**Recent Advances in Environment-Friendly Alkyd Nanocomposites Towards "Greener" Coatings**

Eram Sharmin, Fahmina Zafar, Nahid Nishat and Sharif Ahmad

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/62448

#### **Abstract**

Alkyd nanocomposites have attracted great attention in the field of heavy duty coating materials. This is due to the synergistic action of both alkyds (flexibility, biodegradabili‐ ty, compatibility, good gloss retention, durability, weathering resistance) and nanofil‐ lers (large surface area to volume ratio). Alkyd nanocomposites show good physicomechanical, physico-chemical, anticorrosive, and antimicrobial performances and thermal stability, with application as anticorrosive, anti-fog, self-cleaning, self-healing, and antimicrobial coatings. In view of present drives and legislations towards environ‐ ment-friendly coatings, alkyds have undergone modifications as waterborne, high solids, hyperbranched "greener" nanocomposites. The present chapter deals with a brief overview of alkyds, recent advances in environment-friendly alkyd nanocomposite coatings, and the effects of nanofillers on the performance (physico-mechanical, chemical/ corrosion resistance, thermal stability, and others) of "greener" alkyd nanocomposite coatings.

**Keywords:** alkyds, nanocomposites, coatings, physico-mechanical, chemical resist‐ ance, thermal stability

## **1. Introduction**

Alkyd resins are the most versatile vegetable seed oil (VSO)-based polymeric binders find applications paints and coatings industry. They are polyester-based materials modified with oil or oil derived fatty acids. Alkyd resins owe their wide applications to their versatility and capability to engineer a wide variety of acceptable properties in terms of usage by the Coat‐

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

ings industry.Alkyds now accountfor approximately half of allthe resins consumedin the field of protective coatings [1–6]. Chemically, alkyd resins have been defined as reaction product of condensation polymerization of polyhydric alcohol, polybasic acid, and monobasic fatty acid (saturated or unsaturated; **Figure 1**). They are best classified according to the amount of fatty acid and phthalic anhydride present (**Table 1**) [1].

**Table 1** Alkyd classification.

**Figure 1.** Alkyd synthesis, where R=fatty acid chain (saturated or unsaturated). Where PA:Phthalic anhydride, Gly:Glycerol and TMPTMA: Trimethylolpropane Trimethacrylate.

The reaction of alkyd (**Figure 1**) is based on three basic fundamental building blocks:

Alkyd resins have good color retention, durability in exterior finishes, good weathering resistance, and moderate resistance to corrosive fumes but show poor resistance to chemical splash and spillage, especially in alkaline medium. The thermal stability of these resins goes up to 105°C [3]. The properties of alkyd coatings are derived mainly from the properties of drying oils used in the manufacture of the resins. The extent and kind of unsaturation in drying oil fatty acids have a profound effect on the properties of finished alkyd. The drying time, hardness, color, and moisture resistivity of the resin depends on the degree of unsaturation of the oil used [1,4]. These unsaturation sites are responsible for the curing of alkyd resins through auto-oxidation process (Figure 2). The process creates the active free radicals leading to the formation of a three-dimensional cross-linked network. [1,7].

**Figure 2.** Autoxidation of alkyd.

The standard alkyds are usually soybean and linseed oil alkyds, which show moderate and faster drying rates, respectively. The former has good color retention, whereas the latter reduces the color retention requirement. Dehydrated castor and soybean oil-based alkyds are used for baked finishes. These alkyds in combination with urea formaldehyde and melamine formaldehyde resin exhibit shorter baking time and produce harder film. For light color and maximum color retention, nondrying oils, such as coconut, castor, and cottonseeds, may be used. The alkyd of this type does not dry because of the nonoxidizing character of the parent VSO. They must be blended with some cross-linkers and baked with amine resin, such as urea or melamine formaldehyde, at high temperature (**Figure 3**).

**Figure 3.** Curing reactions of alkyd resins with amino resins.

Nondrying VSO-based alkyds are also used as resinous plasticizers and other lacquer-type polymers. Tung and oiticica in combination with other VSO-based alkyds show faster drying and achieve earlier hardness. Safflower oil-based alkyd has excellent drying properties and color retention [1,8]. Besides these, some nontraditional VSO-based alkyds, such as nahar (*Mesua ferrea* Linn), kamala (*Mallotus phillipinensis*), mahua (*Madhuca longifolia*), barbados nut (*Jatropha curcas*), burra gokharu (*Tribulus terrestris*), undi (*Calophylum inophyllum*), karanja (*Pongamia glabra*), karinotta (*Samera indica*), nigerseed (*Guizotia abyssinica*), babul (*Acacia arabica*), and neem (*Azardirachta indica*), have been reported and used as coating materials [4,9– 11]. Tobacco seed oil has been reportedly used in alkyd preparation for wrinkled finish paints [10]. The use of pentaerythritol as a polyhydric alcohol produces faster drying, greater hardness, better gloss, and better water resistance than alkyds based on glycerol of equal fatty acid content [12].

Modifications of alkyd resins are continuously carried out to achieve improved mechanical and chemical resistance properties and these systems find a wide scope of application as corrosion protective coatings. The modification with acrylic monomer, such as styrene, methyl methacrylate, vinyl toluene, and others, has been extensively done by researchers through unsaturation to improve the performance of resins up to the desired level [13]. Butylmetha‐ crylate-co-maleic anhydride copolymer modified linseed and rubber seed oil alkyds through functional groups are used as co-curing resins with melamine formaldehyde resin to prepare baking-type coating compositions, whereas *Albizia benth* medium oil-based alkyd gives room temperature cured resin, with superior film properties [3,14,15]. The modification of alkyd with chlorinated rubber resulted in improved adhesion as well as improved acid, alkali, and water resistance. The chlorination of soybean and *A. benth* oil-based alkyd transforms into an air-drying, nonconvertible film former with improved mechanical properties [3,16,17]. Chainstop alkyds from solvent fractionated *Argemone* and rubber seed oil are used for specialty alkyd [18]. Heated rubber seed oil-based films show excellent resistance to acid and salt solution. Its combination with cashew nut shell liquid formaldehyde resin has improved the drying ability and chemical resistance [19]. The phenol-modified alkyd resin improves gloss retention as well as water and alkali resistance. Waterborne-baked and air-drying alkyds have also been developed from different VSO having properties similar to their solvent-borne counterparts and found application in paint and coatings [20,21]. In addition, alkyd resins can be modified with epoxies and polyurethanes or other thermoplastic resins to give coatings of improved performance. For example, urethane oils are prepared by reacting diglycerides with toluene diisocynate. The resulting oils are used in alkyd resin preparation or as additive for coatings. Besides these, other alkyds are also prepared, such as imide-modified alkyd, amide-modified alkyd, tetrachlorophthalic anhydride-based alkyd resin with fire-retardant properties, ketene and acetic anhydride modification with terminal hydroxyl groups of alkyd, zinc chromate containing alkyd resin, triphenyl phosphite containing alkyd resin with improved color and drying properties, oil-less alkyds, ultraviolet (UV) light hardenable pigmented alkyd resin laquer preparation, and maleic anhydride-cyclopentadiene adduct in alkyd preparations [22– 24].

In recent years, due to concerns related to energy consumption and environmental contami‐ nation, regulations, and legislations directing us towards "sustainable development" and innovations, efforts are being focused towards the development of (i) "greener" environmen‐ tally benign materials (ii) with improved performance characteristics to meet the present-day demands. Environment-friendly technologies such as high solids, hyperbranched, water‐ borne, and UV curable, are being used to eliminate the use and/or generation of hazardous chemicals and emissions harmful to environment. For improvement in performance, the inclusion of nanosized fillers as nanoreinforcements is being accomplished. In this context, the world of alkyds has also witnessed greater modifications such as switching to high solids, hyperbranched, waterborne and UV curable alkyds (Figure 1)[22,23,25–29]. In our recent review articles, we have described alkyds and their modifications in terms of both in property enhancements and environment-friendly approaches, occurring in the last decade [22,23]. This manuscript provides a brief overview of environment-friendly recent advances that have taken place in the field of alkyds and also focuses on the properties and performance characteristics of high solids, hyperbranched, and waterborne alkyd nanocomposites along with the unex‐ plored areas in the field and possible future research directions.

## **2. Environment-friendly recent advances in alkyds towards "greener" coatings**

Considering the future predictions, energy concerns, associated hazards, and legislations, research progresses in the quest for improved and updated performance characteristics in every field. Alkyds have undergone several modifications recently in consideration of the aforementioned, such as the use of reactive diluents, resorting to solvent free approaches, and others. In alkyd-based coatings, towards the step to eliminate the use of organic solvents, which are often added to achieve the desired viscosity for application over the substrate, tung oil (TO)-based reactive diluents were added to soy alkyd formulations. TO-reactive diluents were modified with alkyoxylsilane, tetraallyl ether, and fluororinated side chain. These diluents participated in the film formation process and significantly reduced the viscosity of alkyds, thereby serving as effective diluents. Alkoxysilane-modified diluents showed somewhat enhanced performance due to *in situ* polycondensation of silicon alkoxide within the organic polymer matrix, which provided an additional functionality for cross-linking [30]. To reduce the content of solvents and to achieve desirable viscosity, carboxymethyl cellulose nitrate ester/ coconut alkyd blends were prepared, which resulted in hydrophilic transparent films [31,32].

In a recent "greener" approach, *Jatropha* oil (JO)-based alkyd was blended with citric acid cured JO-derived epoxy. The final product showed enhanced tensile strength, elongation at break, hardness, increment in gloss due to uniform and smooth surface morphology, good scratch hardness and adhesion conferred by highly cross-linked networks, flexibility of oil chains, and the presence of polar functionalities in the backbone, which also contributed to excellent resistance to solvents (water and ethanol), salt solution, and good acid and alkali resistance [33]. An interesting research includes the synthesis of alkyds from postconsumer polyethylene terephthalate (PET) bottles. Herein, waste PET was glycolyzed using glycerol, trimethylol‐ ethane, trimethylolpropane, and pentaerythritol, giving tetra- and hexafunctional glycoly‐ zates. PET glycolyzates were then used as hydroxyl components in the synthesis of alkyd resins. The approach has multiple advantages: (i) value addition to a waste material (i.e., PET), (ii) reduction in the amount of waste PET in dumps and landfills, (iii) reduction in amount of phthalic anhydride, and (iv) improved performance of alkyd. The best performance was achieved by the inclusion of trimethylolethane and trimethylolpropane, as they had four sterically unhindered primary hydroxyl groups that produced alkyds with higher degree of branching, consequently higher molar mass, which led to improved mechanical, drying, and chemical resistance properties [34].

Laccases are enzymes first discovered in Japanese lacquer tree *Rhus vernicifera* by Yoshida in 1883, which are found in fungi, different bacteria, and plants. In an effort to completely replace the toxic heavy metals by nontoxic and environment-friendly catalysts, laccase-mediator systems have been considered as potential cross-linking and functionalizing agents for alkyds [35]. In the synthesis of alkyds, heterogeneous base catalysts are used such as hydroxides of calcium, potassium, sodium, lithium, oxides of calcium, zinc, and others. Recently, CuO nanocatalyst was introduced, which had dual effects: (i) it catalyzed the alcoholysis-polyest‐ erification reaction, reducing the reaction time, and (ii) it conferred antimicrobial properties to the resin [36]. Thus, the addition of nanofillers leads to enhancement in several properties, often drastically, such as aesthetic appeal, UV resistance, corrosion resistance, scratch resist‐ ance, impact resistance, thermal stability, and others, thus reinforcing the matrix, without losing transparency and other properties. The enhancement in properties is a consequence of the much greater surface-to-volume ratio of the nanofiller. The incorporation of nanoparticles in the polymer matrix offers significant barrier properties for corrosion protection. It reduces blistering or delamination and also enhances the integrity and durability of coatings (the fine particles uniformly dispersed in coatings can fill cavities and can cause crack bridging, crack deflection, and crack bowing) [37,38]. After having a brief idea of the recent advances in the field towards environment-friendly "greener" coatings, in the proceeding sections, we will discuss about some of the recent developments in alkyd-based environment-friendly (water‐ borne, high solids, hyperbranched) nanocomposite coatings.

## **3. Waterborne alkyd nanocomposite coatings**

In these types of coatings, the alkyd matrix selected is waterborne and is further modified with nanoreinforcements depending on the property that needs improvement (Figure 4). Thus, the choice of nanofillers for modification depends on the property that is needed to be augmented or enhanced. The inclusion of nanoalumina improved the scratch, corrosion, UV, and abrasion resistance of coatings. The increased content of nanoalumina reduced the pinhole formation tendency and defended the coatings against humidity [37]. The corrosion protection Occurred by (a) nanoparticles occupying the vacant spaces in the coating matrix, (b) reducing porosity, (c) bridging and interconnecting the constituents of matrix, (d) increasing cross-linking, (e) providing longer diffusion paths to corrosive ions, and (f) improving barrier performance [39]. A similar enhancement in the performance of coatings was also observed when waterborne alkyd coatings were modified with nano-Fe2O3 by the described corrosion protection mecha‐ nism. Even at the lower loading of nano-Fe2O3 (0.05%, 0.1%, and 0.2%), the corrosion process was delayed, whereas, at 0.3% loading of nano-Fe2O3, adequate coating performance was achieved [40,41]. Nano-silica modification improved scratch resistance, abrasion resistance, adhesion properties, impact resistance, glass transition temperature, and thermal stability [42,43]. The introduction of ZnO nanoparticles improved film compactness and abrasion resistance and had a catalytic influence on curing reaction, thus facilitating the formation of hard and complex network. The stronger interactions between nanoparticles and alkyd matrix also conferred enhancement in mechanical properties. As nano-ZnO has UV blocking prop‐ erties, the incorporation of nano-ZnO also improves the UV resistance of coatings [44–46].

**Figure 4** Waterborne alkyd nanocomposites.

Poly(methylmethacrylate-butylacrylate)/nanocalcium carbonate, prepared by emulsion polymerization, was blended with alkyd coating with 50 wt% water as solvent, in various ratios, with dual objectives: (i) using polymer nanocomposite as partial binder and (ii) As a filler to improve the properties. The coatings showed good gloss, mechanical and thermal properties; however, impact resistance was found to be lower. The highly crystalline calcium carbonate nanoparticles deteriorate the impact strength at locations in coatings where the aggregation of particles occurs, thus generating stress at these specific sites [47].

#### **4. Hyperbranched alkyd nanocomposite coatings**

The use of dendritic or hyperbranched polymers as binders in coatings is considered as one of the effective ways to reduce volatile organic compounds (VOCs; **Figure 5**).

**Figure 5** Hyperbranched alkyd, where I=dimethylolpropionic acid, II–IV=hyperbranched polyesters (HBPs), and **V– VII**=their respective hyperbranched alkyds; a–c are dipentaerythritol, pentaerythritol, and 1,3,5-tris(2-hydroxyeth‐ yl)cyanuric acid, respectively; and R=fatty acid chain (unsaturated or saturated).

These polymers have three-dimensional compact structures. They show low viscosity even at higher molecular weight. Thus, the development of hyperbranched nanocomposites has double advantages: (i) overcomes the use of VOCs and (ii) leads to property enhancement.

**Figure 6** Hyperbranched alkyd/silicone or silver nanocomposites.

In a recent research, nanosilver was embedded in hyperbranched urethane alkyd by an *in situ* approach that prevented agglomeration of nanoparticles (**Figure 6**). The nanocomposites showed good antibacterial activity against *Serratia marcescens*, as studied by using agar overlay and disk diffusion methods, and the coatings were gloss retentive and nonleaching. The resin required much lesser solvent for coating formulation and showed improved mechanical properties [48].

An interesting research work was performed on carbon nanofiller modification of hyper‐ branched alkyd. Here, three geometrically different carbon nanofillers, carbon black (CAB), multiwall carbon nanotubes (MWCNT), and graphene (GR), were treated with a surfactant Nonidet P-40 (**Figure 7**). This led to the uniform dispersion of carbon fillers as facilitated by the interactions of π-electron clouds of carbon nanofillers with the delocalized π-electrons of the surfactant and H-bonding interactions between surfactant and hyperbranched alkyd backbone. The former interactions reduce the van der Waals forces present between carbon nanofillers, and the latter interactions improve the interfacial adhesion between the matrix and nanofillers. Due to their stronger interactions with the alkyd backbone and the high aspect ratio and surface area, MWCNT and GR showed better dispersion in the matrix relative to CAB. Thus, modifications with MWCNT and GR provided relatively higher scratch resistance, adhesion, and tensile strength to alkyd coating as well as higher thermal stability. The water vapor transmission rate was found to be lower in nanocomposite alkyd, and least in GR alkyd (due to its plate-like structure), compared to the unmodified alkyd, as the nanofillers provided tortuous path to water and oxygen molecules hindering them to reach the substrate of the coating easily. However, compared to others, GR-alkyd showed the highest corrosion resistance performance due to good dispersion and adhesion of GR; moreover, its plate-like structure also proved advantageous in enhancing the corrosion resistance [49]. The modifica‐ tion with silicones reduces the drying times and improves the adhesion to the substrate, hardness, and gloss of coating (**Figure 6**) [50].

**Figure 7** Hyperbranched alkyd urethane/GR or MWCNT nanocomposites.

## **5. Future suggestions and conclusion**

Environment-friendly alkyd nanocomposites are an emerging field of research. They comprise a vast field for commercial coating applications. They find promising applications as corrosionprotective, antimicrobial, eco-friendly coatings. However, more efforts are required in the field to be established further as "greener" coatings in terms of performance, cost, and environmentfriendly applications. A lot of modifications have been accomplished and much remains unexplored.

The synthesis of alkyds requires higher temperatures and longer reaction times. In view of this, alkyd synthesis can be performed via microwave-assisted methods that reduce reaction times and often temperatures. Another alternative is the synthesis by enzymatic approach. Hydroxylated oils (or polyols) can be used to prepare monoglycerides, which would introduce extra hydroxyl functionality in alkyd backbone increasing the adhesion of coatings produced due to polar hydroxyls. The alkyd with extra hydroxyls in its backbone will serve as alkyd polyol. Considering the present drives towards environment-friendly coatings, efforts should be laid on the development of low solvent or solvent-free alkyd nanocomposite coatings to reduce the use of harmful solvents during the synthesis, processing, formulation, and appli‐ cation of coatings. More emphasis should be laid on the development of waterborne, high solids, hyperbranched, and UV curable alkyd nanocomposites using different nanofillers. A completely water-soluble alkyd nanocomposite would be a significant achievement in the field. Greener isocyanates may be used as curing agents for alkyd polyurethane nanocompo‐ sites. The introduction of nanoparticles by *in situ* approach may reduce reaction steps and also the problems associated with the agglomeration of nanoparticles. Blending with cost-effective reinforcing components will also effectively reduce cost and improve performance character‐ istics. The greater utilization of nonedible and nonmedicinal oils in the preparation of alkyds must be encouraged to add value to underutilized oil as a bioresource. Efforts may also be focused on studying the biodegradation behavior of these materials to determine their ecofriendly disposal.

## **Acknowledgements**

Dr. Fahmina Zafar is thankful to the University Grants Commission, India, for the Dr. D.S. Kothari postdoctoral fellowship, Ref. #F.4/2006(BSR)/13-986/2013(BSR), with Prof. Nahid Nishat.

## **Author details**

Eram Sharmin1\*, Fahmina Zafar2\*, Nahid Nishat2 and Sharif Ahmad3

\*Address all correspondence to<EMAIL_ADDRESS>
\*Address all correspondence to<EMAIL_ADDRESS>
1 Department of Pharmaceutical Chemistry, College of Pharmacy, Umm Al-Qura Universi‐ ty, Makkah Al-Mukarramah, Saudi Arabia

2 Inorganic Materials Research Laboratory, Department of Chemistry, Jamia Millia Islamia (A Central University), New Delhi, India

3 Materials Research Laboratory, Department of Chemistry, Jamia Millia Islamia (A Central University), New Delhi, India

## **References**


Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological Units Using the Integration of SWIR and TIR ASTER Data

*Ronak Jain*

## **Abstract**

Geological studies have been performed using the Band Ratios (BR), Relative Band Depth (RBD), Mineral Indices (MI), Principal Component Analysis (PCA), Independent Component Analysis (ICA), lithological and mineral classification techniques from Short-Wave Infrared (SWIR) and Thermal Infrared (TIR) data. The chapter aims to delineate various geological units present in the area using the combination of SWIR and TIR ASTER bands through the Feature-Oriented Principal Component Selection (FPCS) technique. Different BRs and RBDs were applied to map the minerals having Al-OH and Mg-OH compounds with the chemical composition of clay (kaolinite, smectite), mica (sericite, muscovite, illite), ultramafic (lizardite, antigorite, chrysotile), talc, and carbonate (dolomite) from SWIR bands. The MI was used to map quartz-rich, mafic/ultramafic, and carbonate rocks using TIR bands. The BRs, RBDs, and MIs mapped the geological units but every single greyscale image showed a variety of features. To compile these features False Color Composite (FCC) was prepared by the combination of RBDs and MIs in the R:G:B channels which demarked various geological units to a larger extent present in the region. To overcome the limitation, the FPCS technique was applied with the integration of all BRs, RBDs, and MIs. The FPCS technique extracts valuable information from different input bands and shifts the information in the first few bands. The generated eigenvalues and eigenvectors represented the retrieved information in the specific band. The loadings of the eigenvector were used for the selection of the different brands to create the FCC for the delineation of geological strata. The best discrimination was made by the selection of FPCS1, FPCS3, and FPCS6 which differentiated all the geological units like ultramafics, dolomites, thin bands of talc, and muscovite and illite (as phyllite and mica-schist), silica-rich rocks (as quartzite), and granite outcrops.

**Keywords:** Remote Sensing, Optical data, Feature-Oriented Principal Component Selection, Data integration, Geological studies

## **1. Introduction**

Water (oceans, rivers, lakes, etc.) and land (rocky mountains, hills, peneplain, islands, etc.) are the major components of the Earth's surface out of which only 29% are occupied by the land surfaces. This 29% land coverage included the forest, desert, mountains, islands, etc. so, a very little amount of land is reserved for geological studies.

Traditional mapping methods are time-consuming and require lots of effort for the preparation of lithological maps, mineral maps, structural maps, etc. But sometimes manually collected data may have errors due to inaccessibility and recording of the data which exaggerate in due course. To avoid these errors and corrections introduced therein an advanced technology came into the picture and is known as Remote Sensing. This technique helps in the mapping of the different litho-units and associated structural features with higher accuracy in a short period as compared to the traditional methods.

Remote Sensing is a tool used for the gathering of the target information without any physical/direct contact with the earth's surface [1–6]. It is a widely used science for the identification and mapping of the various objects/materials present on the earth's crust. The electromagnetic wavelength ranges from 0.38 μm to 100 cm i.e. visible to microwave region [3] is utilized for capturing the information from the earth's surface along with different sensors to capture the EM spectrum's energy [4, 5, 7]. This technique is useful for the monitoring, protection, and management of diverse natural resources and land cover [8]. The geological studies include the demarcation of various lithologies, alteration zones, minerals, and structural features.

Multispectral Remote Sensing is utilized in the domain of geosciences for lithological mapping [9–16], mineral mapping [17–24], identification of the alteration zones related to the base metal mineralization [25–42], structural features as a controlling factor for mineralization [26, 28, 42–46] and mapping for demarcating favorable zones of mineralization [21, 47, 48]. Spectral characteristic absorption features of the rocks and minerals are utilized for the identification and mapping of lithologies and minerals like calcite, dolomite, clay, mica, and ultramafics, etc. The spectral absorption features of minerals vary with chemical composition and the resultant spectral curve varies in shape, depth, position, and asymmetry [49].

Wavelength range from 0.38 to 2.5 μm is utilized for the mapping of the various hydroxyl (Al-OH, Mg-OH), iron oxides (Fe-OH), carbonates (CO3 2 ), and sulphates (SO4 2 ) bearing minerals like clay, mica, ultramafics, hematite, limonite, dolomite, calcite, etc., due to the presence of characteristic absorption features in the VNIR and SWIR region of the EM spectrum [5, 42, 50–53]. In the case of feldspar, silica-rich rocks, and discrimination between ultramafics and dolomites are possible due to spectral features associated with the TIR region in the wavelength range of 3 to 50 μm [20, 23, 54–58]. The dissimilarities in the spectrum in the TIR spectral-domain arise due to variation in chemical composition and molecular structure.

Geological studies are done with the help of Landsat series, ASTER, Sentinel 2, SPOT, Worldview series, GeoEye, etc. optical remote sensing satellites. They are mainly utilized for the perspective of mineral exploration by using the various methods like band ratio (BR), relative band depth (RBD), Principal Component Analysis (PCA), Independent Component Analysis (ICA), Minimum Noise Fraction (MNF), unsupervised classification (K-means, isodata, etc.), supervised classification (Spectral Angle Mapper, Spectral Feature Fitting, Mixture Tuned Matched Filtering, etc.), machine learning (support vector machine, decision tree, artificial neural network, etc.). Various BR and RBD have been used for the delineation of the different rock outcrops like dolomite, calcite, Iron rich-rocks, ultramafics, epidote, clay and mica minerals, etc. [17, 21–24, 42, 58–60] and mineral prospects by the demarcation & mapping of the associated alteration zones [20, 22, 27, 28, 37, 45, 61]. Lithological mapping of the exposed outcrops and their associated features are

*Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological… DOI: http://dx.doi.org/10.5772/intechopen.99046*

demarcated with the help of PCA, ICA, and MNF analyses to govern the mineral potentiality of the outcrops [9, 17, 40, 42, 44, 62, 63]. Different supervised, unsupervised, machine learning and prospectivity mapping algorithms were applied to the optical datasets to prepare the mineralogical and prospective zone maps of the region and these maps contain the information about the mineral potential zones which were utilized for the perspective of mineral explorations [17, 20, 21, 31, 42, 47, 48, 64–71].

## **2. Objective of the chapter**

This chapter explains the use of SWIR and TIR spectral bands for the demarcation of the different minerals and lithologies present in the region. The importance of integrated datasets from SWIR and TIR-derived outcomes and the utility of the integrated dataset for the demarcation of the various litho-units has also been explained.

#### **3. Study area and geological setup**

The coverage of the study area extends between latitude 23°510 35.45″ to 24° 180 34.14″ in the North and longitude 73°280 43.95″ to 73°490 34.24″ in the East and occupies the region in Udaipur and Dungarpur districts of Rajasthan, India (**Figure 1**).

#### **Figure 1.**

*Location of the study area in inset maps of India and Rajasthan. Lithological map of the study area. Modified after Gupta et al. [72]. Red dashed lines are representing the existing faults. Mp: Mando ki Pal; Sr: Sarada (BGC); Np: Natharia ki Pal; Ss: Sisa Magra; Kt: Kathalia; Mn: Mandli; Bm: Baroi Magra; Bl: Balicha; Zw: Zawar; Gr: Goran; Sm: Samlaji Formations.*

Geologically the study area falls in the Udaipur sector exposes various lithostratigraphic units of the Archean and Palaeoproterozoic age [72–74] (**Figure 1**, **Table 1**). The basement rocks are the Banded Gneissic Complex (BGC) [73, 75] or the Bhilwara Supergroup (BSG) [72, 74]. They are overlain by the rocks of the Aravalli Supergroup through an erosional unconformity. The Aravalli Supergroup has been categorized into Debari, Udaipur, Bari Lake, Jharol, Dovda, Nathdwara, Lunavada Groups [72]. It has also been subdivided into Lower, Middle, and Upper Aravalli Groups [73].

Majority of the pristine Archean features of the basement rocks have diminished due to tectono-thermal reconstruction of the basement [73]. Basement rocks from Mangalwar Complex are composed of heterogeneous rocks of amphibolite-facies metamorphites [75] or granite-greenstone belt [74]. Gneisses, metabasics, migmatites, and schists constitute the basement while greywacke, chert, marble, dolomite, quartzite, fuchsite quartzite, and mica schist represents the metasediments within the basement [74, 76]. Biotite schist, garnets, and staurolites are present in the Sarara ki Pal inlier [73, 77] and the presence of chlorite and chloritoid represents the retrogression mechanism [78].

The base of the Aravalli Supergroup is having thin bands of quartzites and pebbly oligomictic conglomerate. The continuity of quartzite is interrupted by the ESE-WNW, NE–SW, and ENE-WSW faults. In the majority of the study area phyllites and mica-schists are exposed. Graded bedded greywacke occurs within the phyllite [79]. Poddar & Mathur [80] mentioned the characteristic repetition of graded bedded and slaty phyllite. Different varieties of dolomites are exposed in the Zawar region with gradational contact with greywacke. They are pure to siliceous and massive to gritty nature. Lead-zinc mineralization is confined in the siliceous dolomites [72–75, 77, 81–86]. The lithological and chemical control of the metallogenesis in the region is supporting the concept of the syngenetic origin of lead-zinc sulphides [72]. The Rakhabdev-Dungarpur area consists of ultramafic rocks as linear belts which are serpentinized and are metasomatically altered

#### **Table 1.**

*Stratigraphic succession of the Aravalli Supergroup from the study area. Modified after Gupta et al. [72].*

*Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological… DOI: http://dx.doi.org/10.5772/intechopen.99046*

[73, 87–90]. The ultramafic rocks occur along a prominent lineament named Rakhabdev lineament which passes through the Aravalli fold belt [77, 89]. Thicker ultramafic outcrops are more massive and fractures are developed in an irregular manner [91].

## **4. Image processing techniques used in this investigation**

### **4.1 Dataset**

The present study uses the Advanced Spaceborne Thermal Emission and Reflection Radiometer Level-1 Precision Terrain Corrected Registered At-Sensor Radiance (ASTER L1T) dataset. ASTER sensor carries the VNIR, SWIR, and TIR scanners which have 3 (1–3), 6 (4–9), and 5 (10–14) bands respectively, and its technical specifications mentioned in **Table 2**. The ASTER L1T imagery is already geometrically corrected, georeferenced (WGS-1984) and UTM projected (UTM zone 43 N) [92].

#### **4.2 Methodology**

The overall methodology flowchart for the delineation of the various litho-units is depicted in **Figure 2**. The different litho-units were traced out with the help of the Feature-Oriented Principal Component Selection (FPCS) method which uses the various derived outcomes of band ratios, relative band depths, and mineral indices from SWIR and TIR datasets through an integrated approach.

Vegetation and water bodies are present in the region which creates a hindrance in geological mapping therefore, these land features were masked from the derived outcome. Vegetation coverage was calculated using the Normalized Difference Vegetation Index (NDVI) and the values ranging greater than 0.2 were used for the

**Table 2.**

*Technical specifications of the ASTER L1T dataset. Source: [92].*

preparation of the vegetation mask. Water bodies were masked using band 1. The DN values ranging from 0 to 100 were selected to prepare the water mask. Both of the masks were applied on the derived outcomes to eliminate the vegetative lands and water bodies from the mineral and lithological map of the region.

## *4.2.1 Preprocessing of SWIR and TIR datasets*

The ASTER SWIR dataset has the spillover of the energy from band 4 to band 5 and band 9 which is known as crosstalk effects [17, 41, 45, 47, 93, 94]. Crosstalk correction was applied for the removal of effects from the dataset and to enhances the spectral signatures of the minerals/rocks. A semi-empirical atmospheric correction, QUick Atmospheric Correction (QUAC), was applied to retrieve the surface reflection from the sensor radiance [95–100].

The ASTER TIR datasets were converted into the calibrated radiance from the digital number using Eq. (1) [46, 55, 58, 101, 102].

$$\mathbf{L}\_{\text{sen}}^{\text{i}} = \mathbf{c} \mathbf{f}^{\text{i}} \ast \left( \mathbf{D} \mathbf{N}^{\text{i}} - \mathbf{1} \right) \tag{1}$$

where:

**Figure 2.** *Overall methodology for the derivation of the lithological map.*

*Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological… DOI: http://dx.doi.org/10.5772/intechopen.99046*

#### *4.2.2 Image processing*

Band Ratio (BR) is a method in which one band is divided by another band (Eq. (2)) to get the better delineation of the rocks/minerals instead of using a single band and combined with enhancement of spectral properties.

$$\mathbf{BR} = \mathbf{B1}/\mathbf{B2} \tag{2}$$

where: BR = Output Band Ratio image; B1 and B2 = Brightness value of selected bands.

Relative Band Depth (RBD) is another technique for mineral mapping in which the position and depth of the mineral spectrum were considered for calculation [103]. The RBD governs better discrimination of minerals than BR because it considers the characteristic absorption features and normalizes the effects generated due to topography and albedo [32, 37, 104]. The bands acquired the shoulder position on absorption spectrum are summed up as (S1 and S2) and divided by the band having minimal absorption value (T; Eq. (3); **Figure 3**).

$$\mathbf{RBD} = (\mathbf{S1} + \mathbf{S2})/\mathbf{T} \tag{3}$$

Mineral Indices (MI) is also a mathematical expression derived for mapping of the minerals by using the band math operators with different logics in the TIR wavelength region. The TIR part of the EM spectrum is utilized for the mapping of the feldspars, silicates, carbonates, and ultramafic minerals.

BR and RBD were applied on the atmospherically corrected SWIR datasets and MI was applied on the calibrated radiance TIR datasets (**Table 3**). Al-OH consisting of minerals like mica and clay minerals were delineated with the help of different BRs and RBD6 (**Table 3**). Spectral absorption minima were recorded at band 6 of ASTER at 2.205 μm which highly suitable for the mapping of clay and mica minerals [12, 34, 37, 42, 105]. Similarly, Mg-OH and CO3 �2 containing minerals showed the absorption minima at band 8 of ASTER at 2.336 μm which was used in the RBD8 for mapping of carbonates and ultramafics [34, 37, 106, 107]. The SiO2 containing minerals/rocks showed the emissivity minima at the band 12 of ASTER at 9.075 μm due to vibrational energy along the Si-O bond. The CO3 �2 bearing minerals showed the emissivity minima at 11.318 μm which is represented by the band 14. The Mg-OH bearing minerals of ultramafics recorded the emissivity minima at band 13 at 10.657 μm.

**Figure 3.** *Artistic sketch for interpretation of the RBD for any mineral.*

Principal Component Analysis (PCA) is widely used for the identification and delineation of the litho-units and hydrothermal alteration minerals using the spectral bands generated from different sensors [9, 17, 28, 45, 48, 108]. The PCA uses the statistical mechanism for the transformation of the variables into several linear variables which are not having a correlation with each other, known as Principal Components (PCs). It is implemented on the symmetric matrix which is based on the either correlation matrix or covariance matrix (Eq. (4)). The PCs have the information related to the specific mineral which can be retrieved with the help of loadings of eigenvector (Eq. (5)). The strong eigenvector loadings of the PCs were utilized for the demarcation of the various mineral/groups through its PC indicative bands (Eq. (6)) which showed bright and dark pixels for the specific minerals in the PC image [108]. The present work uses the Feature-Oriented Principal Component Selection (FPCS) on the integrated data derived from BR, RBD, and MI from the ASTER SWIR and TIR data for mapping of the lithological units present in the region. The FPCS was used to achieve the desired goal by the combination of SWIR and TIR-derived outcomes. The phyllite and mica-schist can be marked with the help of BRs and RBD6, carbonates and ultramafics gave a similar tone by the use of RBD8 of SWIR region while MI has the capabilities to distinguish these two minerals/groups. Quartzites were not mapped in the SWIR EM region due to lack of the characteristic absorption band while TIR EM regions have these capabilities. Mineral/rock identification was not possible through the single kind of dataset like only by SWIR only by TIR so, integrated approach was required to delineate all lithological units existed in the study area. Therefore, FPCS was implemented on the basis of covariance matrix of the integrated outcomes of ASTER SWIR and TIR. The derived eigenvector matrix is tabulated in **Table 4**.

$$cov(X, Y) = \frac{1}{n - 1} \sum\_{i=1}^{n} (Xi - \overline{x}) \ (Yi - \overline{y}) \tag{4}$$

**Table 3.**

*BR, RBD, and MI used for the derivation of the mineral maps from ASTER SWIR and TIR bands.*

#### **Table 4.** *Eigenvector matrix generated from the integrated derived mineral maps for FPCS.*

*Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological… DOI: http://dx.doi.org/10.5772/intechopen.99046*

$$\mathbf{A}\overrightarrow{\mathbf{v}} = \lambda \overrightarrow{\mathbf{v}} \text{ or } \overrightarrow{\mathbf{v}}(\mathbf{A} - \lambda \mathbf{I}) = \mathbf{0} \tag{5}$$

$$\mathbf{y} = \mathbf{W}' \times \mathbf{x} \tag{6}$$

where:

cov(X, Y) = Covariance matrix; X and Y = Variables;

Av! = eigenvector of matrix A; λ = eigenvalue (scaler value); I = Identity matrix.

y = Final outcome; W0 = transpose of scaler data; x = Feature vector.

## **5. Results**

## **5.1 Band ratios (BRs) and relative band depths (RBDs)**

### *5.1.1 Distribution of Al-OH consisting minerals*

Clay (kaolinite, illite, montmorillonite) and mica (sericite and muscovite) minerals consist of the Al-OH in their chemical composition. These minerals especially illite, montmorillonite, muscovite, and sericite exhibited characteristic spectral absorption features at a wavelength of 2.205 μm which is detectable with band 6 (2.185–2.225 μm) of the ASTER sensor. Kaolinite mineral also showed minor absorption at 2.165 μm for that band 5 (2.145–2.185 μm). The Al-OH consisting of minerals were mapped in the quartzites south of Rakhabdev and near the granitic outcrop of Kherwara inlier [89]. Phyllite and mica-schist also depicted higher values for Al-OH containing minerals by using BR 7/6 (**Figure 4A**). The granitoids of the basement, granites, and quartzites have high values for Al-OH by using BR 4/6 (**Figure 4B**). On applying BR 7/5, almost the entire region depicted higher values for kaolinite (Al-OH) which is indicative of a poor interpretation (**Figure 4C**). The RBD (5 + 8)/6 gave a similar kind of result like BR 7/6. It depicted higher values of the Al-OH consisting of rocks/minerals for the quartzites, phyllites, mica-schists, conglomerate, and arkose litho-units (**Figure 4D**). Ultramafics and carbonates (dolomite) have very low values from BRs 7/6, 4/5, and RBD6 due to the absence of Al-OH minerals.

## *5.1.2 Distribution of Mg-OH and CO3*�*2 consisting minerals*

Ultramafics are having the Mg-OH while dolomites are having both Mg-OH and CO3�2 constituents in their composition. These minerals have the characteristic absorption feature at 2.33 μm, which occurs at band 8 (2.295–2.365 μm). The RBD (6 + 9)/8 was applied for mapping of the Mg-OH and CO3�2 consisting of minerals. Ultramafics depicted extremely high values while dolomites have moderate values (**Figure 5A**). The regions of Zawarmala and Hati Magra are dominated by dolomite exposures but a poor carbonate map as an outcome may be due to the presence of extreme vegetation on the hills.

A lithological map has also been prepared from RBD6, RBD8, and BR4/6 in RGB channels respectively (**Figure 5B**). Basement rocks are depicted as pinkish-blue, phyllite, and mica-schist as reddish color. Dolomite is depicted as dark green while ultramafics are as green color. Quartzites are light pink in color. The resultant map discriminates the various lithologies present in the area and is comparable with the published geological maps.

*Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological… DOI: http://dx.doi.org/10.5772/intechopen.99046*

**Figure 4.**

*Results from the SWIR data for Al-OH bearing minerals using the techniques of BRs and RBDs. (A) BR 7/6 for mica and clay minerals. (B) BR 4/6 for clay minerals. (C) BR 7/5 for kaolinite. (D) RBD6 (5 + 8)/6 for clay and mica minerals.*

#### **5.2 Mineral indices (MI)**

#### *5.2.1 Distribution of mafics/ultramafics*

The ultramafic map was developed using the mafic index defined by Guha & Vinod Kumar [23]. The derived map of the mafic index mapped the outcrops of the ultramafics with very higher values near the Rakhabdev region and along other thin

#### **Figure 5.**

*Results from the SWIR data. (A) RBD8 (6 + 9)/8 for the mapping of ultramafics and carbonates. (B) Lithological map using the RBD6, RBD8, and BR4/6 in the RGB channels.*

belts of the ultramafic outcrops south of Rakhabdev and on the west of Kherwara (**Figure 6A**). The dolomites were suppressed and showed their uniqueness to distinguish by ultramafics.

## *5.2.2 Distribution of SiO2 consisting minerals*

Silica-rich rocks were marked by using the silica index of Rockwell & Hofstra [56] (**Figure 6B**). Quartzites present on the outer periphery of basement rocks were precisely demarcated through the silica index. Silica index also mapped the quartzites present adjacent to the dolomites in the Zawar region. The derived mineral map showed very low values for the ultramafics and dolomites.

## *5.2.3 Distribution of CO32 consisting minerals*

Ninomiya et al. [54] defined the mathematical expression for the mapping of carbonate rocks and the derived mineral map showed dense noise, consequently, identification of the carbonate outcrops was not precisely obtained (**Figure 6C**). The presence of stripping noise and poor signal at band 14 hinders the demarcation of carbonate outcrops [20, 109, 110]. The ultramafics and quartzitic outcrops were depicting very low values in the carbonate map.

A lithological map was prepared using the silica, mafic, and carbonate indices in RGB channels respectively (**Figure 6D**). Dolomites of the region were marked by bluish-green color but the majority of the region was marked as bluish-green color which is a poor identification for dolomites, quartzites are depicting the maroon color and ultramafics as bright green color. The yellow color at the tips of ultramafics and within the massive outcrops of ultramafics are identified as talc.

*Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological… DOI: http://dx.doi.org/10.5772/intechopen.99046*

**Figure 6.**

*Results derived from the TIR data. (A) Ultramafic map derived using the Guha and Vinod Kumar index [23]. (B) Silica-rich rocks were demarcated by using the Rockwell and Hofstra index [56]. (C) Carbonate map derived using Ninomiya et al. index [54]. (D) Lithological map prepared using the silica-rich, ultramafics, and carbonate maps in RGB channels.*

#### **5.3 Feature-oriented principal component selection (FPCS)**

The FPCS technique was implemented to the integrated derived outcomes from BRs, RBDs, and MIs of the ASTER SWIR and TIR bands for discrimination of the different litho-units present in the study area. The generated eigenvector matrix from the FPCS from the integrated derived mineral maps is shown in **Table 4**. The PC1 shows the extreme values for the ultramafics and moderate values for the dolomites. Quartzites showed very low values and represented dark pixels (**Figure 7**). The PC1 shows the combined outcome from the RBD8 and MI Mg-OH because RBD8 highlighted ultramafics and dolomites of the region while MI Mg-OH mapped the ultramafics and suppressed the quartzites of the region. The PC2 showed extremely high values for phyllite and mica-schists and dark pixels for the quartzites of the region. The ultramafics & dolomites of the region are depicting the low values (**Figure 7**). The PC2 showed the combination of BR 4/6, BR 7/5, and RBD6 in which BR 4/6 highlighted the silica-rich rocks. The Al-OH consisting minerals are suppressed in the PC2 while RBD6 highlighted the phyllite and

**Figure 7.** *FPCS components generated using the PCA technique on integrated BRs, RBDs, and MIs from the SWIR and TIR bands.*

mica-schists as Al-OH consisting rocks and BR 7/5 also highlighted the Al-OH consisting minerals. The PC3 depicted very high values for quartzites i.e. silica-rich rocks as by MI SiO2 but on the south of Rakhabdev the distribution of silica-rich rocks is not showing the vague distribution like MI SiO2, and a clear delineation of quartzites are obtained (**Figure 7**). The PC4 depicted a similar kind of pattern as BR 4/6 but the extremity of the pixel values gets lower down and appearance gets noisy (**Figure 7**). The PC6 depicted higher values for the ultramafics and silica enriched rocks of the granitoids & migmatites from the basement, quartzites, and phyllite, and mica-schist while carbonates are depicted moderate values (**Figure 7**). The PC6 is helpful for the delineation of the litho-units of the region but the band showed an *Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological… DOI: http://dx.doi.org/10.5772/intechopen.99046*

association of the moderate amount of noise. The PC5, PC7, and PC8 are not useful for the discrimination of the geological units due to the presence of a high amount of noise with them (**Figure 7**).

FCC was been prepared using the combinations of bands PC1, PC3, and PC6 respectively for delineation of different litho-units (**Figure 8**). Granitoids and migmatites appeared as greenish-blue colors while quartzites as light green with a mixture of cyan color. Phyllite and mica-schist appeared as dark blue to greenishbrown color. Conglomerate and meta-arkose gave shades of green color. Dolomites appeared as purplish colors and ultramafics as pinkish colors. Light yellow color on the tips of ultramafics and within the ultramafics which showed the presence of talc.

**Figure 8.**

*Lithological map of the study area prepared by the combination of FPCS1, FPCS3, and FPCS6 in the RGB channels respectively.*

## **5.4 Verification of the derived lithological map**

To verify the different litho-units of the region various field reconnaissance was conducted and for the estimation of the overall accuracy of the generated lithological map, GPS surveys were carried out. Various traverses were conducted along the major litho-units of the region and some traverses were conducted for the verification of changes observed in the generated lithological map. Field photographs and rock samples were collected for the determination of accurate locations and associated lithology/ies if present at the contact zone. Pink colored granites from the Kherwara Inlier were observed (**Figure 9A**) and deformed quartzites were present with the contact of it (**Figure 9B**). Serpentinites of the Rakhabdev showed the variation all along the belt-like massive to fibrous nature and open mining pits of the serpentinites in the massive variants (**Figure 9C**, **D**, **G** and **I**). In the field, outcrops of the different dolomites were observed (**Figure 9E**) associated with the quartzites, metagraywacke, phyllite, and mica-schist (**Figure 9F**). Contact between the phyllite & mica-schist and quartzites was also observed (**Figure 9H**). Talc was also observed in the field and it is mainly in the region of deformation (**Figure 9G**). The isolated patch of the serpentinite near the Parbeela region shows the contact with the granites of Kherwara Inlier. Furthermore, the accuracy assessment was carried out between the generated lithological map and field-collected information

#### **Figure 9.**

*Field validation of the different litho-units. (A) Granites from the Kherwara inlier. (B) Mullions of quartzites from Kherwara inlier. (C) Talc mineralization along the serpentinites from southeast of Rakhabdev. (D) Massive serpentinites from Rakhabdev. (E) Dolomites from the northeast of Rakhabdev. (F) Massive quartzites from the east of Rakhabdev. (G) Mining activities for talc from the hinges of serpentinites outcrops from south of Rakhabdev. (H) Contact between the quartzites and phyllites from north of Rakhabdev. (I) Serpetninites and its alteration products from south of Rakhabdev.*

*Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological… DOI: http://dx.doi.org/10.5772/intechopen.99046*

#### **Table 5.**

*Accuracy assessment of the derived lithological map using the GPS survey collected localities.*

using the GPS (**Table 5**). The derived confusion matrix shows the overall accuracy and kappa coefficient as 85.25% and 0.8164 respectively for the lithological map.

## **6. Discussions**

The study area belongs to the Aravalli Orogeny and several deformational histories were recorded [72–75, 77, 81, 84–86, 89, 111–113]. The remote sensing technique is widely used for mineral mapping and lithological mapping around the study area [9, 58, 102, 114]. In the present research, different BR, RBD, & MI and their combinations were generated using the ASTER SWIR and TIR bands for the demarcation of the different litho-units present in the region. The BRs and RBDs were used to derive the Al-OH and Mg-OH & CO32 consisting minerals [8, 12, 35, 37, 42, 106] like phyllite & mica-schist, carbonates, and ultramafics. And their FCC combinations helped to delineate granitoids, granites, phyllite, mica-schist, quartzites, dolomite, and ultramafics (**Figure 5B**). The MIs were used to derive SiO2, Mg-OH, and CO32 mineral maps of the region [23, 54–56, 58, 101], and quartzites, ultramafics, and carbonates were delineated. The FCC also helped a lot to determine the lithologies of the region but were limited to the quartzites, ultramafics, and carbonates (**Figure 6D**).

FPCS technique was utilized for the delineation of litho-units present in the region on the basis of the combined results derived from the BRs, RBDs, and MIs from the ASTER SWIR and TIR bands. The PC1, PC3, and PC6 have capabilities to discriminate the ultramafics, carbonates, quartzites, phyllite, mica-schist, and granitoids. The prepared FCC using the combinations of these PCs demarcated the granitoids, granites, phyllite, mica-schist, quartzites, conglomerate, meta-arkose, dolomites, ultramafics (**Figure 8**). The integrated approach from the ASTER SWIR and TIR proved its potentials for lithological mapping. The generated confusion matrix showed the overall accuracy as 85.25% and kappa coefficient as 0.8164 in which maximum producer's accuracy (%) was attained by dolomite while user's accuracy (%) by granite. Field validation was performed on the generated lithological map by observing the various litho-units present on the surficial exposures and gathered the location information by the use of a GPS survey. Association of quartzites with dolomites and serpentinites with dolomites was observed in the

field. Talc is found with the serpentinites and was produced due to the process of serpentinization and mainly formed at the deformational zones [115].

## **7. Conclusions**

## **Acknowledgements**

The author is thankful to USGS Earth Explorer to provide the ASTER dataset under the open distribution policy. Thanks to the Heads of the Department of Geology for providing the necessary facilities for conducting the research. Some part of this chapter has been taken from the Ph.D. thesis of the author.

## **Conflict of interest**

The author declares no conflict of interest.

*Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological… DOI: http://dx.doi.org/10.5772/intechopen.99046*

## **Author details**

Ronak Jain1,2

1 Department of Remote Sensing, School of Earth Sciences, Banasthali Vidyapith, Banasthali, India

2 Department of Geology, Faculty of Earth Sciences, Mohanlal Sukhadia University, Udaipur, India

\*Address all correspondence to<EMAIL_ADDRESS>
© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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## **Chapter 7**


**2.1 Red and processed meat**

High intake of red/processed meat is linked to high risk of CRC. Red meat such as beef, pork, veal, and lamb, and preserved red meat by smoking, grilling, cooking, frying, salting, and curing are called processed meat.


**Assessment of Soil Contamination of a Cattle Market around River Ogun Basin, Isheri, Nigeria**

A.A. Adeyi, O.M. Omidiran and O. Osibanjo

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/57302


*3.2. Influence of Aluminum Side Heat Dissipation Rate on Semi-Solid Forming and Microstructure Evolution of Brazed Joints*

In order to explore the influence of different Al side heat dissipation rates on ultrasonic assisted brazing weld seams, we set four kinds of Al side heat dissipation rates of 2, 5, 7, and 9 k/s by adjusting the heat exchange equipment at Al plate side.

When the ultrasonic vibration duration is kept at 6 s, the microstructure appearance of each brazing seam sample obtained under different Al-side heat dissipation rates is shown in Figure 6.

Aslong as ultrasonic vibrationis carried out, there are nolarge tree dendritesin theweldmicrostructure of brazing samples with different Al-side heat dissipation rate. Instead, there are rose-like crystals, columnar crystals and spherulites with relatively regular distribution, as can be seen in Figure 6.

The size of columnar crystal on Al side increases with the increase of heat dissipation rate on Al side. When the heat dissipation rate on the Al side increases to 9 K/s, some columnar crystals on the Al side have grown secondary crystal axes, as shown in region d1 of Figure 6d. Through careful observation of the weld microstructure in Figure 6d, we found that the columnar crystal size on the Cu side was much smaller than that firstborn on the Al side, but dendrite microstructure could be observed in the local area (d2). When the heat dissipation rate on the Al side increases to 9 K/s, the elongated columnar crystals generated in the weld joint are not conducive to the formation of semi-solid state spherulites.

In order to achieve a better semi-solid-state effect, we gradually reduced the heat dissipation rate on the Al side. When the rate dropped to 7 K/s, the size of primary columnar crystals on Al side decreases and there is no obvious dendrite tendency, meanwhile the size of primary columnar crystals on Al side decreased, and there was no obvious dendrite tendency. In Figure 6c, the dendrite degree of columnar crystals of C region presents an obvious gradient. Most columnar crystals distributed on the Cu side have secondary axis, but there is no fully developed dendrite structure in the weld seam.

**Figure 6.** Microstructure of brazed joints under different Al-substrate-side heat dissipation rate: (**a**) Al-side heat dissipation rate 2 K/s; (**b**) Al-side heat dissipation rate 5 K/s; (**c**) Al-side heat dissipation rate 7 K/s; (**d**) Al-side heat dissipation rate 9 K/s.

It is concluded that the heat dissipation rate of 7 K/s on Al side is still not conducive to semi-solid spherulites forming. Therefore, the Al-side heat dissipation rate was gradually reduced. Under the combined action of ultrasonic vibration and the Al-side heat dissipation rate down to 5 K/s, the semi-solid state of weld microstructure was well realized, as shown in Figure 6b, where the spherulites in the weld seam have a good sphericity, and these ball spherulites diameters are mainly distributed between 20 and 35 microns. Meanwhile, the spherulite density on both sides of the substrate metal differs.

In order to comprehensively explore the effect of Al side heat dissipation rate on the microstructure of weld joint, we further reduce the heat dissipation rate of the Al side to the rate of 2 K/s. This time, in the welding joint seam, there were no thick columnar crystals or good spherulites on the Al side, but a large number of rose crystals formed (the copper-aluminum compounds are shown in a region of Figure 6a. We used Image software to conduct statistical analysis on the size of weld microstructure and crystal distribution obtained at different Al-side heat dissipation rates. The size of crystals and their distribution in weld microstructure were clearly demonstrated under different Al-side heat dissipation rates, as shown in Figure 7. Under the action of ultrasonic vibration, the influences of different Al-side heat dissipation rates on weld microstructure are quite different.

**Figure 7.** (**a**) columnar crystal length and diameter under four Al side heat dissipation rates (K/s) at 2 K/s, 5 K/s, 7 K/s and 9 K/s; (**b**) columnar crystal length-diameter ratio of Al-side heat dissipation rate (K/s) at 2 K/s, 5 K/s, 7 K/s and 9 K/s.

#### *3.3. Effect of Ultrasonic Duration on Semi-Solid Forming and Microstructure Evolution of Corresponding Weld Seams*

The Al-side heat dissipation rate and ultrasonic vibration are two key factors of semi-solid forming. The Al-side heat dissipation rate affects the morphology of the primary microstructure of the welding joint, while the appearance of weld joint microstructure is also related to ultrasonic vibration. We set a series of ultrasonic vibration duration (the first segment of ultrasound) to explore the mechanism of semi-solid forming under different ultrasonic duration, which are set as 0 s, 2 s, 4 s, 6 s and 9 s respectively in experiments. Under the optimal Al-side heat dissipation rate of 5 k/s, the metallography pictures of welding joints applied different ultrasonic vibration duration are shown in Figure 8.

By observing the metallographic diagrams in Figure 8, it is not difficult to find that, under suitable Al-side heat dissipation conditions at rate of 5 K/s, large dendrites grew from Al substrate material in the brazing process without adding ultrasonic vibration, as shown in Figure 8a. A Strong perturbation or agitation is required in the semi-solid forming process, and the weld joint microstructure of the sample with 2 s ultrasound no longer has large dendrite structure. In the selection area b in Figure 8, the coarse equiaxed crystal structure appears near the Al-substrate material, with each crystal diameter of 25~30 microns, and also find that a certain number of columnar crystal structure below the coarse equiaxed crystal structure, with a length of about 50 microns.

When Ultrasonic vibration duration is 2 s, it can't achieve better semi-solid structure forming, or even can't be called "semi-solid brazed joint". Figure 8c shows the brazed seam microstructure under 4 s ultrasonic vibration duration, which has basically achieved semi-solid state. and the process of primary equiaxed grain nucleation and being sheared can even be observed in the box selected area c.

**Figure 8.** *Cont*.

**Figure 8.** Microstructure of welds with different ultrasonic vibration duration: (**a**) 0 s; (**b**) 2 s; (**c**) 4 s; (**d**) 6 s; (**e**) 9 s.

At the Al-side heat dissipation rate of 5 K/s, the primary nucleation crystals of welding joint on the Al side, which shown in the selected area c have spherulite characteristics. Although ultrasonic vibration 4 s has basically achieved semi-solid welding seam, spherulite sphericity and density still have room for improvement. With the increase of ultrasonic vibration time to 6 s, the density of spherulite in weld increased greatly and the density of spherulite in the weld joint has been greatly improved, which means semi-solid forming effect is ideal, as shown in Figure 8, area d. However, the increase of ultrasonic vibration time will not always provide a positive effect for semi-solid forming, and more deformed spherulites appear in the weld seam of ultrasonic vibration sample of 9 s, as shown in area e Figure 8, which means that too long ultrasonic vibration time will have a negative impact on the semi-solid forming effect.

In order to better characterize the effect of ultrasonic vibration on the sphericity and distribution of semi-solid spherulite of the microstructure of joints, we used image software to analyze the sphericity and spherulite density of samples with different ultrasonic vibration durations, as shown in Figure 9.

**Figure 9.** (**a**) spherulite sphericity of each weld seam area when ultrasonic vibration time is 2 s; (**b**) grain density under different ultrasonic duration of 2 s, 4 s, 6 s and 9 s; (**c**) spherulite sphericity under different ultrasonic duration of 2 s, 4 s, 6 s and 9 s.

Based on the above analyses, the aluminum side heat dissipation rate and ultrasonic duration had significant effects on semi-solid forming and the microstructure evolution of joints.