Archean crust and metallogenic zones in the Amazonian Craton sensed by satellite gravity data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

J G Motta, C R de Souza Filho, E J M Carranza, C Braitenberg

ABSTRACT

The formation of ore deposits has been extensively studied from a shallow crust perspective. In contrast, the association of mineral systems with deep crustal structure of their host terranes remains relatively undisclosed, and there is evidence that processes throughout the lithosphere are coupled for their evolution. The current debate centers on the control of the regional deep crustal architecture in focusing and transferring fluids between geochemical reservoirs. Defining such architecture is not unequivocal, and involves combining indirect information in order to constrain its physical properties and evolution. Herein, based on evidence from satellite gravity, constrained by airborne potential field data (gravity and magnetics), we provide an example on how the lithosphere geometry controlled the location of copper and gold systems in the world-class Archean Carajás Mineral Province (Amazonian Craton, South America). Validation with information from passive seismic (wave speeds, crustal and lithospheric thickness) and geochronologic data (model, crystallization ages, and Neodymium isotope ratio determinations) portrays a significantly enlarged, poly-phase, Archean crust that exerted geometric control on the location of the mineral systems within and adjacent to the province during tectonic quiescence and switches. This new geologic scenario impacts the understanding of the Amazonian Craton. Synergy between multi-source data, as experimented here, can provide robust models efficiently and, conceivably, help to unveil similar terrains elsewhere. More... »

PAGES

2565

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-019-39171-9

DOI

http://dx.doi.org/10.1038/s41598-019-39171-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112308364

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30796278


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39171-9'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39171-9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39171-9'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39171-9'


 

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