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Bruno NC, Mathias R, Lee YJ, Zhu G, Ahn YH, Rangnekar ND, Johnson JR, Hoy S, Bechis I, Tarzia A, Jelfs KE, McCool BA, Lively R, Finn MG. Solution-processable polytriazoles from spirocyclic monomers for membrane-based hydrocarbon separations. Nat Mater 2023:10.1038/s41563-023-01682-2. [PMID: 37845319 DOI: 10.1038/s41563-023-01682-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 09/07/2023] [Indexed: 10/18/2023]
Abstract
The thermal distillation of crude oil mixtures is an energy-intensive process, accounting for nearly 1% of global energy consumption. Membrane-based separations are an appealing alternative or tandem process to distillation due to intrinsic energy efficiency advantages. We developed a family of spirocyclic polytriazoles from structurally diverse monomers for membrane applications. The resulting polymers were prepared by a convenient step-growth method using copper-catalysed azide-alkyne cycloaddition, providing very fast reaction rates, high molecular weights and solubilities in common organic solvents and non-interconnected microporosity. Fractionation of whole Arabian light crude oil and atmospheric tower bottom feeds using these materials enriched the low-boiling-point components and removed trace heteroatom and metal impurities (comparable performance with the lighter feed as the commercial polyimide, Matrimid), demonstrating opportunities to reduce the energy cost of crude oil distillation with tandem membrane processes. Membrane-based molecular separation under these demanding conditions is made possible by high thermal stability and a moderate level of dynamic chain mobility, leading to transient interconnections between micropores, as revealed by the calculations of static and swollen pore structures.
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Affiliation(s)
- Nicholas C Bruno
- School of Chemistry & Biochemistry, Georgia Institute of Technology, Atlanta, GA, USA
| | - Ronita Mathias
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Young Joo Lee
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Guanghui Zhu
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Yun-Ho Ahn
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Neel D Rangnekar
- Corporate Strategic Research, ExxonMobil Research and Engineering, Annandale, NJ, USA
| | - J R Johnson
- Corporate Strategic Research, ExxonMobil Research and Engineering, Annandale, NJ, USA
| | - Scott Hoy
- Analytical Sciences Laboratory, ExxonMobil Research and Engineering, Annandale, NJ, USA
| | - Irene Bechis
- Department of Chemistry, Imperial College London, London, UK
| | - Andrew Tarzia
- Department of Chemistry, Imperial College London, London, UK
| | - Kim E Jelfs
- Department of Chemistry, Imperial College London, London, UK
| | - Benjamin A McCool
- Corporate Strategic Research, ExxonMobil Research and Engineering, Annandale, NJ, USA
| | - Ryan Lively
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
| | - M G Finn
- School of Chemistry & Biochemistry, Georgia Institute of Technology, Atlanta, GA, USA.
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Lee YJ, Chen L, Nistane J, Jang HY, Weber DJ, Scott JK, Rangnekar ND, Marshall BD, Li W, Johnson JR, Bruno NC, Finn MG, Ramprasad R, Lively RP. Data-driven predictions of complex organic mixture permeation in polymer membranes. Nat Commun 2023; 14:4931. [PMID: 37582784 PMCID: PMC10427679 DOI: 10.1038/s41467-023-40257-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 07/17/2023] [Indexed: 08/17/2023] Open
Abstract
Membrane-based organic solvent separations are rapidly emerging as a promising class of technologies for enhancing the energy efficiency of existing separation and purification systems. Polymeric membranes have shown promise in the fractionation or splitting of complex mixtures of organic molecules such as crude oil. Determining the separation performance of a polymer membrane when challenged with a complex mixture has thus far occurred in an ad hoc manner, and methods to predict the performance based on mixture composition and polymer chemistry are unavailable. Here, we combine physics-informed machine learning algorithms (ML) and mass transport simulations to create an integrated predictive model for the separation of complex mixtures containing up to 400 components via any arbitrary linear polymer membrane. We experimentally demonstrate the effectiveness of the model by predicting the separation of two crude oils within 6-7% of the measurements. Integration of ML predictors of diffusion and sorption properties of molecules with transport simulators enables for the rapid screening of polymer membranes prior to physical experimentation for the separation of complex liquid mixtures.
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Affiliation(s)
- Young Joo Lee
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Lihua Chen
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Janhavi Nistane
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Hye Youn Jang
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Dylan J Weber
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Joseph K Scott
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Neel D Rangnekar
- ExxonMobil Technology and Engineering Company, Annandale, NJ, 08801, USA
| | - Bennett D Marshall
- ExxonMobil Technology and Engineering Company, Annandale, NJ, 08801, USA
| | - Wenjun Li
- ExxonMobil Technology and Engineering Company, Annandale, NJ, 08801, USA
| | - J R Johnson
- ExxonMobil Technology and Engineering Company, Annandale, NJ, 08801, USA
| | - Nicholas C Bruno
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - M G Finn
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Rampi Ramprasad
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
| | - Ryan P Lively
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
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Li S, Dong R, Musteata VE, Kim J, Rangnekar ND, Johnson JR, Marshall BD, Chisca S, Xu J, Hoy S, McCool BA, Nunes SP, Jiang Z, Livingston AG. Hydrophobic polyamide nanofilms provide rapid transport for crude oil separation. Science 2022; 377:1555-1561. [PMID: 36173852 DOI: 10.1126/science.abq0598] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Hydrocarbon separation relies on energy-intensive distillation. Membrane technology can offer an energy-efficient alternative but requires selective differentiation of crude oil molecules with rapid liquid transport. We synthesized multiblock oligomer amines, which comprised a central amine segment with two hydrophobic oligomer blocks, and used them to fabricate hydrophobic polyamide nanofilms by interfacial polymerization from self-assembled vesicles. These polyamide nanofilms provide transport of hydrophobic liquids more than 100 times faster than that of conventional hydrophilic counterparts. In the fractionation of light crude oil, manipulation of the film thickness down to ~10 nanometers achieves permeance one order of magnitude higher than that of current state-of-the-art hydrophobic membranes while retaining comparable size- and class-based separation. This high permeance can markedly reduce plant footprint, which expands the potential for using membranes made of ultrathin nanofilms in crude oil fractionation.
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Affiliation(s)
- Siyao Li
- Barrer Center, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Ruijiao Dong
- Barrer Center, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.,Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Valentina-Elena Musteata
- King Abdullah University of Science and Technology, Biological and Environmental Science and Engineering Division, Advanced Membranes and Porous Materials Center, Thuwal 23955-6900, Saudi Arabia
| | - Jihoon Kim
- Barrer Center, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.,Process Design and Research Center, Chemical and Process Technology Division, Korea Research Institute of Chemical Technology, Daejeon 34114, South Korea.,School of Engineering and Materials Science, Queen Mary University of London, London E1 4NS, UK
| | - Neel D Rangnekar
- Corporate Strategic Research, ExxonMobil Research and Engineering, Annandale, NJ 08801, USA
| | - J R Johnson
- Corporate Strategic Research, ExxonMobil Research and Engineering, Annandale, NJ 08801, USA
| | - Bennett D Marshall
- Corporate Strategic Research, ExxonMobil Research and Engineering, Annandale, NJ 08801, USA
| | - Stefan Chisca
- King Abdullah University of Science and Technology, Biological and Environmental Science and Engineering Division, Advanced Membranes and Porous Materials Center, Thuwal 23955-6900, Saudi Arabia
| | - Jia Xu
- Barrer Center, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.,Key Laboratory of Marine Chemistry Theory and Technology (Ministry of Education), School of Materials Science and Engineering, College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, China
| | - Scott Hoy
- Corporate Strategic Research, ExxonMobil Research and Engineering, Annandale, NJ 08801, USA
| | - Benjamin A McCool
- Corporate Strategic Research, ExxonMobil Research and Engineering, Annandale, NJ 08801, USA
| | - Suzana P Nunes
- King Abdullah University of Science and Technology, Biological and Environmental Science and Engineering Division, Advanced Membranes and Porous Materials Center, Thuwal 23955-6900, Saudi Arabia
| | - Zhiwei Jiang
- Barrer Center, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.,School of Engineering and Materials Science, Queen Mary University of London, London E1 4NS, UK
| | - Andrew G Livingston
- Barrer Center, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.,School of Engineering and Materials Science, Queen Mary University of London, London E1 4NS, UK
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