Dynamic pH variation for corrosion testing: setup development and proof of concept

Abstract

This thesis aims to develop a setup to automatically sweep the pH during corrosion testing such as the material under test experienced different environmental pH values as a function of time. Traditional corrosion tests, such as immersion and salt spray tests, are generally performed under constant pH conditions. However, when corrosion starts, acidification and alkalinisation are generated at metal surface. Thus, a protective treatment will have to withstand high or low pH conditions at some point of the service life of a component. Although performing corrosion testing under different pH using the traditional tests is in principle feasible, this would require increasing the number of tests to be performed, which requires a long time and increased cost. The test method developed in this work serves the purpose of applying a pH sweep during corrosion testing, such as the number of specimens is not increase. This should allow obtaining more reliable corrosion testing results compared to testing under a single condition. The thesis presents work on: a. Producing a baseline characterisation to evaluate the effect of pH on anodic oxides. b. Developing a new electrochemical test setup that produces the pH sweep. c. Testing the developed setup, as proof of concept, on the anodic oxides, to evaluate its effectiveness as a corrosion testing method. This thesis begins by examining the extent to which different environments damage the oxide film on the surface of aluminium alloy 2024 T3 after anodising and immersion testing in different pH zones. Following on this, the new electrochemical test set-up is designed to sweep the solution pH by electrolysis of water. A programme written in LabVIEW, coupled with dedicated hardware, can automatically sweep the solution pH value, measure the potential and polarisation resistance of the sample over time and record these data. After the new set-up was developed, 6 different surfaces were tested to evaluate the functionality of the new set-up.

Date of Award	1 Aug 2024
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Fabio Scenini (Supervisor) & Michele Curioni (Supervisor)