| 1. |
- Danish, M., et al.
(författare)
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The Effect of Chelating Agents on Enhancement of 1,1,1-Trichloroethane and Trichloroethylene Degradation by Z-nZVI-Catalyzed Percarbonate Process
- 2016
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Ingår i: Water, Air and Soil Pollution. - : Springer Science and Business Media LLC. - 0049-6979 .- 1573-2932. ; 227:9
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Tidskriftsartikel (refereegranskat)abstract
- This study primarily focused on the performance of 1,1,1-trichloroethane (1,1,1-TCA) and trichloroethylene (TCE) degradation involving redox reactions in zeolite-supported nanozerovalent iron composite (Z-nZVI)-catalyzed sodium percarbonate (SPC) system in aqueous solution with five different chelating agents (CAs) including oxalic acid (OA), citric acid monohydrate (CAM), glutamic acid (GA), ethylenediaminetetraacetic acid (EDTA), and L-ascorbic acid (ASC). The experimental results showed that the addition of OA achieved almost 100 % degradation of 1,1,1-TCA and TCE. The addition of CAM and GA also significantly increased the contaminant degradation, while excessive addition of them inhibited the degradation. In contrast, EDTA and ASC showed negative impacts on 1,1,1-TCA and TCE degradation, which might be due to the strong reactivity with iron and OH● scavenging characteristics. The efficiency with CA addition on 1,1,1-TCA and TCE degradation decreased in the order of OA > CAM > GA > no CAs > EDTA > ASC. The extensive investigations using probe compound tests and scavenger tests revealed that both contaminants degraded primarily by OH● and O2 –● in chelated Z-nZVI-catalyzed SPC system. The significant improvement in 1,1,1-TCA and TCE degradation efficiency was accredited due to the (i) increase in concentration of Fe2+ and (ii) continuous generation of OH● radicals and maintenance of its quantity, ensuring more stability in the aqueous solution. Finally, the complete mineralization of 1,1,1-TCA and TCE in the OA-chelated, Z-nZVI-catalyzed SPC system was confirmed without any chlorinated intermediate by-products detected, demonstrating a great potential of this technique in the application of groundwater remediation.
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| 2. |
- Lin, G., et al.
(författare)
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A regularizing Kohn-Vogelius formulation for the model-free adsorption isotherm estimation problem in chromatography
- 2018
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Ingår i: Applicable Analysis. - : Informa UK Limited. - 0003-6811 .- 1563-504X. ; 97:1, s. 13-40
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Tidskriftsartikel (refereegranskat)abstract
- Competitive adsorption isotherms must be estimated in order to simulate and optimize modern continuous modes of chromatography in situations where experimental trial-and-error approaches are too complex and expensive. The inverse method is a numeric approach for the fast estimation of adsorption isotherms directly from overloaded elution profiles. However, this identification process is usually ill-posed. Moreover, traditional model-based inverse methods are restricted by the need to choose an appropriate adsorption isotherm model prior to estimate, which might be very hard for complicated adsorption behavior. In this study, we develop a Kohn-Vogelius formulation for the model-free adsorption isotherm estimation problem. The solvability and convergence for the proposed inverse method are studied. In particular, using a problem-adapted adjoint, we obtain a convergence rate under substantially weaker and more realistic conditions than are required by the general theory. Based on the adjoint technique, a numerical algorithm for solving the proposed optimization problem is developed. Numerical tests for both synthetic and real-world problems are given to show the efficiency of the proposed regularization method.
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| 3. |
- Zhang, Ye, 1984-, et al.
(författare)
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An adaptive regularization algorithm for recovering the rate constant distribution from biosensor data
- 2018
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Ingår i: Inverse Problems in Science and Engineering. - Oxon, UK : Taylor & Francis. - 1741-5977 .- 1741-5985. ; 26:10, s. 1464-1489
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Tidskriftsartikel (refereegranskat)abstract
- We present here the theoretical results and numerical analysis of a regularization method for the inverse problem of determining the rate constant distribution from biosensor data. The rate constant distribution method is a modern technique to study binding equilibrium and kinetics for chemical reactions. Finding a rate constant distribution from biosensor data can be described as a multidimensional Fredholm integral equation of the first kind, which is a typical ill-posed problem in the sense of J. Hadamard. By combining regularization theory and the goal-oriented adaptive discretization technique, we develop an Adaptive Interaction Distribution Algorithm (AIDA) for the reconstruction of rate constant distributions. The mesh refinement criteria are proposed based on the a posteriori error estimation of the finite element approximation. The stability of the obtained approximate solution with respect to data noise is proven. Finally, numerical tests for both synthetic and real data are given to show the robustness of the AIDA.
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| 4. |
- Zhang, Ye, et al.
(författare)
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An adjoint method in inverse problems of chromatography
- 2017
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Ingår i: Inverse Problems in Science and Engineering. - : Taylor & Francis. - 1741-5977 .- 1741-5985. ; 25:8, s. 1112-1137
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Tidskriftsartikel (refereegranskat)abstract
- How to determine adsorption isotherms is an issue of significant importance in chromatography. A modern technique of obtaining adsorption isotherms is to solve an inverse problem so that the simulated batch separation coincides with actual experimental results. In this work, as well as the natural least-square approach, we consider a Kohn-Vogelius type formulation for the reconstruction of adsorption isotherms in chromatography, which converts the original boundary fitting problem into a domain fitting problem. Moreover, using the first momentum regularizing strategy, a new regularization algorithm for both the Equilibrium-Dispersive model and the Transport-Dispersive model is developed. The mass transfer resistance coefficients in the Transport-Dispersive model are also estimated by the proposed inverse method. The computation of the gradients of objective functions for both of the two models is derived by the adjoint method. Finally, numerical simulations for both a synthetic problem and a real-world problem are given to show the robustness of the proposed algorithm.
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