A new set of textile reference materials has been developed to give recycling facilities and researchers a shared standard for sorting accuracy. More than half of all clothing and textiles are suitable for recycling, yet donated clothing volumes and slow manual sorting mean most are never reintroduced into the supply chain. The materials, from the National Institute of Standards and Technology, address a gap in measurement comparability across facilities.
- Near-infrared spectroscopy, which measures light to identify fibre content, and computer vision, which classifies by colour, are used at recycling centres but lack a common benchmark for verifying results.
- The new material, Research Grade Test Material 10279, consists of five fabric squares made from different fibres, both dyed and undyed, and is distributed to labs for measurement and results sharing.
- AI-enabled sorting offers speed advantages in fibre identification, but its accuracy has not been exhaustively tested, making standardised reference materials a pressing need across the sector.
THE MISSING STANDARD: Research Grade Test Material 10279, Textiles for Feedstock Identification, is a newly developed NIST reference material designed to give recycling facilities and researchers a common standard for sorting. NIST distributes RGTMs to laboratories that agree to measure them and share their results, helping determine whether the material is suitable for its intended purpose. More efficient sorting increases recycling and repurposing while reducing waste and disposal costs.
- Each square measures four inches (10.2 centimetres) on a side and is cut from a distinct fibre type, with both dyed and undyed variants included across the set.
- Unlike standard reference materials, this category is produced on a shorter time frame, making it a faster route to establishing provisional industry benchmarks.
- Participating labs receive the physical squares, apply their own measurement methods to analyse the squares, and return results to inform further development.
- Once textiles are properly sorted, they are sent to recycling manufacturers for processing and made into new products.
FURTHER APPLICATIONS: Textile sorting facilities can apply the material in several ways beyond basic recycling. Many new textiles are blends of different fibres that are hard to identify, making production quality control a growing concern. Labs can also use the physical standard as a benchmark to develop new sorting technologies. Much of the current research in this field has focused on used or heavily worn clothing, but the material could prove useful much earlier, before a piece of clothing is even designed.
- The material provides a way to detect fibre content not reported on the label, which is particularly relevant for recycling accuracy and compliance.
- Where a brand purchases fabric on the basis of a stated composition, the material can help verify whether the actual content matches what was paid for.
- Fashion authentication is a potential application, offering a method to check whether luxury goods are counterfeit, though this is not an area currently being pursued.
- Labs can also use the material as a physical reference to compare their existing sorting methods against established results, supporting the development of new technologies.
THE TESTING PROBLEM: AI technology offers the promise of quickly identifying fibres in textiles, but its accuracy has not been exhaustively tested, and an industrywide measurement challenge has been identified. The interlaboratory study currently under way asks labs, manufacturers and other organisations to use their own sorting and analysis methods on the material, whose fibre composition is undisclosed. Results will remain anonymous and feed into developing a more well-analysed reference material that meets industry's needs.
- AI-enabled sorting has advanced considerably, but the absence of validated standards means facilities cannot reliably confirm whether their identification methods are performing accurately.
- The study's undisclosed fibre composition allows participating organisations to test their methods without prior knowledge of the correct result.
- Anonymous feedback from participating labs and manufacturers will be incorporated into the next stage of reference material development.
- For NIST researchers, determining whether the material can be used by industry in real-world settings remains the immediate priority before broader adoption can be considered.
WHAT THEY SAID
This textile material will help validate sorting methods and make textile sorters' measurements comparable from one center to another … This lays the foundation for expanding supply chains and increasing the recovery of the economic value from textiles and clothing in the U.S.
— Amanda Forster
Materials Research Engineer
National Institute of Standards and Technology
We've identified an industrywide measurement challenge. Standards like this RGTM help improve textile identification and sorting, which supports advances in AI-enabled sorting of textiles and U.S manufacturing and industry.
— Michelle Seitz
Researcher
National Institute of Standards and Technology
