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 , Felipe Holanda dos Santos , Douglas Teixeira Martins , Wagner da Silva Amaral , 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}
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.
Geoscience frontiersEarth 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.