Adsorption isotherms for AsIII adsorption by a bio-adsorbent.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 179 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 252 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"393",leadTitle:null,fullTitle:"Adaptive Filtering Applications",title:"Adaptive Filtering Applications",subtitle:null,reviewType:"peer-reviewed",abstract:"Adaptive filtering is useful in any application where the signals or the modeled system vary over time. The configuration of the system and, in particular, the position where the adaptive processor is placed generate different areas or application fields such as: prediction, system identification and modeling, equalization, cancellation of interference, etc. which are very important in many disciplines such as control systems, communications, signal processing, acoustics, voice, sound and image, etc. The book consists of noise and echo cancellation, medical applications, communications systems and others hardly joined by their heterogeneity. Each application is a case study with rigor that shows weakness/strength of the method used, assesses its suitability and suggests new forms and areas of use. The problems are becoming increasingly complex and applications must be adapted to solve them. The adaptive filters have proven to be useful in these environments of multiple input/output, variant-time behaviors, and long and complex transfer functions effectively, but fundamentally they still have to evolve. This book is a demonstration of this and a small illustration of everything that is to come.",isbn:null,printIsbn:"978-953-307-306-4",pdfIsbn:"978-953-51-6016-8",doi:"10.5772/912",price:139,priceEur:155,priceUsd:179,slug:"adaptive-filtering-applications",numberOfPages:412,isOpenForSubmission:!1,isInWos:1,hash:"fcca6dde43a408a5cc07096108c37ece",bookSignature:"Lino Garcia",publishedDate:"July 5th 2011",coverURL:"https://cdn.intechopen.com/books/images_new/393.jpg",numberOfDownloads:65617,numberOfWosCitations:44,numberOfCrossrefCitations:15,numberOfDimensionsCitations:53,hasAltmetrics:1,numberOfTotalCitations:112,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 7th 2010",dateEndSecondStepPublish:"November 4th 2010",dateEndThirdStepPublish:"February 9th 2011",dateEndFourthStepPublish:"April 10th 2011",dateEndFifthStepPublish:"June 24th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,editors:[{id:"682",title:"Dr.",name:"Lino",middleName:null,surname:"Garcia Morales",slug:"lino-garcia-morales",fullName:"Lino Garcia Morales",profilePictureURL:"https://mts.intechopen.com/storage/users/682/images/1688_n.jpg",biography:"Lino García Morales has graduated in Automatic Control Engineering at Polytechnic Institute “José A. Echeverría”. He has received a master’s degree in Systems and Communications Networks at Technical University of Madrid, PhD. in Communications Technologies and Systems at UPM, PhD. in Contemporary Artistic Practices and Art Theory at European University of Madrid. He has been professor at the Superior Institute of Art (ISA), Comillas Pontifical University (UPCO), Menéndez Pelayo International University (UIMP), Senior Lecturer of Higher Technical School (ESP) at UEM, Coordinator of Electronica and Digital Art Degree and Director of Master in Architectonic and Environmental Acoustic at UEM. At the moment he is professor at UPM. 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Besides the upgrade of LHC to higher luminosity and center of mass energy, a large number of novel international high energy physics facilities is currently in consideration, including, among others, the International Linear Collider (ILC), the Compact Linear Collider (CLIC), the Circular Electron Positron Collider (CEPC), the Super Proton Proton Collider (SPPC), and the Future Circular Collider (FCC). The first aim of this book is to provide an overview of the physics case of such novel facilities, with particular focus on the discovery potential beyond the Physics beyond the Standard Model. The second aim of the book is to outline novel detection technologies under development in order to fulfill the demanding experimental conditions of future facilities, with particular focus on sensors, calorimetry, and tracking detectors. Cross-disciplinary applications of novel theoretical findings and technologies play an important role in modern research. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"59176",title:"Bio-adsorbents for the Removal of Heavy Metals from Water",doi:"10.5772/intechopen.73570",slug:"bio-adsorbents-for-the-removal-of-heavy-metals-from-water",body:'Arsenic (As) is the 20th most abundant element in the earth’s crust, and its concentration on the soil level is about 5–13 mg/kg [1]. Naturally, arsenic is found in different oxidation states: V (arsenate), III (arsenite), 0 (arsenic), and -III (arsine) [2, 3]. Arsenic (As) is one of the elements that occur naturally and commonly found as an impurity in metal ores, and it is in abundance. It can be found in the soil, water, and living organisms. It is produced commercially for use in wood preservatives, metal alloys, and pesticides.
Both AsIII and AsV exist in the pH range of 6–9, and when comparing AsIII and AsV, it is known that AsIII is more toxic than AsV and also in terms of mobility [4]. Depending on the pH, Arsenite (AsIII) exists in four forms in aqueous solution, such as H3AsO3, H2AsO3−, HAsO32−, and AsO33−. In a reductive environment, below pH 9.1 As(III) exists in the form of inorganic arsenite (H3AsO3) and is thermodynamically stable [5].
Since arsenic is one the most well-known poisonous elements in the periodic table, it is known to be carcinogenic in many parts of the world [6]. Long-term exposure to arsenic, through water and food, can lead to serious health problems like neurological effects, hypertension and cardiovascular diseases, and skin and lung cancer [7]. The kidney is the major source for regulation of water and electrolytes, waste, and chemical compounds, and arsenic(III) can affect the role of the proximal tubules and glomerulus of the kidney [8].
Arsenic(III) is the one that is known to be toxic [4]. The World Health Organization (WHO) recommended a more rigid limit of 10 μg/L as the maximum acceptable arsenic level [9]. Commercial methods for removing arsenic involve technologies such as precipitation, membranes, and adsorption. But adsorption is the most easy, flexible, inexpensive method to be applied by using mineral oxides [10], polymer resins [11], and activated carbons [12]. According to literature, waste materials such as rice husks, tea, and agricultural waste have been applied as inexpensive adsorbents [13].
It is well known that South Africa is a developing country with limited resources for water purification; therefore, the aim of this work is to develop a cheaper, easy-to-use method of treating water especially in the rural areas where the water treatment stations are not yet established.
The most crucial aim of the work is that the bio-adsorbent must be manufactured from a locally available material that is reusable in order to save the rural area’s people from daily expenses.
Potassium carbonate and arsenic standard employed in the synthetic application procedures of this work were of analytical grade and obtained from Sigma-Aldrich (St. Louis, MO, USA). Millipore water (Merck, Darmstadt, Germany) of 18 MΩ cm−1 was used throughout the experiments. Concentrated nitric acid (HNO3) (70%) was also purchased from (St. Louis, MO, USA,
The As quantification was performed using inductively coupled plasma optical emission spectroscopy (ICPOES) (iCAP 6500 Duo, Thermo Fisher Scientific, UK) equipped with a charge injection device (CID) detector. The sample injection application was done through a concentric nebulizer and a cyclonic spray chamber. A Mettler Toledo pH meter model 120 (Greifensee, Switzerland) was employed for all pH measurements. The active carbon material production, i.e., activation, was performed in a tubular furnace (Gallenkamp, Germany). The AFWS and ACM were characterized for porosity, pore structures, surface area, and pore volume using N2 gas adsorption BET (Brunauer, Emmett, and Teller) method for surface area, while the crystallinity of the material was determined by X-ray diffraction (XRD, Rigaku, UHMa IV, Japan). Surface morphology and surface functional groups were determined by scanning electron microscopy (SEM, TECAN VEGA 3 XMU, Czech Republic) coupled with energy dispersive spectroscopy (EDS) (TECAN VEGA 3 XMU, Czech Republic) and Fourier transmission infrared spectroscopy (FTIR, PerkinElmer FTIR, UK), respectively.
The precursor for the active carbon material was acquired by collecting avocado seeds. The avocado fruit waste seeds (AFWS) were air-dried and thoroughly washed before rinsing with deionized water. The washed seed residues were then oven-dried overnight at 100°C. The seeds were then pulverized by ball milling it with laboratory hammer mill (Janke and Kunkel Micro-hammer Mill, Staufen IM Breisgau, Germany) to obtain fine powder. The bulky powdered material was later fractionated to diverse particle size using laboratory sieves. The resultant particles of different miniature diameters ranging from 38 to 150 μm were obtained in which 75 μm particle size was subsequently employed in production of active carbon material. The powdered form of avocado seed was then stored inside desiccator until application.
The adsorption studies were carried out to evaluate the efficiency of the avocado peel (bio-adsorbent) for the removal of AsIII from the aqueous solution using the batch adsorption method. The batch adsorption experiments were carried out in 50 mL plastic bottles by shaking a constant mass of a predetermined size of adsorbent with arsenic standard solutions. The pH of the solutions was adjusted accordingly by adding either ammonium hydroxide or acetic acid solution. Each flask was sealed and kept in a state of agitation (200 rpm) using a mechanical laboratory shaker for the material to reach equilibrium. Upon equilibrium, the samples were filtered and analyzed using inductively coupled plasma optical emission spectroscopy (ICPOES). Parameters such as pH, concentration of solution, mass of adsorbent, contact time, and temperature were optimized.
The percentage removal of As(III) in solution was calculated using Eq. (1):
where R is the percentage (%) removal and Co and Ce are the initial and equilibrium concentrations of the analyte, respectively.
The amount of metal adsorbed by adsorbent was calculated from the difference of metal quantity added to the biomass and metal content of the supernatant (Eq. (2) [14, 15]:
where qe is the metal uptake (mgg−1), C0 and Ce are the initial and equilibrium metal concentration (mgL−1), V is the volume of the solution (mL), and M is the mass of the adsorbent (g).
The FTIR spectrum is an important technique which provides the surface functional groups that significantly contribute in the enhanced adsorption efficiency of the adsorbent. FTIR was used to determine the surface functional groups of raw avocado fruit waste seed. In Figure 1, the spectrum of the powdered avocado seed is represented, where the band located at 3259 cm−1 corresponds to v (O─H) vibrations in the hydroxyl group, while the strong peaks at 2913 and 2848 cm−1 bands correspond to v(C─H) vibration in the alkane/alkyl aliphatic group which could be methylene [16, 17, 18, 19, 20]. The presence of alcohols and carbonyl groups was confirmed by the bond vibrations observed at 1633 cm−1. This confirms that avocado seed is composed of carboxylic group which is responsible for adsorption; similar results were reported in the literature [21, 22].
FTIR spectrum of avocado fruit waste seed (AFWS).
The surface morphology and the chemical composition of raw avocado seed was studied with scanning electron microscope coupled with energy dispersive spectroscopy (SEM-EDS). The image in Figure 2(a) showed that raw avocado seed material had a smooth surface with long ridges and a series of graphitic layers with various pores.
Avocado seed images of (a) SEM and (b) EDS.
The EDS analyses performed on avocado seed revealed that the surface contained different mineral particles, such as carbon, oxygen, potassium, phosphorus, and chlorine (Figure 2b). The highest content of oxygen may assist in adsorption due to electron lone pairs.
pH is one of the most important parameters that influence the adsorption of the analyte. In this study, the amount of AsIII adsorbed on avocado seed was the highest at pH 6 and gradually decreased as the pH increased up to 9 (Figure 3a) [7]. However, the highest removal was observed with avocado seed due to the presence of carboxylic group on the surface which increased the affinity toward arsenic to the adsorbent (Figure 1). Oxygen of the carbonyl group easily formed the complex with the arsenic [23]. Arsenic(III) adsorption decreased as the pH goes below 6 due to the increasing ionic strength [24].
Optimization of (a) pH of the solution, (b) concentration of the analyte, (c) bio-adsorbent dosage, (d) contact time between the bio-adsorbent and the analyte, and (e) temperature of the solution.
The effect of the concentration was carried out by increasing the initial concentration from 5 to 30 mg L−1, and the solutions were adjusted to pH 6 at 25°C. It was observed that the percentage removal increased with the increasing concentration of the analyte; this is due to the fact that as the concentration increased more ions were available in the solution for adsorption [25]. It was observed from the results in Figure 3b that the highest removal (65%) was reached using 20 mg L−1 and after there was no significant increase in the percentage (%) removal of AsIII.
The amount of adsorbent is one on the important factors that affects the adsorption capacity. The adsorbent amount of raw avocado seed on the efficiency of adsorption was investigated, and adsorbent amount was varied from 0.025 to 0.8 g. The results observed indicated that the adsorption increased with increasing adsorbent dosage till 0.8 g (Figure 3c). The increase in the percentage removal is due to the availability of active sites for adsorption [26]. It was found that after the dosage of 0.4 g there is no significant change in the percentage removal of arsenic. Then, 0.8 g was used throughout the experiments.
The effect of contact time is an important factor in adsorption because it affects the adsorption kinetics of an adsorbent at the given initial concentration of the adsorbate [26]. The batch adsorption experiments were carried out to investigate the effect of agitation time on the adsorption of As(III). Adsorption rate initially increased rapidly, and the highest removal was reached at 120 min (Figure 3d). Further increase in contact time did not show a significant change in the percentage (%) removal of arsenic.
Temperature is one of the parameters that affect the equilibrium and solubility and can also initiate the chemical reaction. This is because temperature can either increase or decrease the activation energy of the analyte. The effect of temperature on the adsorption of arsenic was investigated from room temperature of 40°C. From the results obtained in Figure 3e, the temperature did not have any effects since there is no significant increase or decrease in the percentage (%) removal of arsenic.
Under optimized conditions, 2 mg L−1 AsIII standard solution was adsorbed by the avocado peels, and 75% AsIII was removed (Figure 4). The adsorption capacity was 93.75 mg/g when Eq. (2) was applied.
Determination of percentage (%) removal from 2 mg L−1 AsIII standard solution by ICPOES.
Adsorption is described by the functions which connect the amount of adsorbate on the adsorbent.
The distribution of metal ions between the liquid phase and the solid phase is described by several isotherm models such as Langmuir and Freundlich [27].
The Langmuir equation can be written in the form of Eq. (3):
where Ce is the equilibrium concentration (mg/L), qe is the amount of arsenic adsorbed onto the solid phase (mg/g), b is the equilibrium adsorption constant related to the affinity of binding sites (L/mg), and qmax is the maximum amount of arsenic per unit weight of adsorbent for complete monolayer coverage.
Freundlich equation is represented as shown in Eq. (4):
where Ce is the equilibrium concentration (mg/L), qe is the amount of arsenic adsorbed onto the solid phase (mg/g), Kf is an indicator of the adsorption capacity, and n is the heterogeneity factor.
The results in Figure 5(a and b) and Table 1 showed that the correlation coefficient for linear Langmuir model (R2, 0.97) was higher than the Freundlich model (R2, 0.72). The data was best fitted in Langmuir model, and this signified that the adsorbent had high affinity for arsenic(III) due to the carboxylic groups that are the surface of the avocado seed [28], meaning that the chemisorption took place. To prove that the data belonged to Langmuir isotherm, the separation value, RL value from Eq. (5) was calculated. RL proves whether the Langmuir adsorption nature is favorable if RL > 0, unfavorable if RL > 1, and irreversible if RL = 0:
where C0 is the initial concentration and KL is a Langmuir constant obtained from plotting 1/qe versus 1/Ce. The results in Table 1 indicated that the equilibrium sorption was favorable for Langmuir isotherm.
(a) Langmuir isotherm displaying the adsorption of AsIII onto the surface of the avocado seed by plotting Ce/qe against equilibrium concentration (Ce). (b) Freundlich isotherm showing the adsorption of AsIII onto the surface of the avocado seed by plotting ln Ce against equilibrium concentration ln qe.
Adsorption isotherm | Parameter | Value |
---|---|---|
Langmuir | KL | 0.0022 L/mg |
RL | 0.17 | |
R2 | 0.97 | |
Freundlich | R2 | 0.72 |
Adsorption isotherms for AsIII adsorption by a bio-adsorbent.
AsIII standard solution adsorbed by avocado seed | Data |
---|---|
Before adsorption | 2.0 mg L−1 |
After adsorption | (0.50; 0.50; 0.50; 0.50; 0.49; 0.49; 0.49; 0.47) mg L−1 |
Mean | 0.49 mg L−1 |
Standard deviation | ± 0.010 mg L−1 |
Relative standard deviation | 2.1% |
The repeatability of AsIII concentration during the adsorption by avocado seed obtained from a local shop in Johannesburg.
Analytical figures of merit for the quantitative analysis of arsenic(III) such as limit of detection (LOD), limit of quantification (LOQ), correlation coefficient (R2), and the relative standard deviation (RSD) were calculated. In order to determine the LOD, the blank solution was subjected to the optimum experimental conditions, and the signals for ten blank samples were measured (n = 10). The limit of detection (LOD), calculated based on 3S/m (where S is the standard deviation of the blank and m is the slope of the calibration curve) was 0.10 mg L−1. The limit of quantification (LOQ = 10S/m) was 0.20 mg L−1 for arsenic(III). The linear calibration curve was plotted with a correlation coefficient of 0.98.
The precision (repeatability) of the batch adsorption method was studied by measurements of eight replicates of 2.0 mg L−1 standard solution of AsIII as shown in Table 2. The precision, expressed in terms of standard deviation (%RSD), was 2.1.
A water sample from East London municipality was adsorbed by the raw avocado seed under the optimized conditions. It is shown in Figure 6(a and b) that the bio-adsorbent is removed (54 and 55%) from sampling area A and B, respectively. During the adsorption of AsIII from environmental water samples, an interference can be experienced from metal ions such as FeIII, FeII, ZnII, CdII, NiII, MnII, AlIII, PbII, and CuII [10].
The determination of the percentage (%) of AsIII removed by the bio-adsorbent from (a) Sample A to (b) Sample B using ICPOES.
This indicated that avocado seed has the great potential in removing heavy metals like AsIII in environmental water samples without being modified.
This work focused on removal of arsenic from aqueous solution using a powdered raw avocado seed. Important parameters that affect adsorption were optimized accordingly, pH 6, analyte 2 mg L−1, dosage mass 0.8 g, and contact time 120 min, and temperature was constant from room temperature of 40°C. It was observed that raw avocado fruit seed can remove more than 50% of arsenic(III) from real water sample without any modification. The advantages of this bio-adsorbent is that it requires less preparation time and is readily available. The use of avocado seeds as a bio-adsorbent will also reduce the waste that is normally discarded in the streets, and it does not affect the food security issues since it is not edible. Due to the advantages that it possesses, it is strongly recommended that it should be incorporated in the removal of toxic heavy metals such as AsIII. The adsorption isotherm data were tested for both Langmuir and Freundlich models. The regression coefficient and RL values, best fitted Langmuir model (R2 = 0.97), and the adsorption capacity was 93.75 mg/g. The Langmuir model means that chemisorption took place at the monolayer of the bio-adsorbent due to the availability of functional groups such as carboxylic acids that have high affinity for metal ions such AsIII.
This work was supported by the National Research Foundation of South Africa (Thuthuka Grant No. 107066 and CPRR Grant No. 98887); the Centre for Nanomaterials Science Research; the National Nanoscience Postgraduate Teaching and Training Platform; the University of Johannesburg (UJ), South Africa; and the Faculty of Science, University of Johannesburg (UJ), South Africa.
Surface plasmon resonance (SPR) biosensors have become one of the most promising, standard, and affordable technology due to prompt research and expansion of SPR phenomenon in the last two decades. Nowadays, SPR sensors are broadly implemented for numerous biological and biochemical analytes identification and characterization due to its high sensitivity, real-time monitoring, level free detection assay, small sample size, and reusable sensor chip [1, 2, 3, 4, 5]. To be detailed, the SPR biosensors are adopted to agriculture and food quality monitoring [6], security and safely analysis [7], in need of medical diagnostics, environmental monitoring, bio-imaging [8, 9, 10], cancer detection [11, 12], DNA hybridization [13, 14], enzyme detection [15], protein-protein, protein-DNA, and protein-virus hybridization [16, 17], microorganisms identifying [18], industrial appliance’s condition monitoring, temperature monitoring [19], gas sensing [20, 21], chemical and biochemical analysis [22, 23], pharmaceutical and biological molecule analysis [24, 25], oil condition monitoring [26], and so on. In the year 1902, Wood [27] first observed unexpected optical power attenuation characteristic at the time of measuring the reflection of light from metallic gratings. This phenomenon occurs due to absorbance and conversion of photon energy to surface plasma wave (SPW) which is the result of combined oscillation of excited electrons called surface plasmon polaritons (SPPs). This oscillating electron consumes maximum energy at a certain wavelength for a specific angle of incidence of light which is called resonance condition. That is why this phenomenon is named surface plasmon resonance (SPR). In 1968, Otto [28] and Kretschmann [29] introduced attenuated total internal reflection (ATR), which encouraged scientists and researchers to concentrate on the implementation of SPR sensing technology practically. In 1982, the SPR sensing technique was first demonstrated by Nylander and Liedberg [4, 30] for the practical application of gas sensing. After that, SPR sensing technology has been getting ceaselessly developing consideration from the scientific and academic network. In 1990, the SPR sensing instrument was first commercially produced and introduced to the market by Biacore AB. Since then a considerable number of manufacturers e.g. IBIS Technologies B.V., Graffinity pharmaceuticals, GWC Technologies, Bio-Red, AutoLab, Farfield Sensors, Genoptics Bio Interactions, Microvaccum, Biosensing Instrument, and SPR Navi have launched their SPR instruments to the market [17, 31].
\nDifferent optical techniques are currently proposed for sensing purposes, including Ramman scattering based sensors [32, 33], grating coupled sensors [34, 35], prism coupled sensors [36, 37], optical fiber-based sensors [38, 39], planner waveguide-based sensors [40, 41] etc. The optical biosensors basically work with the measurement of change in input incident light and detected light at the output terminal. To be specific, the change in phase, amplitude, wavelength, frequency, or polarization of light is measured at the output terminal of the sensors and the changes in these parameters are observed. Among them, the commonly used technique is observing the reflected light angle where maximum light is attenuated. This method is called angular interrogation approach with attenuated total internal reflection (ATR) that is applied usually in prism coupled devices. The performance of an optical sensor is basically measured in terms of its sensitivity, detection accuracy or detection limit, the figure of merits (FOM) and quality factor (QF), etc. The researchers and scientists are continuously working for the improvement of the performances of the SPR sensors [31, 42, 43, 44].
\nIn SPR biosensors, the most crucial parameters determining the characteristics of the sensors are plasmonic materials. Materials with adequate free electrons at their valance bands can be used as plasmonic materials. To be specific, metals e.g. gold (Au), aluminum (Al), silver (Ag), copper (Cu), etc. are a good candidate to be used as a plasmonic material [45, 46]. Al and Cu have not gained much interest to be used because of their high damping nature, prone to oxidation, corrosion, and interband transition characteristics. But Silver (Ag) can be nominated as a potential candidate for SPR sensors as it attributes outstanding optical properties, such as no interband transfer at the visible light frequency, small optical damping, and sharper resonance peak [46, 47, 48], etc. Using Ag in SPR sensors, better sensitivity can be captured, but it shows poor chemical stability as it creates brittle oxide layers with liquid analyte [49]. Some researchers have reported that applying bimetallic layer on the Ag surface can resolve this problem [50, 51]. On the other hand, Au is more chemically stable compared to Ag and free of corrosion and oxidation problems. But, gold offers a slightly higher damping loss and widen SPR curve that restricts the detection accuracy and figure of merits (FOM) of the sensors [52]. The sensitivity of Au-based sensors is also slightly lower because of the low biomolecular adsorption characteristics of the gold surface. In order to improve the sensitivity of the sensors, researchers recommended various approaches in which the application of hybrid structures (multilayer structures) are widely used [53, 54, 55, 56]. Various 2D materials are used in the hybrid configuration of SPR based sensors. A single atom thick carbon nanostructure (graphene) is often applied on the top of the plasmonic materials to avoid oxidation problems and increase the performance of the sensors because of its chemical inertness and high adsorption characteristics [57, 58]. There are also some other nanomaterials e.g. graphene oxides, graphene carbon nitrite (g-C3N4), transition metal dichalcogenides (TMDCs: MoS2, MoSe2, WS2, WSe2, PtSe2, SnSe2, etc.), transition metal chalcogenides (NbSe3, TaSe3), transition metal oxides (TMOs: LaVO3, LaMnO3), Black phosphorene (BP), hexagonal boron nitride (hBN), group IV elements [59, 60] and so on which are summarized in the Figure 1.
\n2D materials library where blue shaded materials are stable at ambient condition, green-shaded are probably stable, pink shaded are unstable at ambient condition but stable at inert condition. The gray shaded mistrials are 3D but can be exfoliated down to monolayers [60, 61].
This chapter mainly focuses on the recent trends applied for enhancing the performance of the Kretschmann configuration based prism coupled SPR sensors and their potential applications. The fundamental theory of SPR phenomena is presented first. Then, the method of angular interrogation utilizing attenuated total internal reflection and the performance measuring parameters of the SPR sensors are narrated. Finally, with their compressive architectures, recent developments of the prism coupled SPR sensors are discussed.
\nMetals are composed of positively charged nuclei with a lot of free electrons in their conduction band (surface of the metal). If an external electric field is applied close to the metal surface, free electrons are dislocated, resulting in an electric dipole [61]. A longitudinal oscillation has resulted from such electron transportation in a metal surface known as surface plasmons (SPs) [49]. To support the generated SPs a metal and dielectric interface is needed [46] whereas excitation of these SPs leads to an enhanced electromagnetic field resulting in a collective oscillation of free electrons or electron plasma [46, 61, 62]. The basic principle of the construction of SPR based sensors lies in the generation and propagation of electromagnetic waves called surface plasmon wave (SPW) due to the interaction of irradiating electric fields and the generated fields for dislocation of the electrons between the metal-dielectric interface [4]. The SPWs can only be produced by the incidence of a transverse magnetic (TM-) or plane (p-) polarized field as Maxwell’s equations supports no solution for transverse electric (TE-) polarized case [46]. Furthermore, the fact that electron oscillation means resistive losses. Thus, when an optical field appears at the metal-dielectric boundary, the SPW produces due to optical absorption of exponentially decaying evanescent waves. Mathematically, when the wave vector of the SPW is equal to the propagation constant of the irradiating lightwave, maximum absorption of evanescent field is observed leading to a strong SPW generation [63, 64]. This condition is called resonance condition. The propagating evanescent wave can be characterized by propagation constant βev\n as follows [10, 65]:
\nWhere λ, n, θ indicate the incident light wavelength, refractive index of the medium, and angle of incident of light at the metal surface, respectively. The equation as follows characterizes the SPW [66]:
\nWhere \n
Where the RI of plasmonic material (\n
Due to its outstanding performance characteristics, commercial standardization, and ease of manufacturing technology, the angular interrogation method using ATR has become more popular today among various SPR based sensors. When light is directly coupled to the metal-dielectric interface, due to a mismatch of momentum, the SPs are not sufficiently excited to generate SPWs [70]. Researchers have suggested several special arrangements called Otto configuration [71], Kretschmann configuration [72, 73] as visualized in Figure 2 to alter the momentum of the photon to couple with the SPPs leading to propagation of SPW. In prism based Otto configuration, there is a distance where a dielectric layer with a smaller RI is used between the prism and metal sheet on which the light is employed. On contrary, Kretschmann configuration the metallic layer is in direct contact with the prism. Among them, the Kretschmann configuration is the most popular solution to ensure the coupling of the strongest evanescent wave passing through the metal and generate SPW [53, 74, 75, 76]. In the Kretschmann configuration, the light is incident at the metal-dielectric interface through a high index prism [77].
\nSpecial Arrangements [74] e.g. (a) Kretschmann configuration, and (b) Otto configuration to match the momentum of incident photon and SPW.
Usually, the incident light bounces back from the interface while the evanescent field is induced by a portion of light penetrating through the metal. For a particular sensor configuration and light frequency, the momentum of the evanescent field is aligned with the wave vector of SPW at a specific angle called resonance angle [76]. Maximum light is coupled to the oscillating electrons at this resonance condition, leading to minimum reflection. If the reflected light is plotted concerning the incident angle, then a resonance dip of reflection spectrum is observed called SPR point which is highly responsive to the RI of the sensing medium. By interrogating this SPR point the analyte can be detected easily. The performance measuring parameters e.g. sensitivity, detection accuracy, FOM, and QF should be as high as possible to eliminate false positive detection. The sensitivity of the sensor operating on the angular interrogation approach depends on the change in the SPR point or resonance angle with a change in RI of the sensing medium. Figure 3 illustrates the SPR curve variation due to change in sensing medium RI where the resonance point is found at \n
Illustration of the SPR curve variation due to change in sensing medium RI.
A sensor’s detection accuracy, which depends on the width of the SPR curve, determines how quickly and accurately the SPR point can be measured by the sensor. It is inversely proportional to the width of SPR. If \n
Nowadays, the prime concern of scientists, researchers, and academicians are to enhance the performance of the SPR based sensor. To date, several attempts have been reported to attain highly sensitive sensors where the use of bimetallic coating and hybridization of numerous 2D materials along with plasmonic materials are the most popular approach to accommodate the angular interrogation approach. Benaziez S. et al. [81] reported a sensor where Ag is considered as an SPR active material. They showed that the addition of mostly used 2D material graphene on Ag surface enables to reduce the oxidation problem as well as increase the sensitivity up to 9.3%. Yet, the detection accuracy of the sensor is slightly reduced. Also, Rouf H. K. and Haque A. [82] proposed a hybrid structure using InP and Ti with the Ag-Au bimetallic configuration. Their sensor shows maximum sensitivity of 70.90 deg/RIU. Similarly, Mishra S. K. and their team [83] have demonstrated a configuration with excellent sensor sensitivity of 229 deg/RIU. They used a rarely used material Rhodium (Rh) with Ag to realize bimetallic configuration. Also, they used a silicon layer on the bimetallic layer to lessen the limitations of Ag. Likewise, N. Mudgal et al. [3] proposed a four-layer hybrid structure that consists of Au, molybdenum disulfide (MoS2), h-BN (hexagonal boron nitride), and graphene to detect urine glucose. The structure can enhance the sensor sensitivity up to 194.12 deg/RIU with the detection accuracy of 16.04/RIU. In the same way, Hailin Xu et al. [84] proposed an optical sensor with the graphene-Al-graphene sandwich structure where graphene prevents the oxidation issue of Al as well as enhances the sensor sensitivity 3.4 times more than only Al-based sensor. Besides, Wang M. et al. [85] suggested a sensor consisting of graphene, Tungsten disulfide (WS2), and Au-Ag bimetallic film. They observed that hybridization of single layer graphene and WS2 with Au-Ag bimetallic nanostructure leads to sensitivity up to 182.5 deg/RIU which is superior to Au-only based sensor. Incorporating the advantages of hybrid structure and bimetallic configuration, very recently Rahman M. et al. [86] also proposed a new configuration of SPR biosensors utilizing the newly emerged TMDC (PtSe2) embedded 2D materials as illustrated in Figure 4.
\nSchematic Illustration of SPR biosensor employing hybridization of 2D materials with Ag/Au [86].
In this configuration, a heterostructure of PtSe2/2D material (e.g., graphene, MoS2, WS2) has been employed to realize the hybrid configuration whereas BK7 prism is used as a coupler that increases the momentum of the evanescent wave to match with the wave vector of the SPW. The sensor comprises a thin layer (50 nm) of Au or Ag as an SPR active material between the prism coupler and PtSe2/2D material heterostructure. A monochromatic He-Ne laser source having a wavelength of 633 nm have been incorporated to excite the SPPs. The sensor parameters are altered and optimized varying the thickness of PtSe2 and number 2D material’s layer to get better performance where the results are revealed in Figure 5.
\nSensitivity variation due to change in the thickness of PtSe2, and number of (a) Graphene layer (b) MoS2 layer, (c) WS2 layer for BK7/Ag (50 nm)/PtSe2/2D materials (Graphene/MoS2/WS2) hybrid structure; and number of (d) Graphene layer, (e) MoS2 layer, and (f) WS2 layer for BK7/Au (50 nm)/PtSe2/2D materials (Graphene/MoS2/WS2) hybrid structure [86].
The effects of alteration of different parameters of PtSe2, and 2D materials have been analyzed comprehensively and two new sensors have been introduced with excellent performance characteristics. The details of optimized design parameters and performances are listed in Table 1. As well, Table 2 shows the performance comparison of different SPR biosensors based on Kretschmann configuration with a hybrid structure.
\nSl. no. | \nProposed SPR sensors with optimized structural parameters | \nOperating range of sensing medium RI | \nFOM [RIU–1] | \nQF [deg/RIU] | \nSensitivity [deg/RIU] | \n||
---|---|---|---|---|---|---|---|
01. | \nAg/PtSe2/WS2\n | \nThickness of Ag (nm) | \n50 | \n1.33-1.38 | \n17.64 | \n34.22 | \n194 | \n
Thickness of PtSe2 (nm) | \n02 | \n||||||
Number of WS2 Layers | \n04 | \n||||||
02. | \nAu/PtSe2/WS2\n | \nThickness of Au (nm) | \n50 | \n1.33-1.38 | \n15.72 | \n29.39 | \n187 | \n
Thickness of PtSe2 (nm) | \n02 | \n||||||
Number of WS2 Layers | \n02 | \n
Details of optimized design parameters and results of the proposed SPR biosensors [86].
Ref. | \nConfiguration of the sensors | \nSensitivity (deg/RIU) | \n
---|---|---|
[83] | \nPrism/Air/Titanium (Ti)/Ag/Au/InP | \n70.90 | \n
[84] | \nPrism/Rh/Ag/Si | \n229 | \n
[3] | \nPrism/MoS2/h-BN/graphene | \n194.12 | \n
[85] | \nPrism/Ag/Au/WS2/graphene | \n182.5 | \n
[86] | \nPrism/Ag/PtSe2/WS2\n | \n194 | \n
[86] | \nPrism/Au/PtSe2/WS2\n | \n187 | \n
[87] | \nPrism/Au/Black Phosphorous (BP) | \n180 | \n
[2] | \nPrism/Au/Graphene/MoS2\n | \n89.29 | \n
[1] | \nPrism/Au/MoS2\n | \n75.34 | \n
[88] | \nPrism/ZnO/Ag/Au/graphene | \n66 | \n
[89] | \nPrism/Au/MoS2/WS2/WSe2\n | \n142 | \n
[90] | \nPrism/Au/MoS2/Au film/graphene | \n182 | \n
[55] | \nPrism/MoS2/aluminum (Al) film/MoS2/graphene | \n190.83 | \n
[91] | \nPrism/Ag/PtSe2\n | \n162 | \n
[91] | \nPrism/Au/PtSe2\n | \n165 | \n
Sensitivity comparison of Kretschmann configuration based SPR biosensors comprising hybrid structures.
This chapter provides a detailed description of the surface plasmon resonance phenomenon with the recent trends that are being applied in the advancement of SPR based sensors where the application of hybrid structures as well as bimetallic configurations are found to be potential techniques to enhance the sensor performances. Besides, it demonstrates different 2D materials applied for sensing capability enhancement of the hybrid SPR biosensors. Also, two 5 layer prism based hybrid heterostructures (Prism-Au-PtSe2-WS2 and Prism-Ag-PtSe2-WS2) have been comprehensively discussed here to show the effectiveness of hybrid technology.
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