AIChemy

Project Overview

X-ray scattering is essential for characterization of the atomic structure of materials, but the data analysis required to go from data to structure is a bottleneck in materials discovery and development. There is a huge potential for significantly advancing data analysis methods in X-ray science through data science. Here, building on advancements in deep learning, we proposed a new generative, data-driven approach to identify and determine atomic structures of nanomaterials directly from scattering data, as well as introducing new approaches to material discovery and generative machine learning.

Project Members

• Collaborators: Kirsten Jensen (PI), Erik Dam (PI)
• Raghavendra Selvan (Co-Applicant)
• Ulrik Friis-Jensen (PhD Candidate)
• Frederik Johansen (PhD Candidate)