carbon Capture Center

NCCC, Alabama

MMMs show stable performance when tested in actual flue gas with contaminants

MMM with MOF A

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Summary: NETL has taken a multifaceted approach to MMM development for low cost CO2 capture

Using high throughput computational

techniques, properties of polymer/MOF can be matched to make better MMMs

For an NETL polymer, the cost of capture can

be reduced from $61 to $46/tonne CO2

MMMs have been tested at NCCC with real

flue gas and show stable performance

MMMs developed at NETL are above the

Robeson Upper Bound

High permeance hollow fiber supports have

been fabricated

Techniques for thin film coatings of MMMs are

being developed

NETL Polymer MMM

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Thanks to our team!

MOF development: Sameh Elsaidi Jeff Culp Nathaniel Rosi Patrick Muldoon Polymer development: Ali Sekizkardes James Baker Simulations and economic analysis: Olukayode Ajayi Samir Budhathoki Jan Steckel Wei Shi Christopher Wilmer Membrane fabrication and testing: Victor Kusuma Fangming Xiang Shouliang Yi Lingxiang Zhu Zi Tong Team leads: Dave Hopkinson Kevin Resnik Program management: Lynn Brickett John Litynski

Acknowledgement: This project was funded by the Department of Energy, National Energy Technology Laboratory, an agency of the United States Government, under the Carbon Capture Field Work Proposal and in part through a support contract with AECOM (DE-FE0004000). Neither the United States Government nor any agency thereof, nor any of their employees, nor AECOM, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.