2026-10-15T04:06:20Z https://www.scidb.cn/oai

10.57760/sciencedb.43418 2026-07-20T10:28:39Z

2026-07-20 EPMA Major-Element Dataset of Magmatic Biotites from Late Jurassic–Early Cretaceous Porphyry Cu-Mo and Cu-Au Deposits, NE China doi:10.57760/sciencedb.43418 en This dataset is derived from magmatic biotites in ore-forming intrusions of eight typical Late Jurassic–Early Cretaceous porphyry Cu‑Mo and Cu‑Au deposits in Northeast China, including the Late Jurassic Huoluotai, Xiaokelehe, Fukeshan, and 770 deposits in the north, and the Early Cretaceous Ershiyizhan, Baoquan, Duluhe, and Sishanlinchang deposits in the east. Samples were collected from ore-related lithologies (e.g., granodiorite porphyry, quartz diorite porphyry, and quartz monzonite porphyry) at each deposit. After preparing standard polished thin sections in the laboratory, fresh, unaltered, and structurally intact biotite grains were carefully selected under optical microscopy and back‑scattered electron (BSE) imaging to ensure that the analyzed grains preserve primary magmatic crystallization signatures. All analytical work was carried out at the Shandong Analysis Center of the China Metallurgical Geology Bureau, using a JEOL JXA‑8230 field‑emission electron microprobe (EPMA) for quantitative major‑element analysis. Operating conditions were: accelerating voltage 15 kV, beam current 10 nA, and beam diameter 5 μm. Peak and background counting times were set differentially according to the element: 10 s/5 s for K, Na, F, and Cl; 40 s/20 s for Ti and Mn; and 20 s/10 s for other elements. Calibration was based on international reference standards (quartz for Si, biotite USNM‑Bi for Mg, Fe, and Al, rutile for Ti, albite for Na, orthoclase for K, fluorite for F, and chlorapatite for Cl). Detection limits (3σ) ranged from 0.003 wt% to 0.009 wt%, and the data were processed with the ZAF correction procedure. The instrument was operated under stable conditions, and systematic errors were effectively controlled.The raw counting data, after ZAF correction, yielded mass percentages of oxides and halogens. Crystallochemical formulae were calculated on the basis of 22 oxygen atoms, and the proportions of Fe³⁺ and Fe²⁺ were estimated using a machine‑learning method based on principal‑component regression (Li et al., 2020). On this basis, we further calculated the magnesium index (XMg = 100 × [Mg/(Mg+Fe)], molar ratio), crystallization temperatures (using the Ti‑in‑biotite geothermometer of Henry et al., 2005), solidification pressures (using the Alᵀ‑based barometer of Uchida et al., 2007), halogen intercepts IV(F), IV(Cl), and IV(F/Cl) (Munoz, 1984), and, using the partition model of Zhang et al. (2022), we inverted the F/OH and Cl/OH ratios as well as the absolute F and Cl concentrations (in ppm) in the silicate melt equilibrated with biotite. All data are compiled into three Excel (.xlsx) supplementary tables: Supplementary Table S1 contains the raw major‑element data for 455 analytical spots, including sample ID, deposit name, spot number, and mass percentages (wt%) of SiO₂, TiO₂, Al₂O₃, FeO (total iron), MnO, MgO, Na₂O, K₂O, F, and Cl, along with the analytical total. Supplementary Table S2 presents the calculated Fe³⁺ and Fe²⁺ values for each spot. Supplementary Table S3 provides the calculated melt‑phase F/OH and Cl/OH ratios, F and Cl concentrations (in ppm), and Cl/F ratios. No missing data exist in any of the tables; every analytical spot is fully recorded.The samples cover Heilongjiang and Jilin provinces in Northeast China, with magmatic and mineralization ages ranging from ca. 150 Ma to 95 Ma (the Late Jurassic deposits cluster at 150–147 Ma, and the Early Cretaceous deposits at 131–95 Ma), representing two major Late Mesozoic porphyry metallogenic events in this region. In terms of quality control, EPMA analyses were calibrated daily using international reference standards, and detection limits and counting statistics errors were incorporated following standard procedures. The Ti‑in‑biotite geothermometer has an uncertainty of –25 °C to +65 °C in the 700–800 °C range (Henry et al., 2005); the pressure calculation carries an error of approximately ±0.5 kbar; and the uncertainty in the Fe³⁺/Fe²⁺ estimation used for halogen‑intercept calculations has been reduced by the machine‑learning approach. The overall data quality is robust and suitable for reconstructing magmatic physicochemical conditions and for comparative studies of ore‑forming mechanisms. This dataset is available in the supplementary materials of this paper; raw mass‑spectrometry data or BSE images can be obtained from the corresponding author upon request. Porphyry copper deposits; Biotite geochemistry; Electron microprobe analysis; Northeast China; Late Mesozoic; Halogen elements Qin Yunxuan Deng Changzhou PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.1016/j.oregeorev.2026.107414 Science Data Bank