In the porphyry Cu ± Au ± Mo deposits (PCDs), chlorite and its mineral assemblages are indicators for exploration. However, chlorite found in PCDs may have different origins because it is a common mineral in different geological environments. Therefore, it is necessary to identify the differences in the composition of PCDs-related chlorites (chlorite_PCDs) and chlorite formed in other geological environments (chlorite_Barren). Here, based on occurrences, mineral assemblages, and compositions of the chlorites from thirty PCDs and barren areas (including geothermal systems, chlorite_GSs; low-grade metamorphic rocks, chlorite_LGMRs; sedimentary rocks, chlorite_SRs), we used principal component analysis (PCA) and random forest (RF) methods to find discrimination approaches. Results show that chlorite_PCDs and chlorite_Barren differ in the Fe, Mg, Al, Ti, and possibly Mn, K, and Ca elements. Based on these differences, wt.% ratios of (MgO + 100*TiO₂)/(FeO + 100*CaO), TiO₂/(CaO + K₂O + Na₂O), Al₂O₃/(100*K₂O*CaO), MgO/(100*CaO*Na₂O), SiO₂/100(CaO + K₂O), and FeO/100TiO₂ and diagrams of Fe/(Fe + Mg) (a.p.f.u. ratio) vs TiO₂/(Na₂O + K₂O + CaO) (wt.% ratio), Fe/(Fe + Mg) (a.p.f.u. ratio) vs MgO/(100*Na₂O*CaO) (wt.% ratio), and Fe/(Fe + Mg) (a.p.f.u. ratio) vs SiO₂/Al₂O₃ (wt.% ratio) are proposed to distinguish chlorite_PCDs from chlorite_Barren. These discrimination approaches have better results in distinguishing chlorite_PCDs from chlorite_LGMRs and chlorite_SRs but are less effective for chlorite_GSs. By comparing the physicochemical conditions, the highly oxidized conditions and high temperature of the ore-related intrusions and fluid properties result in the compositional differences between chlorite_PCDs and chlorite_Barren. Although further researches remain to be done, this study provides potential approaches for identifying chlorite_PCDs based on major elements.

在斑岩型 Cu ± Au ± Mo 矿床 (PCDs) 中，绿泥石及其矿物组合是勘探指标。然而，在 PCD 中发现的绿泥石可能有不同的来源，因为它是不同地质环境中的常见矿物。因此，有必要识别与 PCDs 相关的绿泥石（chlorite _PCDs）与其他地质环境中形成的绿泥石（绿泥石_贫瘠）的成分差异。在这里，基于来自 30 个 PCD 和贫瘠地区（包括地热系统，绿泥石_GS；低品位变质岩，绿泥石_LGMR；沉积岩，绿泥石_{SR ）的产状、矿物组合和组成})，我们使用主成分分析 (PCA) 和随机森林 (RF) 方法来寻找辨别方法。结果表明，绿泥石_PCD和绿泥石_Barren在 Fe、Mg、Al、Ti 以及可能的 Mn、K 和 Ca 元素方面存在差异。基于这些差异，(MgO + 100*TiO ₂ )/(FeO + 100*CaO)、TiO ₂ /(CaO + K ₂ O + Na ₂ O)、Al ₂ O ₃ /(100* K ₂ O*CaO)、MgO/(100*CaO*Na ₂ O)、SiO ₂ /100(CaO + K ₂ O)、FeO/100TiO ₂和Fe/(Fe + Mg)(apfu比)图与 TiO ₂ /(Na ₂O + K ₂ O + CaO) (wt.% ratio), Fe/(Fe + Mg) (apfu ratio) vs MgO/(100*Na ₂ O*CaO) (wt.% ratio), 和 Fe/(Fe + Mg) (apfu ratio) vs SiO ₂ /Al ₂ O ₃ (wt.% ratio) 被提议用来区分绿泥石_PCD和绿泥石_Barren。这些鉴别方法在区分亚氯酸盐_PCD与亚氯酸盐_LGMR和亚氯酸盐_SR方面具有更好的效果，但对亚氯酸盐_{GS的效果较差}. 通过物化条件比较，成矿侵入体的高度氧化条件和高温以及流体性质导致绿泥石_PCDs和绿泥石_贫瘠的成分存在差异。尽管仍有待进一步研究，但本研究提供了基于主要元素识别亚氯酸盐_{PCD的潜在方法。}