With resolution 1,000 times greater than a light microscope, electron microscopes are exceptionally good at imaging materials and detailing their properties. But like all technologies, they have some limitations.
To overcome these limitations, scientists have traditionally focused on upgrading hardware, which is costly. But researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory are showing that advanced software developments can push their performance further.
Argonne researchers have recently uncovered a way to improve the resolution and sensitivity of an electron microscope by using an artificial intelligence (AI) framework in a unique way. Their approach, published in npj Computational Materials, enables scientists to get even more detailed information about materials and the microscope itself, which can further expand its uses.