A new textile test material from the National Institute of Standards and Technology (NIST) could give laboratories and manufacturers a common benchmark for evaluating fiber-identification methods, including near-infrared spectroscopy and automated sorting systems.
NIST developed Research Grade Test Material (RGTM) 10279, Textiles for Feedstock Identification, to address a measurement challenge in textile recycling and manufacturing: different laboratories and sorting facilities use a range of technologies and methods to identify fiber composition, creating a need for physical materials that can be used to assess and compare their performance.
The material consists of five four-inch fabric squares made from different fibers, including dyed and undyed samples. NIST has not disclosed the fiber compositions for the benchmarking study. Unlike NIST’s more extensively characterized Standard Reference Materials, research-grade test materials can be produced on a shorter timeline and evaluated with feedback from participating laboratories.
A benchmark for spectroscopy and sorting methods
Near-infrared (NIR) spectroscopy is already used in textile sorting because fiber types produce spectral information that can be used for identification. Handheld scanners can help workers classify fabrics, while automated systems can combine sensors, cameras, and algorithms to identify textiles moving along conveyor lines. Other approaches include computer vision and hyperspectral imaging.
The challenge is determining whether those systems identify fibers accurately and consistently. NIST says RGTM 10279 provides a physical benchmark laboratories can use to compare methods, develop new sorting technologies, and assess the accuracy of fiber-identification systems.
“This textile material will help validate sorting methods and make textile sorters’ measurements comparable from one center to another,” NIST materials research engineer Amanda Forster said.
For lab managers, the project demonstrates the role that reference materials can play in analytical quality. Reference materials can help laboratories evaluate measurement accuracy and support analytical method development and validation, particularly when methods need to produce comparable results across analysts, instruments, or locations.
Testing complex materials and automated workflows
Textile characterization becomes more complicated when products contain blended fibers, dyes, finishes, seams, or multiple layers. NIST says these features can contribute to incorrect or incomplete identification as textiles move through sorting systems.
RGTM 10279 is intended in part to help researchers evaluate algorithms that identify fiber composition. The material could also support production quality control by giving laboratories a way to assess whether supplied fabrics match their stated composition.
The work reflects a broader measurement challenge for materials laboratories. Recent NIST research has similarly emphasized the importance of reference materials and measurement uncertainty when interpreting nanotechnology data. As laboratories adopt more sophisticated materials characterization techniques, physical benchmarks can provide a common point of comparison for evaluating instruments, analytical methods, and data-processing approaches.
For lab managers overseeing materials testing or analytical chemistry workflows, the NIST project provides a practical example of how reference materials can support method evaluation, quality control, and more comparable measurements as new analytical and automated technologies move into routine use.
This article was created with the assistance of Generative AI and has undergone editorial review before publishing.
