La Trobe
Mg dissolution npj Mater Degrad published.pdf (1.54 MB)

Exploring the Structure-Property Relationship of Magnesium Dissolution Modulators

Download (1.54 MB)
journal contribution
posted on 09.02.2021, 01:41 by David Winkler, Tim Würger, D Mei, B Vaghefinazari, Sviatlana Lamaka, M Zheludkevich, R Meißner, Christian Feiler

https://www.nature.com/articles/s41529-020-00148-z

Abstract: Small organic molecules that modulate the degradation behavior of Mg constitute benign and useful materials to modify the service environment of light metal materials for specific applications. The vast chemical space of potentially effective compounds can be explored by machine learning-based quantitative structure-property relationship models, accelerating the discovery of potent dissolution modulators. Here, we demonstrate how unsupervised clustering of a large number of potential Mg dissolution modulators by structural similarities and sketch-maps can predict their experimental performance using a kernel ridge regression model. We compare the prediction accuracy of this approach to that of a prior artificial neural networks study. We confirm the robustness of our data-driven model by blind prediction of the dissolution modulating performance of 10 untested compounds. Finally, a workflow is presented that facilitates the automated discovery of chemicals with desired dissolution modulating properties from a commercial database. We subsequently prove this concept by blind validation of five chemicals.

History

Publication Date

08/01/2021

Journal

npj Materials Degradation

Volume

5

Article Number

2

Publisher

Springer Nature

Rights Statement

The Author reserves all moral rights over the deposited text and must be credited if any re-use occurs. Documents deposited in OPAL are the Open Access versions of outputs published elsewhere. Changes resulting from the publishing process may therefore not be reflected in this document. The final published version may be obtained via the publisher’s DOI. Please note that additional copyright and access restrictions may apply to the published version.

Usage metrics

Journal Articles

Categories

Licence

Exports