Gemmological Characterisation of Emeralds from Musakashi, Zambia, and Implications for Their Geographic Origin Determination
Krzemnicki et al.
보석학 저널, 2024
DOI: 10.15506/JoG.2024.39.4.338
최근 발표된 보석학 저널 의 연구원들이 이끄는 Swiss Gemmological Institute SSEF 및 Department of Environmental Sciences of the University of Basel employed the icpTOF R to characterize Musakashi emeralds gemologically and chemically. They could be distinguished from Colombian and Afghan emeralds by diagnostic internal features (e.g., ‘sawtooth’-outlined fluid inclusions) and their chemical composition, while they are easily separated from Kafubu-area emeralds based on gemological properties, inclusions, and spectroscopic data.
Zambia’s Kafubu River is the primary source of emeralds, known for their schist-type origin and high iron content. In 2002, the Musakashi deposit in Solwezi District was discovered, producing limited quantities of emeralds distinct from Kafubu material, occurring in Cr-enriched metasediments and resembling Colombian and Afghan emeralds, complicating origin identification.
Starting in 2017, high-quality but small Musakashi emeralds were submitted to the Swiss Gemmological Institute (SSEF) without disclosure of their Zambian origin. Some samples, initially mislabeled as originating from Afghanistan’s Panjshir Valley, were later confirmed to be from Musakashi. This error, detailed in a 2021 article, highlighted valuable gemological data but required correction. Subsequent analyses and verified samples clarified the distinction between Musakashi emeralds and those from Colombia, Afghanistan, and Zambia’s Kafubu area. This article provides a comprehensive dataset to aid accurate identification and differentiation.
The authors employed laser ablation ICP-TOFMS (GemTOF platform) for detailed chemical analysis of 308 emeralds from Musakashi, Kafubu, Colombia, and Afghanistan’s Panjshir Valley. Each emerald was analyzed at multiple spots for elemental composition using high-resolution mass spectrometry. Data visualization with the t-SNE machine-learning algorithm, based on concentrations of 56 elements, revealed clustering by geographic origin. This advanced technique enables accurate identification and differentiation of emeralds from various sources, showcasing the power of the icpTOF in gemological research.
