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Artificial Intelligence applied to X-ray / synchrotron techniques


Artificial intelligence is an emerging tool that is becoming ubiquitous in X-ray and synchrotron facilities. Mindful of its importance and as part of the upgrade of French CRG beamlines at ESRF, we also wish to discuss how these tools can be useful for us and for the community of scientists working on X-rays or synchrotron techniques. Therefore, we will start a series of webinars (online seminars) dedicated to applications of artificial intelligence (machine and deep learning) to techniques based on x-rays and synchrotrons. The next webinar of this series will be:


Transforming the analysis of X-ray Absorption Spectra using Deep Neural Networks

Tom Penfold (Newcastle University, UK)

April 22 at 2:00 pm / 14:00 (CET)

It is now possible for X-ray spectroscopy to deliver highly-detailed information about the local geometric, electronic and spin structure of matter in a broad range of different environments and under challenging operating conditions, e.g. in operando measurements of batteries and femtosecond time-resolved studies. However, to translate observation into scientific breakthroughs these experiments bring into focus a new challenge: How do we efficiently and accurately analyse these data to ensure that valuable quantitative information encoded in each spectrum can be extracted?  In this presentation, I will discuss our recent work on supervised machine learning for X-ray absorption spectra through the development of a novel deep neural network (DNN). I show that we are able to estimate Fe K-edge X-ray absorption near-edge structure spectra in less than a second with no input beyond geometric information about the local environment of the absorption site. The performance of the DNN is promising, as illustrated by its application to the structural refinement of tris(bipyridine)iron(II) and nitrosylmyoglobin.

The link to connect to the webinar will be sent by e-mail. To receive it, please register for free by clicking here:


For more information about upcoming webinars on this series, please click here.