This PhD provides an exciting and unique opportunity for someone to work at the interface between two quite different fields, namely corrosion control and pharmaceutical drug design, to address the following hypothesis:
Computational Molecular Design can be applied to in silico selection of high performing organic corrosion inhibitors.
Corrosion of metallic engineering components remains a bête-noire of our modern world, resulting in significant economic and other costs. Consequently, engineers seek to minimise corrosion-induced degradation using approaches including
operando addition of organic species, known as corrosion inhibitors, that reduce corrosion through substrate binding. This approach is well established, and highly effective in many real-world applications. Selection of these inhibitors is, however, currently expensive and time consuming, relying largely on trial-and-error testing.
The goal of this project is to minimise the burden of searching for suitable inhibitors and to broaden the pool of candidates, through using state of the art computational molecular design (CMD) approaches that have transformed the search for pharmaceuticals to facilitate rapid in silico selection of organic corrosion inhibitors. Key structure/performance data concerning published corrosion inhibitor studies will be collated to produce a searchable virtual library that can be used to identify correlations between molecular structure and corrosion inhibitor performance. These data will be employed to drive searches of a broad range of chemical compound databases to find alternative, higher performing, corrosion inhibitors; in silico predictive power will be validated through experimental measurements of corrosion inhibitor performance. In turn, these measurements will inform new designs creating a virtuous circle of improvement. Concepts from pharmaceutical design including matched molecular pairs, novel encodings of molecular shape and quantum mechanical “theoceptor” approaches will all be explored and applied.
Academic background of candidates
Applicants should have or expect to achieve at least a 2.1 honours degree in Materials Science, Chemistry, Physics, Mathematics or a related subject.
At the University of Manchester, we pride ourselves on our commitment to fairness, inclusion and respect in everything we do. We welcome applications from people of all backgrounds and identities and encourage you to bring your whole self to work and study. We will ensure that your application is given full consideration without regard to your race, religion, gender, gender identity or expression, sexual orientation, nationality, disability, age, marital or pregnancy status, or socioeconomic background. All PhD places will be awarded on the basis of merit.
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