In 1985, a new form of carbon called fullerene (C60) was first discovered, which consists of sixty carbon atoms situated at sixty vertices, all together forms 20 hexagons and 12 pentagons 1. It was also reported that C60 is considered the most symmetric molecule with 120 symmetry operations possible due to the unique structure formed by the arrangement of carbon atoms as 20 hexagons and 12 pentagons 2. Altogether it includes a hollow spherical cage-like structure with the unique ability to trap particles of size even in nanometers. The unique physical and chemical properties of fullerene have opened up tremendous usages in various essential areas like solar cells 3, semiconductor (OSC) materials 4, photocatalysts 5, organic optoelectronic applications 6,7, and biological and Biomedical applications respectively8–10. Buseck et al. reported the occurrence of naturally occurring fullerene in the shungite rocks of Karelea 11. Later in India, fullerene bearing shungite rocks were discovered in the Mangampet baryte mine located in Kadapa District, Andhra Pradesh 12. It also states that the interlayered thick black colored slates of carbonaceous shale present in baryte mines confirm that shungite suit of rocks have a composition of carbon-hydrogen-sulphur. Further, Inductively Coupled Plasma Mass Spectrometry (ICP-MS) shows the traces of Be, Co, Ga, Ge, Y, Zr, etc. The laser desorption/ionization mass spectrometry gives the main peaks near m/z = 720amu and 840 amu indicating the presence of C60 and C70. It is estimated to about 74 million tonnes of reserves in Mangampet mine, which is known to be the largest in the World. The Andhra Pradesh Mineral Development Corporation Limited (APMDC) is engaged in the mining of barytes, and baryte mining contributes more than 95% of the turnover. The fullerene-bearing shungite deposits along with white shale are left as mine dumps. So the need for converting this material into value-added products and marketing is the main concern of the scientific community.
Remote sensing applications of geology and mineral exploration start with the advent of Landsat multispectral satellite imagery, which was mainly used to delineate potential mineral occurrences related to hydrothermal alteration zones. The band ratio, principal component analysis (PCA), and spectral angle mapper (SAM) applied to Landsat ETM + and OLI data successfully detect alteration minerals associated with porphyry copper mineralization 13. Later, shortwave infrared bands of ASTER and Landsat 8 were used to successfully extract the solid information about clays and iron oxide minerals.The techniques such as Spectral Angle Mapping (SAM), Mixture Tuned Match Filtering (MTMF), Crosta technique, and Spectral Feature Fitting (Hewson and Cudahy 2010, Pour and Hashim 2014) were used. RGB composites, Spectral Angle Mapping (SAM), Color composites of PC bands derived from Landsat ETM+, ASTER, and Sentinel-2A discriminates granitic intrusions associated with copper mineralization 14, alteration zones related to igneous bedrock 15, lithological units 16, and rock units associated with ophiolite complex 17. The advent of hyperspectral imagery, such as Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) made a significant mineral mapping breakthrough. The MTMF, Spectral Feature Fitting (SFF), SAM, and Spectral Information Divergence (SID) applied to AVIRIS-NG and Hyperion successfully maps hydrothermal alteration minerals 18–20. A wide range of mineral types ranging from copper-gold mineralization, chromite occurrences, mafic-ultramafic rocks, hydrothermal alteration minerals, beach minerals were successfully demarcated using remote sensing data and techniques. Apart from band ratio, spectral indices and PCA, advanced image classification algorithms including Machine Learning, Random Forest, and Artificial neural networks were also used for mapping lithology 21, gold mineralization 22, Cu potential areas 23, etc. In mineral exploration studies, structural and geochemical characterisation is fundamental to confirm the mineral type, grain size, etc. The X-ray diffraction (XRD) spectra of clays in rock samples were collected from the region where the hydrothermal alteration mapping was carried out using Landsat and ASTER 13,24. The XRD and XRF techniques were used to confirm the iron ore deposits mapped using Maximum Likelihood supervised classification of LandsatTM + data 25. The XRF analysis confirms the presence of gold collected from alteration zones (gossanic ridges) mapped using spectral band rationing techniques applied to Landsat 8 OLI image and thereby validated the importance of remote sensing exploration26.
As follow-up to our previous study on beach sediments, we tried to investigate baryte deposits in Mangampet mine of Andhra Pradesh, India using hyperspectral analysis followed by image classification using MTMF and SVM. The reference spectra developed from the laboratory spectra is used for deriving the true endmembers from ASTER and Landsat data. The validation of fullerene bearing baryte deposits was also carried out using ED-XRF, XRD, XPS, FTIR, HPLC, and MALDI analyses.