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Investigating an electroplating method of Co-Cr alloys: A design of experiment approach to determine the impact of key factors on the electroplating process
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
2018 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Solar energy is increasingly being considered a promising solution to reduce the emissions of CO2 and green house gas. The performance of solar collectors largely depends on the ability to absorb incoming solar radiation with minimal thermal radiation losses. To weigh the potential absorbed energy to thermal losses, the performance criterion (PC) can be used, calculated as PC =α−xε, where α is absorptance, ε is emittance and x is a scaling factor < 1. It has been shown by G. Vargas et al. that Co-Cr alloys excibit great potential (α = 0.98 and ε = 0.03) for use in solar concentrators. The main goal of this project is to quantify the impact of key factors (controlled input variables) on an electroplating process of Co-Cr alloys, using the design of experiment (DOE) methodology. It is part of an ongoing collaboration between Absolicon and the physics department at Umeå university. Six factors were investigated using a fractional factorial (FrF) design. Data was collected through a series of experiments where stainless steel substrates were electroplated with Co-Cr alloys. The resulting samples were analyzed in terms of α and ε as well as the quality of deposition (QD). Using the experimental results, three models were made in a DOE-software called MODDE. Models are used to correlate the factors with each response, i.e. α, ε and QD. Ideally the predictive power of the models (Q2) should be as high as possible, and at least > 0.5. The analysis of variance (ANOVA) test was used to determine the significance of the models. Based on the models, the ’Optimizer’ tool in MODDE was used to predict two set of optimum factor settings, producing two samples, S1 and S2. S1 and S2 were evaluated in terms of α, ε and Qas well as chemical composition and structural properties of the coatings. The predictive power of the models was 0.49 for α, 0.38 for ε and 0.53 for QD. The predictive power of the models were therefore limited. ANOVA-test showed that the models for α and Qwere statistically significant. For all three responses the significant effects were mostly two factor interactions. All three models showed significant lack of fit (model error) as a result of high reproducibility. S1 had the best PCAbsolicon (performance criterion for Absolicons solar collectors) of all samples with 0.858. S2 was not as good, even though it was predicted to have a higher value of PCAbsolicon by MODDE. EDS, XPS and SEM measurements of samples S1 and S2 showed that the two samples were very similar in terms of chemical composition. The main difference was that the coating of S1 was more porous, and also thicker than S2, 0.81 μm compared to 0.26 μm. Even though the models showed some predictive capabilities, the impact of the factors could not be fully determined. That is due to the nature of the FrF-design, which cannot accurately determine two-factor interactions.

Place, publisher, year, edition, pages
2018. , p. 62
Keywords [en]
design of experiment, electroplating, selective surfaces, Co-Cr, Fractional factorial design, concentrating solar collectors
Keywords [sv]
experimentell design, elektroplätering, solfångare
National Category
Physical Sciences
Identifiers
URN: urn:nbn:se:umu:diva-148512OAI: oai:DiVA.org:umu-148512DiVA, id: diva2:1214585
External cooperation
Absolicon Solar Collector AB
Subject / course
Energiteknik
Educational program
Master of Science Programme in Energy Engineering
Supervisors
Examiners
Available from: 2018-06-07 Created: 2018-06-07 Last updated: 2018-06-07Bibliographically approved

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