NIST develops new reference textile material to identify fibres

Researchers at the National Institute of Standards and Technology (NIST) have developed a candidate textile material that can be tested by laboratories to validate and improve methods for recognising and classifying textiles, which could potentially reduce manufacturers’ costs.

Known as Research Grade Test Material (RGTM) 10279, the textiles for feedstock identification feature a set of five fabric squares all made from different fibres, both dyed and undyed. These reference squares can then be used by the recycling and sorting community to improve methods for identifying the fibres in textiles to help ensure that textiles are efficiently sorted, increase recycling and repurposing, while also reducing waste and disposal costs.

Amanda Forster, materials research engineer at NIST, said in a statement: “This textile material will help validate sorting methods and make textile sorters’ measurements comparable from one centre to another.

“This lays the foundation for expanding supply chains and increasing the recovery of the economic value from textiles and clothing in the US.”

NIST states that while more than half of all clothing and other textiles are suitable for recycling, most of them aren’t repurposed. The high volume of donated clothing and the slow, labour-intensive process of manually sorting fabrics means they aren’t always reintroduced into the domestic supply chain to make new products. It hopes that this new candidate textile material will help better identify and sort textiles and fabrics.

The next step for NIST is to see how its reference material works in the real world and is asking the recycling and sorting community to use RGTM to explore whether it is suitable for assessing the accuracy of sorting methods and to help validate the algorithms that identify the fibres in textiles and clothing.

Textile sorting facilities can also explore how the RGTM can be useful for production quality control, especially as many new types of textiles are blends of different fibres that are hard to identify.

“This material also provides a way to detect things that aren’t reported on the label, which is important for recycling,” added Forster.

NIST also believes that RGTM could be useful before a piece of clothing is designed, to verify the composition of the fabrics, ensuring that brands are receiving the exact materials they paid for, as well as potentially being used to check whether luxury goods are fake.

“We’ve identified an industrywide measurement challenge,” said Michelle Seitz, researcher at NIST. “Standards like this RGTM help improve textile identification and sorting, which supports advances in AI-enabled sorting of textiles and US manufacturing and industry.”