Optimizing the Electrochemical Cell Variables Using Taguchi and Grey Relational Analysis (GRA)
Publish place: Advanced Journal of Chemistry-Section A، Vol: 8، Issue: 5
Publish Year: 1404
Type: Journal paper
Language: English
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Document National Code:
JR_AJCS-8-5_012
Index date: 12 November 2024
Optimizing the Electrochemical Cell Variables Using Taguchi and Grey Relational Analysis (GRA) abstract
The electrochemical method of recovering tungstic acid uses nitric acid as the electrolyte. At the anode, carbide material is oxidized, yielding insoluble tungstic acid (H2WO4) and cobalt ions in the solution. Tungstic acid is then used to make tungsten oxide (WO3), a valuable industrial material. Initially, experiments in this study were prepared and carried out using experimental design approaches and grey relational analysis (GRA), which was based on the Taguchi method and carried out using Minitab17 software. Datafit (Versions 9.1) software was used to create regression models for predicting weight loss and energy usage. The goal function of the tests was anode weight loss/hour and electrochemical cell power consumption, whereas the impacting variables were current density, electrolyte concentration, cell temperature, and cathode electrode type. The optimal electrochemical cell has a current density of 4000 A/m2, 1.8 M electrolyte concentration and 70 °C cell temperature, and an aluminum cathode.
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Optimizing the Electrochemical Cell Variables Using Taguchi and Grey Relational Analysis (GRA) authors
Lubna M. Taj-Aldeen
Department of Metallurgical Engineering, College of Material's Engineering, University of Babylon, Hila, Iraq
Haydar Al-Ethari
Department of Metallurgical Engineering, College of Material's Engineering, University of Babylon, Hila, Iraq
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