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SPECTROSCOPY


Image of the ARTIST system


SP AI-BASED T


here is a small but growing number of organisations around the world that are trialling the use of artificial intelligence (AI)-based (or assisted)


spectroscopy techniques. So, what are the most recent developments? What AI software and spectroscopy technologies are being used? What are the current and potential applications? And what innovations and trends can we expect in this expanding sector in the coming years?


INSTANTANEOUS PREDICTIONS One of the most interesting recent initiatives is the Artificial Intelligence for Spectroscopy (ARTIST) project at Aalto University in Finland, which employs AI to speed up the spectroscopic analysis of materials and the discovery of new molecules and materials. As


project lead Patrick Rinke, head of the Computational Electronic Structure Teory (CEST) group at Aalto University, explains, the idea for ARTIST was born out of the observation that conventional spectroscopy – of the experimental as well as the theoretical type – is ‘slow, expensive and often tedious.’ “Experiments require large-scale facilities or expensive equipment, and dedicated staff that maintain the equipment and have expertise in using it. Teoretical spectroscopy, that is a computational solution of the Schrödinger equation, also requires large-scale infrastructure in the form of super computers, complex software that solves the equations and expert knowledge on using the software,” he says. “Tis implies that materials are often


ECTROSCOPY


Andrew Williams reports on the projects that are bringing extra intelligence to spectroscopy


studied very thoroughly one at a time, but not on a large scale of thousands or hundreds of thousands at a time,” he adds. However, in recognition of the fact that spectroscopy is one of the essential measurement techniques in the natural sciences, and one that has been used for decades, Rinke explains that a lot of spectroscopic data is ‘already out there in the world’ – and, in its different forms, can be used to ‘establish a relation between the structure and composition of a material and its properties.’ “Tis relation is encoded in the


spectrum. With ARTIST we wanted to tap into this resource and train an AI to infer structure-spectra and spectra- property relationships from the world’s spectroscopy data. Properly trained, the AI could then make spectra or property


www.scientistlive.com 33


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