Forensic dye analysis in cultural heritage: Unraveling the authenticity of the earliest Persian knotted-pile silk carpet

Smith, Gregory D.; Esson, J.; Chen, Victor; Hanson, Robin M.

doi:10.1016/j.fsisyn.2020.11.004

Cited by 13 publications

(9 citation statements)

References 33 publications

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“…Dye analysis can be telling for dating purposes since a plethora of synthetic colorants have been introduced since the late-1800s, and the first introduction date of most of these dyes is accurately known [1]. These modern dyestuffs can help to refine the dating of authentic museum textile artworks [2] or can unmask clever forgeries of purportedly ancient textiles [3,4]. Despite significant progress in molecular techniques like Raman [5,6] and UV-Vis-NIR reflectance spectroscopies [6], liquid chromatography with diode array detection coupled to mass spectrometry (LC-DAD-MS) has been described as the technique par excellence [7] for this type of analysis because of its small sample requirement, high sensitivity, and comprehensive analysis of all extractable components [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Combined, sequential dye analysis and radiocarbon dating of single ancient textile yarns from a Nazca tunic

et al. 2022

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The accessioning of ancient textiles into museum collections often requires objective information regarding the object’s appropriateness and authenticity before purchase or gift acceptance. In the case of colored fabrics, the identification of dyestuffs consistent with the attributed time period and culture builds confidence and reduces the chances of the object being a simple forgery or fake produced using modern materials. Moreover, this information adds to the technical, cultural, and conservation knowledge regarding the object. Increasingly, chronometric age estimates in the form of radiocarbon dating are also needed to establish the object’s age or to further prove the materials match the purported date range of the textile. Each of these analyses consumes a small sample of the object, and typically they are conducted separately by different laboratories on individual sample yarns. This report demonstrates for the first time the sequential, combined analysis of dyes by liquid chromatography-diode array detection-mass spectrometry and radiocarbon dating of the same residual dye-extracted sample. The chemicals and solvents used in various dye extraction protocols are shown not to contaminate the extracted yarns for radiocarbon dating purposes. The approach was used in the authentication study of an ancient Nazca tunic made from natural fibers (wool) and dyes (indigoids, anthraquinones, and flavonoids) shown to have most likely been produced between 595 and 665 CE.

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Section: Introductionmentioning

confidence: 99%

Combined, sequential dye analysis and radiocarbon dating of single ancient textile yarns from a Nazca tunic

et al. 2022

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“…Additionally, the removal of two SO 3 groups and one N 2 produced a characteristic peak at 463 m/z, and the removal of two SO 3 groups combined with both N 2 groups generated a peak at 432 m/z. Apart from these observations, Congo red exhibited the other fragmentation, leading to the formation of radical structures with molecular masses of 416,234, 233, and 235 m/z [ 77 ]. The other peaks that can be seen in the spectrum refer to the complexity and broadening of the obtained spectrum were attributed to various probable reactions forming these radical structures and their resulting products, as well as reactions involving compound detachment and rearrangements.…”

Section: Resultsmentioning

confidence: 99%

Novel magnetic nanocomposites BiFeO3/Cu(BDC) for efficient dye removal

Shahrab,

Tadjarodi

2023

Heliyon

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“…Combining dye identification by Raman spectroscopy and historical data from dye manufacturing [ 68 ] may help for dating purposes. Although showing a stylistic aspect of the 15th century an historical silk carpet proved to be a late 19th or early 20th creation due to the use of synthetic dyes.…”

Section: Instrumental Methodsmentioning

confidence: 99%