Materials informatics: Moving beyond screening via generative machine learning models

You are invited to join us for the Physical Sciences in NFDI colloquium on June 15, 2023 at 11:00, in Berlin and online. Taylor D. Sparks (University of Utah) will give the talk Materials informatics: Moving beyond screening via generative machine learning models.


Machine learning already enables the discovery of new materials by providing rapid predictions of properties to complement slower calculations and experiments. However, a persistent criticism of machine learning enabled materials discovery is that new materials are very similar, both chemically and structurally, to previously known materials. This begs the question “Can machine learning ever learn new chemistries and families of materials that differ from those present in the training data?” In this talk, I will describe new generative machine learning approaches that can be used to generate structures that do not yet exist, but are likely to. I will compare generative models including variational autoencoders, generative adversarial networks, and diffusion models which have become standard in machine learning for images. I will describe the unique challenges that we face when using tools of this nature to generate periodic crystalline structures.


Dr. Sparks is an Associate Professor of Materials Science and Engineering at the University of Utah and currently a Royal Society Wolfson Visiting Fellow on sabbatical at the University of Liverpool. He holds a BS in MSE from the UofU, MS in Materials from UCSB, and PhD in  Applied Physics from Harvard University. He was a recipient of the NSF CAREER Award and a speaker for TEDxSaltLakeCity. When he’s not in the lab you can find him running his podcast “Materialism” or canyoneering with his 4 kids in southern Utah. 

Find Taylor D. Sparks on Twitter, YouTube and LinkedIn.

This event is hosted by FAIRmat as a member of Physical Sciences in NFDI. Physical Sciences in NFDI is a collaboration between the NFDI consortia DAPHNE4NFDI, FAIRmat, MaRDI, NFDIMatWerk, NFDI4Cat, NFDI4Chem and PUNCH4NFDI. We unite experts on a broad spectrum of topics in physics, chemistry, mathematics and informatics. In our talk series we invite leading scientists to showcase good data practices to an international, interdisciplinary audience.