The angle’s value formed by the two substrates of five samples.
\r\n\tBiosensors are devices used to measure or detect the presence or concentration of a biological analyte in a quantitative or semiquantitative manner, such as a biomolecule, a biological structure or a microorganism. Biosensors consist of three parts: a component that recognizes the analyte (a biological recognition element) and produces a signal, a signal transducer, and a reader device.
\r\n\r\n\tThe aim of this book is to highlight the current and novel strategies for biosensing. This book project includes different kinds of receptors and/or transducers strategies for biosensing, such as Schiff base metal complexes, biological molecules (DNA, proteins, enzymes, antibodies, multi-organisms, etc.), graphene oxide- nanomaterials, metal-organic frameworks, and electrospun fibers. Chapter's proposals can focus their work on the mode of physicochemical transduction (such as optical, thermal, piezoelectric and electrochemical) or the biorecognition element. Applications of these biosensors can include biomedical, environmental, bioremediation, and industrial amongst others.
\r\n\r\n\tChapters can include original research or recompilation of existing data, discussing the state of the art of biosensing technologies.
",isbn:"978-1-83962-438-4",printIsbn:"978-1-83962-431-5",pdfIsbn:"978-1-83962-439-1",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"028f3e5dbf9c32590183ac4b4f0a2825",bookSignature:"Dr. Luis Jesús Jesús Villarreal-Gómez and Dr. Ana Leticia Iglesias",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/9883.jpg",keywords:"Metal-Organic-Frameworks, Electrochemical-MOF Biosensor, DNA Biosensors, Optical Sensors, Schiff Base, Electrochemical Sensors, Nanoparticles, Gold, Electrospinning Nanofibers, Polymeric Fibers, Conductance, Lab on a Chip",numberOfDownloads:929,numberOfWosCitations:0,numberOfCrossrefCitations:3,numberOfDimensionsCitations:5,numberOfTotalCitations:8,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"June 9th 2020",dateEndSecondStepPublish:"September 11th 2020",dateEndThirdStepPublish:"November 10th 2020",dateEndFourthStepPublish:"January 29th 2021",dateEndFifthStepPublish:"March 30th 2021",remainingDaysToSecondStep:"7 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Obtained his Ph.D. in Chemical Science and Engineering from Universidad Autónoma de Baja California with interests in electrospinning technique, tissue engineering, filters, drug delivery systems, biosensors, microelectronics, solar cells, electrodes, and batteries. Dr. Villarreal-Gómez is a member of the National System of Researchers in Mexico.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"126286",title:"Dr.",name:"Luis Jesús",middleName:"Jesús",surname:"Villarreal-Gómez",slug:"luis-jesus-villarreal-gomez",fullName:"Luis Jesús Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",biography:"Dr. Luis Jesús Villarreal Gómez is a research professor from the Facultad de Ciencias de la Ingeniería y Tecnología (Faculty of Engineering Sciences and Technology), Universidad Autónoma de Baja California (University Autonomous of Baja California), Tijuana, Baja California, México. His research interest includes the use of electrospun nanofiber in several applications such as biosensors, drug delivery systems, biotechnology, and tissue engineering. Moreover, Dr. Villarreal is a member of the National System of Researchers in Mexico.",institutionString:"Facultad de Ciencias de la Ingeniería y Tecnología",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"0",institution:null}],coeditorOne:{id:"161297",title:"Dr.",name:"Ana Leticia",middleName:null,surname:"Iglesias",slug:"ana-leticia-iglesias",fullName:"Ana Leticia Iglesias",profilePictureURL:"https://mts.intechopen.com/storage/users/161297/images/system/161297.jpg",biography:"Dr. Ana Leticia Iglesias is a research professor from the Facultad de Ciencias de la Ingeniería y Tecnología (Faculty of Engineering Sciences and Technology), Universidad Autónoma de Baja California (University Autonomous of Baja California), Tijuana, Baja California, México. Her research interest includes transition metal coordination and organometallic chemistry for applications therapeutic, catalytic and biosensing applications.",institutionString:"Facultad de Ciencias de la Ingeniería y Tecnología",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"11",title:"Engineering",slug:"engineering"}],chapters:[{id:"74457",title:"Hybrid Heterostructures for SPR Biosensor",slug:"hybrid-heterostructures-for-spr-biosensor",totalDownloads:70,totalCrossrefCites:0,authors:[null]},{id:"73628",title:"Novel Biosensing Strategies for the in Vivo Detection of microRNA",slug:"novel-biosensing-strategies-for-the-in-vivo-detection-of-microrna",totalDownloads:97,totalCrossrefCites:0,authors:[null]},{id:"74301",title:"Theranostic Microneedle Devices: Innovative Biosensing and Transdermal Drugs Administration",slug:"theranostic-microneedle-devices-innovative-biosensing-and-transdermal-drugs-administration",totalDownloads:68,totalCrossrefCites:1,authors:[null]},{id:"76048",title:"Microfluidic Adsorption-Based Biosensors: Mathematical Models of Time Response and Noise, Considering Mass Transfer and Surface Heterogeneity",slug:"microfluidic-adsorption-based-biosensors-mathematical-models-of-time-response-and-noise-considering-",totalDownloads:1,totalCrossrefCites:0,authors:[null]},{id:"74225",title:"Advanced Biosensing towards Real-Time Imaging of Protein Secretion from Single Cells",slug:"advanced-biosensing-towards-real-time-imaging-of-protein-secretion-from-single-cells",totalDownloads:86,totalCrossrefCites:0,authors:[null]},{id:"73990",title:"Advanced Materials and Assembly Strategies for Wearable Biosensors: A Review",slug:"advanced-materials-and-assembly-strategies-for-wearable-biosensors-a-review",totalDownloads:140,totalCrossrefCites:1,authors:[null]},{id:"73766",title:"Nanomaterial-Enhanced Receptor Technology for Silicon On-Chip Biosensing Application",slug:"nanomaterial-enhanced-receptor-technology-for-silicon-on-chip-biosensing-application",totalDownloads:186,totalCrossrefCites:0,authors:[null]},{id:"73441",title:"Nucleic Acids for Electrochemical Biosensor Technology",slug:"nucleic-acids-for-electrochemical-biosensor-technology",totalDownloads:132,totalCrossrefCites:0,authors:[null]},{id:"73399",title:"Ultra-Precise MEMS Based Bio-Sensors",slug:"ultra-precise-mems-based-bio-sensors",totalDownloads:83,totalCrossrefCites:1,authors:[null]},{id:"73454",title:"Control Strategy for Underactuated Multi-Fingered Robot Hand Movement Using Electromyography Signal with Wearable Myo Armband",slug:"control-strategy-for-underactuated-multi-fingered-robot-hand-movement-using-electromyography-signal-",totalDownloads:72,totalCrossrefCites:0,authors:[null]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"297737",firstName:"Mateo",lastName:"Pulko",middleName:null,title:"Mr.",imageUrl:"https://mts.intechopen.com/storage/users/297737/images/8492_n.png",email:"mateo.p@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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This is an essential physical property of liquid crystals and is a key element in how they are implemented in the display [1, 2], photonic devices [3], communications signal processing [4], and beam steering [5].
\nWhen light propagates through anisotropic media such as liquid crystals, it will be divided into two rays which travel through the material at different velocities, and therefore have different refractive indices, the ordinary index (no), and extraordinary index (ne), and the difference is called as birefringence or double refraction (∆n = ne − no). Depending on the values of ne and no, birefringence can be positive or negative [6, 7].
\nTemperature plays a fundamental role in affecting the refractive indices of LCs. As the temperature increases, ordinary (no) and extraordinary (ne) refractive indices of LCs behave differently from each other [8, 9].
\nSeveral techniques have been studied to describe the temperature effect on LC refractive indices. Horn measured the refractive indices as a function of temperature throughout the nematic phase of 4-n pentyl-4-cyanobiphenyl (5CB) and the smectic A and nematic phases of 4-n-octyl-4-cyanobiphenyl (8CB) using the method of Pellet and Chatelain at the wavelength (589 and 632.8 nm) [10]. Wu developed a single-band model and a three-band model for understanding the refractive index dispersions of liquid crystals. The three- and two-coefficient Cauchy equations based on the three-band model for the wavelength- and temperature-dependent refractive indices of anisotropic liquid crystals were derived by Jun Li and Wu. For low birefringence liquid crystal mixtures, the two-coefficient Cauchy model works equally well as the three-coefficient model in the off-resonance spectral region [11]. A four-parameter model for describing the temperature effect on the refractive indices of LCs based on the Vuks equation was derived by Jun Li et al. Four different LC materials with different birefringence were used to validate these parameters. An excellent agreement between theory and experiment was obtained [12]. Jun Li et al. measured the refractive indices of E7 LC mixture at six visible and two infrared (λ = 1.55 and 10.6 μm) wavelengths at different temperatures using Abbe and wedged cell refractometer methods [13]. In the present chapter, the temperature effect on nonlinear refractive indices of several types of liquid crystal (LC) compounds has been studied. In the beginning, the mathematical models are discussed. Second, using the refractive indices data, other parameters can be determined, such as birefringence (Δn), average refractive indices, and the temperature gradient of refractive indices (dne/dT, dno/dT). Finally, the bistability of nonlinear refractive indices with temperature of LC is also reported. The measurements performed at 1550 nm wavelength using wedged cell refractometer method. The variation in refractive indices was fitted theoretically using the modified four-parameter model, which is based on the Vuks equation.
\nThe classical Clausius-Mossotti equation correlates the dielectric constant (
The Lorentz-Lorenz equation correlates the refraction index of anisotropic medium with molecular polarizability at optical frequencies and obtained the following equation [14, 15]
\nFor an isotropic LC, the ordinary and extraordinary refractive indices are determined by corresponding ordinary and extraordinary molecular polarizability αo and αe. Vuks modified the Lorentz-Lorenz equation by assuming that the internal field in a liquid crystal is equal in all directions, and therefore produce a semi-empirical equation correlating macroscopic refractive index with microscopic molecular polarizability [11, 15].
\nne and no are the extraordinary and ordinary refractive indices, <n2> is defined as <n2> = (ne2 + 2no2)/3
\nThe temperature-dependent LC refractive indices based on Vuks model can be expressed by the average refractive index <n> and birefringence ∆n as [11, 16],
\nOn the other hand, the LC birefringence is linearly proportional to the order parameter S. Through Haller’s semi-empirical equation, the order parameter can be approximated as
\nwhere T is the operating temperature, Tc is the clearing temperature of LC material, and
where (∆n)o is the LC birefringence in the crystalline state at absolute zero (T = 0 K). From Eqs. (6) and (7), the order parameter can be written as:
\nThe average refractive index decreases linearly with increasing temperature as [16]:
\nSubstituting Eqs. (7) and (9) back to Eqs. (4) and (5), the modified four-parameter model for describing the temperature effect on the LC refractive indices is obtained [17, 18, 19]:
\nEqs. (10) and (11) contain four unknown parameters A, B, (∆n)o, and
Five samples have been investigated in this work; two of them are E7 and MLC 6241-000 samples, the clearing temperatures are 333 and 373.7 K, respectively. The other three have been obtained by mixing the previous two liquid crystals in different proportions (75% E7 with 25% MLC 6241-000, 50% E7 with 50% MLC 6241-000, and 25% E7 with 75% MLC 6241-000). The clearing temperature (Tc) of three mixture samples is measured using hot-stage optical microscope, and they are found to be 348, 353, and 368 K, respectively.
\nThe effect of temperature variation on nonlinear refractive indices of these liquid crystal compounds has been reported using wedged cell refractometer method. The cell is made up of two glass substrates separated by two spacers that have different thickness as shown in Figure 1. The wedged angle was measured using an optical method [9], and the angle value of five samples is shown in Table 1.
\nThe used liquid crystal wedged cell.
Sample | \nAngle | \n
---|---|
E7 | \n0.036215581 | \n
25% E7 with 75% MLC 6241-000 | \n0.036635508 | \n
50% E7 with 50% MLC 6241-000 | \n0.049305551 | \n
75% E7 with 25% MLC 6241-000 | \n0.032724923 | \n
MLC 6241-000 | \n0.052359877 | \n
The angle’s value formed by the two substrates of five samples.
The experimental setup used during this work is shown in Figure 2, and a more detailed description of this setup and the measurement method can be found in [9]. The laser beam is divided into two rays, when it passes through LC sample because of birefringence of LC, the values of two refractive indices (no and ne) of the liquid crystal can be calculated by these equations
\nThe experimental setup for the measurement of the refractive indices of LC.
where θ is the angle of the wedged formed by two plates, δo and δe are the angles formed by two beams Ro and Re.
\nSo that
\nThese measurements have been repeated many times by changing the temperature of the LC sample to measure the refractive indices at different temperatures. Also, this experiment has been repeated by decreasing the temperature of LC sample to study the bistability of liquid crystal due to temperature.
\nThe refractive indices of the five liquid crystals were measured using wedged cell refractometer method at 1550 nm wavelength [9]. Figure 3 shows the temperature dependence of the refractive indices no and ne of E7 and MLC 6241-000. Red squares and blue circles are experimental data for refractive indices ne and no of E7 and MLC 6241-000, respectively. The solid curves are fittings using the four-parameter model Eqs. (10) and (11). The fitting parameters are listed in Table 2.
\nTemperature dependent refractive indices of E7 and MLC 6241-000 at λ = 1550 nm. Red squares and blue circles represent the refractive indices ne and no of E7 and MLC 6241-000, respectively. The solid curves are the fitting using Eqs. (
LC materials | \n<n> | \nΔn | \n||
---|---|---|---|---|
A | \nB (K−1) | \n(Δn)o | \n||
E7 | \n1.750172 | \n5.88 × 10−4 | \n0.301812 | \n0.259542 | \n
25% E7 with 75% MLC 6241-000 | \n1.61647 | \n4.17 × 10−4 | \n0.153497 | \n0.246991 | \n
50% E7 with 50% MLC 6241-000 | \n1.622715 | \n4.18 × 10−4 | \n0.189193 | \n0.22493 | \n
75% E7 with 25% MLC 6241-000 | \n1.650715 | \n4.49 × 10−4 | \n0.182306 | \n0.204806 | \n
MLC 6241-000 | \n1.6008 | \n4.21 × 10−4 | \n0.147301 | \n0.248339 | \n
Fitting parameters for the average refractive index <n> and birefringence Δn of five LCs at 1550 nm.
The temperature dependence of refractive indices of three LC mixtures is shown in Figure 4. Blue squares, green triangles, and red circles represent the refractive indices of (50% E7 with 50% MLC 6241-000, 25% E7 with 75% MLC 6241-000, and 75% E7 with 25% MLC 6241-000), respectively. The solid curves are fittings using Eqs. (10) and (11).
\nTemperature-dependent refractive indices of three mixture samples at λ = 1550 nm. Red circles, blue squares, and green triangles represent the refractive indices ne and no of (75% E7 with 25% MLC 6241-000, 50% E7 with 50% MLC 6241-000, and 25% E7 with 75% MLC 6241-000), respectively. The solid curves are the fitting using Eqs. (
Brugioni et al. also studied the temperature effect on nonlinear refractive indices of E7 liquid crystal at mid-infrared region (10.6 μm) using a wedge cell refractometer method as shown in Figure 5 [13, 25].
\nTemperature-dependent refractive indices of E7 at 10.6 μm. The filled circles are the refractive indices measured by the wedged LCcell refractometer method. The filled triangles are the average refractive index calculated by the experimental data. The open circles represent no and ne extrapolated from the experimental data measured at visible spectrum using the extended Cauchy model. The open triangles are the average refractive index calculated by the extrapolated ne and no, respectively. The solid curves are the fitting using Eqs. (
Figure 6 shows the wavelength-dependent refractive indices of E7 at T = 25°C. Squares and circles represent the ne and no of E7 in the visible region, while the downward and upward triangles stand for the measured data at λ = 1.55 and 10.6 μm, respectively [25]. Figure 6 also indicates that the refractive indices will saturate in the far-infrared region, the agreement between experiment and theory is very good.
\nWavelength-dependent refractive indices of E7 at T = 25°C. The open squares and circles are the ne and no of E7 measured at the visible spectrum. The solid curves are the fittings to the experimental data measured at the visible spectrum using the extended Cauchy model. The downward and upward triangles are ne and no of E7 measured at T = 25°C and λ = 1.55 and 10.6 μm, respectively.
The temperature-dependent birefringence of E7 and MLC 6241-000 at 1550 nm is shown in Figure 7. Blue squares and red circles represent the birefringence of E7 and MLC 6241-000, respectively, while solid lines are fitting results using Eq. (7). The fitting parameters for these samples are also listed in Table 2. Through fittings, we obtain parameters (Δn)o and
Temperature-dependent birefringence of E7 and MLC 6241-000 at λ = 1550 nm, blue squares and red circles represent the birefringence of E7 and MLC 6241-000, respectively. Solid lines are fitting results using Eq. (
Figure 8 shows the temperature-dependent birefringence of three mixing samples. Blue triangles, green circles, and red squares, represent the birefringence LCs of (50% E7 with 50% MLC 6241-000, 25% E7 with 75% MLC 6241-000, and 75% E7 with 25% MLC 6241-000), respectively. The solid lines are fitting curves using Eq. (7). The LC mixture (50% E7 with 50% MLC 6241-000) has higher birefringence.
\nTemperature-dependent birefringence of three mixture samples at λ = 1550 nm. Red squares, blue triangles, and green circles represent the birefringence LCs (75% E7 with 25% MLC 6241-000, 50% E7 with 50% MLC 6241-000, and 25% E7 with 75% MLC 6241-000), respectively. Solid lines are fitting results using Eq. (
The temperature-dependent average refractive index of five liquid crystal samples is shown in Figure 9. Green triangles, red squares, black circles, brown stars, and blue monoclinic represent the average refractive index LCs of E7, 75% E7 with 25% MLC 6241-000, 50% E7 with 50% MLC 6241-000, and 25% E7 with 75% MLC 6241-000, and MLC 6241-000), respectively, while solid lines are fitting results using the four-parameter model (Eq. (9)). The fitting parameters A and B for these five samples are listed in Table 2. Average refractive index decreases linearly as the temperature increases.
\nTemperature-dependent average refractive index > n < of five LCs at 1550 nm. Green triangles, red squares, black circles, brown stars, and blue monoclinic represent the average refractive index LCs of E7, 75% E7 with 25% MLC 6241-000, 50% E7 with 50% MLC 6241-000, and 25% E7 with 75% MLC 6241-000, and MLC 6241-000), respectively. Solid lines are fitting results using Eq. (
For practical applications, it is necessary to operate the LC device at room temperature. So, LC should be designed with crossover temperature (To) lower than 300 K to obtain a positive dno/dT at room temperature. The temperature dependence of −dne/dt and dno/dt for liquid crystal can be found using Eqs. (12) and (13). These are shown in Figure 10a–e. The calculated values of crossover temperatures for LCs (E7, MLC 6241-000, 25% E7 with 75% MLC 6241-000, 50% E7 with 50% MLC 6241-000, and 75% E7 with 25% MLC 6241-000) are ~311.1, 360.54, 354.61, 335.8, and 333.56 K, respectively. Negative temperature gradient (−dne/dt) positive for all LC samples, that means the extraordinary refractive index decreases with increase in temperature, whereas the positive temperature gradient (dno/dt) changes its sign from negative to positive value. The dno/dt is negative when the temperature is below To, whereas it becomes positive when the temperature is above To. To achieve a high dno/dT, high birefringence and low clearing temperature are two important factors for this.
\nTemperature gradient for ne and no of LC samples (a) E7, (b) MLC 6241-000, (c) 25% E7 with 75% MLC 6241-000, (d) 50% E7 with 50% MLC 6241-000, and (e) 75% E7 with 25% MLC 6241-000 at 1550 nm. Blue and red solid lines represent the calculated dno/dT and −dne/dT, respectively. The crossover temperature for these samples are around 311.2, 360.6, 354.7, 335.9, and 333.6 K for E7, MLC 6241-000, 25% E7 with 75% MLC 6241-000, 50% E7 with 50% MLC 6241-000, and 75% E7 with 25% MLC 6241-000, respectively.
The refractive indices of the five liquid crystal samples were measured at λ = 1550 nm in the temperature range from 290 to 330 K. Figure 11a–e shows the temperature-dependent extraordinary refractive index of E7, MLC 6241-000, and three mixture samples (25% E7 with 75% MLC 6241-000, 75% E7 with 25% MLC 6241-000, and 50% E7 with 50% MLC 6241-000), respectively. From these figures, the bistability of LCs due to temperature for extraordinary refractive index is clearly observed. In the case of mixture (50% E7 with 50% MLC 6241-000), the two curves of increasing and decreasing liquid crystal’s temperature intersect at 310 K to be equal until they reach to 291 K as shown in Figure 11e.
\nTemperature dependent extraordinary refractive index of (a) E7, (b) MLC 6241-000, (c) 25% E7 with 75% MLC 6241-000, (d) 75% E7 with 25% MLC 6241-000, and (e) 50% E7 with 50% MLC 6241-000, at 1550 nm. Squares and circles represent extraordinary refractive index for increasing (red line) and decreasing (blue line) temperature, respectively.
Figure 12a–e shows the temperature dependent ordinary refractive index of E7, MLC 6241-000, and three mixture samples (25% E7 with 75% MLC 6241-000, 75% E7 with 25% MLC 6241-000, and 50% E7 with 50% MLC 6241-000), respectively. Also, from these figures the bistability of LCs due to temperature is clearly observed for ordinary refractive index. As shown in Figure 12e, for mixture (50% E7 with 50% MLC 6241-000), the values of ordinary refractive index in the case of decreasing temperature become larger than its values in the case of increasing temperature case after the intersect point at 310 K.
\nTemperature-dependent ordinary refractive index of (a) E7, (b) MLC 6241-000, (c) 25% E7 with 75% MLC 6241-000, (d) 75% E7 with 25% MLC 6241-000 and (e) 50% E7 with 50% MLC 6241-000 at 1550 nm. Squares and circles represent ordinary refractive index for increasing (red line) and decreasing (blue line) temperature respectively.
Figure 13a–e shows the birefringence bistability of the five liquid crystal samples. The bistability is represented by the area between the temperature refractive indices and birefringence (increasing and decreasing). The measured areas are listed in Table 3.
\nTemperature-dependent birefringence (Δn) of (a) E7, (b) MLC 6241-000, (c) 25% E7 with 75% MLC 6241-000, (d) 75% E7 with 25% MLC 6241-000, and (e) 50% E7 with 50% MLC 6241-000 at 1550 nm. Squares and circles represent birefringence refractive index for increasing and decreasing temperature.
Sample | \nArea | \n||
---|---|---|---|
Extraordinary R.I | \nOrdinary R.I | \nBirefringence | \n|
E7 | \n0.16882 | \n0.01577 | \n0.15304 | \n
25% E7 with 75% MLC 6241-000 | \n0.06328 | \n0.05379 | \n0.00599 | \n
50% E7 with 50% MLC 6241-000 | \n0.03333 | \n0.00693 | \n0.0264 | \n
75% E7 with 25% MLC 6241-000 | \n0.05007 | \n0.02704 | \n0.02303 | \n
MLC 6241-000 | \n0.05643 | \n0.0337 | \n0.02272 | \n
The area between increasing and decreasing temperature curves of liquid crystal samples.
From these measurements, the extraordinary refractive index has larger bistability than the ordinary refractive index.
\nThe ordinary and extraordinary refractive indices of five types of liquid crystals were measured at near-infrared region (1550 nm) and in temperature range from 290 to 330 K, using a wedged cell refractometer method. The variation in refractive indices, and average refractive index were fitted theoretically using a modified four-parameter model. Excellent agreement between the experimental data and fitted values by using four-parameter model is obtained. In addition, the birefringence of liquid crystal as a function of the temperature is calculated; high birefringence is obtained when the mixing is 50% E7 with 50% MLC 6241-000. The temperature gradients of liquid crystal refractive indices are presented; high birefringence and low clearing temperature are two important factors to achieve large dno/dT. The bistability of LCs due to temperature is also studied. The liquid crystal bistability based on the temperature is clearly observed for all samples. Also, the extraordinary refractive index has larger bistability than the ordinary refractive index.
\nIn 2017, total world energy consumption was approximately 13,511 million-ton equivalent of petroleum (MTEP). With the fast industrial growth of developing nations over the last decade, the industrial sector consumed approximately 2852 MTEP. It is estimated that in 2035, the world consumption of energy will increase by more than 30% [1].
\nApproximately 33% of the total energy consumed in the industry is rejected as residual heat, presenting as a major problem the fact that the most of this rejected energy is identified as low-quality residual heat [2]. This type of waste heat has a small working potential, and the temperatures are below 230°C, which implies a low energy density [3]. Concurrently with the concern for global warming and the issues of diminishing oil consumption, there is a strong incentive for the development of more efficient and clean technologies for heat recovery and energy conversion systems using waste heat.
\nIn order to minimize the waste of energy with residual heat, energy recovery systems have been more explored. These systems can become an important object of research and/or application if, at least, part of the thermal energy expelled by industrial equipment to the atmosphere can be reused [4]. In this context, experimental analysis of the direct conversion of thermal energy into electric energy, using thermoelectric generators, was carried out.
\nThe Seebeck effect is related to the appearance of a difference of electric potential between two different materials, placed in contact, however, at different temperatures [5]. Basically, this is the same effect that occurs in thermocouples, where two different materials are connected and submitted to a temperature difference, causing a potential difference to be generated and translated into a temperature reading. In addition to this application, the thermoelectric effect can be explored in the generation of energy for wristwatches and aerospace applications or, even, in the generation of electric energy from the heated gases released in the internal combustion of engines, boiler gases, and/or the geothermal sources. The thermoelectric generators (TEG) have as main characteristics the reduced dimensions, easy adaptation in complex geometry, and very low maintenance [6]. Its conversion efficiency is about 5%; however, studies conducted at the NASA laboratory have reached 20% efficiency for high temperatures [2].
\nThe studied thermoelectric generator consists of an arrangement of small blocks of bismuth telluride (Bi2Te3) doped with
Schematic diagram of a thermoelectric generator.
The top of the
The experimental apparatus and procedure developed for this research are described in details in this section.
\nThe experimental bench developed to obtain the thermoelectric generator characteristic curve, shown in Figure 2(a), consisted of a laptop (
Experimental apparatus. (a) Experimental bench. (b) Test section and data acquisition system.
The thermoelectric generator used in this experiment is made of bismuth telluride (Bi2Te3) and has dimensions of 56 mm by 56 mm with a height of 3.3 mm, totaling a surface area of 0.003136 m2. An illustration of the generator and, also, its main specifications can be seen in Figure 3 and Table 1, respectively.
\nIllustration of the thermoelectric generator TEG1-12611-6.0.
Parameters | \nValue | \nUnit | \n
---|---|---|
Hot-side temperature | \n300 | \n[°C] | \n
Cold-side temperature | \n30 | \n[°C] | \n
Open-circuit voltage | \n8.4 | \n[V] | \n
Matched load resistance | \n1.2 | \n[ohms] | \n
Matched load output voltage | \n4.2 | \n[A] | \n
Matched load output current | \n3.4 | \n[A] | \n
Matched load output power | \n14.6 | \n[W] | \n
Heat flow across the module | \nApproximately 365 | \n[W] | \n
Heat flow density | \n11.6 | \n[W/cm2] | \n
AC resistance under 27°C at 1000 Hz | \n0.5 to 0.7 | \n[ohms] | \n
Main specifications of the thermoelectric generator TEG1-12611-6.0.
To measure the temperatures of the thermoelectric generator, K-type thermocouples with mineral insulation
Schematic diagram of the data acquisition in the experimental apparatus.
For the performance of the experimental tests, the ambient temperature was maintained at 16°C ± 1°C by thermal conditioning system
As can be seen in Figure 4, the thermoelectric generator was positioned between the heat exchanger and the heating system. The heat exchanger consists of an aluminum block with machined channels inside. Water is fed by an ultrathermostatized bath with a flow rate of 1 L/min, passes through the channels in order to exchange heat with the upper surface of the TEG, and returns to the ultrathermostatized bath. The heat exchanger, the water inlet, and the water outlet in the exchanger can be observed in items (1), (2), and (3) in Figure 2(b), respectively.
\nThe heating system consists of an aluminum block located inside the base of the experimental apparatus, item (4) in Figure 2(b). The block contains two cartridge resistors associated in parallel, which are responsible for the heating of the block and, consequent, the dissipation of the heat to the TEG. Each cartridge resistor has power of 200 W. In order to increase the heat exchange between the surfaces, the heating system was insulated on its sides using aeronautic thermal insulation. In addition, an aluminum bracket and two threaded rods were used to exert constant pressure in the whole system, increasing the contacts between heat exchanger - TEG and TEG - heating system. These contacts will ensure the required temperature gradient in order to get the Seebeck voltage.
\nThe tests were performed by varying the potential difference (pd) applied to the heating system resistances, which simulate the residual heat, in order to obtain thermal loads from 40 to 320 W, with a variation of 40 W. Each thermal load was maintained for 20 minutes, where the
The temperature data of the hot and cold surfaces of the TEG were recorded every 10 seconds using the two thermocouples and the data acquisition system, which are saved by the software
For this, an
The analysis of experimental uncertainties aims to quantify the validity of the data and their accuracy and, therefore, to allow the estimation of the random error present in the experimental results. The error is defined as the difference between the actual value and the indicated value [8].
\nThe experimental uncertainties present in this research were associated to direct and indirect measurements, shown in Tables 2 and 3, respectively, and they were calculated according to the error propagation method described in [9]. The direct uncertainties are those relative to the parameters obtained using a measuring tool, being the current, input voltage and temperature, the voltage generated, and other temperatures. The uncertainty of indirect measurement is calculated in the function of other parameters, and a specific tool did not measure it. In the case of this experiment, the only indirect uncertainty is related to the power supplied by the power supply unit to the cartridge resistors, in the heating system. The power quantity was obtained by multiplying the voltage and current supplied by the source.
\nParameters | \nMeasuring instrument | \nUnit | \nUncertainty | \n
---|---|---|---|
Input current | \nPower source | \n[A] | \n± 0.01 | \n
Input temperature | \nUltrathermostatized bath | \n[°C] | \n± 1.00 | \n
Other temperatures | \nK-type thermocouple | \n[°C] | \n± 1.27 | \n
Input voltage | \nPower source | \n[V] | \n± 0.01 | \n
Generated voltage | \n[V] | \n± 0.01 | \n
Uncertainties of direct measurements.
Power of the power supply unit [W] | \nUncertainty [W] | \n
---|---|
40 | \n± 0.38 | \n
80 | \n± 0.53 | \n
120 | \n± 0.64 | \n
160 | \n± 0.72 | \n
200 | \n± 0.83 | \n
240 | \n± 1.01 | \n
280 | \n± 1.29 | \n
320 | \n± 1.72 | \n
Uncertainties of indirect measurements.
First of all, the water flow through the heat exchanger, the power dissipated by the electric resistances, and the constant ambient temperature are fixed. After obtaining the
Output voltage
It may be noted that the output current and voltage increase according to the temperature difference between the sides of the thermoelectric generator. It is evident from the analysis of Figure 5 that there is high linearity obtained in the results. It may be further noted that curves have similar slopes; this means that the internal resistance of the thermoelectric generator changes minimally when the operating temperature is varied.
\nIn Figure 6, for each temperature difference value, the thermoelectric generator has different internal resistance values. It is possible to note that the resistance values increase in a quadratic form with the rise of the temperature difference.
\nInternal resistance of the thermoelectric generator.
A curve adjustment with coefficient of determination (
\n
Therefore, the characteristic curve of the thermoelectric generator studied can be expressed by
\n\n
Figure 7 shows the open-circuit voltage (
Open-circuit voltage and closed circuit voltage
The curve fit for the open-circuit voltage (
\n
\n
Figure 8 shows the behavior of the output power (
Output power
As expected, the characteristic curves obtained follow a highly quadratic behavior, indicated by the coefficient of determination R2 close to 1. The maximum power generated occurs when the resistance of the external load is equal to the resistance of the internal load. At this point, the power of 7068 mW is generated with a voltage of 2340 mV for the temperature difference of 230°C.
\nFigure 9 indicates an alternative way to illustrate the output power data: output power (
Output power
Another important point to analyze is the comparison of the amount of power generated by different types of generators. For this, it is of extreme relevance to consider the size of the generators and the generated power density and not just the amount of generated power [W]. As a result, it is important to evaluate how much power is generated per square meter of the generator [W/m2]. Thus, Table 4 shows the power generated by the thermoelectric generator area as a function of the temperature gradient.
\nTemperature difference [°C] | \nGenerated power per area [W/m2] | \n
---|---|
30 | \n25.65 | \n
60 | \n114.14 | \n
90 | \n262.75 | \n
110 | \n567.12 | \n
140 | \n888.71 | \n
170 | \n1345.38 | \n
200 | \n1723.54 | \n
230 | \n2253.93 | \n
Generated power in relation to temperature difference per area.
As shown in Table 4, it can be seen that in a condition such as that found in processes with residual heat release, with a temperature gradient in the range of 60°C, the thermoelectric generator is capable of generating 114.14 W/m2. This value is almost the produced power by a photovoltaic solar panel of monocrystalline cells (
Figure 10 shows the behavior of the output power (
Output power
Furthermore, the output power is limited only by the operating temperature of the thermoelectric generator, which is 270°C. Eq. (5) correlates the values of temperature difference for the electric power with a coefficient of determination of 0.996, for temperature differences greater than 7°C.
\n\n
In this chapter, experimental analysis of the direct conversion of thermal energy into electric energy was carried out. An experimental analysis was performed to obtain the operating characteristics of a thermoelectric generator of bismuth telluride (Bi2Te3). For this, it was necessary to develop an experimental apparatus to provide the necessary operating conditions. Therefore, it was possible to obtain the operating curves of the thermoelectric generator for a temperature difference between the surfaces of the thermoelectric generator of 30 and 230°C. It is noted that the highest power values delivered by the thermoelectric generator were for the greater temperature differences. Normalizing the power generated by the photovoltaic solar panel and the thermoelectric generator, in conditions close to the real ones of use, both have values of generated power, around 152.60 and 114.14W/m2, respectively. Also, the thermoelectric generator can reach values of 2253.93 W/m2 for a temperature gradient of 230°C. In conclusion, the application of thermoelectric generators in the recovery of residual heat is a great instrument to be explored. This kind of device is compact, requires very low maintenance, and has a geometry that can be coupled in most of the industrial systems.
\nAcknowledgments are provided to the CAPES, the CNPq, the PROPPG/UTFPR, the DIRPPG/UTFPR, the PPGEM/UTFPR/Ponta Grossa, and the DAMEC/UTFPR/Ponta Grossa.
\n\n electromotive force of the electric generator [mV] electric current [mA] power [mW] resistance of the thermoelectric generator [ohms] coefficient of determination temperature difference [°C] output voltage of the generator [mV] voltage [mV] output internal generator open circuit closed circuit
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I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. I have served as the editor for many books, been a member of the editorial board in science journals, have published many papers and hold many patents.",institutionString:null,institution:{name:"Sheffield Hallam University",country:{name:"United Kingdom"}}},{id:"54525",title:"Prof.",name:"Abdul Latif",middleName:null,surname:"Ahmad",slug:"abdul-latif-ahmad",fullName:"Abdul Latif Ahmad",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"20567",title:"Prof.",name:"Ado",middleName:null,surname:"Jorio",slug:"ado-jorio",fullName:"Ado Jorio",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidade Federal de Minas Gerais",country:{name:"Brazil"}}},{id:"47940",title:"Dr.",name:"Alberto",middleName:null,surname:"Mantovani",slug:"alberto-mantovani",fullName:"Alberto Mantovani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"12392",title:"Mr.",name:"Alex",middleName:null,surname:"Lazinica",slug:"alex-lazinica",fullName:"Alex Lazinica",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/12392/images/7282_n.png",biography:"Alex Lazinica is the founder and CEO of IntechOpen. After obtaining a Master's degree in Mechanical Engineering, he continued his PhD studies in Robotics at the Vienna University of Technology. Here he worked as a robotic researcher with the university's Intelligent Manufacturing Systems Group as well as a guest researcher at various European universities, including the Swiss Federal Institute of Technology Lausanne (EPFL). During this time he published more than 20 scientific papers, gave presentations, served as a reviewer for major robotic journals and conferences and most importantly he co-founded and built the International Journal of Advanced Robotic Systems- world's first Open Access journal in the field of robotics. Starting this journal was a pivotal point in his career, since it was a pathway to founding IntechOpen - Open Access publisher focused on addressing academic researchers needs. Alex is a personification of IntechOpen key values being trusted, open and entrepreneurial. Today his focus is on defining the growth and development strategy for the company.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"19816",title:"Prof.",name:"Alexander",middleName:null,surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/19816/images/1607_n.jpg",biography:"Alexander I. Kokorin: born: 1947, Moscow; DSc., PhD; Principal Research Fellow (Research Professor) of Department of Kinetics and Catalysis, N. Semenov Institute of Chemical Physics, Russian Academy of Sciences, Moscow.\r\nArea of research interests: physical chemistry of complex-organized molecular and nanosized systems, including polymer-metal complexes; the surface of doped oxide semiconductors. He is an expert in structural, absorptive, catalytic and photocatalytic properties, in structural organization and dynamic features of ionic liquids, in magnetic interactions between paramagnetic centers. The author or co-author of 3 books, over 200 articles and reviews in scientific journals and books. He is an actual member of the International EPR/ESR Society, European Society on Quantum Solar Energy Conversion, Moscow House of Scientists, of the Board of Moscow Physical Society.",institutionString:null,institution:{name:"Semenov Institute of Chemical Physics",country:{name:"Russia"}}},{id:"62389",title:"PhD.",name:"Ali Demir",middleName:null,surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62389/images/3413_n.jpg",biography:"Dr. Ali Demir Sezer has a Ph.D. from Pharmaceutical Biotechnology at the Faculty of Pharmacy, University of Marmara (Turkey). He is the member of many Pharmaceutical Associations and acts as a reviewer of scientific journals and European projects under different research areas such as: drug delivery systems, nanotechnology and pharmaceutical biotechnology. Dr. Sezer is the author of many scientific publications in peer-reviewed journals and poster communications. Focus of his research activity is drug delivery, physico-chemical characterization and biological evaluation of biopolymers micro and nanoparticles as modified drug delivery system, and colloidal drug carriers (liposomes, nanoparticles etc.).",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"61051",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"100762",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"St David's Medical Center",country:{name:"United States of America"}}},{id:"107416",title:"Dr.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Texas Cardiac Arrhythmia",country:{name:"United States of America"}}},{id:"64434",title:"Dr.",name:"Angkoon",middleName:null,surname:"Phinyomark",slug:"angkoon-phinyomark",fullName:"Angkoon Phinyomark",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/64434/images/2619_n.jpg",biography:"My name is Angkoon Phinyomark. I received a B.Eng. degree in Computer Engineering with First Class Honors in 2008 from Prince of Songkla University, Songkhla, Thailand, where I received a Ph.D. degree in Electrical Engineering. My research interests are primarily in the area of biomedical signal processing and classification notably EMG (electromyography signal), EOG (electrooculography signal), and EEG (electroencephalography signal), image analysis notably breast cancer analysis and optical coherence tomography, and rehabilitation engineering. I became a student member of IEEE in 2008. During October 2011-March 2012, I had worked at School of Computer Science and Electronic Engineering, University of Essex, Colchester, Essex, United Kingdom. In addition, during a B.Eng. 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