X-ray diffraction takes a new look at nanotextures

“This method can be readily applied to study dynamics in-situ or operando. For example, we plan to use the method to study how the structure changes within picoseconds after excitation with short laser pulses, which might enable new concepts for future terahertz technologies.”Ziming Shao, Cornell University

Using a combination of high-powered X-rays, phase-retrieval algorithms and machine learning, researchers at Cornell University have revealed intricate nanotextures in thin-film materials, offering scientists a new, streamlined approach to analyzing potential candidates for quantum computing and microelectronics, among other applications.

Scientists are especially interested in nanotextures that are distributed non-uniformly throughout a thin film because they can confer novel properties on the material. The most effective way to study these nanotextures is to visualize them directly, a challenge that typically requires complex electron microscopy and does not preserve the sample.

The new imaging technique, reported in a paper in the Proceedings of the National Academy of Sciences, takes a different approach. It uses phase retrieval and machine learning to invert conventionally-collected X-ray diffraction data – such as that produced at the Cornell High Energy Synchrotron Source, where data for the study was collected – into real-space visualization of the material at the nanoscale.

The use of X-ray diffraction makes the technique more accessible to scientists and allows for imaging a larger portion of the sample, said Andrej Singer, assistant professor of materials science and engineering and a faculty fellow in Cornell Engineering. Singer led the research with doctoral student Ziming Shao.

“Imaging a large area is important because it represents the true state of the material,” Singer explained. “The nanotexture measured by a local probe could depend on the choice of the probed spot.”

Another advantage of the new method is that it doesn’t require the sample to be broken apart, allowing the dynamic study of thin films, such as introducing light to see how structures evolve.

“This method can be readily applied to study dynamics in-situ or operando,” Shao said. “For example, we plan to use the method to study how the structure changes within picoseconds after excitation with short laser pulses, which might enable new concepts for future terahertz technologies.”

The researchers tested the technique on two thin films, the first of which had a known nanotexture and was thus used to validate the imaging results. Upon testing a second thin film – a Mott insulator with physics associated with superconductivity – the researchers discovered a new type of morphology that had not been observed in the material before – a strain-induced nanopattern that forms spontaneously during cooling to cryogenic temperatures.

“The images are extracted without prior knowledge,” Shao said, “potentially setting new benchmarks and informing novel physical hypotheses in phase-field modeling, molecular dynamics simulations and quantum mechanical calculations.”

This story is adapted from material from Cornell University, with editorial changes made by Materials Today. The views expressed in this article do not necessarily represent those of Elsevier. Link to original source.