The Application of Raman Spectroscopic Ratiometric Analysis for Distinguishing between Wool and Mohair

Notayi, Mzwamadoda; Hunter, Lawrance; Engelbrecht, Jan R.; Botha, Anton F.; Minnaar, E.G.; Lee, Mike E.; Erasmus, Rudolph M.

doi:10.1080/15440478.2022.2028212

Cited by 7 publications

(4 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The analysis was conducted on neat wool, pristine SWCNT, and SWCNT/wool composites (Figure e). The Raman spectrum of the SWCNT/wool composites contains peaks of both the neat wool and the pristine SWCNT: tyrosine (Tyr), tryptophan (Trp), amide 1, disulfide (S–S) bond stretch, CH 2 and CH 3 bending peaks of the wool, , radial breathing mode (RBM), and D, G ‑ , and G + peaks of the SWCNT. , In particular, the diameter of the SWCNTs predicted from the RBM mode peak (271.349 cm –1 ) was 0.8255 nm, which did not deviate much from the original specification (0.78 nm; Sigma-Aldrich) before material compounding. The inherent nanoscale properties of SWCNTs embedded in the composites were confirmed to be well preserved without significant aggregation (see the Section ).…”

Section: Resultsmentioning

confidence: 99%

Omnidirectional Energy Harvesting Fleeces

Park

Goh

Kim

et al. 2023

ACS Appl. Mater. Interfaces

View full text Add to dashboard Cite

Underwater mechanical energy harvesters are of rising interest due to their potential for various applications, such as self-powered ocean energy harvesters, monitoring devices, and wave sensors. Pressure-responsive films and stretch-responsive fibers, which provide high electrical power in electrolytes and have simple structures that do not require packing systems, are promising as harvesters in the ocean environment. One drawback of underwater mechanical energy harvesters is that they are highly dependent on the direction of receiving external forces, which is unfavorable in environments where the direction of the supplied force is constantly changing. Here, we report spherical fleece, consisting of wool fibers and single-walled carbon nanotubes (SWCNTs), which exhibit repetitive electrical currents in all directions. No matter which direction the fleece is deformed, it changes the surface area available for ions to access SWCNTs electrochemically, causing a piezoionic phenomenon. The current per input mechanical stress of the fabricated SWCNT/wool energy harvester is up to 33.476 mA/MPa, which is the highest among underwater mechanical energy harvesters reported to date. In particular, it is suitable for low-frequency (<1 Hz) environments, making it ideal for utilizing natural forces such as wind and waves as harvesting sources. The operating mechanism in the nanoscale region of the proposed fleece harvester has been theoretically elucidated through all-atom molecular dynamics simulations.

show abstract

Section: Resultsmentioning

confidence: 99%

Omnidirectional Energy Harvesting Fleeces

Park

Goh

Kim

et al. 2023

ACS Appl. Mater. Interfaces

View full text Add to dashboard Cite

show abstract

“…Alternative methods of fiber identification using spectroscopies, such as Fourier Transform Infrared Spectroscopy (FTIR), sensible to amino acids variation correlated with animal species, and Raman spectroscopy, were investigated. Although some works have not produced satisfactory results [94,98], positive results were obtained when FTIR analysis was coupled with chemometric tools. Indeed, in recent work as a proof-of-concept study, illustrating the potential of ATR FT-IR spectroscopy in animal fibers identification, Sharma et al [6] obtained a complete differentiation between cashmere, angora and shahtoosh using FT-IR spectroscopy coupled with Partial Least Squares Discriminant Analysis (PLS DA).…”

Section: Spectroscopymentioning

confidence: 99%

Analytical Methods for the Identification and Quantitative Determination of Wool and Fine Animal Fibers: A Review

Zoccola

Bhavsar

Anceschi

et al. 2023

Fibers

View full text Add to dashboard Cite

The identification and quantitative determination of wool and fine animal fibers are of great interest in the textile field because of the significant price differences between them and common impurities in raw and processed textiles. Since animal fibers have remarkable similarities in their chemical and physical characteristics, specific identification methods have been studied and proposed following advances in analytical technologies. The identification methods of wool and fine animal fibers are reviewed in this paper, and the results of relevant studies are listed and summarized, starting from classical microscopy methods, which are still used today not only in small to medium enterprises but also in large industries, research studies and quality control laboratories. Particular attention has been paid to image analysis, Nir spectroscopy and proteomics, which constitute the most promising technologies of quality control in the manufacturing and trading of luxury textiles and can find application in forensic science and archeology.

show abstract

“…The research project concluded that test samples could readily be authenticated for uncomplicated cases by solely near-infrared spectra visual inspection; for more comprehensive identification of unknown samples, principal component analysis combined with soft independent modeling of class analogies was applied. Very recently, Notayi et al 17 reported on the analysis of wool fiber bundles using a Fourier transform (FT) Raman system, equipped with an Nd:YAG excitation laser (1064 nm), to determine whether such a system can be used to distinguish Merino wool. They showed that even in cases where the Raman spectra are similar, the heights of the spectra contain information about certain chemical bands, which can facilitate wool-type identification.…”

mentioning

confidence: 99%

“…Very recently, Notayi et al. 17 reported on the analysis of wool fiber bundles using a Fourier transform (FT) Raman system, equipped with an Nd:YAG excitation laser (1064 nm), to determine whether such a system can be used to distinguish Merino wool. They showed that even in cases where the Raman spectra are similar, the heights of the spectra contain information about certain chemical bands, which can facilitate wool-type identification.…”

mentioning

confidence: 99%

Optical coherence tomography imaging can identify Merino lambs’ wool using automatic machine learning vision

Sabuncu

Özdemi̇r

2023

Textile Research Journal

View full text Add to dashboard Cite

Merino lambs’ wool fiber has a unique chemical structure that gives the wool many unique properties and technical benefits. For example, the small fiber diameters mean that Merino wool is soft, countering the scratchiness commonly associated with wool. It is also biodegradable, organic, and environmentally friendly, making it a popular choice of sustainable fabric material. Unfortunately, some fiber sellers unduly sell coarse wool tops to wool yarn factories as Merino wool tops. It is, therefore, an important task to identify the actual wool type for quality assurance in the textile manufacturing process. This paper describes applying the spectral-domain optical coherence tomography (OCT) imaging and automatic machine learning (AutoML) techniques for distinguishing Merino wool from coarse wool. We present the results of wool measurements that were performed by the OCT scans and AutoML algorithms. We conclude that OCT imaging and AutoML algorithms can be applied to distinguish Merino wool from coarse wool in a simple, non-destructive, and contactless manner.

show abstract

The Application of Raman Spectroscopic Ratiometric Analysis for Distinguishing between Wool and Mohair

Cited by 7 publications

References 23 publications

Omnidirectional Energy Harvesting Fleeces

Omnidirectional Energy Harvesting Fleeces

Analytical Methods for the Identification and Quantitative Determination of Wool and Fine Animal Fibers: A Review

Optical coherence tomography imaging can identify Merino lambs’ wool using automatic machine learning vision

Contact Info

Product

Resources

About