The communication titled “Data Driven Tools to Select Corrosion Inhibitors”, co-authored by Tiago L. P. Galvão, Gerard Novell-Leruth, Alena Kuznetsova, Inês Ferreira, João Tedim and José R. B. Gomes, was awarded the best poster award at the 14th Physical Chemistry Meeting, a biennial conference organized by the Portuguese Chemical Society, which was held online on 29-31 March 2021. The research results were obtained in the frame of project DATACOR (https://datacorproject.wixsite.com/datacor), which aims to produce data driven tools to help corrosion scientists and engineers select and design more efficient organic corrosion inhibitors for replacing traditional anti-corrosion pigments that can cause acute toxicity problems to human health and the environment.
The research team has built an interactive exploratory data tool for the selection of the ideal corrosion inhibitor taking into account different application conditions (type of alloy, electrolyte, pH, etc.) based on previously published information (https://datacor.shinyapps.io/cordata/), and is currently developing multicondition machine learning models (https://doi.org/10.1021/acs.jpcc.9b09538) and an online tool to perform an initial virtual screen of potential molecules to be tested as corrosion inhibitors. These two approaches will contribute to the digitalization of inhibitor search, helping speed up research in corrosion science and tailor corrosion protective technologies in a more efficient and condition specific manner.
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