English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

Pyrite analysis enhanced by dimensionality reduction: investigating texture, trace elements, and sulphur isotope signatures in the Kibali gold district, DRC

Authors

Waku,  Yann Mpaka
External Organizations;

Von der Heyden,  Björn
External Organizations;

Hurst,  Gary
External Organizations;

Lawrence,  David M.
External Organizations;

Mwandale,  Etienne
External Organizations;

/persons/resource/sglynn

Glynn,  S.
3.1 Inorganic and Isotope Geochemistry, 3.0 Geochemistry, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in GFZpublic
Supplementary Material (public)
There is no public supplementary material available
Citation

Waku, Y. M., Von der Heyden, B., Hurst, G., Lawrence, D. M., Mwandale, E., Glynn, S. (2023): Pyrite analysis enhanced by dimensionality reduction: investigating texture, trace elements, and sulphur isotope signatures in the Kibali gold district, DRC - Abstracts, 17th SGA Biennial Meeting "Mineral Resources in a Changing World" (Zürich, Switzerland 2023).


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5027955
Abstract
Pyrite is the most abundant sulphide mineral in the various ore zones hosted within the world-class Kibali gold district. Because of its affinity for trace elements and gold incorporation, pyrite mineral chemistry is increasingly being used as a powerful tool to assess the characteristics of ore formation. This study presents a novel dimensionality reduction-based approach for pyrite classification. This approach incorporates the strengths of both Uniform Manifold Approximation and Projection (UMAP) and Principal Component Analysis (PCA) with k-Means clustering to analyse the large trace element datasets derived from in-situ laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) including sulphur isotope from Secondary Ion Mass Spectrometry (SIMS). The results suggest that 8 clusters may be defined from the pyrite mineral chemistry signatures. This clustering served to direct a refined classification relative to the initial textural analysis. We anticipate that our approach may be adopted by other workers who wish to disentangle complex pyrite growth and gold mineralisation histories in a variety of geological contexts.