I view our system as another source of information that the experts can leverage in their search for better materials.
MIT researchers and their collaborators have demonstrated a novel system using artificial-intelligence techniques to help identify methods of fabricating materials, especially those that look promising in computer simulations. In one test, the system scanned half a million journal articles, recognized those that contained “recipes” for synthesizing various metal oxides, and produced a massive dataset of parameters such as operating temperatures and times. It then scanned the dataset to find patterns that highlight critical parameters. In a test focusing on one compound, the system generated values for certain operating conditions that are realistic but don’t appear anywhere in the literature. Thus, with no guidance, the system leveraged the database to come up with a novel recipe that could be tested in a lab. The researchers are now working to improve the system’s accuracy and to refine its user interfaces so that experts can easily interpret the results, interact with the system, and select directions for further investigation.