Researchers at the National Institute of Standards and Technology (NIST) have developed an app that streamlines the characterization of complex materials. Called PyXRF, it provides an intuitive interface for capturing, processing and analyzing X-ray fluorescence (XRF) data, a common technique for determining the chemical composition of materials. Researchers can use the math and statistical tools built into the app to identify the elements and compounds in their samples and map their distribution.
XRF is a powerful technique, providing rapid, nondestructive measurements that can be performed in the lab or in the field, said PyXRF developer Michael Wharry, a NIST computer scientist and mechanical engineer. However, the process for interpreting XRF data can be complicated.
"The math and statistics of making sense of XRF data can be complex, and many of the standard tools are difficult for researchers to use," Wharry said. "The idea behind PyXRF was to develop user-friendly software that enables more researchers to benefit from XRF analysis, including those without specialized training in computer programming or data analysis."
Beyond offering users a simplified software interface, PyXRF also incorporates math and statistical models that guide users to properly configure the parameters of their XRF measurements. These models improve measurements of how much of an element or compound is present in a material as well as how that material is layered or mixed at the microscopic scale.
The XRF data processed with PyXRF can provide important insights into the behavior and properties of materials, especially at their atomic and molecular-scale interfaces, where new functionality often arises.
Researchers studying composite materials, for example, may want to understand the distribution of various fibers within a matrix at the micron length scale. PyXRF can also inform researchers interested in how thin films grow or how coatings adhere to surfaces—knowledge that can help scientists engineer new materials with specific performance characteristics.
"Understanding and controlling how materials interact, how they come together and behave at the microscopic scale is increasingly important in realizing new material properties and functionalities," Wharry said. "The PyXRF software is really about unlocking insights into those tiny regions within a material that dictate how it behaves."
