Award Abstract # 2029282
EFRI DCheM: One-step conversion of CH4 and CO2 to liquid fuels with the use of a multi-functional pseudo catalytic system

NSF Org: EFMA
Emerging Frontiers & Multidisciplinary Activities
Recipient: OHIO STATE UNIVERSITY, THE
Initial Amendment Date: September 1, 2020
Latest Amendment Date: October 14, 2020
Award Number: 2029282
Award Instrument: Standard Grant
Program Manager: Carole Read
cread@nsf.gov
 (703)292-2418
EFMA
 Emerging Frontiers & Multidisciplinary Activities
ENG
 Directorate For Engineering
Start Date: September 15, 2020
End Date: August 31, 2024 (Estimated)
Total Intended Award Amount: $2,000,000.00
Total Awarded Amount to Date: $2,000,000.00
Funds Obligated to Date: FY 2020 = $2,000,000.00
History of Investigator:
  • Liang-Shih Fan (Principal Investigator)
    fan.1@osu.edu
  • Vicky Doan-Nguyen Trigg (Co-Principal Investigator)
  • Andrew Tong (Co-Principal Investigator)
  • Joel Paulson (Co-Principal Investigator)
Recipient Sponsored Research Office: Ohio State University
1960 KENNY RD
COLUMBUS
OH  US  43210-1016
(614)688-8735
Sponsor Congressional District: 03
Primary Place of Performance: The Ohio State University
340A CBEC, 151 W. Woodruff Ave
Columbus
OH  US  43210-1350
Primary Place of Performance
Congressional District:
03
Unique Entity Identifier (UEI): DLWBSLWAJWR1
Parent UEI: MN4MDDMN8529
NSF Program(s): EFRI Research Projects
Primary Program Source: 01002021DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s): 763300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

Stranded natural gas resources are currently flared due to economic limitations associated with prohibitive transportation costs and small reservoir sizes. Successfully transforming these remotely distributed gas resources to useful energy products will contribute significantly to the U.S. energy economy and its energy security. The goal of this project is to develop a small-scale modular chemical processing system to convert stranded natural gas and carbon dioxide into value-added liquid fuel products. This technology as proposed is transformative and environmentally sustainable as it will achieve both the monetization of stranded gas resources and will consume carbon dioxide as a feedstock in the gas conversion process. The researchers are Ohio State University (OSU) faculty members who will use a data-driven approach to integrate the reactor system components and will further the fundamental understanding of the gas upgrading chemistry by identifying an efficient catalyst to promote the reactions. This interdisciplinary OSU project team will work with industrial partners Velocys, Inc. and Jan Lerou LLC. to leverage their industrial expertise to optimize the system design using an advanced manufacturing protocol and state-of-the-art computational tools. The?proposed project?will advance fundamental understanding of liquid fuel conversion processes as well as provide multiple learning experiences for K-12, undergraduate, and graduate students. The project team will work with local high schools to promote the inclusion of under-represented students in its research activities. The?foundational knowledge?generated by this project will also serve as a science, engineering, and technology-oriented learning resource for undergraduate and graduate education.

The proposed work addresses the technological and scientific barriers to building a thermo-catalytic flared-gas reforming (TC-FGR) system for monetizing stranded gas resources. The TC-FGR system is a small-scale, modular GTL (gas to liquid) process that intensifies syngas production from natural gas and integrates a commercially demonstrated micro-channel F-T (Fischer-Tropsch) synthesis system in one reactor vessel. Furthermore, a novel pseudo-catalytic metal oxide (PMO) material will be developed to reduce the unit operations required for conventional small-scale F-T systems. The research team will develop the PMO material using first-principles computational methods and experimental parametric testing. The team also will develop a machine learning-informed integrated, flexible reactor design that intensifies modular GTL systems and will assess the economic feasibility of the proposed technology. The PMO is an iron-based metal oxide composite, capable of exhibiting several oxidation states, that allows CH4 to react with the PMO, abstracting the lattice oxygen to form partial-combustion products CO and H2. At the same time, CO2/H2O re-oxidizes the PMO forming additional CO/H2. This unique activation with the PMO acting as the oxygen mediator adds additional degrees of freedom for process optimization, enhancing the production rate of syngas as well as providing a means of controlling its composition. The unique microchannel design used by the industrial partner of this project results in enhanced heat and mass transfer capabilities; this coupled with a highly active catalyst allows for productivity that is 10-15 times higher than conventional F-T systems. The project will synergistically use multi-scale models and advanced optimization/control methods at every project step to ensure that the intensified TC-FGR system is viable in distributed applications with small economic margins. The resulting integrated, modular TC-FGR system can be deployed over several wells, providing a transformative alternative to the wasteful gas flaring that is current practice. Widespread applications of the TC-FGR stranded gas process will further mitigate greenhouse gas emissions through carbon dioxide conversion. Sustainable technology such as TC-FGR constitutes a bridge towards reducing the carbon footprint of fossil fuels.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Paulson, Joel A. and Lu, Congwen "COBALT: COnstrained Bayesian optimizAtion of computationaLly expensive grey-box models exploiting derivaTive information" Computers & Chemical Engineering , v.160 , 2022 https://doi.org/10.1016/j.compchemeng.2022.107700 Citation Details
Kudva, Akshay and Sorourifar, Farshud and Paulson, Joel A. "Constrained robust Bayesian optimization of expensive noisy black?box functions with guaranteed regret bounds" AIChE Journal , v.68 , 2022 https://doi.org/10.1002/aic.17857 Citation Details
Paulson, Joel A. and Makrygiorgos, Georgios and Mesbah, Ali "Adversarially robust Bayesian optimization for efficient auto?tuning of generic control structures under uncertainty" AIChE Journal , v.68 , 2022 https://doi.org/10.1002/aic.17591 Citation Details
Liu, Yan and Qin, Lang and Pan, Jianhua and Chen, Yu-Yen and Goetze, Josh W. and Xu, Dikai and Fan, Jonathan A. and Fan, Liang-Shih "SBA-16-Mediated Nanoparticles Enabling Accelerated Kinetics in Cyclic Methane Conversion to Syngas at Low Temperatures" ACS Applied Energy Materials , v.3 , 2020 https://doi.org/10.1021/acsaem.0c01495 Citation Details

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