Use of Nanoscale Iron and Bimetallic Particles for Environmental Remediation: A Review of Field-scale Applications

Author(s):  
Jacqueline Quinn ◽  
Daniel Elliott ◽  
Suzanne O'Hara ◽  
Alexa Billow
Author(s):  
Bin Wang ◽  
Yin Feng ◽  
John Blears ◽  
Karsten Thompson ◽  
Richard Hughes

Nanoparticle (NP) transport is increasingly relevant to subsurface engineering applications such as aquifer characterization, fracture electromagnetic imaging and environmental remediation. An efficient field-scale simulation framework is critical for predicting NP performance and designing subsurface applications. In this work, for the first time, a streamline-based model is presented to simulate NP transport in field-scale subsurface systems. It considers a series of behaviors exhibited by engineered nanoparticles (NPs), including time-triggered encapsulation, retention, formation damage effects and variable nanofluid viscosity. The key methods employed by the algorithm are streamline-based simulation (SLS) and an operator-splitting (OS) technique for modeling NP transport. SLS has proven to be efficient for solving transport in large and heterogeneous systems, where the pressure and velocity fields are firstly solved on underlying grids using finite-difference (FD) methods. After tracing streamlines, one-dimensional (1D) NP transport is solved independently along each streamline. The adoption of OS enhances flexibility for the entire solution procedure by allowing different numerical schemes to solve different governing equations efficiently and accurately. For the NP transport model, an explicit FD scheme is used to solve the advection term, an implicit FD scheme is used for the diffusion term and an adaptive numerical integration is used to solve the retention terms. The model is implemented in an in-house streamline-based code, which is verified against analytical solutions, a commercial FD reservoir simulator (ECLIPSE) and an academic FD colloid transport code (MNMs). For a 1D homogeneous case, the effluent breakthrough curves (BTC) produced by the in-house simulator are in good agreement with the analytical solution and MNMs, respectively. For a two-dimensional (2D) heterogeneous case, the BTC and concentration pattern of the in-house simulator all match well with the solution produced by commercial simulator. Simulations on a synthetic three-dimensional (3D) nanocapsule application engineering design case, are performed to investigate the effect of fluid and NP properties on the displacement pattern of an existing subsurface fluid.


2020 ◽  
Vol 48 (2) ◽  
pp. 399-409
Author(s):  
Baizhen Gao ◽  
Rushant Sabnis ◽  
Tommaso Costantini ◽  
Robert Jinkerson ◽  
Qing Sun

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to ‘knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.


2016 ◽  
Vol 15 (4) ◽  
pp. 923-934 ◽  
Author(s):  
Mohammadreza Kamali ◽  
Ana Paula Duarte Gomes ◽  
Zahra Khodaparast ◽  
Tahereh Seifi

2019 ◽  
Author(s):  
Chem Int

Iron nanoparticles have gained tremendous attention due to their application in magnetic storage media, ferrofluids, biosensors, catalysts, separation processes, environmental remediation and antibacterial activity. In the present paper, iron nanoparticles were synthesized using aqueous flower extract of Piliostigma thonningii, a natural nontoxic herbal infusion. Iron nanoparticles were generated by reaction of ferrous chloride solution with the flower extract. The reductants present in the flower extract acted as reducing and stabilizing agents. UV-vis analysis of the iron nanoparticles showed continuous absorption in the visible range suggesting the iron nanoparticles were amorphous. This was confirmed by X-ray diffraction (XRD) analysis which did not have distinct diffraction peaks. Scanning electron microscopy (SEM) analysis revealed that the synthesized iron nanoparticles were aggregated as irregular clusters with rough surfaces. FT-IR studies showed the functional groups that participated in the bio-reduction process to include a C-H stretch (due to alkane CH3, CH2 or CH), C=O stretch (due to aldehydes), O-H bend (due to tert-alcohol or phenol), C-O stretch (due to aldehydes or phenols) and C-O stretch (due to alcohols) corresponding to absorptions at 2929.00, 1721.53, 1405.19, 1266.31 and 1030.02 cm-1 respectively. The iron nanoparticles showed significant antibacterial activity against Escharichia coli and Staphylococcus aureus suggesting potential antibacterial application.


1991 ◽  
Vol 24 (5) ◽  
pp. 85-96 ◽  
Author(s):  
Qingliang Zhao ◽  
Zijie Zhang

By means of simulated tests of a laboratory–scale oxidation pond model, the relationship between BOD5 and temperature fluctuation was researched. Mathematical modelling for the pond's performance and K1determination were systematically described. The calculation of T–K1–CeCe/Ci) was complex but the problem was solved by utilizing computer technique in the paper, and the mathematical model which could best simulate experiment data was developed. On the basis of experiment results,the concept of plug–ratio–coefficient is also presented. Finally the optimum model recommended here was verified with the field–scale pond data.


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