Open access peer-reviewed chapter

Application of Infrared Spectroscopy in the Characterization of Lignocellulosic Biomasses Utilized in Wastewater Treatment

Written By

Marwa El-Azazy, Ahmed S. El-Shafie and Khalid Al-Saad

Reviewed: 04 November 2022 Published: 24 November 2022

DOI: 10.5772/intechopen.108878

From the Edited Volume

Infrared Spectroscopy - Perspectives and Applications

Edited by Marwa El-Azazy, Khalid Al-Saad and Ahmed S. El-Shafie

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Abstract

Global economies are confronting major energy challenges. Mitigating the energy depletion crisis and finding alternative and unconventional energy sources have been subjects for many investigations. Plant-sourced biomasses have started to attract global attention as a renewable energy source. Maximizing the performance of the biomass feedstock in different applications requires the availability of reliable and cost-effective techniques for characterization of the biomass. Comprehending the structure of lignocellulosic biomass is a very important way to assess the feasibility of bond formation and functionalization, structural architecture, and hence sculpting of the corresponding structure−property liaison. Over the past decades, non-invasive techniques have brought many pros that make them a valuable tool in depicting the structure of lignocellulosic materials. The current chapter will be focused on the applications of Fourier transform infrared (FTIR) spectroscopy especially in the mid-infrared region in the compositional and structural analysis of lignocellulosic biomasses. The chapter will provide a display of examples from the literature for the application of FTIR spectroscopy in finding the composition of various biomasses obtained from different parts of plants and applied for wastewater treatment. A comparison between biomasses and physically/chemically treated products will be discussed.

Keywords

  • biomasses
  • leaves
  • seeds
  • peels
  • wastewater treatment
  • adsorbents
  • characterization
  • Fourier transform infrared (FTIR) spectroscopy
  • adsorption capacity

1. Introduction

Nowadays, the global economies are confronting two major energy challenges: indemnifying an affordable source of energy and simultaneously realizing the transformation into a clean, efficient, and sustainable energy system [1, 2]. To that end, mitigating the energy depletion crisis and finding alternative and unconventional energy sources have been the subject for many investigations. Recently, plant-sourced biomasses have started to attract global attention as a sustainable, untapped, and renewable energy source. The feasibility of conversion of the raw feedstock into liquid fuels and other value-added products via processes such as thermochemical, microbial, or enzymatic treatments is an advantage. On the other hand, the chemical composition of the biomasses is unique and could certainly affect these conversion processes and the nature of the obtained products in different ways [1, 2, 3, 4, 5, 6]. Moreover, biomasses are abundantly available and therefore can be regenerated in copious amounts annually. Preponderantly, biomass is a composite mixture of both organic (major) and inorganic (minor) components. Lignocellulose is one of the main wood extractives and is usually a mixture of lignin and the cellulosic carbohydrates (cellulose and hemicellulose). The term “lignocellulose” is generally employed to signify the plant biomass [1]. Lignocellulosic biomasses could therefore have different applications.

One of the most important categories of biomasses is agricultural residues or the waste biomass—a secondary product for the agricultural industry [7]. Representing a major part of the annual overall biomass production, especially in developing countries, agro-waste biomasses epitomize a valuable source of energy and fuel. Yet, several other applications entail the usage of biomass both in the raw format (biomass) or following a thermochemical treatment (biochar or hydrochar). These applications include use of biomass/biochar as an animal feed and fertilizer, for pollutant sequestration for wastewater treatment, and as a substitute for petrochemical-based plastics and, hence, biodegradable packaging [6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16].

Guaranteeing and maximizing the performance of biomass feedstock in different applications require the availability of reliable and cost-effective techniques for structural and compositional characterization of the biomass. For example, comprehending the microstructure of lignocellulosic biomass is a very important way to assess the heat and mass transfer phenomena, the feasibility of bond formation and functionalization, and structural architecture and hence sculpting of the corresponding structure−property liaison, which are essential for designing and developing value-added products. While several “traditional” analytical techniques for biomass characterization are already in use, some of these techniques are time-consuming and require tough chemicals that, in turn, could need further remediation. Moreover, some of these techniques require pre-treatment procedures that also encompass the use of hazardous chemicals. Most importantly, many of these techniques are invasive/destructive. Wet chemical methods such as hydrolysis using sulfates, alkali, gas chromatography, high performance liquid chromatography, nitrobenzene oxidation, and transesterification are among these conventional approaches [16, 17, 18, 19]. Consequently, finding an effective alternative approach that is cost-effective, non-laborious, and non-invasive for compositional analysis and characterization of the lignocellulosic biomass is important to improve researchers’ insights into the structure–property–performance relationships.

From that point, and over the past decades, non-invasive techniques are attracting the attention of the scientific community. In addition to being non-destructive, these techniques bring many other pros such as minimizing the wastes and hence supporting the method greenness, allowing the repetitive measurements of the same property over time, and hence improving the quality of the output. Moreover, these techniques are cost-effective, user-friendly, and fast. Several imaging and spectroscopic techniques could be classified under this category, including scanning electron microscopy (SEM), X-ray micro-computed tomography (X-ray μCT), and Fourier transform infrared (FTIR) and near-infrared spectroscopies (NIRS) [16, 17].

SEM analysis depends on the detection of the interaction of the gold-coated sample atoms with the high-energy (0−30 kV) accelerated and diffracted backscattered electrons to generate the SEM micrographs that show the morphological and topography data (e.g., crystallinity, variations in chemical structure prior to and following any sort of treatment, fiber distribution, and size variations). In addition, elemental analysis of the surface can also be performed with the energy dispersive X-ray (EDX) aspect. Compared to optical microscopes, SEM has a much higher resolution that could hit 0.01 μm [16, 20, 21, 22, 23]. On the other hand, X-ray μCT depends on the creation of virtual 3D images following the interaction of the X-ray photons with the sample. X-ray μCT is a non-invasive approach that is useful in finding the internal architecture of the composite biomaterials, and it could provide both qualitative and quantitative data on the spatial distribution of properties such as porosity, average pore-to-pore distance, internal defects, and structural discontinuity [24, 25].

Vibrational spectroscopy-based techniques (infrared and Raman spectroscopies) are used to measure the molecular vibrations following the absorption of photons. Both techniques give spectral sketches that express the chemical temperament of a sample. Three zones could be recognized in the infrared (IR) region: (1) the far IR (FIR, 400–10 cm−1, 25–300 μm), (2) the mid-IR (MIR, 4000–400 cm−1, 2.5–25 μm), and the near-IR (NIR, 14,000–4000 cm−1, 0.7–2.5 μm) [16, 26, 27, 28]. Yet, it is important to point out that each of the three regions has substantial applications in different fields.

FTIR spectrometers are usually used for measurements in near- and mid-IR regions. NIRS is basically based on the interaction of light with the sample in the NIR region. Two major processes could be observed in the NIR region: molecular overtones and combination bands associated with hydrogen bonds. Yet, these spectral bands are of much weaker intensities compared to the fundamental vibrational bands, an issue that causes absence of the distinctive characteristics and anharmonicity [16, 26, 27, 28, 29]. The NIR spectrometer is simple, speedy, portable, non-destructive, and of low cost and high throughput. Therefore, there are various applications of NIRS including both qualitative and quantitative investigations [30, 31, 32, 33, 34, 35, 36]. Selective absorption of NIR radiation by the principal functionalities in the lignocellulosic materials makes NIRS a powerful approach for studying woods and lignocelluloses and identifying the composition of biomasses, their biochemical properties following the application of certain treatment conditions, and the impact of genetic engineering on lignocellulosic feedstock [37, 38, 39, 40, 41, 42, 43, 44]. On the other hand, the mid-IR spectra, unlike the NIR spectra, are completely interpretable, especially the absorbance bands, because of the chemical peak specificity. Applications entailing the mid-IR region are therefore more known [45, 46, 47, 48, 49, 50].

The current chapter will be focused on the applications of FTIR especially in the mid-IR region in the characterization of lignocellulosic biomasses. The discussion throughout this chapter would revolve around the impact of the detected chemical composition on the performance and adsorptive capacities of the characterized adsorbents for wastewater treatment applications. Readers will be first introduced to the working principle of FTIR spectroscopy and applications in functional groups determination. Application of FTIR spectroscopy in identification of structural changes of agro-waste materials following physical and chemical treatments will be reviewed. Discussion will further continue to include the classification of agricultural waste materials-based sorbents according to the employed plant part. Comparison among the different waste-derived adsorbents will entail features such as the nature of the water pollutant, adsorption capacity, and proposed sorption mechanism.

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2. FTIR in the characterization of lignocellulosic biomasses

In this section, an overview of the working principle of FTIR spectroscopy will be presented. The advantages of application of FTIR spectroscopy in analyzing biomass structure and monitoring changes that occur from physical and chemical treatments will be also discussed.

2.1 Working principle and advantages

In general, FTIR spectroscopy is a technique that is based on the detection of the interaction between a substance that possesses a functional moiety (chemical functional groups) and the IR radiation. Samples can be in any physical form (solid, liquid, or gas). An FTIR spectrometer measures the frequencies at which the sample absorbs and generates unique absorption spectra. The spectrometer measures the intensities of these absorption bands as well. With such a unique spectrum, identification of peaks at different wavenumbers is beneficial for the recognition of a particular chemical constituent by contrasting them with those in a reference library. The intensity of the measured peaks can be utilized quantitatively for finding the concentration of a component. The spectrum is a 2D-plot in which the axes are characterized by the intensity and frequency of the sample absorption.

Attenuated total reflection–Fourier transform infrared (ATR-FTIR) spectroscopy is a technique that has a plethora of applications. The coupling of FTIR to ATR allows the determination of samples in different states using different techniques, for example, mounting of solid or liquid samples on an ATR crystal and mixing the powdered sample with KBr [16, 26, 51]. The conventional ATR-FTIR spectroscopy entails using a single detector and generating a single spectrum per measurement. Such a spectrum is an average signal for the area of the sample under consideration. In ATR-FTIR imaging, however, many spatially resolved spectra are compiled utilizing an array detector [52]. Yet, the combination of the power of the FTIR array detectors with that of the algorithms of the software serves to fortify the sensitivity as well as the accuracy of the technique. Furthermore, the absence of the water background absorbance, being non-destructive, the high signal-to-noise ratio, in addition to the fast-scanning speed compared to the dispersive instruments and applicability to a wide range of samples have widened the applications of FTIR spectroscopy. Add to that the liability for coupling to multivariate statistical techniques, which facilitates obtaining quantitative data and hence building predictive models [53].

2.2 Compositional analysis of biomasses

Biomasses can be classified into four classes according to their origin: (1) non-woody plants, which are rich in starch, cellulosic material, and saccharides; (2) woody plants, which are mainly the source of cellulose, hemicellulose, and lignin; (3) agricultural residues, which are also rich in lignocellulosic materials; and (4) biofluids oleaginous materials, which are sources of fatty acids and esters. These materials represent the raw feed for industrial conversion processes, which could be chemical (catalytic), biochemical (fermentation or enzymatic routes), or thermochemical processes (gasification, pyrolysis, and combustion) [54]. Each of these materials before and after conversion processes possesses a unique chemical structure that facilitates its employment for the designated task and helps its identification using the available analytical procedure.

Further classification of biomasses into subgroups, species, and varieties could be done according to their diversity, sources, and origin. For example, wood and woody biomasses could be classified into soft and hard, for example, stems, leaves, shrubs, barks, and branches. Herbaceous and agricultural biomasses could be annual or perennial, field- or processed-based biomasses from different species such as grasses, flowers, straws, stalks, fibers, shells, husks, pits and stones, and other residues such as cobs, pulps, coir, seeds, grains, and so on. Chemically, biomass is a mixture of organic matter (major) and inorganic matter (minor) comprising a variety of solid and fluid well-associated phases. The organic matter is usually in the solid state and could be non-crystalline (cellulose, lignin, etc.) or crystalline (organic minerals). The inorganic content is also solid and could be crystalline (minerals such as phosphates, carbonates, etc.), semi-crystalline, and amorphous (e.g., glasses, silicates). The fluid matter is mostly inorganic and could be in the fluid, liquid, or gas state [55].

Analyzing the composition and hence comprehending the properties of biomasses either in their raw format or following physical or chemical treatments is therefore needed to guarantee the quality of the materials and the production processes and therefore supporting the execution of both market and environmental regulations. This, in turn, facilitates new products to be created that enhance the value of the biomass and the derived products and accordingly support the concepts of the circular economy. First and foremost, determining the target for which the biomass will be used is the most crucial when finding the appropriate analytical technique. For example, the analysis of oleaginous material content that will be utilized to produce biodiesel needs a different analytical approach from those needed for the analysis of sugarcane to be utilized to produce ethanol or sucrose.

Another example: using FTIR spectroscopy to determine the nature of the functional groups on the surface of the biomass/biochar intended to be used for water treatment applications via adsorption helps maximize the removal efficiency and understanding the sorption mechanism. Focusing on fiber research, ATR-FTIR spectroscopy has been widely used for fast depiction of the cell wall structure with an emphasis on the analysis of pectin and its degree of esterification [56, 57]; cell wall polysaccharides, especially cellulose, hemicellulose, lignin, and starch [58, 59, 60, 61]; mapping of the chemical composition of investigated fibers with the purpose of assessing the purity and the structure [62]; and the impact of modification (physical or chemical treatments) on fruits’ and vegetables’ fiber structures [63, 64, 65, 66].

The next few subsections will focus on the applications of FTIR spectroscopy for the identification of functional groups in different plant parts and the impact of thermal treatment on the adsorption performance.

2.2.1 Biomass-based adsorbents

Various investigations have been reported in the literature to find the applications of agricultural waste materials (fruits, vegetables, etc.) for wastewater treatment. More than a few advanced composite materials that are agro-waste-based have been engineered for particular applications in wastewater treatment. Agro-wastes, for instance, leaves, seeds, pruning, peels, shells, pulps, and so on, possess distinct elemental compositions and characteristic structures and morphologies, which in the long run impact the product. These wastes represent a burden on the environment if not properly recycled and reused. Therefore, recycling into value-added products for wastewater treatment has been a subject for many investigations, as will be detailed in the next few subsections.

2.2.2 FTIR analysis of peel-based adsorbents

Among the different agro-waste-derived biosorbents, the waste peels are deemed as promising waste resources for the development of biosorbents, thanks to their high lignocellulosic content and the high carbon and oxygen content as illustrated by their elemental composition. Proximate analysis shows that banana peels, for example, are constituted of mainly hemicellulose (41.38%) and cellulose and lignin to a lower extent [67]. On the other hand, biopolymer compositional analysis shows that peanut shells contain 18.8% of cellulose and 81.2% of lignocellulose [68]. Table 1 shows examples of the applications of peel-based adsorbents (raw, thermally, and chemically treated) for the removal of various pollutants (heavy metals, dyes, and drugs) [69, 70, 71, 72, 73, 74, 75, 76]. Table 1 shows the most characteristic FTIR peaks of the studied peels; the suggested removal mechanism of the target pollutant, whether physi- or chemisorption; as well as the reported maximum sorption capacity (qmax, mg/g).

AdsorbentAdsorbateν(cm−1)AssignmentMechanismqmax (mg/g)
Watermelon rinds (thermal treatment)Acridine orange (AO)2916C–H symmetric and asymmetric stretching vibrations- At low [AO]: Chemisorption
– At high [AO]: Physisorption
69.44[14]
Pistachio nut shells (thermal treatment)Basic fuchsin1600C=C stretchingPhysisorption118.2[69]
1379methyl group vibration
1060C=O vibration of carboxylic acid and ketone
1590–C=C stretching
1027C − O − C stretching for hemicellulose and cellulose
1450–1310Bending vibrations of O-H and C-H groups
Pomegranate peels (thermal treatment)Ni(II)3348alcohol, phenol, carboxylicNS*NS*[70]
1227Bending of –OH
3254N–H stretching
2921 & 2879stretching aliphatic C–H group bond
1724Carbonyl (C=O) stretching vibration from aldehyde, ketone, carboxylic acid
1608.74Stretching vibrations bonds of C=O and C=C aromatic, C=N, N–H of amines or amides, or C–C aromatic stretching
1320C–O group from alcohol, phenol, ether, ester
1017.33C − O or C–N groups
881C-S bond
Potato peels (thermal treatment)Cd(II)3000–3300–OH vibration (derived from cellulose, hemicellulose, and lignin)Physisorption239.64[71]
2938C-H stretching
1632–C=O stretching vibration
1572aromatic C=C stretching mode
1409 & 1154aryl OH groups
1081 & 1364–OH and C–O stretching
ZnO-impregnated activated carbon prepared from jackfruit peelCiprofloxacin969.07–1517.25O–H hydroxyl and C–O–C ether groups in polysaccharidesNS*15.75[72]
1638.39 & 1771.87C–O &C=O vibration (quinolone)
2476.06COO stretching
3414.34N–H stretching
Garlic peel
(one-step carbonization method)
Enrofloxacin1675–COOH groupPhysisorption150.17[73]
1514–1465aromatic C=C
1205–1109–S=O/C–O vibration
791S–O stretching vibration
Pomelo fruit
peel (thermal treatment)
Pb(II)3449Stretching vibration of the bonded hydroxyl group in the cellulose moleculeElectrostatic interactions & ion exchanges & adsorptive
Interactions
92.13[74]
1587Stretching vibration of the C=C bond
1375Bending vibration of C–H bond
1034Stretching vibration of the C–O bond
Persimmon peel (chemical modification)Ga(III)1161 and 1726C=O and C–O stretchingElectrostatic adsorption and cation exchange128[75]
1029Si–O vibrations
3393–OH vibration
Banana blossom peels (chemical treatment)Cr(VI)3500–3300Hydroxyl (O-H) stretching vibration of celluloseNS*227.27[76]
2920C–H stretching
1616O–H bending of adsorbed water
1311 and 1375C–H & O–H bending vibrations
1244C–O stretching

Table 1.

Peel-based adsorbents (raw, thermally treated, chemically modified).

NS: not stated.


The structural changes in hemicelluloses, cellulose, and lignin following the pyrolysis, torrefaction, or any thermal treatment can be observed in the FTIR spectra. Comparing the spectrum of raw pistachio nutshell (RPNS) to that of the thermally treated candidate at 500°C (PNS500), it can be deduced that the thermal treatment has led to the removal of hydroxyl, carboxylic, carbonyl, and esters groups in the form of water, CO, CO2, and small volatile organic compounds. Such a behavior could be ascribed to the dehydration that happens during the thermal treatment process (Figure 1) [69]. Similar attributes could be observed upon chemical modification of biomasses or biochars [72]. FTIR spectroscopy identifies not only the structural alterations of the lignocellulosic biomass but also the presence of carbohydrate, protein, and lipid in the non-lignocellulosic biomass [77].

Figure 1.

Fourier-transform infrared (FTIR) spectra of raw pistachio nutshells (RPNS) and the thermally treated sample at 500°C (PNS500) (reproduced from [69], Licensee MDPI, Basel, Switzerland, under the terms and conditions of the Creative Commons Attribution (CC BY) license).

Different mechanisms have been reported for the removal of inorganics and organics from wastewater using agro-waste materials. Reflecting on the adsorption mechanism of peel-based sorbent, we can see the involvement of surface complexation, ion-exchange, surface precipitation, physisorption, chemisorption, or both physi- and chemisorption depending on pollutant concentration. Proposal of a sorption mechanism is greatly dependent on the source biomass, the nature of the surface in terms of porosity, surface area, and the existence of functional groups. The presence of polar organic groups on the sorbent surface could help in the formation of chelates with metal-ion pollutants. The role and relevance of functional moieties on the surface of the agroforestry-based sorbents in the removal of organics were confirmed using statistical physics and density functional theory. Findings showed that the existence of hydrogen and oxygen functional groups on the biomass surface were the main responsible functionalities for dye adsorption [78].

2.2.3 FTIR analysis of leaf-based adsorbents

Similar to the peel-based biosorbents, the leaf-based biosorbents are composed of a variety of inorganic and organic compounds, which, in turn, represent the potential binding sites that could scavenger potential contaminants during the adsorption process. The presence of these potential binding sites is dependent on the experimental conditions and whether the leaves will be used in their raw format (biomass) or after chemical or physical treatments. Table 2 shows examples from the literature of different leaf-derived biosorbents and their structural composition as elucidated by FTIR spectroscopy [79, 80, 81, 82, 83, 84, 85].

AdsorbentAdsorbateν(cm−1)AssignmentMechanismqmax (mg/g)
Green tea (thermal treatment)Methylene blue3279–OH vibration or N-HRGTW: Chemisorption
TTGTW500: Physisorption
RGTW: 68.28
TTGTW500: 69.01
[13]
2918 & 2845–C–H stretching of the alkane
1624–C=O stretching vibration
1533Secondary amine
1455N–H bending
1342C– H or –CH3 bending
1234–SO3 stretching
1146C − O group
1027C=O
Pineapple leaves (thermal treatment)Rose Bengal3325 & 3318.4–OH or N–H vibrationPhysisorption58.8[79]
2913–2920C–H stretching
1595–1585.8bending N–H of amines
1365 & 1375Bending–OH
1034.3C–O stretching
Aloe Vera leaves (thermal treatment)Titan yellow3300–OH vibrationPhysisorption55.25[15, 80]
2916–2850C–H stretching
1731–C=O stretching vibration
1586–COO stretching vibration
1250C–C stretching
1153C − O − C stretching of aliphatic ether
1019C–O stretching
Tea leaf-based biochar (thermal treatment)Chlortetracycline3442Stretching vibrations of O–Hπ–π interaction627[81]
1734C=O group
1232C–O group
1060C–O–C group
Olive tree leaves (reflux extraction method)Pb(II)3500 & 3100–OH stretching vibration*NS35.97[82]
2950Symmetric C–H band
2700Asymmetric C–H bands
1600 & 1650–OH and –COOH
1400–1325C–O stretching of cellulose
1120–950Organic phosphates (P–O–P), carbonates (C–O), and silicates (Si–O–Si) deformation vibrations
780C–O stretching band
568C–C stretching band
Platanus
orientalis Linn (POL) leaves (modified with KMnO4 & K2Cr2O7)
Cd(II)3700–3200–OH stretching vibrationsCation-π interaction, and ion exchange52.5[83]
1750–1540C=O stretching vibration
1420CO3−2
880C–H in the benzene rings
700–500Tetrahedral complexes (Mn2+–O2−)
Aegle marmelos leaves (raw material)Cr(VI)3275.54O–H stretch*NS8.12[84]
2918.58C–H stretch
1595.10C–C stretch
1375.02N-O asymmetric stretching
1243.45C–N stretch (primary cause of interaction with anions HCrO4)
Mulberry leaves (microwave treatment)Methyl orange3680–3000 & 1421C–H deformation*NSMPC dosage (0.1 g) 100: 0.0181[85]
1700Stretching vibration of C=O
1980C=C bonding
2882Lignin composition
875Hemicellulose

Table 2.

Leaf-based adsorbents (raw, thermally treated, chemically modified).

NS: not stated; RGTW: Raw green tea waste; TTGTW500: Thermally treated green tea waste at 500°C.


The lignocellulosic composition could vary from one plant part to another. In banana leaves, for example and when compared to the peels of the same fruit, reports show that hemicellulose content is much less (23.46%), while the cellulose content is higher (35.58%). The elemental composition of both is almost the same [67]. Pineapple leaves (PAL) have been used for the depollution of rose Bengal-contaminated water [79]. FTIR spectra of the non-thermally treated biomass (RPAL) and the thermally treated species at 250°C (TTPAL250) were depicted and compared. The lignocellulosic composition was reflected on the FTIR spectra with a difference in intensity and location of some peaks. This could be ascribed to the decomposition of lignocellulosic materials upon thermal treatment, a finding that explains the inferior adsorption capability of the thermally treated PAL compared to the RPAL.

2.2.4 FTIR analysis of seed-based adsorbents

By the same token, seeds and stones have also been applied to cleanse polluted water. As could be understood, stones and seeds are rich in lignin, and consequently, adsorbents with carbon content of 45–50% could be obtained from seeds and stones of several fruits (Table 3) [78, 86, 87, 88, 89, 90, 91, 92]. Olive stones have been widely applied for wastewater treatment. Pristine and magnetic stones were applied for the treatment of antibiotic-contaminated wastewater [89]. Peaks attributed to the aromatic skeletal vibration of lignin and C–H deformation of cellulose were detected. Brazilian berry seeds were used to remove methylene blue from wastewater [78]. Results showed that dye could be adsorbed via the interaction with two functional groups of the Brazilian berry seed. FTIR characterization together with modeling and density functional theory showed that the hydrogen and oxygen functionalities could be the main functional groups accountable for the interaction with the dye molecule.

AdsorbentAdsorbateν(cm−1)AssignmentMechanismqmax (mg/g)
Date pits (thermal treatment)Cu(II)3330–OH or –NH or bothMixture of physisorption & chemisorption4.036[86]
2921 & 2843Aliphatic C–H stretching
1739–C=O stretching vibration
1602–C=C– stretching vibration
1039C − O stretching vibration
Date pits biochar and Magnetic date pits (thermal treatment followed by chemical modification)Tigecycline3181hydroxyl (–OH) stretching vibrationChemisorption at low concentrations followed by physisorption at higher drug concentrations57.14[87]
1610 &1632N–H bending vibration of the quinolines moiety
1118 & 1097C–O stretching of aliphatic ether
892 &793C=C bending of the alkene
570Fe–O bond vibration
Spent coffee grounds impregnated with TiO2 (thermal treatment followed by chemical modification)Balofloxacin3400Hydrogen bonded OHPhysisorption196.73[88]
2927 & 2855aliphatic C–H stretching vibration
2164 & 2168C–C stretching vibration in alkyne
1500–1700Carboxyl C=O and aromatic C=C stretching vibrations
1063C–OH vibration
1630bending vibration modes of Ti–OH
1383Ti–O stretching mode
Pristine and magnetic olive stones biochar (thermal treatment followed by chemical modification)Clofazimine1580Aromatic skeletal vibration in ligninPhysisorption174.03[89]
1370C–H deformation
1170C–O–C vibration
890C–H deformation in cellulose
760Aryl C–H or the aryl C–O groups
564Fe–O bond vibration
Adenanthera Paronina L seed-activated carbon
(thermal & chemical modification)
Reactive Red 195 Dye3602–3617–OH stretching belongs to alcoholsNS82.35[90]
3413–3435–NH stretching belongs to aliphatic primary amines
2893 & 2924Aliphatic C–H stretching vibration
1380–1384–CH bending of alkenes
Sodium alginate–flax seed ash beads (thermal & chemical modification)Methylene blue3234, 1594, &1405Asymmetric and symmetric C=O stretching vibrationsIon-exchange mechanism333.3[91]
1025C–O stretching
3113–OH vibrations
1593, 1417 &
1015
Asymmetric COO symmetric COO & C–O–C stretching, respectively
1421 and 1030C=O bending and C–O stretching vibrations
Magnetic Fe3O4 nanoparticle-loaded papaya (Carica papaya L.) seedCongo red3439Stretching vibrations of the hydroxyl groupHydrogen bonding and electrostatic interactions216.9[92]
2893C–H stretching vibration in CH and CH2
1638–C=O stretching vibration
1412 &1324–C–O group
1017Stretching vibrations of the C–O group
778C–H in out-of-plane bending vibrations
608Stretching vibration of Fe–O
Brazilian berry seedsMethylene blue3428O–H elongationHydrogen and oxygen functionalities of biomass surface were the main functional groups responsible for dye adsorption206.24[78]
2925 & 2849Vibrational bonds of C–H
1700C=O and N–H stretching vibration
1061 & 1012Vibration bonds of C–O
602C–N bond

Table 3.

Seed-based adsorbents.

2.3 Functional groups and adsorption mechanism

Several variables influence the adsorption mechanism of any adsorbent, including the existence of functional groups, surface area, surface charge, and pH. Several investigations have described the significance of the existent functional groups in removing various contaminants (organics and inorganics) [15, 70, 93]. Chemical interactions of the existing functionalities on the sorbent surface and the different pollutants depend mainly on the carbon surface’s chemistry and heterogeneity, the aqueous solution ionic properties, and the pollutant structure. As illustrated in Figure 2, the interaction mechanisms between the adsorbate and the adsorbent from an aqueous solution include several mechanisms [94]. Their particular involvement in the adsorption approach differs greatly depending on the adsorbate structure, solution ionic conditions, and the nature of the carbon materials. Two mechanisms are commonly used to describe the adsorption of different pollutants from aqueous solution, including chemisorption (ion exchange, complexation, precipitation) or physisorption (electrostatic interaction) [15, 86, 87, 88]. Most of these mechanisms are strongly related to surface functional groups, such as ion exchange, electrostatic interaction, surface complexation via electrostatic forces, binding site creation, and covalent bonding [95]. One of the key mechanisms for the adsorption of various pollutants, such as heavy metals, is the ion exchange mechanism between pollutants and protons present in oxygen-containing functional groups such as carboxyl and hydroxyl groups [96]. The efficacy of the ion exchange method in the adsorption of various contaminants onto carbonaceous surfaces is mostly determined by the pollutant’s ionic size and the kind of functional group of the adsorbent. On the other hand, electrostatic interaction occurs between positively charged pollutants like heavy metals and cationic dyes and negatively charged carbonaceous adsorbents containing anionic functional groups [15]. This process is considered relatively inefficient; the contribution of electrostatic interaction to cationic pollutants’ adsorption onto carbonaceous adsorbents is considered a secondary contribution. The reason for that is that the charge of the carbonaceous surfaces is varied, and the efficiency of the electrostatic interaction is dependent mainly on the pH of the adsorbate solution and the point of zero charges of the prepared adsorbent. The interaction between carbon and the pollutant depends on the surface functional groups’ ionization degree. Finally, surface complexation mainly describes heavy metals’ adsorption and includes the formations of multi-atom structures with particular metal-functional group interactions. For instance, heavy metal can be effectively adsorbed by forming a complex with different functional groups on the adsorbent surface, such as carboxyl, phenolic, and lactone groups [97].

Figure 2.

Adsorption mechanisms onto biochar and their regeneration processes. (Reproduced from [94], Licensee MDPI, under the terms and conditions of the Creative Commons Attribution (CC BY 4.0) license).

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3. Conclusions

Plant-sourced biosorbents are currently attracting global attention. Being easily functionalized with high surface area and superior adsorption capacity for various contaminants, biomasses represent a sustainable solution with a tremendous potential for wastewater treatment. Recycling of these waste materials into value-added products offers ample advantages in terms of protecting the environment from a possible burden in case these wastes were not properly reused and simultaneously offering a green and economic solution for decontaminating water. Analysis of the composition and hence comprehending the properties of biomasses either in their raw format or following physical or chemical treatments is crucial to guarantee the quality of the produced materials and the production processes and therefore supporting the execution of both market and environmental regulations. Throughout this chapter, we have shown the readers the importance of using Fourier transform infrared (FTIR) spectroscopy in depicting the composition of biomass-based adsorbents, an issue that is essential for designing and developing the value-added products. Compared to the traditional analytical techniques, FTIR spectroscopy offers many advantages and is an effective alternative that is cost-effective, non-laborious, and non-invasive for compositional analysis and characterization of the lignocellulosic biomasses.

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Conflict of interest

The authors declare no conflict of interest.

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Written By

Marwa El-Azazy, Ahmed S. El-Shafie and Khalid Al-Saad

Reviewed: 04 November 2022 Published: 24 November 2022