| 项目编号: | 1511346
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| 项目名称: | GOALI: Development of Spatiotemporal Metabolic Models for Syngas Fermentation in Industrial Bubble Column Reactors |
| 作者: | Michael Henson
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| 承担单位: | University of Massachusetts Amherst
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| 批准年: | 2014
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| 开始日期: | 2015-06-01
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| 结束日期: | 2018-05-31
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| 资助金额: | USD300000
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Engineering - Chemical, Bioengineering, Environmental, and Transport Systems
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| 英文关键词: | gas fermentation
; bubble column reactor
; spatiotemporal metabolic modeling
; syngas
; umass
; lanzatech
; model
; industrial bubble column reactor
; spatiotemporal metabolic model
; student
; method development work
; goali project
; bubble column model development work
; industrial leader
; synga fermentation
; research
; model refinement
; transport model
; efficient model formulation
; commercial development
; such spatiotemporal metabolic model
; impact industrial practice
; modeling approach
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| 英文摘要: | Henson - 1511346
One of the most promising routes to renewable liquid fuels and chemicals is the fermentation of waste carbon by specialized microbes. This can not only enable advanced biofuel and renewable chemical production but could also help reduce carbon emissions. Commercial development of gas fermentation technology is being led by emerging companies such as LanzaTech, but many fundamental research problems must be addressed to further advance the technology towards economic competitiveness. A particularly important challenge is to develop integrated metabolic and transport models that describe gas fermentation in industrially relevant bubble column reactors. The development of such spatiotemporal metabolic models is an emerging research problem with numerous potential applications in environmental science, biotechnology, bioenergy and human health. The objectives of this GOALI project are to develop general tools for spatiotemporal metabolic modeling and to evaluate the methods through application to gas fermentation in bubble column reactors.
The PIs plan to convert CO-rich waste streams as well as synthesis gas (syngas - mainly comprised of H2/CO/CO2) to liquid fuels and chemicals in bubble column reactors. His proposed modeling approach involves combining genome-scale reconstructions of species metabolism with transport equations that govern the relevant convective and/or diffusional processes within the spatially varying system. The resulting models consist of linear programs for intracellular metabolism embedded within partial different equations for spatial and dynamic variations within the extracellular environment. UMass will develop efficient model formulation and robust numerical solution techniques using gas fermentation and biofilm growth problems as in silico testbeds. The syngas fermentation models will be developed in collaboration with LanzaTech, an industrial leader in gas fermentation and bubble column reactor technology. These models will be formulated by combining a recently developed genome-scale metabolic reconstruction of the syngas fermenting bacterium Clostridium ljungdahlii with convective transport equations for the feed gas components and the major metabolic byproducts, ethanol and acetate. Following initial testing at UMass, the syngas fermentation models will be validated with data collected from a LanzaTech laboratory/pilot facility. Using these data, the spatiotemporal metabolic models will be refined as necessary to capture the key features of industrial bubble column reactors.
Broader Impacts: The proposed research will both advance fundamental research and impact industrial practice. While a few isolated papers have been published on spatiotemporal metabolic modeling, our research will produce a considerably more general treatment of this important problem. We expect the application work focused on syngas fermentation to produce new computational tools to simulate, design and optimize industrial bubble column reactors. The UMass graduate student supported by NSF funds will complete a four month internship at LanzaTech?s Skokie, IL research facility to participate in data collection and to perform model refinement and validation. The student will be co-advised by the two project investigators, with Prof. Henson (UMass, PI) leading the methods development work and Dr. Griffin (LanzaTech, co-PI) overseeing the bubble column model development work. While at LanzaTech, the student will work with a broad array of scientists and engineers in a highly multidisciplinary and team oriented environment. Tight integration of the UMass and LanzaTech efforts will be achieved through frequent email exchanges, biweekly videoconferences and biannual project meetings. At least two undergraduate students will participate in the research by having the funded Ph.D. student serve a partial advising role. These students will interact with other students funded through the Institute of Massachusetts Biofuels Research (TIMBR) and participate in ongoing TIMBR activities. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/94532
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| Appears in Collections: | 影响、适应和脆弱性
气候减缓与适应
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| Recommended Citation: | |
Michael Henson. GOALI: Development of Spatiotemporal Metabolic Models for Syngas Fermentation in Industrial Bubble Column Reactors. 2014-01-01.
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