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| Funder | Vinnova |
|---|---|
| Recipient Organization | Stockholm University |
| Country | Sweden |
| Start Date | Nov 18, 2022 |
| End Date | Aug 30, 2023 |
| Duration | 285 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | Swedish Research Council |
| Grant ID | 2022-03118_Vinnova |
Purpose and goal:
A rapid ambient ionization technique was applied to detect potentially harmful chemicals present in recycled textiles. Desorption electrospray ionisation coupled with high-resolution mass spectrometry (DESI-HRMS) was validated and optimised for textile samples. Then a range of 21 commercially available recycled textile samples were analysed for the presence of chemicals of interest.
Optimised DESI conditions were determined by central composite design of experiment, the performance of the HRMS was validated using a mixture of known substances. Expected results and effects:
Data-independent acquisition was performed by collecting high- and low-collision energy mass spectrum from substances contained in the textiles. Features were extracted from these mass spectra for further interrogation by suspect and non-target screening techniques. This study provides a useful case study for the rapid and cost-effective analysis of commercial textiles to screen for regulated, banned, and otherwise harmful substances in textiles before entering the market.
Approach and implementation:
Mass spectrum for each sample were converted to mzXML format, centroided and summed across all scans before LockMass correction. MATLAB was used to pick regions of interest (ROI) using 100 m/z bin sizes and the components were then filtered using a 1:10 blank threshold and SN > 1. mzR was used to extract the low- and high-energy peaks and concatenated for non-negative matrix factorization analysis. Multiway curve resolution (MCR) is used to extract the MS1 and MS2 peak list from each samples.
Stockholm University
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