Like people, materials evolve over time. They also behave differently when they are stressed and relaxed. Scientists looking to measure the dynamics of how materials change have developed a new technique that leverages X-ray photon correlation spectroscopy , artificial intelligence and machine learning.
"The goal of the AI is just to treat the scattering patterns as regular images or pictures and digest them to figure out what are the repeating patterns. The AI is a pattern recognition expert." -- James Horwath, Argonne National Laboratory For researchers to better understand what they are studying, they have to condense all the data into fingerprints that carry only the most essential information about the sample."You can think of it like having the material's genome, it has all the information necessary to reconstruct the entire picture," Horwath said.
AI, simply put, has good general pattern recognition capabilities, making it able to efficiently categorize the different X-ray images and sort them into the map."The goal of the AI is just to treat the scattering patterns as regular images or pictures and digest them to figure out what are the repeating patterns," Horwath said."The AI is a pattern recognition expert."