Abstract
The complexity of mineral processing investigations is rapidly increasing the demand for precise composition and phase distribution analysis in complicated ore assemblages. Here, we present a systematic mineralogical approach to assess the chemical composition of geological ores (namely: S-7, S-8, S-12, S-13, S-15, S-17 and S-18) by key characterization techniques including: X-ray diffraction (XRD), Scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX) and Fourier transform infrared spectroscopy (FTIR). The XRD analyses reveal that the ores are comprised of different minerals including: quartz, microcline, albite, kaolinite, muscovite, barite, fluorite, calcite and hydroxyapatite. The microstructural, morphological and surface topography are determined by SEM using secondary electron (SE) imaging while backscattered electron (BSE) imaging effectively differentiates the various regions within the ore samples according to their compositional difference. Both qualitative and quantitative elemental analyses are provided by EDX spectra. A total of 25 elements were detected, including rare-earth elements as well. Moreover, the functional groups which are the finger prints of the minerals present in the ores were investigated by FTIR spectroscopy. The IR absorption bands are well assigned and interpreted. The experimental results from XRD, SEM-EDX and FTIR are well associated with one another and successfully classify the ore samples on the basis of their lithologies.
Acknowledgment
The authors acknowledge the contributions of Mr. Hidayat Ullah and Mr. Syed Zahid Hussain, PINSTECH for FTIR and XRD data collection.
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Research ethics: No experiments on human subject, human material, human tissues, or human data were conducted in this study.
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Informed consent: Informed consent was obtained from all individuals included in this study.
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Author contributions: A. Z. and M. W. conceived the idea and designed the project. T.A carried out the SEM-EDX characterization. A.Z analyzed the XRD, SEM-EDX and FTIR data and interpreted the results. R. N. Q performed the principal component analysis. A.Z. wrote the paper and conducted the whole study.
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Use of Large Language Models, AI and Machine Learning Tools: There is no use of Large Language Models, AI and Machine Learning Tools during the manuscript preparation.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: The authors declare that no funds and grants were received during the preparation of this manuscript.
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Data availability: The data can be obtained on request from the corresponding author.
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Supplementary Material
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- Frontmatter
- Original Papers
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- Study on empirical formulae for (n,f) reaction cross sections of thorium isotopes between 1 and 20 MeV
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