Zi-ying Yuan

Ms. Zi-ying Yuan


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 October 2026 in Minerals
Verified
Journal Article
Open access
PDF file
LYLin-Chao Yang
Lin-Chao Yang
YLYubin Li
Yubin Li
CYCheng-ye Yang
Cheng-ye Yang
RSRui Shao
Rui Shao
WZWen-Yu Zhao
Wen-Yu Zhao
ZYZi-ying Yuan
Zi-ying Yuan
Spectral variations in hydrothermal alteration minerals can provide information on hydrothermal zonation and may inform mineral-exploration interpretation. The Mamupu Cu–Au skarn deposit, located in the southern Yulong porphyry copper belt of eastern Tibet, records multistage skarn formation and hydrothermal alteration. Drill core from six boreholes across the main orebody and its surrounding area was investigated using short-wave infrared (SWIR) and Fourier-transform infrared (FTIR) spectroscopy, focusing on two chlorite types, mica-group minerals, and garnet. Ch-1 Pos2250 decreases with increasing distance to the main orebody (R2 = 0.67), whereas the Ch-2 spectral parameters show mixed relationships with this distance variable. Mica-group Pos2200 also decreases with increasing distance to the main orebody (R2 = 0.61), while Dep2200 and the crystallinity index show no statistically significant linear relationships. In garnet, the Position of the FTIR feature near 875 cm−1 decreases with increasing distance to the skarn body (R2 = 0.36), whereas Height shows no statistically significant linear relationship. Overall, band-position parameters show clearer spatial associations with distance than absorption-depth or intensity-related parameters in the datasets examined. These results provide preliminary constraints on spectral variations associated with alteration and mineralization-related geological environments at Mamupu. However, the observed associations have not been tested independently of lithology, alteration, or mineralization, and the garnet relationship is based on the selected sample subset described below. Their predictive value for untested deep or peripheral areas therefore remains to be evaluated.