Select parameters.
\r\n\t
",isbn:"978-1-83969-057-0",printIsbn:"978-1-83969-056-3",pdfIsbn:"978-1-83969-058-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"5f388543a066b617d2c52bd4c027c272",bookSignature:"Prof. Christophe Hano and Dr. Jen-Tsung Chen",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10539.jpg",keywords:"Plant Description, Botany, Phylogeny, Genome, Phytochemical Analysis, Extraction, Phytochemical Diversity, Phytochemical Analysis, Extraction, Phytochemical Diversity, Biotechnological Production, Traditional Medicinal Uses",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 8th 2020",dateEndSecondStepPublish:"November 23rd 2020",dateEndThirdStepPublish:"January 22nd 2021",dateEndFourthStepPublish:"April 12th 2021",dateEndFifthStepPublish:"June 11th 2021",remainingDaysToSecondStep:"3 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Assistant Professor at the University of Orleans at Research INRAE Lab LBLGC USC1328 and a member of the Cosm'ACTIFS Research Group (CNRS GDR3711). 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He has written more than 100 scientific papers, reviews and book chapters in internationally renowned journals and edited one book as well as a variety of journal topical issues on plant secondary metabolism, including polyphenols. He is Academic, Assistant Editor and/or Editorial Board Member of several renowned Q1 Journals in Plant Biochemistry and Biotechnology (including Plos ONE, Biomolecules, Plant Cell Tissue and Organ Culture, Frontiers in Plant Science, Cosmetics). He was reviewers for more than 500 papers for ca 35 International Journals, and recognized scientific expert for several national and international Institutions. Currently, he is developing research projects aimed at studying plant secondary metabolism to lead to the development of natural products with interests in pharmacology or cosmetics. 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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:"57168",title:"Performance of Aqueous Ion Solution/Tube-Super Dielectric Material-Based Capacitors as a Function of Discharge Time",doi:"10.5772/intechopen.71003",slug:"performance-of-aqueous-ion-solution-tube-super-dielectric-material-based-capacitors-as-a-function-of",body:'\nHigh-pulsed electrical power is required for lasers, flash photography, spark ignition, spot welders, fusion reactors, kinetic weapon systems, rapid acceleration of electric vehicles, etc. Capacitors, generally electric double layer capacitors (EDLC), also known as supercapacitors, are preferred for pulse power applications, because they provide far higher power electric pulses, per weight/volume, than batteries [1, 2]. Moreover, unlike batteries, capacitors are not damaged by providing pulsed power. This robust feature leads to their employment as power load levelers to extend battery life. For example, in satellites, systems designed to transfer high power demand from batteries to a parallel capacitor system can significantly increase battery and satellite, lifetime.
\nMost research into increasing capacitor energy density is focused on developing graphene, the conductive material with the highest surface area (~2600 m2/g), electrodes for the next generation EDLC [3–7]. The theory suggests that capacitors with graphene electrodes could have an ultimate energy density of ~800 J/cm3, a value far less than the current generation commercial lithium ion battery (~2200 J/cm3). Notably, current commercial supercapacitors have an energy storage rating of <50 J/cm3.
\nRecently, a new type of ‘supercapacitor’ was invented, NP supercapacitors (NPS) with energy density rivaling the best prototype EDLC, but based on an entirely different paradigm [8–14]. Unlike EDLC that gain energy density through the use of high surface area electrodes with low dielectric value, NPS use low surface area electrodes and dielectrics with remarkably high dielectric constants, specifically super dielectric materials (SDM), that is materials with dielectric values greater than 105, although values >1011 are reported. SDM are composed of an ‘active phase’, such as salt dissolved in a liquid, and an ‘inactive’ mechanical phase such as anodized titania, T-SDM [8, 9], high surface area porous refractory oxides, Powder-SDM [10–12], or even simple fabrics, Fabric-SDM [13], that hold the active phase in place. The theoretical basis of SDM [8, 9] is that in an electric field the ions in solution travel to create dipoles, which are far longer (ca. 1 μm) than those found in solid dielectrics (ca. 10−4 μm). It is the ‘field canceling’ effect of dipoles, proportional to length, which leads to increased capacitance, as per the classic model of dielectric behavior [15–17].
\nIt is reasonable to label NPS, a new type of supercapacitor based on the energy storage values achieved, approx. 400 J/cm3 for T-SDM with aqueous NaCl solutions at very slow discharge rates, rivaling, perhaps surpassing, the best graphene-based EDLC prototypes [18–20]. One unresolved issue: NPS performance as a function of frequency. Given the theory of NPS requires micron scale ionic migration in a liquid to form giant dipoles, there should be significant performance degradation (‘roll-off’) with increasing frequency. That is, if not enough time is available in a charge cycle for dipoles to fully form via ion travel, the dielectric value, energy density, etc. will be reduced. Thus, it is important to directly test the performance of NPS as a function of frequency. Given the most likely application, power release over very short times, ca. 0.05 s, special attention should be paid to discharge rate dependence of power and energy.
\nThe one study of NPS performance as a function of discharge time was on F-SDM, a variety not found to have particularly high energy density. Significant roll-off of all parameters with decreasing discharge period (roughly equivalent to increasing frequency) was documented. The roll-offs, all parameters, were well fit by simple power law relations over orders of magnitude of discharge time. In the present study, we employed the same method used in the earlier study to characterize performance as a function of discharge period of a variety of high energy density NPS, those employing anodized titania saturated with various aqueous free ion solutions. Once again, significant roll-off was observed as expected and the power law relation was found. Still, even with the noted degradation, the performance at the time periods of interest (e.g. 0.05 s discharge) was better than any commercial supercapacitor and possibly any EDLC prototype. Notably, comparison with EDLC prototype performance was difficult as fitted data on time response of these capacitors are apparently nonexistent.
\nThe NP supercapacitors were constructed of anodized titania foils filled with various aqueous salt solutions. The remaining metal of the original titania was one electrode and a graphitic material served as the other electrode. The performance of these capacitors was characterized using standard galvanostat constant current protocols. All procedures are described below.
\nAnodization process–Titanium foil anodes (99.99% Sigma Aldrich), approx. 0.05 mm thick, were anodized, as described elsewhere [8, 9, 21–23], in an ethylene glycol solution containing small quantities of ammonium fluoride (0.25% w/w) and water (2.75% w/w), using a titanium cathode (2 cm distant from the anode) at a constant DC voltage of 40 V for 46 min. This process created a layer of cylindrical hollow titania tubes on the parent titanium, average length measured to be 7.7+/−0.4 μm [24], but for purposes of conservative computation of energy density and all other parameters, assumed to be 8 μm in length. The tube diameter was found to be approximately 90 nm, but that figure does not enter the computations. In prior studies employing a nearly identical protocol, but using different anodization time periods, the intent was to create anodized layers/tubes of various lengths in order to test the impact of tube length on dielectric value and energy density. In this study, the intent was to focus only on the impact of the liquid phase composition, thus all the matrix material, that is the anodized titania, was produced using a single protocol and produced nearly identical anodized layers. Typical tubes formed from this process are very regular in structure and densely packed together [8, 9, 23, 24]. They are all oriented with the long axis perpendicular to the surface of the parent foil. No effort was made to crystallize the tubes via a thermal treatment.
\nAssembly of capacitors—All the capacitors employed were a standard parallel plate construction, consisting of an electrode composed of the unanodized section of the original titania foil, the dielectric consisting of the anodized section (2 × 1 cm) filled with an free ion containing aqueous solution, and a positive electrode of Grafoil, a form of compressed graphite. The tubes in the anodized layer were filled with solution simply by placing them in a beaker filled with the solution for 50 min at room temperature. Three different ion precursors were used: sodium nitrate (NaNO3), ammonia chloride (NH4Cl), and potassium hydroxide (KOH). Capacitors were constructed from aqueous solutions of the three salts, specifically three weight percent concentrations of each salt, 10, 20, and 30%, for a total of nine capacitors. A ‘control study’ employing distilled water was run as well.
\nAfter the salt solution saturation, the capacitor had one electrode, the metallic component of the anodized titanium foil, and a compound dielectric in the form of the titania tubes filled with aqueous solution. Placing a Grafoil sheet (2 × 1 cm) on top of the open tube end of the anodized film completed the capacitor. Specifically, a rectangle of Grafoil (compressed natural graphite, 99.99% carbon [25, 26]) 0.3 mm thick was placed on top. The metallic part of the anodized foil was connected to the negative terminal of the galvanostat, and the Grafoil sheet connected to the positive terminal. The final volume used in subsequent calculations was that of the dielectric section, 8 μm × 2 cm × 1 cm. Greater detail is given elsewhere [24].
\nAll parameters, including energy density, power density, capacitance, and dielectric values, were derived from ‘constant current’ galvanostat data (BioLogic Model SP 300 Galvanostat, Bio-Logic Science Instruments SAS, Claix, France). Operated in constant current charge/discharge mode over a selected voltage range (2.3–0.1 V), the data can be employed directly to determine capacitance as a function of voltage from the slope of voltage as a function of time, that is, for constant current:
\nClearly for capacitance which is not a function of voltage, this equation predicts a perfect saw tooth voltage vs. time pattern. In fact, in this and earlier studies, it was found that the capacitance is a function of voltage, leading to ‘irregular wave forms’ [8–13]. As discussed in earlier work, this indicates that the capacitance is voltage dependent, specifically decreasing as voltage increases. For this reason, the capacitance reported herein is for the voltage region between 0.1 and ~0.8 V. In this voltage regime, the voltage vs. time relationship was always found to be nearly linear for all discharge times greater than 0.001 s indicating constant capacitance over this voltage region. In all cases, it was found that capacitance decreases with increasing voltage as a function of discharge time. The shorter the discharge time the more pronounced the departure from constant capacitance (Figure 1).
\nDeviation from voltage independent capacitance. (Top) For relatively long discharge times (>1 s), the capacitance is nearly independent of voltage to nearly 2 V, as illustrated by the dashed line nearly matching data over a broad voltage range. (sample: NH4Cl 30%; charge rate: 10 mA). (Bottom) As the discharge time decreases, the deviation from ideal behavior, capacitance independent of voltage, becomes more pronounced (sample: NH4Cl 30%; charge rate: 100 mA). For all discharge times studied, the capacitance was nearly constant below 0.8 V.
Given the variability of capacitance with voltage, energy cannot be computed directly from ‘capacitance’, but it can be determined directly from the constant current data. Specifically, energy was determined from the integrated area under the total discharge curve (volt seconds) multiplied by the constant current. Power was determined by dividing the directly determined energy, by the time required, during discharge, for the voltage to go from the maximum to the minimum value. Energy and power density were then determined by dividing energy or power by the volume of the dielectric.
\nMethods to determine energy and power density that require the use of data ‘extrapolated’ beyond the voltage range actual measured can lead to severe errors, generally overestimates. For example, impedance spectroscopy measures the dielectric constant over a narrow voltage range, generally 0 ± 15 mV [27, 28], and provides little reliable information about energy storage characteristics. Determining the energy storage/power production of most capacitors requires a collection of data over the full voltage operating range [29–31].
\nGalvanostats operated in the constant current mode do not permit selection of frequency. In order to obtain capacitance as a function of frequency, the current is changed. In essence increasing the current decreases the period required to charge/discharge. Hence, each capacitor was tested over a wide range of current values over the range 5–250 mA. In all cases, the charging current was the same magnitude as the discharge current, but of opposite sign. For each capacitor studied nine different currents in this range were used to determine capacitive behavior over approximately four orders of magnitude of the discharge time. At each selected constant current at least 10 complete cycles were recorded and generally 20. Averaged data from these cycles are reported. As noted, in all cases, the voltage was in the range 2.3–0.1 V. The finding that linear power law data could fit the data collected in this fashion (see Results) demonstrates the efficacy of this method for determination of frequency response. An error analysis of this approach available elsewhere [13] suggests that all data for energy and power density is accurate to within 10% absolute.
\nIn brief, experiments were interpreted to yield information regarding the frequency dependence of these parameters: capacitance and dielectric values below 0.8 V, energy density, and power density over the range of 0.1–2.3 V. For all nine capacitors containing aqueous solutions with dissolved ions, but not the control using distilled water, the data permitted excellent power law fits to all parameters.
\nA capacitor employing distilled water as the electrolyte had such low values of relevant parameters that it was difficult to determine any parameters with precision, given the small capacitor size and the parameter ranges chosen for this study. A reliable power law ‘roll-off’ function was not obtained for any parameter as the absolute values were so small that the signal/noise ratio was large; however, it can be stated with certainty that the highest measured energy density was less than 0.03 J/cm3 clearly demonstrating that anodized titania-based T-SDM containing distilled water are not SDM.
\nIn order to illustrate general trends for all three solutes, the data on all three capacitors created with KOH-based SDM are presented in detail. The trends of energy and power density as well as dielectric and capacitance values determined below 0.8 V are shown on log-log plots, and in each case, it is clear that the data are well represented by simple power law relations over a wide range of discharge times.
\nEnergy and power values are derived directly from data over the entire discharge voltage, thus may be considered as the most reliable. As shown in Figure 2, all the energy density data for KOH are well fit by simple power law relationships over four orders of magnitude of discharge time, that is from 20 to 0.002 s. Moreover, the curve fit is clearly of a quality that permits reasonable extrapolation to the energy density anticipated even for a 1000 s discharge. This value of energy density at this very slow discharge rate is suggested herein as a reasonable comparison point with battery energy densities (Table 1). It is notable that energy density is not a linear function of KOH concentration, but the 30 wt% sample was clearly superior.
\nEnergy density vs. discharge time for KOH-based capacitors. At all three KOH concentrations, the energy density ‘rolls off’ as a very specific function of discharge time. This allows determination of energy density with high precision over a broad discharge time range. Note the curve slope increases, and the energy density at all concentrations increases with increasing solute concentration. Employing the linear fitting equations with DT, in seconds, yields energy in J/cm3.
Solute (wt%) | \nDielectric constant<0.8V | \nEnergy density (J/cm3) | \nPower density (Watt/cm3) | \n||
---|---|---|---|---|---|
\n | 10 s | \n1000 s | \n10 s | \n1000 s | \n0.01 s | \n
KOH (10) | \n1.1 E+8 | \n7.3 E+8 | \n22 | \n208 | \n74 | \n
KOH (20) | \n1.2 E+8 | \n1.0 E+9 | \n21 | \n230 | \n58 | \n
KOH (30) | \n2.1 E+8 | \n1.8 E+9 | \n44 | \n602 | \n85 | \n
NH4Cl (10) | \n2.7 E+8 | \n4.1 E+9 | \n35 | \n556 | \n56 | \n
NH4Cl (20) | \n2.2 E+8 | \n2.9 E+9 | \n30 | \n356 | \n72 | \n
NH4Cl (30) | \n2.1 E+8 | \n1.9 E+9 | \n34 | \n363 | \n98 | \n
NaNO3 (10) | \n1.3 E+7 | \n9.8 E+7 | \n4 | \n23 | \n26 | \n
NaNO3 (20) | \n3.1 E+7 | \n3.0 E+8 | \n12 | \n125 | \n37 | \n
NaNO3 (30) | \n3.0 E+7 | \n2.8 E+8 | \n12 | \n142 | \n36 | \n
Select parameters.
The values at 10 s (discharge time) are in the measured range. The values at 1000 s are extrapolated values based on using the power law fits.
Power density, following a trend observed previously for capacitors constructed with fabric-SDM (13), increases as the discharge time decreases. The data for the KOH SDM-based capacitors are shown in Figure 3. The trend shown was also found for SDM based on NaNO3 and NH4Cl aqueous solutions. The absolute values are also very informative. For example, the capacitors can provide of the order 100 W/cm3 for discharges of 0.01 s, a remarkably high value appropriate for many pulsed power applications. The data for NaNO3 and NH4Cl are only shown in a figure representing a summary of all nine capacitors. Greater detail is available elsewhere [24].
\nPower density vs. discharge time for KOH-based capacitors. At all three KOH concentrations, the power density increases with decreasing discharge time. The data clearly follow a simple power law in all cases, permitting determination of power density with high precision over a broad discharge time range. Employing the linear fitting equations, with DT, in s, yields power in W/cm3.
Capacitance as a function of discharge time for all three KOH-based systems is shown in Figure 4. These values were computed directly from the slope of the curves below ~0.8 V (Figure 1) and hence are only valid below this value. Despite this limitation, the data are of interest as it shows remarkably high values for very small volume systems.
\nCapacitance vs. discharge time for KOH-based capacitors. At all three KOH concentrations, the capacitance clearly follows a simple power law in all cases, permitting determination of its value with high precision over a broad discharge time range.
It is notable that none of the parameters, including capacitance, show a clear pattern with salt concentration. The fact that key parameters do not track with salt concentration has been noted with all other SDM-based capacitors [9–13].
\nThe final parameter of interest is the dielectric constant, generally an excellent engineering value as it permits the selection of capacitors, based on this single number, with a high degree of certainty they will perform as anticipated. However, for SDM-based capacitors employed for energy storage, for which dielectric constant is not a constant of voltage or frequency, it is not a quantitative predictor of performance. Notably, the dielectric constant also does not serve any role in rating EDLC for which dielectric constants in the traditional sense cannot really be measured. In fact, for EDLC a dielectric constant with units, F/cm2 is the only ‘dielectric’ value cited [31–34]. Still, there are two good reasons for measuring and reporting this value. First, it provides a qualitative predictor of energy and power density. Second, the values (Figure 5) permit a quantitative comparison with the historic database of dielectric materials, including other super dielectric materials. For example, the far greater values of dielectric constants for SDM below ~1 V, generally more than 105 greater than any solid dielectric, show them to be a distinct class of materials.
\nDielectric constant vs. discharge time for KOH-based capacitors. At all three KOH concentrations, the dielectric constant follows, below ~0.8 V, a simple power law, permitting determination of its value with high precision over a broad discharge time range. The absolute values of the dielectric constant are greater than 106 even at a discharge time of order 10−3 s, indicating these materials were super dielectric materials over the full range tested.
The only complete data set shown for the aqueous NH4Cl-based dielectric is the dielectric constant as a function of discharge time (Figure 6). The values of this parameter are similar to those of the aqueous KOH-based dielectrics and the other values are as well. Only dielectric constant is displayed as this parameter is most easily compared to the historic data set of dielectric materials. It is also notable that the data derived from aqueous NH4Cl solutions show greater variability than data from capacitors made with either of the other solutions.
\nDielectric constant vs. discharge time for NH4Cl-based capacitors. At all three NH4Cl concentrations, the dielectric constant follows, below ~0.8 V, a simple power law. The absolute values of the dielectric constant are similar to those of KOH at all discharge times, and greater than 106 even at a discharge time of order 10−3 s, indicating these materials were super dielectrics over the full range tested.
For the aqueous NaNO3-based dielectric, the only complete data set provided is the dielectric constant as a function of discharge time (Figure 7). The values of this parameter are distinctly less, on the order of a factor of five at any given discharge time, than those observed for both the aqueous KOH- and NH4Cl-based dielectrics. This is a qualitative indicator that the energy and power density of capacitors built T-SDM employing this solution will not perform as well for storing energy and providing power. This is shown to be true in the next section.
\nDielectric constant vs. discharge time for NaNO3-based capacitors. At all three concentrations, the dielectric constant follows, below ~0.8 V, a simple power law. The absolute values of the dielectric constant are about an order of magnitude less than the KOH and NH4Cl-based capacitors at any given discharge time. Still, at all discharge times tested the dielectric constant was greater than 105, indicating these materials were super dielectrics over the full range tested.
The energy density for all three aqueous salt solutions with 30 wt% concentration is shown in Figure 8. The energy density for two of these solutions, KOH and NH4Cl, are very similar across the entire range of discharge times collected. This is consistent with the observations that they have very similar dielectric values over the same tested time range. The energy density of the capacitors employing NaNO3 is less than a third the value of capacitors built using either of the other two solutions at any given frequency and also qualitatively consistent with the relatively low dielectric value of this solution. Also notable is the clear indication that the method does not provide reliable data for discharge times less than approximately 0.001 s. At this high rate of discharge, the method does not capture a sufficient number of data points to provide a reliable integrated energy density.
\nEnergy density comparisons. The energy density for capacitors built with three different 30 wt% salt solutions is shown over more than three orders of magnitude of discharge time. The data below 0.001 s discharge time are considered inaccurate due to insufficient data collection times.
A comparison of the power density for the three capacitors built with 30 wt% salt solutions is shown in Figure 9. Once again, the KOH and NH4Cl behavior is very similar, as anticipated based on the similarity in the reported dielectric values over the full range of discharge times studied. It is also clear that the aqueous NaNO3 capacitor yields the lowest power densities, by a factor of approximately three at all discharge times, as expected given the lower dielectric values reported. Although not shown here, the relative energy and power densities observed for the 30% solutions are exemplary of the relative values of these parameters at all concentrations.
\nPower density comparisons. The power density for capacitors built with three different 30 wt% salt solutions is shown over more than three orders of magnitude of discharge time.
The following were observed for all nine ion capacitors containing dissolved ions: (i) All the capacitors displayed ‘roll-off’ of capacitance (<0.8 V), dielectric constant (<0.8 V), and energy density (0.1–2.3 V) as discharge time decreased. (ii) The roll-off, of all these parameters, is well described by simple power law expressions derived from data covering more than three orders of magnitude of discharge times. (iii) Power density is also well described by a simple power law, but in contrast to all other parameters of interest, increased in all cases as the discharge time was reduced. (iv) The identity and concentrations of the solutes had a strong impact on the value of all capacitor performance parameters. (v) The value of all parameters was not a clear function of solute concentration, although the highest weight concentration, 30%, performed the best. (vi) In general, capacitors based on KOH and NH4Cl were similar in behavior, but the NaNO3-based capacitors consistently showed the lowest values.
\nThe data presented herein provide the first report on the behavior of T-SDM as a function of discharge time. This information is critical for assessing the value of any type of capacitor for application to ‘pulsed power’. Indeed, the measured power densities, just greater than 100 W/cm3 for both the aqueous KOH- and NH4Cl-based capacitors, for discharges of 0.01 s, are exceptional. As shown in Figure 10, the KOH-based capacitor parameters fall above the ‘range’ of operation anticipated for EDLC-based supercapacitors and are far better than the performance determined using the identical methodology employed in this work to assess real commercial ‘supercapacitors’ [24] in our laboratory. Three supercapacitors were tested and the best passed through the bottom range of values anticipated by the plot shown (Figure 10), and the other two were completely below the ‘bubble’ of performance anticipated for ‘double layer capacitors’.
\nKOH 30 wt% NPS energy/power performance. On a modified US Defense Logistics Agency Ragone chart, it is clear that the 30 wt% KOH-based capacitor (solid line) is superior to that anticipated for EDLC or double layer capacitors. Also, the data fall on a line, which can reasonably be extrapolated using the power law fits (dashed curve). It was assumed that the dielectric is half salt water and half titania with density 2.6 g/cm3.
It is also important to compare the data obtained in this study with earlier work on T-SDM. That earlier work was undertaken with a different objective: Study very slow discharges (>1000 s) appropriate for determining their potential use of T-SDM as energy storage devices. The measured energy densities reported herein, for both KOH- and NH4Cl-based capacitors, are comparable to the values obtained in prior studies. Those were obtained using a different solution, 30% NaCl, and a different measurement method, the traditional RC time constant method. In fact, using the simple power law dependencies obtained here and extrapolating to 1000 s, the energy density is a remarkable ~600 J/cm3. In the earlier RC time constant work a nearly identical titania matrix containing 30 wt% NaCl aqueous solution yielded nearly 400 J/cm3 for similar discharge times. Given the different ionic solutions, the different measurement protocols and other minor differences, there is an excellent agreement between the two studies.
\nThe basic model of T-SDM presented elsewhere [7, 8, 10] predicts high capacitance that decrease as the discharge time decreases. To understand both, a brief review of the static model of SDM and a qualitative review of the dynamics of SDM is required. Regarding the former: As illustrated by the cross-section model of an anodized titania filled with aqueous solution, Figure 11, dipoles created by the movement of ions in solution toward oppositely polarized electrodes create ‘giant dipoles’. These dipoles, opposite in polarization to the electrodes, reduce the field, everywhere, created by charges on the electrodes. As voltage is the line integral of field from ground to electrode, the lowering of field everywhere reduces the voltage. Thus, it takes more charge on the electrodes to reach the same voltage when these giant dipoles are fully (static conditions) aligned. More charge, at the same voltage, means a higher capacitance, by definition. In essence, dipole formation is the basis for capacitance enhancement for all types of dielectrics; however, for SDM the dipoles are orders of magnitude longer than in any solid so the field reduction, and consequently the increase in capacitance, is more dramatic. Next, it is necessary to reflect on the dynamics of dipole formation, that is the impact of frequency, or period, on dipole strength. Specifically, if the electrode polarization is switched too quickly for the ions in solution to ‘swim’ to the maximal (static) dipole positions, the net or effective, dipole length, and concomitantly the dielectric and capacitance values, are reduced. The data suggest that effective dipole length follows a very simple pattern as a function of discharge time.
\nX-Section model of dipole formation in SDM. 1. Top electrode, Grafoil. 2. Tube filled with aqueous ion solution. 3. 90 nm × 8 μm titania tubes formed by anodization. 4. Titanium metal electrode. Upon the application of a field, the ions in solution migrate to form dipoles oppositely polarized to the electrodes. The effective dipole strength in the dielectric is a function of time. Given sufficient time (static) dipoles of maximum length and charge separation form. The effective dipole length/strength is a function of net length and thus is discharge time/frequency dependent.
It is notable that this is only the second time [13] the constant current charge/discharge method has been employed to determine the power law relationship for ‘supercapacitor’ parameters, specifically capacitance, dielectric constant, and energy and power density, over orders of magnitude of discharge times. This method arguably provides higher fidelity, more reliable, insight into ‘frequency’ dependence of this type of capacitor than other measurement protocols.
\nThis study establishes, empirically, that T-SDM capacitors, based on dielectrics created by filling micron scale titania tubes that form during titanium ionization with aqueous salt solutions, are superior to all other energy storage capacitors, relative to standard metrics. Using a recently developed constant current protocol, it was demonstrated that the capacitance, dielectric constant, and energy and power density as a function of discharge time follow power law relationships. Plotted on a Ragone chart, the power vs. energy density data is linear. All data lie above the values recorded for supercapacitors, ultra capacitors, and electrolytic capacitors on standard Ragone charts. Furthermore, the consistency of the data, that it resulted in power law relationships for capacitors derived from nine different salt solutions, indicates that the data and the fitted power laws are precise and are probably accurate. Notably, dielectric constants of more than 108 were recorded, and even for very short discharges for all capacitors, the dielectric constant was >105, establishing that the dielectrics are SDM over a broad range of discharge times (ca. 10−3–>10 s). Finally, it should be noted that the measured power delivery increases as the discharge time decreases. For three of the capacitors, the measured power delivery was greater than 70 W/cm3 for a 10 ms discharge, a time frame and a power delivery value consistent with the needs of pulsed power systems.
\nProteins are chains of amino acids which are involved in nearly every process in the body. Proteins function as enzymes, transcription factors, binding proteins, transmembrane transporters and channels, hormones, receptors, structural proteins, and signaling proteins [1]. However, the primary role of protein in the diet is to provide amino acids required for the synthesis of new proteins. We especially rely on dietary protein to provide the nine essential amino acids, which cannot be synthesized in the body. Protein intake greater than the dietary recommendations may prevent sarcopenia [2], help maintain energy balance [3], improve bone health [4, 5, 6, 7] and cardiovascular function [8, 9, 10], and aid in wound healing [11]. This chapter focuses on the role of dietary protein, and the associated health benefits, throughout the life cycle.
\nThe current dietary recommendations for protein intake include the estimated average requirement (EAR) [12] and the recommended dietary allowance [12]. For daily protein intake, the EAR for dietary protein is 0.66 g kg−1 day−1, and the RDA is 0.8 g kg−1 day−1 for all adults over 18 years of age. This can become confusing when trying to make recommendations for individuals at different stages of life. Even the Food and Nutrition Board recognizes a difference between what is recommended in the RDA and the level of protein intake needed for optimal health [12]. Therefore, there is a third recommendation for protein called the acceptable daily macronutrient range (ADMR) [13, 14]. The ADMR includes a recommendation for protein intakes ranging from 10 to 35% of daily energy (e.g., calorie intake), which makes the ADMR easier to use when developing dietary recommendations for protein [12].
\nA majority of the adult population in the United States exceeds the minimum recommendations for protein intake [15]. The current dietary protein intake in the United States is approximately 82 g d−1 for men and 67 g d−1 for women [16]. \nTable 1\n details the current protein intake as percent of energy intake in the United States based on sex and age. A majority of dietary protein comes from animal protein (46%), followed by plant protein (30%), dairy (16%), and mixed foods (8%) [16]. There is increasing evidence indicating that consuming dietary protein at levels above the current RDA (0.8 g dietary protein kg body weight−1 day−1) may be beneficial for children, adults, older adults, and physically active individuals [17]. For example, protein intake above the RDA may help reduce the risk of chronic diseases such as obesity, cardiovascular disease, type 2 diabetes, osteoporosis, and sarcopenia [13, 17]. However, high protein intake without a subsequent decrease in carbohydrates attenuates the beneficial effects of dietary protein [18].
\nAge | \nTotal | \nMen | \nWomen | \n
---|---|---|---|
Protein | \n|||
20–44 years | \n15.7 | \n16.1 | \n15.3 | \n
45–64 years | \n15.8 | \n16.0 | \n15.7 | \n
65–74 years | \n16.3 | \n16.6 | \n16.1 | \n
75 years and older | \n15.7 | \n16.1 | \n15.3 | \n
Percentage macronutrient intake in the United States by sex and age [19].
Adequate dietary protein intake is essential to support cellular integrity, growth, and physical function. Although protein malnutrition is not prevalent in the United States, there is little research on optimal protein requirements for health benefits in children. Current EARs are based on the factorial method and the nitrogen balance technique. The factorial method incorporates the estimated nitrogen (protein) requirement plus the rate of protein deposition and an estimate of the efficiency of protein utilization [20] which is derived from adult dietary protein needs [12]. By using the indicator amino acid oxidation method in a group of healthy children 6–11 years old, it was found that the mean and population-safe (upper 95% CI) protein requirements were 1.3 and 1.55 g kg−1 day−1, respectively. This is higher than the 2005 DRI for protein (0.76 and 0.95 g kg−1 day−1, respectively) [12]. A similar study using the nitrogen balance technique also found that protein requirements in children in this age range are above current recommendations at 1.2 g kg−1 day−1 [21]. These higher estimated protein requirements in children seem to be in line with current protein consumption patterns in different pediatric age groups. For instance, children 2–3 years old are currently daily consuming ~3.6 g/kg of ideal body weight, children 4–8 years old are currently consuming ~2.6 g kg−1 ideal body weight−1, and children 9–13 years old are consuming ~1.6 g kg−1 ideal body weight−1 [15]; however, the optimal protein intake for children is still under debate [22]. There are racial/ethnic differences in protein consumption in children (2–18 years old). For example, non-Hispanic black children eat about 5% below, non-Hispanic white children eat about 3% below, Hispanic children eat about 2% below, and Asian children eat less than 1% below the EAR for protein [15].
\nAlthough the currently established recommendations for protein intake in children may be lower than the requirements, the effect of diets higher in protein (e.g., 30% of total energy intake) in children is unclear [22]. Several studies have alluded to the potential benefit of higher protein intake dietary practices. For instance, diets higher in protein with a low glycemic index can be protective against obesity in children aged 5–18 years [23], and diets higher in protein can lead to smaller waist circumference, blood pressure, insulin, and serum cholesterol than lower-protein diets in children from the same age group. A recent cohort analysis found that protein intake in 8-year-olds is associated with higher fat-free mass [24], and an additional cohort analysis found that at ages 11, 15, and 22 years, protein intake is inversely associated with early adulthood BMI. However, protein intake at 2 years was positively associated with BMI and lean mass at age 22 [25], suggesting there are conflicting results regarding the benefits of increased dietary protein in children.
\nPregnancy is a period of rapid tissue growth during a short period of time. Maternal tissues, including breast, uterine, and adipose tissues, blood volume, and extracellular fluids, account for the largest amount of protein accretion during pregnancy at 60%. The remaining 40% of protein accretion occurs within the amniotic fluid, fetus, and placenta [26, 27]. In fact, protein needs to increase soon after conception to support tissue growth and development, maintenance of maternal homeostasis, and lactation preparation [27, 28, 29]. These alterations occur in an exponential way and only in response to adequate total energy intake. This means that protein deposition does not significantly change in the first trimester compared to pre-pregnancy, but increases during the second trimester and significantly increases to the highest levels of protein deposition in the third trimester. This variable period of growth makes it difficult to define recommendations regarding protein requirements. Thus, although current recommendations suggest constant protein intake throughout the duration of pregnancy, pregnancy may actually require an increase in protein intake throughout gestation to support adequate growth, although further research is needed. There are several benefits of protein intake during pregnancy including adequate maternal weight gain within recommendations, lower early pregnancy BMI, and decreased postpartum weight [30].
\nAlthough the benefits of increased protein intake during pregnancy are apparent as stated above, protein requirements during pregnancy are difficult to measure. This is due to the involved nature of some of the techniques used to measure protein requirements. Therefore, the current dietary protein recommendations during pregnancy are based on factorial estimates of recommendations for healthy, nonpregnant populations. Pregnancy protein needs have been derived from the EAR and RDA for healthy, nonpregnant populations and are set to 0.88 g kg−1 day−1 (EAR) and 1.1 g kg−1 day−1 (RDA) [12]. However, newer studies found protein needs to be 1.2 g kg−1 day−1 at 11–20 weeks, increasing to 1.52 g kg−1 day−1 at 30–38 weeks [31]. Both nonpregnant women of childbearing age (20–44 years) and pregnant women consume at or above the current recommendations of protein intake [32, 33]. One study [31] found that pregnant women consume the same amount of protein in early pregnancy (1.44 ± 0.30 g kg−1 day−1) as they do in late pregnancy (1.47 ± 0.53 g kg−1 day−1), not taking fluid retention and changes in body composition into account. These findings support others that have noted little overall change in dietary protein patterns from early to late pregnancy [33]. Collectively, these findings demonstrate that pregnant women meet the recommendations for dietary protein intake. Improvements may potentially be made to increase dietary protein requirements as pregnancy progresses.
\nAn important factor to consider when incorporating protein into the diet is how the source of dietary protein (e.g., protein derived from animal or plant sources) affects nutrient intake, nutrient adequacy, and diet quality [13, 34, 35]. Proteins with differing amino acid profiles exhibit varied digestion and absorption rates [36, 37, 38], and amino acid profiles depend directly on the quality and quantity of the dietary protein [37]. For example, the digestion and absorption rates of fast- (e.g., whey) versus slow (e.g., casein)-digesting proteins need to be taken into consideration when developing protein recommendations. One study provided young, healthy subjects with either a whey protein meal (30 g) or a casein meal (43 g) (both contained the same amount of leucine [one of the BCAAs]) and measured whole-body protein synthesis. Researchers determined that the subjects consuming the whey (fast) protein meal had a high, rapid increase in plasma amino acids, while subjects consuming the casein (slow) protein meal had a prolonged plateau of EAA [39]. In addition, the chemical structure and the presence of anti-nutritional compounds such as phytic acid within the protein source can influence digestion and amino acid availability [40]. Compared to animal sources, plant proteins are shown to have a lower anabolic impact on muscle; however, the reduced ability to elicit anabolic effects can be overcome by increasing protein intake and increasing the content of leucine [41].
\nWhether or not the amino acid source is derived from the whole protein or a mixture of free amino acids can also influence the rate of muscle protein synthesis [42]. For example, when older subjects were given either an EAA mixture (15 g) or a whey protein supplement (13.6 g) after an overnight fast, subjects consuming the EAA mixture had higher mixed muscle fractional synthetic rate [42], which is often associated with increases in muscle mass. The differing response could be due to the differing leucine content between the supplements (EAA, 2.8 g leucine, and whey, 1.8 g leucine) or because the EAA supplement was composed of individual amino acids while the whey protein supplement was intact protein. These subtle differences could influence the rate of appearance of the amino acids into blood circulation and thus the protein synthetic response.
\nAnother potential confounder of the protein synthetic response of various proteins is the form or texture of the protein itself, such as ground beef versus a beef steak [43]. When, older men consumed 135 g of protein as either ground beef or as a beef steak, the amino acids from the ground beef appeared more rapidly in the circulation than the amino acids from the beef steak. Whole-body protein balance was higher after consumption of the ground beef versus the beef steak. However, 6 h after the beef meals, muscle protein synthesis was not different [43]. Nonetheless, these data support that the form of the protein that is being consumed impacts digestion, absorption, and the rate of appearance of amino acids into circulation [35].
\nThe timing of dietary protein intake has received ample attention in the past several decades. Adults typically consume the majority of their protein intake at dinner (38 g) versus breakfast (13 g) [44]. However, recent research suggests that ingestion of more than 30 g of protein in a test meal does not further stimulate the effect of dietary protein on muscle protein synthesis [45]. This had led to discussion related to optimal timing of protein intake. For example, distributing protein intake throughout the day, timing of protein around nighttime eating, and protein eating at breakfast are all areas of increased interest. In general, research covering these topics is performed in young, healthy populations, or aging populations, and very few, if any, studies have been conducted in children and pregnant women.
\nBreakfast is often recognized as the most important meal of the day [46, 47, 48]. However, there is debate as to what defines the ideal breakfast meal [47], in addition to a lack of strong evidence to define which nutrients should be represented at breakfast [47]. A recent commentary published by the American Academy of Nutrition and Dietetics suggests that protein-containing foods (e.g., eggs, lean meat, and low-fat dairy products) should be included in breakfast meals [47]. Literature supports diets higher in protein aid in the treatment of chronic, metabolic diseases such as obesity, type 2 diabetes, and heart disease and have been shown to increase EE, improve satiety, regulate glycemic control, and improve body composition (reviewed in [13, 14, 34, 49]).
\nEating protein at night and immediately before bedtime has received substantial attention in the past decade. Although past common knowledge would claim that eating before bed precipitates negative effects on health and body composition, more recent studies show that there may be many metabolic, health, and body composition-related benefits [50]. Much of the previous research claiming the negative effects of nighttime eating was performed in shift workers [51], populations with night eating syndrome, who consume ≥50% of daily calories after dinner [52], and epidemiological data [53]. Although some of the negative effects of nighttime eating in these populations may include high BMI and abdominal obesity [54]; increased triglyceride concentration, dyslipidemia, and impaired glucose tolerance [55]; impaired kidney function [56]; and increased carbohydrate oxidation and decreased fat oxidation [57], many other factors need to be taken into consideration. For example, these populations are awake during abnormal hours and report sleep disturbances [58, 59]. In fact, the duration of sleep is inversely related to BMI [60, 61]. These populations also consume significantly more carbohydrate, protein, and fat throughout the day. Nonetheless, it is clear that eating large amounts of energy in the evening hours, in particular when the energy is carbohydrate- and fat-laden, may not be beneficial for health and body composition outcomes.
\nHowever, much more evidence has shown that eating a small protein snack (~200 kcal) before bed may elicit significant benefits. Improved muscle protein recovery, muscle mass, and strength gains mediated by enhanced overnight and next-morning muscle protein synthesis have been shown to be enhanced with 40 g of casein protein supplementation in elderly [62] and recreationally active men [63]. These effects are particularly enhanced when this dietary practice is added to the practice of resistance exercise [63]. In addition, reported hunger is lower and satiety is higher, and resting energy expenditure is higher the following morning after a small protein snack compared to a noncaloric placebo [50, 62]. Chronically (4 weeks) there are also reports of decreased blood pressure, decreased arterial stiffness [64], and a greater decrease in body fat in overweight and obese women when consuming nighttime protein [65, 66]. Importantly, these benefits are accompanied by no significant alterations in overnight or next-morning lipolysis, fat oxidation, substrate utilization, or any blood markers in obese men or resistance-trained young women [67].
\nCurrent research demonstrates that even distribution of protein intake throughout the day is more effective at stimulating a 24-h protein synthesis compared to an uneven distribution [68, 69]. This is supported by data from a longitudinal study on nutrition and aging, which found that even distribution of daily protein intake across meals is independently associated with greater muscle strength and higher muscle mass in older adult, but is not associated with loss in muscle mass [70] or mobility [71] over 2–3 years. However, there are some studies that fail to confirm the importance of spreading protein intake out over the course of the day [71, 72]. Additional studies have compared pulse feeding (72% of daily protein at lunch) versus protein being evenly distributed over four daily meals in hospitalized older patients for 6 weeks [73, 74]. These studies found that pulse feeding of protein increased postprandial amino acid bioavailability [75] and increased lean mass [74] compared to spreading protein intake throughout the day. Taken together, the optimal timing and distribution of protein intake still need to be determined.
\nObesity is a major public health concern [76] and is associated with the development of metabolic diseases such as cardiovascular disease, nonalcoholic fatty liver disease, and type 2 diabetes mellitus in both children and adults [77, 78]. Obesity is defined as having a body mass index (BMI) (weight in kilograms divided by height in centimeters squared) greater than or equal to 30.0. In 2015–2016, the prevalence of obesity (\nTable 2\n) in the United States was 39.6 for adults and 18.4% for youth [76]. Obesity also impacts racial and ethnic groups differently. For example, non-Hispanic black and Hispanic adults and youth have higher rates of obesity compared to non-Hispanic white and Asian populations [79].
\nAge group (years) | \nTotal (percent) | \nBoys or men (percent) | \nGirls or women (percent) | \n
---|---|---|---|
Youth, 2–19 | \n18.5 | \n19.1 | \n17.8 | \n
Young children, 2–5 | \n13.9 | \n14.3 | \n13.5 | \n
Youth, 6–11 | \n18.4\n$\n\n | \n20.4\n$\n\n | \n16.3 | \n
Adolescents, 12–19 | \n20.6\n$\n\n | \n20.2 | \n20.9\n$\n\n | \n
Adults, 20+ | \n39.6 | \n37.9 | \n41.1 | \n
Young adults, 20–39 | \n35.7 | \n34.8 | \n36.5 | \n
Middle-aged adults, 40–59 | \n42.8\n*\n\n | \n40.8\n*\n\n | \n44.7\n*\n\n | \n
Older adults, 60+ | \n41.0 | \n38.5 | \n43.1 | \n
Prevalence of obesity in the United States by age group and sex [76].
Significantly different from young children.
Significantly different from young adults.
A primary factor in controlling and preventing obesity and associated chronic diseases is through diet, for example, diets higher in protein [13, 14, 80, 81]. Diets higher in protein (>30% of energy intake) have been shown to improve body composition [82], improve glycemic response [81, 83, 84, 85], increase satiety [85, 86, 87], and increase postprandial energy metabolism [88, 89], which are all mediating factors of weight loss.
\nSarcopenia is the term for age-associated loss of muscle mass and function [35]. The loss of muscle function associated with sarcopenia is often referred to as dynapenia [90]. A loss or reduction in skeletal muscle function often leads to increased morbidity and mortality either directly, or indirectly, via the development of secondary diseases such as diabetes, obesity, and cardiovascular disease [91]. The causes of sarcopenia include poor nutrition, diminished responsiveness to anabolic hormones and/or nutrients, and a sedentary lifestyle.
\nThe loss in muscle mass observed with aging is often accompanied by an increase in fat mass [92], which can happen even in the absence of changes in BMI [35]. The loss in muscle mass results in a decrease in basal metabolic rate (BMR) or the amount of caloric energy we use while at rest [93]. The loss of muscle mass induces a 2–3% decrease in BMR per decade after the age of 20 and a 4% decline in BMR per decade after the age of 50 [93, 94]. Muscle loss and subsequent reduction in metabolic rate contribute to obesity that accompanies the aging process.
\nSeveral studies identify protein as a key nutrient for aging adults [2, 95]. Low protein intake is linked to a decrease in physical ability in aging adults [96]. However, protein intake greater than the dietary guidelines may prevent sarcopenia [96], help maintain BMR [3], improve bone health [4, 5, 6, 7], and improve cardiovascular function [8, 9, 10]. These benefits of increasing protein in the diet may improve function and quality of life in healthy older adults, as well as improve the ability of older patients to recover from disease and trauma [91].
\nCurrently, the dietary recommendations for protein intake are the same for all healthy adults above the age of 19. However, experts in the field of protein and aging recommend a protein intake between 1.2 and 2.0 g kg−1 day−1 or higher for elderly adults [91, 95, 97]. The RDA of 0.8 g kg−1 day−1 is well below these recommendations and reflects a value at the lowest end of the AMDR. It is estimated that 38% of adult men and 41% of adult women have dietary protein intakes below the RDA [16, 44].
\nBoth protein amount and source are important to consider when recommending protein intake to older adults [34, 35]. There are three important aspects to take into consideration when recommending a protein source: (1) the characteristics of the specific protein, such as the amount of essential amino acids (EAA); (2) the food matrix in which the protein is consumed, for example, as part of a beverage or a complete meal; and (3) the characteristics of the individuals consuming the food, including health status, physiological status, and energy balance [34]. In addition, the difference in digestibility and bioavailability of a protein can impact the quantity of protein that needs to be ingested to meet metabolic needs; this is especially important in older adults since gastric motility and nutrient absorption decrease with age. The speed of protein digestion and absorption of amino acids from the gut can influence whole-body protein building [36]. Proteins with differing amino acid profiles exhibit different digestion and absorption rates [36, 38, 98]. Amino acid availability depends directly on both the quality and quantity of the dietary protein [98].
\nOver the past 15 years, the gut microbiome has received increased attention regarding its role in impacting overall health [99]. Interestingly, it has been shown to influence diseases associated with metabolic health [100]. The intestinal mucosa houses nearly a trillion microorganisms, and the plasticity of this environment is highly reactive to changes in diet [101]. For instance, the gut becomes an active site for protein and amino acid metabolism prior to absorption. Following enzymatic denaturation by intestinal proteases, amino acids can become fermented into various metabolites which include short-chain fatty acids and ammonia [102]. The acute microbial response and long-term adaptation associated with dietary habits have become an important area of research.
\nAs gut assay methodologies improve, researchers have identified associations between microbial populations and their metabolite concentrations in response to dietary patterns. For instance, in vitro and human models demonstrate a potential negative link between animal protein intake and protein fermentation end products such as ammonia and trimethylamine-N-oxide [103, 104]. However, favorable outcomes associated with animal- and plant-based protein sources have been observed. For example, ingestion of both whey [105] and pea protein [106] has been shown to increase favorable gut bacterial species such as Bifidobacterium. In addition, supplementation with pea protein intake has been shown to increase the production of short-chain fatty acids, an important energy substrate utilized by enterocytes [106].
\nThere is sufficient evidence that protein intake higher than the current dietary recommendations is beneficial for most healthy individuals throughout the life cycle. However, benefits of dietary protein depend on the quality, the quantity, and the timing of protein intake. Although health benefits of dietary protein have been well-established for older adults, more research is needed to determine the health benefits of increased dietary protein intake through each state of life.
\nThis work was supported by a grant to J.I.B. and E.B. from the Arkansas Biosciences Institute.
\nThe authors have no conflicts of interest to declare.
IntechOpen publishes different types of publications
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\\n\\nEdited Volumes can be comprised of different types of chapters:
\\n\\nRESEARCH CHAPTER – A research chapter reports the results of original research thus contributing to the body of knowledge in a particular area of study.
\\n\\nREVIEW CHAPTER – A review chapter analyzes or examines research previously published by other scientists, rather than reporting new findings thus summarizing the current state of understanding on a topic.
\\n\\nCASE STUDY – A case study involves an in-depth, and detailed examination of a particular topic.
\\n\\nPERSPECTIVE CHAPTER – A perspective chapter offers a new point of view on existing problems, fundamental concepts, or common opinions on a specific topic. Perspective chapters can propose or support new hypotheses, or discuss the significance of newly achieved innovations. Perspective chapters can focus on current advances and future directions on a topic and include both original data and personal opinion.
\\n\\nINTRODUCTORY CHAPTER – An introductory chapter states the purpose and goals of the book. The introductory chapter is written by the Academic Editor.
\\n\\nMonographs is a self-contained work on a particular subject, or an aspect of it, written by one or more authors. Monographs usually have between 130 and 500 pages.
\\n\\nTYPES OF MONOGRAPHS:
\\n\\nSingle or multiple author manuscript
\\n\\nCompacts provide a mid-length publishing format that bridges the gap between journal articles, book chapters, and monographs, and cover content across all scientific disciplines.
\\n\\nCompacts are the preferred publishing option for brief research reports on new topics, in-depth case studies, dissertations, or essays exploring new ideas, issues, or broader topics on the research subject. Compacts usually have between 50 and 130 pages.
\\n\\nCollection of papers presented at conferences, workshops, symposiums, or scientific courses, published in book format
\\n"}]'},components:[{type:"htmlEditorComponent",content:"IntechOpen Edited Volumes are integrated collections of chapters about particular topics that present new areas of research or novel syntheses of existing research and, as such, represent perspectives from various authors.
\n\nEdited Volumes can be comprised of different types of chapters:
\n\nRESEARCH CHAPTER – A research chapter reports the results of original research thus contributing to the body of knowledge in a particular area of study.
\n\nREVIEW CHAPTER – A review chapter analyzes or examines research previously published by other scientists, rather than reporting new findings thus summarizing the current state of understanding on a topic.
\n\nCASE STUDY – A case study involves an in-depth, and detailed examination of a particular topic.
\n\nPERSPECTIVE CHAPTER – A perspective chapter offers a new point of view on existing problems, fundamental concepts, or common opinions on a specific topic. Perspective chapters can propose or support new hypotheses, or discuss the significance of newly achieved innovations. Perspective chapters can focus on current advances and future directions on a topic and include both original data and personal opinion.
\n\nINTRODUCTORY CHAPTER – An introductory chapter states the purpose and goals of the book. The introductory chapter is written by the Academic Editor.
\n\nMonographs is a self-contained work on a particular subject, or an aspect of it, written by one or more authors. Monographs usually have between 130 and 500 pages.
\n\nTYPES OF MONOGRAPHS:
\n\nSingle or multiple author manuscript
\n\nCompacts provide a mid-length publishing format that bridges the gap between journal articles, book chapters, and monographs, and cover content across all scientific disciplines.
\n\nCompacts are the preferred publishing option for brief research reports on new topics, in-depth case studies, dissertations, or essays exploring new ideas, issues, or broader topics on the research subject. Compacts usually have between 50 and 130 pages.
\n\nCollection of papers presented at conferences, workshops, symposiums, or scientific courses, published in book format
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