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Title: Microbiological-enhanced mixing across scales during in-situ bioreduction of metals and radionuclides at Department of Energy Sites

Bioreduction is being actively investigated as an effective strategy for subsurface remediation and long-term management of DOE sites contaminated by metals and radionuclides (i.e. U(VI)). These strategies require manipulation of the subsurface, usually through injection of chemicals (e.g., electron donor) which mix at varying scales with the contaminant to stimulate metal reducing bacteria. There is evidence from DOE field experiments suggesting that mixing limitations of substrates at all scales may affect biological growth and activity for U(VI) reduction. Although current conceptual models hold that biomass growth and reduction activity is limited by physical mixing processes, a growing body of literature suggests that reaction could be enhanced by cell-to-cell interaction occurring over length scales extending tens to thousands of microns. Our project investigated two potential mechanisms of enhanced electron transfer. The first is the formation of single- or multiple-species biofilms that transport electrons via direct electrical connection such as conductive pili (i.e. ‘nanowires’) through biofilms to where the electron acceptor is available. The second is through diffusion of electron carriers from syntrophic bacteria to dissimilatory metal reducing bacteria (DMRB). The specific objectives of this work are (i) to quantify the extent and rate that electrons are transported between microorganisms in physicalmore » mixing zones between an electron donor and electron acceptor (e.g. U(IV)), (ii) to quantify the extent that biomass growth and reaction are enhanced by interspecies electron transport, and (iii) to integrate mixing across scales (e.g., microscopic scale of electron transfer and macroscopic scale of diffusion) in an integrated numerical model to quantify these mechanisms on overall U(VI) reduction rates. We tested these hypotheses with five tasks that integrate microbiological experiments, unique micro-fluidics experiments, flow cell experiments, and multi-scale numerical models. Continuous fed-batch reactors were used to derive kinetic parameters for DMRB, and to develop an enrichment culture for elucidation of syntrophic relationships in a complex microbial community. Pore and continuum scale experiments using microfluidic and bench top flow cells were used to evaluate the impact of cell-to-cell and microbial interactions on reaction enhancement in mixing-limited bioactive zones, and the mechanisms of this interaction. Some of the microfluidic experiments were used to develop and test models that considers direct cell-to-cell interactions during metal reduction. Pore scale models were incorporated into a multi-scale hybrid modeling framework that combines pore scale modeling at the reaction interface with continuum scale modeling. New computational frameworks for combining continuum and pore-scale models were also developed« less
Authors:
 [1] ;  [2] ;  [1] ;  [1] ;  [3]
  1. Univ. of Illinois, Urbana-Champaign, IL (United States)
  2. Univ. of Texas, Austin, TX (United States)
  3. Univ. of Houston, TX (United States)
Publication Date:
OSTI Identifier:
1223732
Report Number(s):
DOE-Illinois--SC0006771
ER65251-1038465-001753; TRN: US1600085
DOE Contract Number:
SC0006771
Resource Type:
Technical Report
Research Org:
Univ. of Illinois, Champaign, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; BIOREMEDIATION; BACTERIA; METALS; BINDING ENERGY; ELECTRONS; REDUCTION; MIXING; BIOMASS; RADIOISOTOPES; VALENCE; GROWTH; ELECTRON TRANSFER; DIFFUSION; INJECTION; NANOWIRES; HYPOTHESIS; INTERFACES; REACTION KINETICS; FILMS; SIMULATION; SUBSTRATES; MATHEMATICAL MODELS; URANIUM; CONTAMINATION; UNDERGROUND groundwater; metals; radionuclides; dissimilatory metal reduction; micro-fluidics; pore-scale modeling; hybrid modeling