Utilizing UV-Visible Spectroscopy for Color Analysis of Fabrics

Significance of the Topic

Color is a critical quality attribute across industries such as textiles, coatings and forensics. Objective, instrumentally derived color metrics remove observer bias and allow reproducible quality control, verification of color fastness, and precise color matching (for example camouflage or product batches). UV–Visible spectroscopy combined with standardized color spaces (CIE L*a*b*, CIE L*C*h*) provides a robust approach to quantify perceived color and to compute color differences relevant for QA/QC decisions.

Objectives and Study Overview

This application note demonstrates the use of UV–Vis reflectance spectroscopy, supported by FTIR for material identification, to:

• Quantify color coordinates (CIE L*a*b*) for dye solutions and textile samples.
• Compare cotton and polyester samples of visually similar colors to reveal subtle differences.
• Illustrate how ΔE*ab and derived chromatic parameters can inform acceptability in QC contexts.

Instrumentation Used

• Thermo Scientific Evolution One Plus UV–Vis Spectrometer configured for reflectance with an integrating sphere (ISA-220).
• Thermo Scientific Insight Pro Software for CIE calculations and selection of illuminant/observer (D65, 10°).
• Thermo Scientific Nicolet iS20 FTIR Spectrometer with iTX diamond ATR accessory and Omnic software for library correlation (material confirmation).
• Spectralon white disk as reference standard for % reflectance measurements.

Methodology

• Dye solutions: three direct dyes (Direct Blue 71, Direct Red 81, Direct Yellow 27) prepared at low micromolar concentrations to keep absorbance <1. UV–Vis absorption spectra recorded to identify peak positions.
• Fabrics: two sets of commercially obtained textiles (pure cotton and pure polyester), six apparent colors each (white, black, red, blue, yellow, green). FTIR-ATR used to confirm polymer type via library matching.
• Spectral acquisition: UV–Vis data collected from 780 nm to 380 nm with 1 nm bandwidth and 1 nm interval, integration time 0.30 s. Reflectance spectra reported as %R relative to Spectralon.
• Color calculation: CIE tristimulus and CIE L*a*b* coordinates computed using Insight Pro, following ASTM-E308 and USP <1061> conventions; illuminant D65 and 10° observer were used. ΔE*ab used to quantify color differences (noting ΔE*ab < 3 is typically indistinguishable by eye).

Main Results and Discussion

• Dye absorption: direct dyes showed expected visible absorptions at complementary wavelengths — yellow ≈ 400 nm, red ≈ 512 nm, blue ≈ 586 nm — consistent with perceived colors.
• Dye CIE coordinates: calculated L*a*b* values aligned with expected chromatic signs (e.g., positive a* for red, positive b* for yellow, negative b* for blue), validating the computational pipeline.
• Fabric reflectance and color coordinates: reflectance spectra alone did not always make differences obvious; computed CIE L*a*b* values allowed objective comparison between cotton and polyester samples.
• Material confirmation: FTIR-ATR spectra and library correlation confirmed the cotton and polyester identities prior to color comparison.
• Color differences: most cotton–polyester color pairs produced ΔE*ab < 3 (visually indistinguishable), except notable outliers — the green sample pair produced a very large ΔE*ab (~30), indicating a clear visual and instrumental difference. For several samples, the principal difference was L* (lightness), indicating shade variation rather than hue shift.
• Practical implication: the method revealed subtle but quantifiable differences that can influence acceptance criteria in QC, especially when visual appraisal is unreliable.

Benefits and Practical Applications

• Objective, repeatable color specification and inspection for textile manufacturing, dye formulation, batch certification, and camouflage matching.
• Ability to detect small chromatic or shade differences that are ambiguous to the naked eye, improving lot-to-lot consistency and customer satisfaction.
• Combined use of UV–Vis colorimetry and FTIR enables both color and material confirmation in a single QA workflow.

Future Trends and Applications

• Adoption of advanced color-difference formulas (e.g., CIEDE2000) and perceptually uniform metrics to better correlate instrument results with human perception.
• Integration with spectral imaging and hyperspectral cameras for spatially resolved color mapping of patterned or non-uniform textiles.
• Portable and in-line reflectance systems for real-time process control in dyeing and finishing lines.
• Application of machine learning to predict long-term colorfastness from accelerated aging spectral data and to automate accept/reject decisions.
• Extended multimodal workflows combining colorimetry, FTIR, and other surface-analytical techniques for forensic and regulatory purposes.

Conclusion

UV–Visible reflectance spectroscopy, when combined with standardized CIE color metrics and appropriate illuminant/observer settings, provides a sensitive and reproducible method for quantifying color of dyes and fabrics. In this study, the Evolution One Plus system and Insight Pro software effectively distinguished subtle chromatic and shade differences between cotton and polyester samples; FTIR confirmed material identity. The approach supports robust QA/QC and can be extended with newer color-difference formulas, spectral imaging and automated analytics for broader industrial application.

References

1. Hossain MA. UV–Visible–NIR Camouflage Textiles with Natural Plant Based Natural Dyes on Natural Fibre against Woodland Combat Background for Defence Protection. Scientific Reports. 2023;13(1).
2. Čorak I, Brlek I, Sutlović A, Tarbuk A. Natural Dyeing of Modified Cotton Fabric with Cochineal Dye. Molecules. 2022;27(3).
3. ASTM International. Standard Practice for Computing the Color of Objects by Using the CIE System.
4. Goodpaster JV, Liszewski EA. Forensic Analysis of Dyed Textile Fibers. Analytical and Bioanalytical Chemistry. 2009.
5. United States Pharmacopeia and National Formulary. <1061> Color—Instrumental Measurement. Rockville, MD.