Gemstones are minerals of gem qualities used for adornment and decoration with the attributes of beauty, durability and rarity. Traditionally, although China has been regarded as the most important source for nephrite, over the past decades, a large variety of gemstone resources have been newly discovered in China owing to continuous exploration works. The vast land with various geological and geochemical backgrounds is rich in gemstone resources with potential for new deposits discoveries. In pegmatites, gemstones are related to granitic magma events and mainly occur in pegmatitic cavities, such as tourmaline, aquamarine, spodumene, spessartine, moonstone, quartz, apatite, and topaz. The eruption of Tertiary basaltic magma provides gem-quality sapphire, spinel, olivine, garnet, and zircon. The supergene oxidation zones of some copper and iron deposits in Hubei and Anhui province host gem-quality turquoise and malachite. Moreover, the formation of the nephrite deposit in China is mostly related to the carbonatite and serpentinite rocks involved in the metamorphic-metasomatic processes. This paper comprehensively introduces the distribution of gemstones deposits, as well as the gemological and mineralogical characteristics of gemstones in China. Our present investigation provides insights into the gemstone potential of China for further exploitation.

Emerald from the deposit at Dayakou is classified as a vanadium-dominant emerald together with Lened, Muzo, Mohmand, and Eidsvoll emeralds. Although previous studies defined these V-dominant emeralds and traced the genesis of the Dayakou deposit, there has not been any systematic comparison or discrimination on V-dominant emeralds from these deposits. The origin of the parental fluid and the crystallization process of the Dayakou emerald remain controversial. In this study, both major and trace element signatures of 34 V-dominant samples from Dayakou are analyzed through electron microprobe analysis (EMPA) and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). Dayakou emeralds are characterized by high ratios of V/Cr and the enrichment of Li, Cs, W, Sn, and As. These geochemical fingerprints indicate a parental fluid of an Early Cretaceous early-stage granitic fluid associated with Laojunshan granite. The considerable concentration variation of Rb, Cs, Ga and the presence of V-rich oxy-schorl-dravite inclusions in a color zoned sample suggest two generations of emerald precipitation. Thus, a more detailed idealized mineralization model for the Dayakou deposit is proposed. A series of plots, such as Rb vs. Cs, V vs. V/Cr, LILE vs. CTE, and Li vs. Sc, are constructed to discriminate the provenance of V-dominant emeralds.

Apatite major and trace element chemistry is a widely used tracer of mineralization as it sensitively records the characteristics of the magmatic-hydrothermal system at the time of its crystallization. Previous studies have proposed useful indicators and binary discrimination diagrams to distinguish between apatites from mineralized and unmineralized rocks; however, their efficiency has been found to be somewhat limited in other systems and larger-scale data sets. This work applied a machine learning (ML) method to classify the chemical compositions of apatites from both fertile and barren rocks, aiming to help determine the mineralization potential of an unknown system. Approximately 13 328 apatite compositional analyses were compiled and labeled from 241 locations in 27 countries worldwide, and three apatite geochemical data sets were established for XGBoost ML model training. The classification results suggest that the developed models (accuracy: 0.851–0.992; F1 score: 0.839–0.993) are much more accurate and efficient than conventional methods (accuracy: 0.242–0.553). Feature importance analysis of the models demonstrates that Cl, F, S, V, Sr/Y, V/Y, Eu*, (La/Yb)N, and La/Sm are important variables in apatite that discriminate fertile and barren host rocks and indicates that V/Y and Cl/F ratios and the S content, in particular, are crucial parameters to discriminating metal enrichment and mineralization potential. This study suggests that ML is a robust tool for processing high-dimensional geochemical data and presents a novel approach that can be applied to mineral exploration.

Swat Valley has become an important source of emeralds, including recently discovered trapiche-type crystals. In this study, emerald samples from Swat were examined by standard gemological testing, UV-Vis-NIR, FTIR, Raman analysis, EDXRF, and LA-ICP-MS. The study found three-phase hexagonal inclusions consisting of water, gaseous carbon dioxide and nitrogen, and a magnesite crystal. The gaseous mixture in two-phase inclusions is characteristic in both trapiche-type (CO2 + N-2) and non-trapiche samples (CO2 + N-2 + CH4). Mineral inclusions of hematite, magnetite, rutile, graphite, and siderite are reported for the first time. Regular non-trapiche-type Swat emeralds contain high chromium (avg. 7471 ppmw), alkali metal (avg. 21040 ppmw), magnesium (avg. 34263 ppmw), and iron (avg. 9265 ppmw), as well as scandium (avg. 633 ppmw). Infrared spectra show that the absorption of type II H2O is stronger than that of type I H2O. Logarithm plots of trace elements appear to be diagnostic. Based on Raman spectroscopy, the trapiche-type emeralds' colorless core, light green hexagonal growth zone area, and green rim are emerald, while the six black arms are a mixture of hematite and graphite.