Complexity to clarity: detecting, identifying and analysing complex materials systems at the molecular level with machine learning

点击翻译按钮获取中文摘要

This project aims to develop machine learning methodologies to characterise, classify and predict the properties of complex materials systems including nanostructured functional surfaces, multilayers and coatings. This project expects to generate a framework for deep level and precise forensic investigation of materials type, source, origin and manufacture, employing self organising maps and innovative hyperspectral data visualisation. Expected outcomes of this project include enhanced capacity to investigate unknown materials, deconstruct complex failures and degradation processes and predict structure - function relationships. This will provide significant benefits in addressing threats from emerging materials technologies and processes.