“Many of the greatest challenges of our time, from clean energy to environmental justice, require new approaches to the craft of scientific experimentation. This is exceedingly apparent in the field of electron microscopy. As researchers utilize this powerful window to peer into the atomic machinery behind today’s technologies, they are increasingly inundated with data and constrained by traditional operating models. We must leverage artificial intelligence and machine learning in our scientific instruments if we are to unlock breakthrough discoveries,” says Steven R. Spurgeon, a materials scientist at Pacific Northwest National Laboratory (PNNL) and international expert in the study of nanomaterials using electron microscopy.
To bring the microscopy platform to life, Spurgeon assembled a team from inside and outside PNNL, including Kevin Fiedler, a mathematician from Washington State University. Fielder partnered with a computer scientist to designed an architecture to process and analyze incoming images to enable large-area montaging and stage feedback.