Speaker
Description
New materials are conventionally developed via trial and error in laboratory experiments.
This process is in general slow and involves significant resources and research eEorts.
Furthermore, it can overlook potential candidates, properties, or business-case criteria
related to their use. Computational simulation methods can help solve these problems by
accelerating the screening process and reducing costs. However, applying these methods
requires expert knowledge – uncommon in most industries – not to mention that they do not account for business criteria of utmost importance for industrial development.
We address this need by developing a materials informatics platform that allows our
industrial partners to screen out and find new materials for their applications with little to no prior knowledge of theoretical methods. Our solution combines atomistic simulations –
from density-functional theory to molecular dynamics – and machine learning models with
cost and sustainability data to oEer a holistic solution to materials screening. Our scoring
and ranking algorithms compare, and rate materials data based on chemical, physical, as
well as sustainability, and cost-related criteria. The technology behind our success has been developed at the German Aerospace Center (DLR), which ExoMatter spun out of.
We highlight the path from first-principles data to usable, application-related materials
properties, relevant for industrial applications. We show exemplary use cases in the areas
of carbon capture, polymer development and ceramics, and highlight our first steps towards an open materials data platform for science and industry.