IF 8.5 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Geoscience frontiers Pub Date : 2025-03-01 DOI:10.1016/j.gsf.2025.102035
Evilarde Carvalho Uchôa Filho , Felipe Holanda dos Santos , Douglas Teixeira Martins , Wagner da Silva Amaral , José Alberto Rodrigues do Vale
{"title":"Cobalt enrichment in Paleoproterozoic African and Brazilian manganese deposits","authors":"Evilarde Carvalho Uchôa Filho ,&nbsp;Felipe Holanda dos Santos ,&nbsp;Douglas Teixeira Martins ,&nbsp;Wagner da Silva Amaral ,&nbsp;José Alberto Rodrigues do Vale","doi":"10.1016/j.gsf.2025.102035","DOIUrl":null,"url":null,"abstract":"<div><div>This study highlights a new by-product source for cobalt by recycling Paleoproterozoic Mn deposits. We present a geochemical modeling approach utilizing Principal Component Analysis (PCA) for available geochemical data of Paleoproterozoic manganese deposits found in Africa and Brazil, which exhibit anomalous cobalt contents (up to 1200 ppm) along with other metals such as copper, nickel, and vanadium. The PCA results for the correlation coefficient matrix of the Enrichment Factor (EF) values of major and trace elements from samples of eight Mn deposits found in Africa and Brazil (Kisenge-Kamata, Moanda, Nsuta in Africa, and Azul, Buritirama, Lagoa do Riacho, Morro da Mina, and Serra do Navio in Brazil) yielded a cumulative variance of 53.3% for PC1 (34%) and PC2 (19.3%). In PC1, the highest positive loadings correspond to the variables Mn<sub>EF</sub>, Ni<sub>EF</sub>, and Co<sub>EF</sub>, while the highest negative loadings correspond to the variables Si<sub>EF</sub>, Fe<sub>EF</sub>, K<sub>EF</sub>, Ti<sub>EF</sub>, Cr<sub>EF</sub>, and Zr<sub>EF</sub>. PC2 exhibits the highest positive loadings for the variables Ca<sub>EF</sub>, Mg<sub>EF</sub>, and P<sub>EF</sub>, while the highest negative loadings are for Cu<sub>EF</sub> and V<sub>EF</sub>. The biplot diagram representation showed that clusters of vectors Mn<sub>EF</sub>, Ni<sub>EF</sub>, Co<sub>EF</sub>, V<sub>EF</sub>, and Cu<sub>EF</sub> influence samples of Mn-carbonate rock, Mn-carbonate–silicate rock, Mn-silicate rock, and Mn-carbonate-siliciclastic rock, all with high Co<sub>EF</sub> values (up to 414). The cluster of vectors Ca<sub>EF</sub>, Mg<sub>EF</sub>, and P<sub>EF</sub> significantly influence carbonate rock and dolomite marble, which have low Co<sub>EF</sub> values (close to 0). The cluster of vectors Si<sub>EF</sub>, Fe<sub>EF</sub>, K<sub>EF</sub>, Ti<sub>EF</sub>, Cr<sub>EF</sub>, and Zr<sub>EF</sub> strongly influences siliciclastic rock, which exhibits low Co<sub>EF</sub> values. On the other hand, the cluster of vectors Cu<sub>EF</sub> and V<sub>EF</sub> influences oxidized Mn ore, which exhibits Co<sub>EF</sub> values of up to 108. The results reveal a dichotomy regarding the origin of cobalt and other metal enrichments in these deposits linked to the Mn redox cycle. This process involves the formation of Mn-oxyhydroxides with the adsorption of Co and other metals under oxic conditions, followed by the burial of these Mn oxides in an anoxic diagenetic environment, where microbial sulfate reduction leads to the nucleation of Mn-carbonates and the formation of metal-rich sulfides (Fe, Co, Ni, V). Additionally, detrital input and sulfide phases (e.g., framboidal pyrite) for the formation of Mn-rich siliciclastic rocks associated with Mn-carbonate rocks are evidenced by proxies Si<sub>EF</sub>, Fe<sub>EF</sub>, K<sub>EF</sub>, Ti<sub>EF</sub>, Cr<sub>EF</sub>, and Zr<sub>EF</sub>. This new exploration approach, supported by geochemical modeling through PCA, enhances our understanding of the genesis of these Paleoproterozoic manganese deposits and highlights a new route for cobalt exploration. In the increasing global demand for cobalt, particularly in applications involving electric vehicle batteries and energy storage, exploring these deposits emerges as an alternative source to produce these critical metals.</div></div>","PeriodicalId":12711,"journal":{"name":"Geoscience frontiers","volume":"16 3","pages":"Article 102035"},"PeriodicalIF":8.5000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscience frontiers","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1674987125000350","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

本研究强调了通过回收利用古生代锰矿床获得钴的新副产品来源。我们针对非洲和巴西发现的古生代锰矿床的现有地球化学数据,提出了一种利用主成分分析(PCA)的地球化学建模方法,这些矿床的钴含量(高达 1200 ppm)与铜、镍和钒等其他金属一起呈现出异常。非洲和巴西发现的八个锰矿床(非洲的 Kisenge-Kamata、Moanda、Nsuta 和巴西的 Azul、Buritirama、Lagoa do Riacho、Morro da Mina 和 Serra do Navio)样品中主要元素和微量元素富集因子(EF)值的相关系数矩阵的 PCA 结果显示,PC1(34%)和 PC2(19.3%)的累积方差为 53.3%。在 PC1 中,正载荷最高的变量是 MnEF、NiEF 和 CoEF,负载荷最高的变量是 SiEF、FeEF、KEF、TiEF、CrEF 和 ZrEF。PC2 中,正载荷最高的变量是 CaEF、MgEF 和 PEF,负载荷最高的变量是 CuEF 和 VEF。双折线图显示,锰-碳酸盐岩、镍-碳酸盐岩、钴-碳酸盐岩、锰-碳酸盐-硅酸盐岩和锰-碳酸盐-硅质岩的 CoEF 值都很高(最高达 414),而锰-碳酸盐岩、镍-碳酸盐岩、钴-碳酸盐岩、钒-碳酸盐岩和铜-碳酸盐岩的 CoEF 值都很低。CaEF、MgEF 和 PEF 矢量群对 CoEF 值较低(接近 0)的碳酸盐岩和白云石大理岩有显著影响。SiEF、FeEF、KEF、TiEF、CrEF 和 ZrEF 向量群对硅质岩影响较大,其 CoEF 值较低。另一方面,CuEF 和 VEF 向量群对氧化锰矿石有影响,其 CoEF 值高达 108。研究结果表明,这些矿床中钴和其他金属富集的起源与锰氧化还原循环有关。这一过程包括在氧化条件下吸附钴和其他金属形成锰氧氢氧化物,然后将这些锰氧化物埋藏在缺氧的成岩环境中,微生物的硫酸盐还原作用导致锰碳酸盐成核并形成富含金属的硫化物(铁、钴、镍、钒)。此外,SiEF、FeEF、KEF、TiEF、CrEF 和 ZrEF 等代用指标也证明了与锰碳酸盐岩相关的富锰硅质岩形成的碎屑输入和硫化物相(如框架黄铁矿)。这种新的勘探方法得到了通过PCA建立地球化学模型的支持,增强了我们对这些古新生代锰矿床成因的了解,并为钴勘探指明了一条新的道路。随着全球对钴的需求不断增加,特别是在涉及电动汽车电池和能源储存的应用中,勘探这些矿床成为生产这些关键金属的替代来源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Cobalt enrichment in Paleoproterozoic African and Brazilian manganese deposits
This study highlights a new by-product source for cobalt by recycling Paleoproterozoic Mn deposits. We present a geochemical modeling approach utilizing Principal Component Analysis (PCA) for available geochemical data of Paleoproterozoic manganese deposits found in Africa and Brazil, which exhibit anomalous cobalt contents (up to 1200 ppm) along with other metals such as copper, nickel, and vanadium. The PCA results for the correlation coefficient matrix of the Enrichment Factor (EF) values of major and trace elements from samples of eight Mn deposits found in Africa and Brazil (Kisenge-Kamata, Moanda, Nsuta in Africa, and Azul, Buritirama, Lagoa do Riacho, Morro da Mina, and Serra do Navio in Brazil) yielded a cumulative variance of 53.3% for PC1 (34%) and PC2 (19.3%). In PC1, the highest positive loadings correspond to the variables MnEF, NiEF, and CoEF, while the highest negative loadings correspond to the variables SiEF, FeEF, KEF, TiEF, CrEF, and ZrEF. PC2 exhibits the highest positive loadings for the variables CaEF, MgEF, and PEF, while the highest negative loadings are for CuEF and VEF. The biplot diagram representation showed that clusters of vectors MnEF, NiEF, CoEF, VEF, and CuEF influence samples of Mn-carbonate rock, Mn-carbonate–silicate rock, Mn-silicate rock, and Mn-carbonate-siliciclastic rock, all with high CoEF values (up to 414). The cluster of vectors CaEF, MgEF, and PEF significantly influence carbonate rock and dolomite marble, which have low CoEF values (close to 0). The cluster of vectors SiEF, FeEF, KEF, TiEF, CrEF, and ZrEF strongly influences siliciclastic rock, which exhibits low CoEF values. On the other hand, the cluster of vectors CuEF and VEF influences oxidized Mn ore, which exhibits CoEF values of up to 108. The results reveal a dichotomy regarding the origin of cobalt and other metal enrichments in these deposits linked to the Mn redox cycle. This process involves the formation of Mn-oxyhydroxides with the adsorption of Co and other metals under oxic conditions, followed by the burial of these Mn oxides in an anoxic diagenetic environment, where microbial sulfate reduction leads to the nucleation of Mn-carbonates and the formation of metal-rich sulfides (Fe, Co, Ni, V). Additionally, detrital input and sulfide phases (e.g., framboidal pyrite) for the formation of Mn-rich siliciclastic rocks associated with Mn-carbonate rocks are evidenced by proxies SiEF, FeEF, KEF, TiEF, CrEF, and ZrEF. This new exploration approach, supported by geochemical modeling through PCA, enhances our understanding of the genesis of these Paleoproterozoic manganese deposits and highlights a new route for cobalt exploration. In the increasing global demand for cobalt, particularly in applications involving electric vehicle batteries and energy storage, exploring these deposits emerges as an alternative source to produce these critical metals.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Geoscience frontiers
Geoscience frontiers Earth and Planetary Sciences-General Earth and Planetary Sciences
CiteScore
17.80
自引率
3.40%
发文量
147
审稿时长
35 days
期刊介绍: Geoscience Frontiers (GSF) is the Journal of China University of Geosciences (Beijing) and Peking University. It publishes peer-reviewed research articles and reviews in interdisciplinary fields of Earth and Planetary Sciences. GSF covers various research areas including petrology and geochemistry, lithospheric architecture and mantle dynamics, global tectonics, economic geology and fuel exploration, geophysics, stratigraphy and paleontology, environmental and engineering geology, astrogeology, and the nexus of resources-energy-emissions-climate under Sustainable Development Goals. The journal aims to bridge innovative, provocative, and challenging concepts and models in these fields, providing insights on correlations and evolution.
期刊最新文献
Implications of the newly discovered Triassic suites from the eastern segment in the giant Tongshan porphyry Cu deposit, northeast China Development of a comprehensive framework for wetland ecosystem assessment and management Cobalt enrichment in Paleoproterozoic African and Brazilian manganese deposits Erratum to “Cretaceous magmatic arc in Hainan and the peri-South China Sea as evidenced by geochemical fingerprinting of granitoids in the region” [Geosci. Front. 15(5) (2024) 101866] Geochemical cycling, tectonic drivers and environmental impacts of CH4-rich mud extrusions in subduction zones
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1