More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
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Our breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
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“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
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Additionally, each book published by IntechOpen contains original content and research findings.
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We are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
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Simba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
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IntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\n
Since the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\n
Our breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n
“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\n
Additionally, each book published by IntechOpen contains original content and research findings.
\n\n
We are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n
\n\n
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"8008",leadTitle:null,fullTitle:"Antioxidants",title:"Antioxidants",subtitle:null,reviewType:"peer-reviewed",abstract:"Antioxidants are substances that can prevent or slow damage to living cells caused by free radicals, which are unstable molecules the body produces as a reaction to environmental and other pressures. 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He is a member of seven international specialized scientific societies, besides his local one, and\nhe has won seven prizes.",institutionString:"Cairo University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Cairo University",institutionURL:null,country:{name:"Egypt"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1182",title:"Clinical Pharmacology",slug:"clinical-pharmacology"}],chapters:[{id:"65225",title:"Antioxidant Categories and Mode of Action",doi:"10.5772/intechopen.83544",slug:"antioxidant-categories-and-mode-of-action",totalDownloads:1093,totalCrossrefCites:0,totalDimensionsCites:4,signatures:"Manal Azat Aziz, Abdulkareem Shehab Diab and Abeer Abdulrazak Mohammed",downloadPdfUrl:"/chapter/pdf-download/65225",previewPdfUrl:"/chapter/pdf-preview/65225",authors:[{id:"276717",title:"Associate Prof.",name:"Manal",surname:"Azat Aziz",slug:"manal-azat-aziz",fullName:"Manal Azat Aziz"},{id:"286369",title:"Dr.",name:"Abdulkareem",surname:"Shehab Diab",slug:"abdulkareem-shehab-diab",fullName:"Abdulkareem Shehab Diab"},{id:"312155",title:"Dr.",name:"Abeer Abdulrazak",surname:"Mohammed",slug:"abeer-abdulrazak-mohammed",fullName:"Abeer Abdulrazak Mohammed"}],corrections:null},{id:"66259",title:"Antioxidant Compounds and Their Antioxidant Mechanism",doi:"10.5772/intechopen.85270",slug:"antioxidant-compounds-and-their-antioxidant-mechanism",totalDownloads:5059,totalCrossrefCites:18,totalDimensionsCites:49,signatures:"Norma Francenia Santos-Sánchez, Raúl Salas-Coronado, Claudia Villanueva-Cañongo and Beatriz Hernández-Carlos",downloadPdfUrl:"/chapter/pdf-download/66259",previewPdfUrl:"/chapter/pdf-preview/66259",authors:[{id:"143354",title:"Dr.",name:"Raúl",surname:"Salas-Coronado",slug:"raul-salas-coronado",fullName:"Raúl Salas-Coronado"},{id:"148546",title:"Dr.",name:"Norma Francenia",surname:"Santos-Sánchez",slug:"norma-francenia-santos-sanchez",fullName:"Norma Francenia Santos-Sánchez"},{id:"193718",title:"Dr.",name:"Beatriz",surname:"Hernández-Carlos",slug:"beatriz-hernandez-carlos",fullName:"Beatriz Hernández-Carlos"},{id:"278133",title:"Dr.",name:"Claudia",surname:"Villanueva-Cañongo",slug:"claudia-villanueva-canongo",fullName:"Claudia Villanueva-Cañongo"}],corrections:null},{id:"65142",title:"Effect of the Ozonization Degree of Emu Oil over Healing: An Emerging Oxidation Treatment",doi:"10.5772/intechopen.83383",slug:"effect-of-the-ozonization-degree-of-emu-oil-over-healing-an-emerging-oxidation-treatment",totalDownloads:618,totalCrossrefCites:0,totalDimensionsCites:0,signatures:"Daniel Martin Márquez López, Tomás A. 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1. Introduction
Bottom-up synthesis methods like chemical vapour deposition (CVD) are those that better ensure the growth of continuous graphene films [1]. Evidence of the potential to move to industrial scale synthesis has been proven [2, 3]. When the various graphene nuclei reach the coalescence phase, they join to each other, forming a continuous layer. In this growth model, the grain boundaries are proven defects points affecting the quality of the graphene layer, both concerning mechanical and electrical properties. Thus, it is an emergency to proceed with the growth of wafer-scale single crystal graphene domains [4–10]. Efficient growth approaches should ensure a low nucleation density of graphene domains, followed by high growth rates. Parameters that affect the synthesis process are the gas mixture and growth pressure, temperature and time [11]. Copper foil is one of the preferred substrates for the CVD growth as it permits the production of large-scale, single-layer graphene domains [12]. Carbon atoms show a low solubility into the copper. More carbon species remain in the surface of the foil participating in the formation of the graphene sheet [1]. A conventional CVD growth method consists of a continuous flow of carbon gas precursor/H2/Ar mixture in order to generate the graphene growth [13]. In all experiments described in this chapter, methane is used as carbon precursor. As described in the work of Li et al. [14], the steps for the graphene CVD growth are the following:
Exposure of Cu to methane, argon and hydrogen.
Catalytic decomposition of methane on Cu to mainly form CHy species.
As a result of the temperature, methane pressure, methane and hydrogen flow and partial pressure, the Cu surface appears undersaturated, saturated or supersaturated with CHy species.
Formation of nuclei as a result of local supersaturation of CHy.
Nuclei grow to form graphene islands.
Full Cu surface coverage by graphene under specific temperature flow rates and pressure conditions.
The hydrogen presence has proved to play a critical role in the process, as it affects different mechanisms. It reduces the native copper oxide layer and activates the graphene growth. At the same time, it can apply an etching on the material. Thus, it is fundamental to fully understand the above mechanisms. It has been investigated before how hydrogen can affect thickness, shape, size, edge configuration and crystalline quality of graphene islands/domains as well the control of the nucleation density [15–21], which is very important, taking advantage of the low solubility of carbon into copper [21–27]. Polishing of the copper surface or even enclosure of the substrate in special ‘pockets’, enables the control of the gases mixture, has proven to help in the control of the nuclei density [12]. The use of high growth temperatures favours the copper recrystallization, permitting the growth of high-quality graphene [28]. Searching for means to further reduce the nucleation, it has been proposed the oxidation of the copper surface [29, 30] resulting in very low domain density with size up to 1 cm2 [31]. In order to reduce the copper surface, thermal annealing processes are usually applied, which require long periods of baking [32].
In this chapter, we present new experiments and results evidencing the effect of the partial pressure of H2 at a given CH4/H2 gas flow ratio on the growth of bi-dimensional crystals of graphene and on their morphology.
To provide a better understanding of the physicochemical mechanisms that govern film formation, we include them in the framework of atomic level phenomena such as adsorption, diffusion and nucleation, providing the possibility to have a full control on the growth process. We study the CVD growth of graphene in the range between 970 and 1070°C, examining the temperature effect in the graphene growth ratio and nucleation density. By fitting the graphene coverage ratio as a function of growth time, we estimate an activation energy of 3.01 eV.
Finally, we study the formation of ripples in the surface of the graphene sheet. Ripples in the graphene surface are proven to affect its electronic structure [33], carrier transport[34] and chemical properties.[35] Therefore, the capability to control the formation of this kind of corrugation is urgent.
In other recent works, Park et al. have demonstrated the capability to control the density and height of such ripples through control of the cooling ratio, which follows the growth step [36, 37]. Slow cooling permits the formation of molecular hydrogen, which can result in the suspension of the graphene film. Moreover, they have demonstrated the importance of such ripple morphology in the mobility properties of the graphene. Graphene with fewer and smaller ripples demonstrates better transport properties when it is embodied in electronic devices.
2. Experimental part
The whole process was carried out in a suitable CVD oven (schematically drawn in Figure 1). The reactor consists of a furnace, where the CVD process takes place, coupled to a spherical chamber with a magnetron sputtering system. The turbomolecular pump can achieve a vacuum in the order of ~10–4 Pa, providing a very pure atmosphere for the graphene growth. This allows us to deposit different thin films (copper-nickel on silicon) in ultrapure conditions (without oxygen) and to perform directly the graphene growth without exposing the substrate to the ambient. By this method, all the treatments, since the cleaning process and reduction/annealing of the copper foil or the deposition of the metal catalyst by sputtering, can be performed ‘in situ’ by a single run. For the evaluation of the obtained graphene, we used Raman spectroscopy as well as scanning electron and atomic force microscopy. The scanning electron microscopy (SEM) images were taken with a JEOL JSM7100F microscope in 5 keV. The Raman spectroscopy was performed with a Jobin-Yvon LabRam HR 800 system. A green laser with a 2 μm spot diameter has been used. Atomic force microscopy (AFM) image has been obtained with an AFM Multimode 8, electronica Nanoscope V (Bruker), and operated by the NOVA software.
Figure 1.
Illustration of the reactor. The system consists of two parts, a chamber with a magnetron sputtering head for thin films deposition and a quartz tube where the CVD processes take place.
2.1. Pretreatment of copper foil
Polycrystalline copper foil 75 μm thick and 99% pure was cut in pieces of 2 × 2 cm2. The foil piece is cut in pieces of 2 × 2 cm2. It is pre-cleaned with acetone and isopropanol immersed in an ultrasonic bath for 10 min. Then it is being introduced into the CVD reactor. In other works, the application of argon/hydrogen of helium/hydrogen plasma for the effective pre-treatment of the copper foil is being introduced. Plasma pre-treatment is, moreover, found to improve the crystallinity of the formed graphene [38]. Here we present the performance of hydrogen plasma for the same purpose. From previous studies made in our group [39], we have been able to optimize the parameters necessary to use in order to reduce the native copper oxide layer. According to these results, first, a background pressure of 7 × 10−4 Pa is applied with a turbomolecular pump to secure that the whole process is taking place under high purity conditions. Radio frequency (RF) hydrogen plasma is then applied to chemically reduce the copper substrate. To generate the plasma, we introduce hydrogen with 20 sccm flow rate and applied 100WRF power at 20 Pa. The hydrogen radicals react with the copper oxide .
CuO+2H→Cu+H2OE1
2.2. Graphene CVD growth
The authors have investigated in various works [40, 41] the growth mechanisms of graphene and the effect of parameters like the hydrogen concentration, growth pressure, time and temperature. The hydrogen flow appears to perform an etching in the graphene domains, which affects their morphology and uniformity, when its concentration exceeds some limits. The results reveal that a sufficient graphene growth is possible when we optimize the switching of the carbon precursor/hydrogen flow ratio during the process. This reduces the etching effect that the hydrogen is performing, allowing the growth of graphene and the full cover of the substrate by it.
We first perform experiments varying the gas mixture ratio, hydrogen/methane and the total pressure. By analysing images obtained by scanning electron microscopy, under stable methane/hydrogen flow rate and varying the total pressure, we study the variation in the nucleation density and size of the graphene domains. Under stable pressure and varying the hydrogen flow, we observe the anisotropical etching that the second performs when its concentration exceed an equilibrium amount
Samples grown under different conditions have been observed by SEM, using the Image J software. The amount of samples analysed can be seen in the size distribution histograms presented in this chapter. We keep a stable methane/hydrogen ratio, 5/20 sccm, and control the total pressure in the chamber by rotating the conductance valve which is placed in the turbomolecular pump. In Figure 2, we have the series of samples that were grown at 20 min, in a range of pressures between 12.5 and 20 Pascal. To control the hydrogen effect, we perform growths of the same duration, under stable pressure and methane flow and varying the hydrogen flow in the range between 10 and 20 sccm (Figure 3). All the experimental conditions are presented in Table 1. To study the size of the graphene domains, we use the length of the lobes.
Sample (corresponding image)
Total pressure (Pa)
Hydrogen flow (sccm)
Crystal’s lobe length (μm)
Nucleation density (nucleus/1000 μm2)
% Surface cover
Image 2a
12.5
20
13
0.8
15
Image 2b
15
20
27
1.2 (full cover)
100
Image 2c
17.5
20
14
3.7
82
Image 2d
20
20
32
0.5
40
Image 3a
15
10
30.5
2.6
55
Image 3b
15
15
30.1
0.8
82
Image 3c
15
20
27
1.3
95
Table 1.
Experimental conditions of the samples presented in Figures 2 and 3. The methane flow is the same in all experiments, 5 sccm, as well as the growth time (20 min) and temperature is 1040°C. In the table, the effect of growth total pressure and hydrogen flow to the crystal size as well as the nucleation density is presented.
Figure 2.
Scanning electron emission images of graphene grown in stable methane/hydrogen (5/20 sccm) flows under different total pressures. Figure (a) 12.5 Pa total pressure, (b) 15 Pa, (c) to 17.5 Pa, (d) to 20 Pa. The size of the crystals is dependent on the growth total pressure in a not linear way. In panel (b) is being provided a Raman spectrum of the continuous graphene film after its transfer on top of SiO2. The length of the X direction is 200 μm in all figures.
Figure 3.
Scanning electron microscopy images of graphene grown under 5 sccm of methane, at 15 Pa total pressure, in 1040°C, during 20 min. Varying the hydrogen flow, at (a) 10, (b) 15 and (c) 20 sccm affects the morphology of the film. The scale bar is in all the images 10 μm. In panel (d) the plot demonstrates the percent graphene covered area. The highest coverage, ~95% corresponds to the highest hydrogen flow.
2.3. Temperature effect
We investigated the growth of graphene in the range between 970 and 1070°C. Below that temperature graphene nucleation was not observed, while the upper limit was chosen in order to be as close as possible to copper melting temperature (1084°C). The rest of the growth process is followed as explained in the previous chapter. The pressure is stable at 15 Pa and the CH4/H2 = 5/20. The only varying factor is the growth temperature (Table 2).
Sample
Methane flow (sccm)
Hydrogen flow (sccm)
Pressure (Pa)
Temperature (°C)
1
5
20
15
970
2
5
20
15
990
3
5
20
15
1030
4
5
20
15
1070
Table 2.
(a) Graph image exhibiting the various steps of the growth process and (b) growth conditions of the different samples.
2.4. Strain control via the H2 flow
To study the effect of hydrogen in the formation of ripples in the graphene surface, we have performed growths where only the flow of hydrogen is varying. The rest of the parameters are stable. Growth temperature is always 1040°C and the growth time is set in 20 min. The flow of methane is 5 sccm. We performed growth from 10 to 35 sccm H2 (Table 3). The growth time was always 20 min. After that time, the furnace was opened and cooling to 500°C took about 10 s.
Sample
Hydrogen flow (sccm)
Ripples density (number/µm)
2D FWHM (cm–1)
2D position (cm–1)
Strain ε (%)
A
15
2.6
32.6
2719
–0.002
B
20
3.6
26.6
2701.6
–0.0011
C
25
3.8
24.75
2694.75
–7.3E-4
D
30
4.3
30.4
2680.5
–2.6E-5
E
35
4.3
30.75
2696
–8.4E-4
Table 3.
Experimental data of the ripples density and the 2D peak characteristics (position and FWHM). The strain is calculated through the 2D peak shift.
3. Results and discussion
3.1. Copper oxide reduction
During the hydrogen plasma treatment the hydrogen radicals react with the copper oxide reducing it to metallic copper [23]. We use optical emission spectroscopy to determine and evaluate the reduction of the copper surface. The outcoming light from the discharge was collected by a spectrophotometer (Stellarnet EPP2000C), which operated in the range 300–850 nm. The evolution of the OH radical integral spectral intensity in the spectral range of 305–330 nm is a sufficient tool to evaluate the removal of the oxide [42]. Results show that the intensity of the peaks corresponding to OH radicals decrease after 5 min of plasma treatment. In particular, the first peak at 305 nm decreases from 22.6 to 5.9 a.u., as we can see in Figure 4. The reduction in the OH concentration reveals the reduction of the oxygen radicals (as a result of the oxide reduction). Nevertheless, as the copper oxide cannot be completely removed, the peak does not decrease more with further treatment [43]. Figure 5(a) shows the copper foil used as a substrate before (up and down sample) and after (medium sample) the hydrogen etching and the graphene growth. Graphene protects copper from oxidation which explains that even after the passage of days the reflected colour of the substrate does not change [44]. Copper foil before etching appears with a higher pitch of red because of the copper oxide layer on the top. After the treatment it appears brighter and large crystalline domains can be distinguished at naked eyes. This process is much more time sufficient, compared to the usual pre-annealing required for the Cu substrates taking up to several hours [32]. As an additional tool to characterize the copper surface, we used electron backscattered diffraction (EBSD). It is a large area imaging method which detects the different index copper facets. Here, EBSD is used in order to demonstrate the growth of the copper grains after the H2 plasma and the growth process, with respect to the as-received copper foil. In Figure 5, we provide the EBSD mapping of untreated polycrystalline copper foil of 75 μm (Figure 5(b)), copper foil after 20 min growth (Figure 5(c)) and copper foil after 40 min growth (Figure 5(d)). As we see, the grains of the untreated copper have various sizes with most of them not overcoming ∼30 μm2.The boundaries between the grains are randomly oriented. During the heating and the growth the necessary energy is provided to the grains in order to increase in size. In our experiments, the heating is taking place under no presence of gas, in very high vacuum, and in the order of 10−4 Pa. The growth is taking place under the presence of hydrogen and methane, in a pressure of ∼20 Pa and in a temperature of ∼1040°C. As we see in Figure 5(c) and (d), with the longer growth, the grains grow larger. We see gains of sizes up to ∼2000 μm2 for the longer growth. The edges between the grains now are much straighter. These factors affect the quality of the grown graphene later. Graphene needs smooth and large grains to grow over. Usually, the boundaries are defect sites for the graphene, so the less possible boundaries mean the less possible defects.
Figure 4.
Optical emission spectroscopy of hydrogen plasma during reduction of copper: after 1 min (red line) and after 5 min (black line). The reduction of the OH radical peak intensity in the spectral range of 305–330 nm reveals the removal of the oxide layer.
Figure 5.
(a) Polycrystalline copper foil before (up piece) and after (down piece) the hydrogen etching. The difference in the surface colour indicates the deoxidation of it. The red line indicates 4 cm. EBSD maps of (b) the as-received polycrystalline copper foil (scale bar 50 μm), (c) the foil after plasma annealing and 20 min graphene growth at 1040°C (scale bar 100 μm), and (d) the foil after plasma annealing and 50 min graphene growth (scale bar 200 μm).
3.2. Lobe’s length and nucleation density of graphene bi-dimensional islands
Graphene crystals are grown forming planar dendritic geometries. The carbon species are being attached in the border of the islands. Varying the pressure results in formation of different graphene, considering both the size and the nucleation density of the domains. The nucleation density varies 8, 12, 37, 5 nuclei/10.000 μm2, respectively, for 12.5, 15, 17.5 and 20 Pa. The different shapes of the domains that can be seen in Figure 2a are a result of the different copper orientation. As it has been explained [45] domains with four cusps grow over Cu (221) and domains with six cusps over Cu (310). The Raman spectra in the inset of Figure 2b ensures us about the single-layer nature of the graphene film. We can also observe some second-layer nucleation in some spots, below the first layer [46, 47]. We are interested in growing graphene with the lowest nucleation density possible, in order to decrease the amount of grain boundaries in the film, which usually introduce defects. For this reason, samples grown under 12.5 and 20 Pa are more adequate. We use a residual gas analyser to record the methane and hydrogen pressure during the growth. The δPH/δPCH4 ratio increases exponentially with the increase of the total pressure. This is probably due to the insufficiency of the turbomolecular pump to evacuate the low-mass atomic hydrogen. This results in higher concentration of hydrogen in the chamber.
Making some calculations, we observe that if the surface coverage is normalized with the quadratic lobe´s length , we can extract the linear dependence between it and the nucleation density. In Figure 6(a), we see the agreement between our experimental data and this model.
Figure 6.
(a) Diagram demonstrating the linear dependence between the C/L2 and the nucleation density. (b) Histogram of the lobe\'s length distribution measurements for the growth taking place in 12.5 Pa total pressure (c) and in 17.5 Pa. The tree peaks here is a result of the anisotropic growth of the lobe\'s in the (310) facet as well as the lobe\'s length in the (221) facet. (d) Same for 20 Pa total pressure. (e) Diagram presenting the variation in the nucleation density for each pressure and in relation to the copper facet. The copper facet (310) favours the nucleation.
CL2=332nE2
The value of the slope, b = 1.5 × 10–4, of the fitted line in Figure 6(a) is the constant of the surface growth rate, dS/dt as a function of the lobes growth rate dL/dt.
In Figure 6b–d, we present the histograms of the results of the lobe’s length size distribution measurements (independently of the copper facet) for the growth processes taking place at 12.5, 17.5 and 20 Pa. The two-peak distribution in histogram of Figure 6d is a result of the different growth velocity for the orientations of graphene cusps grown on the (310) copper crystalline facet. At 15 Pa, we have formation of a continuous layer, therefore we cannot estimate the size of the single domains.
3.3. Nucleation density and copper facet
From the SEM figures, we also observe a relation between the nucleation density and the copper orientation. Similar observations have been reported elsewhere [48]. According to the shape of the graphene domains, in our samples, we observe nucleation over the copper facets (221) and (310). We observe that in all pressures, nucleation density is higher in the (310) facet. The results are demonstrated in Figure 6e. Thus, we can conclude that the facet (221) is more suitable for the growth of films with fewer boundaries. This is interesting to know as it establishes the possibility of growing graphene in single crystallinity copper surfaces.
3.4. Graphene coverage
Using the Image J software, we can know the percent surface coverage with graphene. We see that for the lowest nucleation, in 12.5 and 20 Pa, the coverage is lower that for the higher ones (Figure 7). The highest coverage appears in 15 Pa growth pressure. We observe that coverage plot follows a similar fluctuation as the nucleation density plot. On the right axis, we presented the <PH2>/<PCH4> ratio of the average relative pressure values as a function of time, for the different total pressures, which follow a similar fluctuation as well, revealing a connection between the two. From the above, we underline the critical role of hydrogen. When its concentration is not sufficient, it cannot catalyze the graphene growth through the formation of active surface-bound carbon species (CyHx)s. When the concentration is too high, the etching effect is reinforced. Graphene nucleation, the growth rate and the termination size of grains are affected by competition of these two processes.
Figure 7.
On the left Y axis we see thegraphene percent coverage of the surface as a function of the total pressure. On the right Y axis we see the <PH2>/<PCH4> ratio of the average relative pressure values as a function of time, for the different total pressures. The match in the variation of the values between the two graphs is evidence of the importance of hydrogen in the graphene growth.
3.5. Effect of the growing time
When we study the effect of growth time in the formation of graphene film, we can observe clearly the etching effect (Figure 8). We obtain a continuous film in 20 min. If we prolong the growth time, we observed the etching of the film and its damage as a result of the high hydrogen concentration in the chamber. To overcome this problem, techniques have been proposed which involve performing a two-step growth [14]. In the first step, a lower flow of methane is introduced in order to achieve low nucleation. In the second step, the methane flow and pressure increase in order to rapidly fill the gaps in the surface of the film.
Figure 8.
Variation of growth time. (a) At 10 min growth, 20 μm lobe’s length crystals are obtained. (b) At 20 min growth, the film appears continuous. (c) At 30 min growth, the film appears partially damaged. (d) At 40 min growth, most of the graphene have been etched away from the catalyst substrate. The scale bar is always 50 μm.
3.6. Growth of graphene on large copper surface
We perform growth in larger copper pieces, 12 cm2 with respect to 4 cm2 that were used before. We do an extensive Raman analysis to study if graphene of same quality grows in the whole surface. The results indicate that single-layer graphene grows in the whole area, from the centre up to the edges. The spectra are obtained with a green laser. The G position appears at 1578 ± 3 cm−1 and the 2D at 2671 cm−1, confirming the single-layer nature of the film [49]. The IG/I2D ratio is 0.27 ± 0.03 with a FWHM of 30 cm−1. All data are presented in Figure 9a. Graphene of same quality is grown in the back side of the foil (Figure 9b). Then, the graphene is transferred onto different substrates, quartz and SiO2, to study possible effects. The transfer is made by electrochemical delamination of the graphene [32]. By using this method, we avoid introducing any impurities from the metal etchant. G and 2D peak appear shifted by very few cm−1. Such shifts can be due to edges, dislocations, cracks or vacancies in the sample that cause the so-called self-doping of the graphene [50].
Figure 9.
(a) Table presenting the Raman spectroscopy results. (b) Raman spectra after the transfer of the graphene film to glass (with thermally grown quartz on top, black line) and on SiO2 (red line).
3.7. Temperature effect
We are interested to study how the growth temperature can affect the nuclei formation and growth velocity of graphene. In addition, we study the formation of ripples in the graphene layer. The ability to control the formation of such ripples is of high interest if we want to obtain graphene films with enhanced mobility properties [37].
Considering the application of the hydrogen plasma, its efficiency in removing the copper oxide layer has been discussed in previous works of the authors [40] . In the same work, we provided back scattered electron microscopy figures where the evolution of the copper domains is shown. During the heating, the copper grains grow up, forming domains with size up to 104 μm2.
In Figure 10, we present the various scanning electron microscopy (SEM) images of graphene grown in different temperatures. Figure 10a corresponds to growth taking place at 970, (b) 990, (c) 1030°C and (d) 1070°C. We observe that nucleation of the graphene only occurs in the initial instants. This explains the high homogeneity in the graphene domains’ size. In addition, higher temperatures lead to lower nucleation density and higher growth rates. No second layer nucleation below the first layer is observed in any of the figures.
Figure 10.
SEM images of graphene domains grown in different temperatures: (a) at 970, (b) 990, (c) 1030 and (d) 1070°C. The X axis is always 100 μm.
In these figures, with the exception of Figure 10d, the domains do not reach the coalescence phase. Further growth times should be required to obtain a continuous graphene layer. Before, we have studied in depth the growth mechanisms of such continuous layers. We underline the dual role of the hydrogen in this process. Control of the growth is also performed through the growth pressure and its influence on the residence time of the carbon atoms in the surface. Careful selection of the above two parameters resulted in the formation of large continuous layers. Further extension of the growth time resulted in the anisotropic etching of the graphene.
Here we focus in the temperature effect and we study the kinetics of the graphene growth based on it. The study of the SEM figures provides information considering the nucleation density of the graphene crystals, growth velocity and surface coverage. Kinetics of two-dimensional graphene nucleation over copper has been studied both theoretically and experimentally by Kim et al. [51] before. When methane reaches the copper surface, it breaks down. The concentration of carbon active species increases until it reaches a critical supersaturation level. Nucleation starts upon this point. Nucleation and growth of the supersaturated nuclei deplete the adsorbed carbon species surrounding them and the nucleation rate becomes negligible. The growth of the nuclei continues until supersaturated amount of surface carbon species is consumed and equilibrium between graphene, surface carbon and CH4/H2 is reached. Depending on the amount of available carbon, graphene domains will either coalesce to form a continuous layer or stop growing to reach a saturated, final incomplete coverage [52].
To understand the kinetics of the existing nucleation model, we study the nucleation density and growth rate with respect to the growth temperature. In Figure 11a, we show the Arrhenius plot of the temperature-dependent density of graphene nuclei. According to Robinson model [53], there are two nucleation regimes which are a result of the competition between the processes of adatom capture, surface diffusion and re-evapouration. In the high temperature regime (T > 870°C), the desorption of the carbon adatoms is significant compared to their mobility, so their lifetime and nucleation rate is desorption-controlled. The decrease in the nucleation density for increasing temperatures is explained due to the increase of the desorption rate, reducing the probability of further nucleation, as discussed by Kim et al. [51]. In Figure 11b, we observe how the growth rate increases with the increase of the growth temperature. In this plot, we assume that the growth is linear for the growth time. Higher growth rates occur thanks to the lower nuclei density. Previous studies [51] have shown no significant differences of the growth rates on three main crystalline orientations [Cu(111), Cu(100) and Cu(103)] of the polycrystalline Cu.
Figure 11.
(a) Analysis of graphene nucleation behaviour. Natural logarithm of density of graphene nuclei versus 1/T from SEM analysis. (b) Linear plot of the graphene nucleus growth rate versus 1000/T.
To calculate the activation energy, we will apply the kinetic model proposed by Xing et al. [54]. According to this model, growth rate is proportional to the uncovered copper surface.
dcoveragedt=a(1−coverage)E3
According to the above equation, the rate is the highest in the initial moments and decreases during the graphene growth. By integrating it, we derive the coverage equation coverage =– eat+1 where t is the time and a is a constant defined by the growth temperature. As seen in Figure 12b, coverage increases with the increase in temperature, result which can be explained taking into account the previous observations considering the nucleation density and growth rate behaviour. On the same time, a increases with the temperature as well. To calculate the activation energy E of the graphene growth, we use the Arrhenius equation a ~ e–E/kT, where k is the the Boltzmann’s constant and T is the absolute temperature. From the Arrhenius plot of Figure 12a, we can extract the activation energy from the slope of the linear fit. The activation energy is calculated to be 3.01 eV. In previous studies, a wide range of activation energies (1–3) have been proposed for graphene growth over copper. The energy barrier depends on the growth temperature and on the dominant nucleation mechanism. In lower temperatures, the adsorption energies of carbon monomers depend on the crystalline orientation of copper [55]. In higher temperatures, where desorption is the principle responsible nucleation mechanism, the differences in activations energies are minimal with respect to the copper orientation, both for low and atmospheric pressure CVD[11].
Figure 12.
(a) Arrhenius plot of the ln (a) as a function of 1000/T. From the slope of the linear fitting we obtain the activation energy. (b) Graphene coverage on Cu as a function of different growth temperatures.
3.8. Strain control via the H2 flow
By the SEM images, we could determine the density of the ripples in each sample. Figure 13 shows the SEM images for the different hydrogen flows in the studied range.
Figure 13.
SEM images of graphene/copper surface: (a–e) graphene films growth at different hydrogen flows, resulting in an increase in the ripple\'s density. (a) 15, (b) 20, (c) 25, (d) 30 and (e) 35 sccm hydrogen flow. Scale bar is always 1 µm.
Figure 14a provides the Raman spectrum corresponding to samples grown at different hydrogen flows. The copper photoluminescence background has been removed from all the spectra. In previous works, the copper luminescence has been attributed to the different quenching effect of the deposited graphene owing to probably irregular thickness distribution. Another explanation can be the quenching effect of graphene as a function of distance between Cu surface and graphene. The suspended graphene can result from the ripple\'s formation in the copper surface during the cooling step [37]. In Figure 14b, we can see an enlarged image of the above spectra where the shift in the 2D peak becomes evidenced by the evolution of the hydrogen flow.
Figure 14.
(a) Raman spectra of the different samples grown at several hydrogen flow rates. (b) Enlarged figure of the 2D peak of the same samples.
The absence of a D peak in the spectra presented in Figure 14a proves the highly crystalline nature and the absence of defects in the graphene films. The ration ID/IG is proportional to the mean distance between two defect points in a graphene film. The absence of the D peak corresponds to pristine graphene [56]. A small D peak can be distinguished in the spectra corresponding to graphene growth under the higher hydrogen flow rate (35 sccm) probably owing to the hydrogen etching on the graphene surface. The defects concentration of the graphene surface can be obtained by Eq. (4) [57]
nD(cm−2)=1014π2[CA(rA2−rS2)+CSrS2]IDIGE4
nD=1.02×1011cm−2E5
Where rAand rS are the radius of two circular areas measured from the defect site. The first length, rS, is the radius of the structurally disordered area around the defect. rA defines the disk where the D peak scattering takes place and it defines the activated area. CA depends only on the Raman mode, being roughly given by the ratio of the electron-phonon coupling between the two phonons considered. CS,x represents the Raman cross section of I(x)/I(G) associated with the distortion of the crystal lattice after defect introduction per unit of damaged area. The following parameters were reported for intensity measured as height: rA ∼ 3 nm, rS ∼ 1 nm, CA = 4.2, CS = 0.87[57]. For samples grown at lower hydrogen flow rate, the presence of defects from Raman analysis is negligible.
In previous works[58], the formation of ripples in graphene during CVD growth has been studied. During CVD growth, graphene tends to replicate the morphology of the substrate. When graphene is grown over copper foil, the formation of these ripples is a common phenomenon. When the copper foil is exposed at the same heating and cooling process (as CVD graphene growth) but in the absence of any hydrocarbon, no ripples are formed and the formation of dendrite-like structures or ‘snowflakes’ is observed. Therefore, the presence of hydrocarbon seems a necessary condition for the formation of ripples.
One possible mechanism describing the ripple\'s formation is the following. At high temperatures, above 1000°C, a massive near-surface movement of the copper atoms takes place underneath the growing graphene. This gives rise to the surface reconstruction and to the formation of nano-ripples. While cooling down to room temperature, the copper substrate contracts, whereas the graphene which is on top tries to expand according to its negative thermal expansion coefficient[59]. In the areas where graphene is pinned to the copper, it is displayed to a strong compressive stress, whereas in the areas where the graphene is suspended above the nano-ripples it is allowed to relax some amount of the compressive strain through out-of-plane deformation (rippling)[60–61].
In the present work, when we measure the ripples in the samples corresponding at different hydrogen flows, a sigmoid increase of the density of ripples at higher hydrogen flows takes place (Figure 15). More specifically, the ripple density increases from 2.6 to 4.3 ripples/µm while the hydrogen flow increases from 15 to 30 sccm (with a step of 5 sccm). Finally, at 35 sccm of hydrogen flow the ripple density is 4.3 ripples/µm as well.
Figure 15.
Ripples density of graphene for various hydrogen flows.
In all above described experiments, the methane flow was kept constant; therefore, the variation of the hydrogen flow is the factor that apparently affects the density of the formed ripples. Figure 16 shows the Raman measurements of the different hydrogen flows. In Figure 16a, we see the full width half maximum (FWHM) of the 2D peak versus the hydrogen flow. Despite some extreme values, mainly in the samples grown at 25 and 30 sccm of hydrogen flow, the majority of the spectra presents an FWHM close to the value of 28 cm–1, which is the reference value of the 2D peak FWHM for single-layer graphene[62 ]. Narrower 2D bands are correlated with flat and undoped regions on the Cu (100) and (110) surfaces. The generally compressed (0.3% of strain) and n-doped (Fermi level shift of 250 meV) graphene on Cu (111) shows the 2D band FWHM minimum of 20 cm-1. In contrast, graphene grown on Cu foil under the same conditions reflects the heterogeneity of the polycrystalline surface and its 2D band is accordingly broader with FWHM > 24 cm–1 [63]. The authors have previously studied the polycrystalline nature of the copper surface by electron backscatter diffraction (EBSD) mapping. After the heating up to 1040°C and posterior cooling, the domains increase significantly in size. According to these observations, graphene domains grow forming different morphologies which depend on the copper lattice orientation, in accordance to previous theoretic and experimental results[45]. In concrete, we have observed how graphene domains with a four-lobe morphology grow over the Cu (100) plane, while graphene domains with a butterfly-like morphology grow over the Cu (221) plane.
Figure 16.
(a) Plot of the 2D FWHM with respect to the different hydrogen flows. The blue line corresponds to the reference value of the 2D peak FWHM for single-layer graphene, (b) plot of the 2D position with respect to the different hydrogen flows. The blue line at 2680 cm–1 corresponds to the position of relaxed graphene.
By the shift in the 2D peak, we calculate the graphene strain. Figure 16b shows the position of the 2D peak versus the hydrogen flow. The position of the 2D peak shifts from 2719 to 2680 cm–1 with the increase of the hydrogen flow from 15 to 30 sccm. The values presented in Table 1 regarding the 2D FWHM and the 2D position for the different hydrogen flows are the average values resulting from those presented in the plots of Figure 16a and b.
The results reveal an average red-shift of the 2D peak following the hydrogen flow increase. We have associated this shift with the strain introduced to the graphene as a result of the ripple\'s formation and the partial ablation of graphene. Such shifting of the 2D peak between suspended and supported graphene has been observed before[64]. Rao et al. have observed a shifting of the order of 10 cm–1. In our case, we propose to explain the decrease of the compressive strain effect as the origin of this shift. As mentioned earlier, the graphene replicates the morphology of the copper substrate. In order to understand this phenomenon, we propose a mechanism based on thermal mobility of Cu adatoms. Surface adatoms can take energy from hydrogen bombardment, which facilitates their migration and ripple\'s formation.
Theory of thermal grooving was first developed by Mullins et al.[65]. In this work, surface migration is proposed as the most probable mechanism of groove formation. The origin of the grooves can be due to evapouration or due to surface diffusion of the copper adatoms. As temperature falls, surface diffusion is favoured thanks to its small activation energy, in compare to the enthalpy of evapouration. Although, in their model, Mullins et al. consider that the grooves are formed during the heating of the surface. As the development of the groove is proportional to t1/4, where t is the annealing time, they come in accordance with experimental results which indicate that the grooves did not develop more after some hours of annealing.
Today we know thank to in situ observations that the grooves, or ripples as we refer to in our text, develop during the cooling step. As observed by in situ scanning electron microscopy[66], ripples are formed in the copper surface during the cooling step, in concrete in the range between 600 and 700°C. Surface re-construction of the pre-melted copper occurs in this range of temperatures.
The model proposed by Mullins allows us to calculate the depth of the groove when we know the separation of two consecutive maxima.
sd=4.73mE6
where s is the separation between the two maxima, d is the groove depth and m = tanb = 0.10 (b is the equilibrium angle).
As we know the separation of the two maxima from the SEM images (~0.5μm), we calculate the depth d = ~10 nm. Values of this order are very similar to the ones observed by other authors[67].
The increase in the hydrogen bombardment increases the adatoms density and, therefore, the ripple\'s density. From molecular dynamic simulations that have been performed by Rosen et al. [68], it has been calculated that the positive energy transfer that can occur during the bombardment of metallic clusters by a gas. This energy can promote the diffusion of the metallic adatoms, promoting the formations of ripples. Graphene grows overlapping the copper ripples. The migration of the copper adatoms results in the formation of convex regions where copper is disordered. Ordered copper adatoms remain in the concave regions (Figure 17a)[69]. The ordered placement of the copper adatoms in these regions favours the matching with the graphene.
Figure 17.
(a) Illustration of the ripple\'s formation as a result of the hydrogen bombardment. (b) Aspect of the graphene film after its ablation from the concave regions.
As explained above, while cooling, the copper foil contracts. This induces an increase in the compressive stress of the graphene in the concave region. In the convex region, the graphene detaches from the copper and remains suspended and relaxed. This detachment probably is the reason that graphene in the convex regions favours the hydrogen storage. As explained in previous works by experimental and density functional theory calculations[69], graphene chemisorption of atomic hydrogen is energetically favourable in the convex regions (Figure 18b). In that work, scanning tunnelling microscopy (STM) images have shown a large increase in corrugation due to the C−H bonds on the convex areas of the graphene surface after the exposure of pristine graphene to atomic hydrogen. DFT simulations have observed and resolved hydrogen dimers and tetramers on top of the carbon atoms, on distances that do not extend beyond 4 Å between them.
Figure 18.
Calculated compressive strain (Eq. 7) of graphene layer for the different hydrogen flow rates from the 2D Raman peak shift.
According to Goler et al.[69] calculation and using 650°C (∼930 K) as the approximate temperature of the hydrogen desorption from the puckered graphene, the only positions where hydrogen is stable at elevated temperatures, a desorption energy barrier of 1.4 eV is calculated. The hydrogen dimers are calculated to be as stable as molecular hydrogen. This is a result of the favourable hydrogen chemisorption on the convex areas, like we propose in the model of Figure 5b. In this case, the local curvature increases after the first H atom is adsorbed because the carbon atom protrudes out of the graphene plane. This effect induces adhesion of subsequent H atoms. In accordance with Goler et al., the adhesion of atomic hydrogen becomes thus barrierless.
In our work, we consider that the red-shift of the 2D peak is a result of the reduction/absence of the compressive strain with the increase in the hydrogen flow. With the increase in the ripples density, more regions where graphene is relaxed are contained in each spectrum, resulting in reinforcing of the red-shift of the 2D peak.
From the shift in the 2D peak, we can calculate the strain of the graphene. This is calculated by equation
ε=−Δu2D2u2D0γDE7
where ε is the value of the strain, γD = 3.55 is the Gruneisen parameter and Δu2D denotes the shift of the frequency of the 2D phonon mode with respect to u2D0=2680cm−1 (which is the position of the 2D peak for unstrained pristine graphene) [70]. The compressive strain is reduced with the increase of the hydrogen flow from ε= –0.2% for 15 sccm of hydrogen to ε = –0.026% for 30 sccm of hydrogen flow rate (Figure 18).
4. Conclusions
In the present chapter, we study the CVD growth of graphene over copper foils. We are interested in the effect of the growth parameters, gases mixtures, pressure, temperature in the graphene synthesis. The characterization of SEM images gives information about the effect of hydrogen in the process. The lower nucleation density results in formation of larger crystals but lower total coverage. Considering the coverage, the etching effect of hydrogen in the graphene film plays an important role. In addition, we underline the linear dependence between the C/L2 and the nucleation density. We highlight the increase of hydrogen partial pressure under stable flow and the fact that the relative pressure <PH2>/<PCH4> ratio diagram follows the same variation as the percent coverage diagram.
We study the kinetics, from a perspective of temperature dependence, of CVD-grown graphene in low pressure and over polycrystalline copper substrate. Growth temperature ranges between 970 and 1070°C. The growth takes place in a methane/hydrogen atmosphere. In all samples, high-quality, defect-free single-layer graphene is grown, as revealed by Raman spectroscopy. SEM images analysis provide information considering the nucleation density, in the range between 0.5 and 8 nuclei/1000 μm2, and the growth rate, in the range between 150 and 1400 μm2/20 min, of the graphene domains. Activation energy of 3.01 eV has been derived from the Arrhenius equation. Finally, we study the profile of the ripples formed in the graphene surface. Ripples of 0.2 μm and 4 nm height are formed, introducing an intrinsic strain in the graphene. The geometry of the ripples is not affected by the growth temperature.
Through the control of the flow, the ripple density is regulated. An increase in the flow of hydrogen can reduce the compressive strain, as a result of the levitation of graphene from the copper substrate in the concave regions. However, the introduced hydrogen flow should be selected with care, as high flow rates can lead to anisotropic etching of the graphene film.
Acknowledgments
The first author was founded by the Greek State Scholarships Foundation (IKY). The authors would like to thank the CCiT-UB for help with the structural and morphological characterization. This work was developed in the frame of the project 2014SGR984 of AGAUR from the Generalitat de Catalunya and the projects MAT2010-20468 and ENE2014-56109-C3 1-R of MICINN from the Spanish Government.
\n',keywords:"graphene films, chemical vapour deposition, ripples formation, hydrogen effect",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/54139.pdf",chapterXML:"https://mts.intechopen.com/source/xml/54139.xml",downloadPdfUrl:"/chapter/pdf-download/54139",previewPdfUrl:"/chapter/pdf-preview/54139",totalDownloads:1187,totalViews:382,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,dateSubmitted:"September 6th 2016",dateReviewed:"January 11th 2017",datePrePublished:null,datePublished:"May 17th 2017",dateFinished:null,readingETA:"0",abstract:"Currently, the graphene industry is moving forward to the import of graphene in a number of novel applications. To take full advantage of the excellent properties of the material, the standardization of the growth process is an emergency. The suitable growth technique should ensure the high yield, accompanied by high quality of single-layer graphene sheets. Chemical vapour deposition is the technology that fulfils the above requirements, promoting the growth of largescale graphene films through automatized processes. In the present chapter, we present the latest advances in this field, summarizing the most recent publication activity of the authors. The results outline how the control in the growth process over parameters like the gases flow, growth temperature and pressure can affect the nucleation density of graphene domains, the growth rate and percent coverage. Growth of graphene domains with different morphologies depends on the crystallographic orientation of the copper lattice. At the same time, the formation of ripples occurs in the graphene surface as a result of the copper foil compression during the cooling step. These ripples are responsible for the appearance of a compressive stress in the graphene sheets. We demonstrate the control over such stress through the variation in the hydrogen flow during the growth.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/54139",risUrl:"/chapter/ris/54139",book:{slug:"graphene-materials-structure-properties-and-modifications"},signatures:"Stefanos Chaitoglou, Enric Bertran and Jose Luis Andujar",authors:[{id:"22835",title:"Prof.",name:"Enric",middleName:null,surname:"Bertran",fullName:"Enric Bertran",slug:"enric-bertran",email:"ebertran@ub.edu",position:null,institution:{name:"University of Barcelona",institutionURL:null,country:{name:"Spain"}}},{id:"38322",title:"Dr.",name:"José-Luís",middleName:null,surname:"Andújar",fullName:"José-Luís Andújar",slug:"jose-luis-andujar",email:"jandujar@ub.edu",position:null,institution:null},{id:"195457",title:"Dr.",name:"Stefanos",middleName:null,surname:"Chaitoglou",fullName:"Stefanos Chaitoglou",slug:"stefanos-chaitoglou",email:"schaitog@gmail.com",position:null,institution:{name:"University of Barcelona",institutionURL:null,country:{name:"Spain"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Experimental part",level:"1"},{id:"sec_2_2",title:"2.1. Pretreatment of copper foil",level:"2"},{id:"sec_3_2",title:"2.2. Graphene CVD growth",level:"2"},{id:"sec_4_2",title:"2.3. Temperature effect",level:"2"},{id:"sec_5_2",title:"2.4. Strain control via the H2 flow",level:"2"},{id:"sec_7",title:"3. Results and discussion",level:"1"},{id:"sec_7_2",title:"3.1. Copper oxide reduction",level:"2"},{id:"sec_8_2",title:"3.2. Lobe’s length and nucleation density of graphene bi-dimensional islands",level:"2"},{id:"sec_9_2",title:"3.3. Nucleation density and copper facet",level:"2"},{id:"sec_10_2",title:"3.4. Graphene coverage",level:"2"},{id:"sec_11_2",title:"3.5. Effect of the growing time",level:"2"},{id:"sec_12_2",title:"3.6. Growth of graphene on large copper surface",level:"2"},{id:"sec_13_2",title:"3.7. Temperature effect",level:"2"},{id:"sec_14_2",title:"3.8. Strain control via the H2 flow",level:"2"},{id:"sec_16",title:"4. 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Phys. 2011;52:D927–32.'},{id:"B43",body:'Chang Y M, Leu J, Lin B H, Wang Y L and Cheng Y L. Comparison of H2 and NH3 treatments for copper interconnects. Adv. Mater. Sci. Eng. 2013;7:825195.'},{id:"B44",body:'Chen S, Brown L, Levendorf M et al. Oxidation resistance of graphene-coated Cu and Cu/Ni alloy. ACS Nano 2011;5:1321–7.'},{id:"B45",body:'Meca E, Lowengrub J, Kim H, Mattevi C and Shenoy V B. Epitaxial graphene growth and shape dynamics on copper: phase-field modeling and experiments. Nano Lett. 2013;13:5692–7.'},{id:"B46",body:'Hong J, Park M K, Lee E J, Lee D E, Hwang D S and Ryu S. Origin of new broad Raman D and G peaks in annealed graphene. Sci. Rep. 2013;3:2700.'},{id:"B47",body:'Wu P, Zhai X, Li Z and Yang J. Bilayer graphene growth via a penetration mechanism. J. Phys. Chem. C 2014;118:6201–6.'},{id:"B48",body:'Wood J D, Schmucker S W, Lyons A S, Pop E and Lyding J W. Effects of polycrystalline Cu substrate on graphene growth by chemical vapour deposition. Nano Lett. 2011;11:4547–54.'},{id:"B49",body:'Costa S D, Righi A, Fantini C, Hao Y, Magnuson C, Colombo L, Ruoff R S and Pimenta A. Resonant Raman spectroscopy of graphene grown on copper substrates. Solid State Commun. 2012;152:1317–20.'},{id:"B50",body:'Das A, Chakraborty B and Sood A. Raman spectroscopy of graphene on different substrates and influence of defects. Bull. Mater. Sci. 2008;31:579–84.'},{id:"B51",body:'Kim H, Mattevi C, Reyes Calvo M, Oberg J, Artiglia L, Agnoli S, Hirjibehedin C, Chhowalla M and Saiz E. Activation energy paths for graphene nucleation and growth on Cu. ACS Nano 2012;6:3614–23.'},{id:"B52",body:'Loginova E, Norman C B, Peter J F and Kevin F M. Evidence for graphene growth by C cluster attachment. New J. Phys. 2008;10:093026.'},{id:"B53",body:'Robinson V N E and Robins J L. Nucleation kinetics of gold deposited onto UHV cleaved surfaces of NaCl and KBr. Thin Solid Films 1974;20:155–75.'},{id:"B54",body:'Xing S, Wu W, Wang Y, Bao J and Pei S. Kinetic study of graphene growth: temperature perspective on growth rate and film thickness by chemical vapour deposition. Chem. Phys. Lett. 2013;580:62–6.'},{id:"B55",body:'Hayashi K, Sato S, Ikeda M, Kaneta C and Yokoyama N. Selective graphene formation on copper twin crystal. J. Am. Chem. Soc. 2012;134:12492.'},{id:"B56",body:'Lucchese M M, Stavale F, Martins Ferreira E H, Vilani C, Moutinho M V O, Capaz R, Achete C and Jorio A. Quantifying ion-induced defects and Raman relaxation length in graphene. Carbon 2010;48:1592–7.'},{id:"B57",body:'Eckmann A, Felten A, Verzhbitskiy I, Davey R and Casiraghi C. Raman study on defective graphene: effect of the excitation energy, type, and amount of defects. Phys. Rev. B 2013;88:035426.'},{id:"B58",body:'Cancado L G, Jorio A, Ferreira E H M, Stavale F, Achete C A, Capaz R B, Moutinho M V O, Lombardo A, Kulmala T S and Ferrari A C. Quantifying defects in graphene via Raman spectroscopy at different excitation energies. Nano Lett. 2011;8:3190.'},{id:"B59",body:'Paronyan T M, Pigos E M, Chen G and Harutyunyan A R. Formation of ripples in graphene as a result of interfacial instabilities. ACS Nano 2011;5:9619–27.'},{id:"B60",body:'Yoon D, Son Y and Cheong H. Negative thermal expansion coefficient of graphene measured by Raman spectroscopy. Nano Lett. 2011;11:3227–31.'},{id:"B61",body:'Tapasztó L, Dumitrica T, Kim S, Nemes-Incze P, Hwang C and Biró L P. Breakdown of continuum mechanics for nanometre-wavelength rippling of graphene. Nat. Phys. 2012;8:739–42.'},{id:"B62",body:'Lin Z, Ye X, Han J, Che Q, Fan P, Zhang H, Xie D, Zhu H and Zhong M. Precise control of the number of layers of graphene by picosecond laser thinning. Sci. Rep. 2015;5:11662.'},{id:"B63",body:'Frank O, Veravova J, Hol V, Kavan L and Kalbac M. Interaction between graphene and copper substrate: the role of lattice orientation. Carbon 2014;68:440–51.'},{id:"B64",body:'Rao R, Chen G, Arava L M, Kalaga K, Ishigami M, Heinz T F, Ajayan P M and Harutyunyan A R. Graphene as an atomically thin interface for growth of vertically aligned carbon nanotubes. Sci. Rep. 2013;3:1891.'},{id:"B65",body:'Mullins W W. Theory of thermal grooving. J. Appl. Phys. 1957;28:333.'},{id:"B66",body:'Wang Z, Weinberg G, Zhang Q, Lunkenbein T, Klein-Hoffmann A, Kurnatowska M, Plodinec M, Li Q, Chi L, Willinger M et al. Direct observation of graphene growth and associated copper substrate dynamics by in situ scanning electron microscopy. ACS Nano 2015;9:1506–19.'},{id:"B67",body:'Meng L, Su Y, Geng D, Yu G, Liu Y, Dou R, Nie J and He L. Hierarchy of graphene wrinkles induced by thermal strain engineering. Appl. Phys. Lett. 2013;103:251610.'},{id:"B68",body:'Westergren J, GrSnbeck H, Rosh A and Nordbolm S. Molecular dynamic simulations of metal cluster cooling and heating in noble gas atmosphere. Nanostruct. Mater. 1999;12:281–6.'},{id:"B69",body:'Goler S, Coletti C, Tozzini V, Piazza V, Mashoff T, Beltram F, Pellegrini V and Heun S. Influence of graphene curvature on hydrogen adsorption: Toward hydrogen storage devices. J. Phys. Chem. C 2013;11:11506–13.'},{id:"B70",body:'Troppenz G V, Gluba M A, Kraft M, Rappich J and Nickel N H. Strain relaxation in graphene grown by chemical vapour deposition. J. Appl. Phys. 2013;114:214312.'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Stefanos Chaitoglou",address:"schaitog@gmail.com",affiliation:'
FEMAN Group, IN2UB, Department of Applied Physics, University of Barcelona, Barcelona, Catalonia, Spain
FEMAN Group, IN2UB, Department of Applied Physics, University of Barcelona, Barcelona, Catalonia, Spain
'},{corresp:null,contributorFullName:"Jose Luis Andujar",address:null,affiliation:'
FEMAN Group, IN2UB, Department of Applied Physics, University of Barcelona, Barcelona, Catalonia, Spain
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\n
1. Introduction
\n
Malnutrition is a universal public health problem in both children and adults globally [1]. It is not only a public health concern but it is an impediment to global poverty eradication, productivity and economic growth. By eliminating malnutrition, it is estimated that 32% of the global disease burden would be removed [2]. As a widespread serious problem affecting children in developing countries, progress towards tackling the different forms of malnutrition remains relatively slow [3]. Malnutrition occurs due to an imbalance in the body, whereby the nutrients required by the body and the amount used by the body do not balance [1]. There are several forms of malnutrition and these include two broad categories namely undernutrition and over nutrition. Undernutrition manifests as wasting or low weight for height (acute malnutrition), stunting or low height for age (chronic malnutrition), underweight or low weight for age, and mineral and vitamin deficiencies or excessiveness. Over nutrition includes overweight, obesity and diet-related non-communicable diseases (NCDs) such as diabetes mellitus, heart disease, some forms of cancer and stroke [1]. Malnutrition is an important global issue currently, as it affects all people despite the geography, socio-economic status, sex and gender, overlapping households, communities and countries. Anyone can experience malnutrition but the most vulnerable groups affected are children, adolescents, women, as well as people who are immune-compromised, or facing the challenges of poverty [3].
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According to the World Health Organization (WHO), 462 million adults are underweight, while 1.9 billion adults are overweight and/or obese. In children under 5 years of age, 155 million are stunted, 52 million are wasted, 17 million are severely wasted and 41 million are overweight and/or obese [1]. The manifestation of malnutrition is multifold, but the paths to addressing prevention are key and include exclusive breastfeeding for the first 2 years of life, diverse and nutritious foods during childhood, healthy environments, access to basic services such as water, hygiene, health and sanitation, as well as pregnant and lactating women having proper maternal nutrition before, during and after the respective phases (levels and trends) [3].
\n
It is vital that malnutrition is addressed in children as malnutrition manifestations and symptoms begin to appear in the first 2 years of life [4]. Coinciding with the mental development and growth periods in children, protein energy malnutrition (PEM) is said to be a problem at ages 6 months to 2 years. Thus, this age period is considered a window period during which it is essential to prevent and/or manage acute and chronic malnutrition manifestations [4, 5, 6]. Child and maternal malnutrition together have contributed to 3.5 million annual deaths. Furthermore, children less than 5 years of age have a disease burden of 35% [7]. In 2008, 8.8 million global deaths in children less than 5 years old were due to underweight, of which 93% occurred in Africa and Asia. Approximately one in every seven children faces mortality before their fifth birthday in sub Saharan Africa (SSA) due to malnutrition [8].
\n
Young malnourished children are affected by compromised immune systems by succumbing to infectious diseases and are prone to cognitive development delays, damaging long term psychological and intellectual development effects, as well as mental and physical development that is compromised due to stunting [7, 9, 10, 11]. A malnutrition cycle exists in populations experiencing chronic undernutrition and in this cycle, the nutritional requirements are not met in pregnant women. Thus, infants born to these mothers are of low birth weight, are unable to reach their full growth potential and may therefore be stunted, susceptible to infections, illness, and mortality early in life. The cycle is aggravated when low birth weight females grow into malnourished children and adults, and are therefore more likely to give birth to infants of low birth weight as well [9]. Malnutrition is not just a health issue but also affects the global burden of malnutrition socially, economically, developmentally and medically, affecting individuals, their families and communities with serious and long lasting consequences [1].
\n
Studies in Sudan, Ethiopia, Bangladesh, and Haiti have indicated that the causes of malnutrition are multi-faceted, with both environmental and dietary factors contributing to malnutrition risk in young children [12]. Diet and disease have been identified as primary immediate determinants; with household food security, access to health facilities, healthy environment, and childcare practices influenced by socio-economic conditions [13]. Mother’s antenatal visit and body mass index were also identified as risk factors for malnutrition [14]. In children under 3 years of age some of the main factors included poor nutrition, feeding practices, education and occupation of parent/caregiver, residence, household income, nutrition knowledge of mother [15]. These studies have suggested that nutrition education for the mother is important, as it is a resource that mothers can utilize for better care of their children. It can also provide the necessary skills required for childcare, improvement of her feeding practices, enable her to make choices and have preference of health facilities available, increase her nutritional needs awareness, and give her the chance of changing her beliefs regarding medicine and disease [16]. Some of the nutritional interventions that have had some success in addressing malnutrition include exclusive breastfeeding for the first 6 months of life, vitamin A supplementation, deworming, zinc treatment and rehydration salts for diarrhea, food fortification, and folic acid/iron for lactating and pregnant women, improvement of access to piped water and hygiene [17]. These interventions have positively influenced the development, growth and survival of children [18]. Malnutrition is not a uniform condition and therefore groups and areas that experience high risk of malnutrition must be identified and targeted interventions available to assist [17].
\n
To determine both over and undernutrition, assessment of the nutritional status is important. This identifies those individuals who are vulnerable and at risk, and how to guide a response [19]. In determining the nutritional status of a child, it must be referenced in comparison to a healthy child [20]. Most of the anthropometric indices are used with reference tables such as that of the National Center for Health Statistics (NCHS) and the currently widely recommended and used 2006 WHO child growth standards [21]. In expressing anthropometric indices relative to a reference population, the measurements are developed using the median and standard deviations of the reference populations, which are known as Z scores [22, 23, 24]. The Z score classification system interprets weight for age (W/A), weight for height (W/H) and height for age (H/A). Z scores describe a child’s mid upper arm circumference (MUAC)/weight/height in comparison to the median and the mid upper arm circumference (MUAC)/weight/height of the child relative to the reference population [25]. The anthropometric value is expressed by the two score system as “a number of standard deviations or Z scores below or above the reference mean or median value” [26]. Thus, the Z score is calculated as follows:
\n
\n\nZ\n\nscore\n=\n\n\nobserved value\n−\nmedian value of the reference population\n\nstandard deviation value of reference population\n\n\nE1
\n
\n
\n
2. Classification of malnutrition
\n
As previously mentioned malnutrition consists of both over and undernutrition (Table 1).
\n
\n
2.1 Undernutrition
\n
Undernutrition does not only affect the health of individuals but impacts greatly on the growth of the economy and productivity, as well as the eradication of poverty. To support their growth and development, infants and young children have increased nutritional needs and therefore are most affected by undernutrition [27, 28]. Prolonged malnourished status in children can lead to the development of motor function and physical growth delays, lack of social skills, and low infection resistance, thus making them susceptible to common ailments and infections [28, 29]. Additionally, due to frequent infection, susceptible children become engaged in a negative cycle whereby infections lead to growth delays and their learning abilities are hindered, and infections in malnourished children may lead to childhood mortality [30].
\n
Undernutrition is subdivided into two categories that include micronutrient malnutrition and growth failure. To differentiate between acute or chronic malnutrition, the nutritional status of an individual is assessed by using anthropometry [27]. According to Zere and McIntyre [31], anthropometry is advantageous over biochemical evaluation, as it is less invasive and cost effective; hence, in addressing child survival nutritional status anthropometry is one of the favored predictors [32]. To assess the growth status of children the most common indices used in anthropometry include low weight for height or wasting, stunting or low height for age, underweight or a low weight for age and waist/arm circumference.
\n
\n
\n
2.2 Undernutrition/protein energy malnutrition (PEM)
\n
In PEM the condition is characterized by the individual being susceptible to infection due to long-term consumption of protein and energy that is insufficient to meet the body’s needs. While the body may first attempt to utilize the nutrients to meet the energy demands, if there is insufficient intake of energy then the consumed protein is used to meet the energy demands and does not address the functions of the protein in the body, hence leading to PEM. While PEM requires the measuring of growth parameters such as height and weight as it is not immediately obvious, in severe PEM children present with marasmus and kwashiorkor [33, 34]. Marasmus is characterized by a lack of protein and energy in the diet, while an inadequate intake of protein causes kwashiorkor. Marasmus or severe wasting (below −3SD) presents with a MUAC less than 115 mm in children under age five. Children with marasmus present with an “old man” appearance and are very thin [33]. In kwashiorkor, a child does not necessarily appear as undernourished but there is the presence of oedema. The children present with hair that is discolored and skin that is shiny and very tight. The weight for height is greater than or equal to −2SD. In marasmic-kwashiorkor bilateral oedema is present, with a weight for height less than −2SD [33, 34, 35].
\n
\n
\n
2.3 Underweight (weight for age or W/A)
\n
A common presentation of PEM in children is underweight. Underweight is seen as children having a weight for age with a Z score of −2SD, with severe underweight at −3SD [36, 37]. Since proteins and/or energy are insufficient in a diet, there is weight loss or failure to gain weight. This can be accompanied by a decline in linear height [38]. While the children may present with normal body proportions such as weight to height ratios, they will be undersized and underweight [39]. Through regular monitoring of growth indices such as height and weight, underweight can be identified at an early stage [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39]. In 2013, 99 million children less than 5 years of age were underweight. Of this figure, one third of the children were from Africa and two-thirds present in Asia. An estimated 14.6% of newborns were with low birth weight in 2015, and approximately nine out of 10 of the newborns were from low and middle income countries (LMICs). Approximately 45% of deaths in LMICs in children under age five is due to underweight. In adolescent girls the underweight prevalence increased from 5.5% in 2000 to 5.7% in 2016 [40].
\n
\n
\n
2.4 Stunting (height for age or H/A)
\n
Stunting is a major public health concern that begins in intrauterine life although children are only classified as stunted at approximately age 2 years. The detrimental effects of stunting include intrauterine growth retardation, as well as inadequate nutrition required for growth and development of children [41]. High frequency of infection and decreased disease resistance such as diarrhea and pneumonia are influenced by stunting. Childhood stunting may also lead to increased mortality, poor recovery from disease and is also an obesity risk factor in adulthood [41, 42]. Stunting causes growth impairment during childhood that is associated with increased cardio-metabolic disease and obesity risk and cognitive development delay in adulthood [43]. This creates both short and long term effects that indicate the importance of stunting being identified and monitored in early life [42].
\n
In children the initial 1000 days of life are an important window period for intervention implementation and tracking for the improvement of child growth and development [7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44]. Often stunting is correlated with poor socio-economic status, as well as environmental conditions surveys in South Africa (SA) have identified an increased stunting prevalence in black people compared to their Indian or white counterparts [31]. Some surveys looked at a wider age range of children (0–14 years) and higher stunting prevalence was found in children living informal settlements within urban and rural areas [36, 37, 38, 39, 40, 41, 42, 43, 44, 45].
\n
In stunting or low height for age the Z score is below 2 standard deviations [21]. It is prevalent usually in infants and children younger than 5 years [36], who are susceptible to infection and have an insufficient intake of nutrients over the long term. Low height for age is seen as the failure of an individual to reach full linear growth and if stunting occurs before age two then irreversible poor cognitive and motor developments may occur [41]. Severe stunting is indicated by a height for age that is lesser than the median by 85% to represent a standard deviation of −3SD [46]. In 2013 in children under 5 years of age, 161 million were identified as stunted globally. The trend of global decrease were evident from the period 2000–2013, during which figures declined from 199 million to 161 million (33–25%). However, one third of stunted children were still found in Africa [47]. During 2000–2018 the number and proportion of stunted children under age five rose by 6.5 million in Central and Western Africa and by 1.4 million in Southern and Eastern Africa. Thus, the stunting burden continues to escalate in Africa, creating serious human capital development complications [40].
\n
\n
\n
2.5 Overweight and obesity
\n
In the last five decades overweight and obesity appears to be reaching epidemic levels in both developing and developed countries [48, 49]. Eclipsing infectious disease and under-nutrition as a significant mortality and ill-health contributor, overweight and obesity have presented as the most prevalent global nutritional problem over the last two decades. Globally an estimated 1 billion adults are overweight, with 300 million of them being obese [49]. An estimated 155 million obese children contribute to this epidemic [50]. Obese children tend to become obese adults. Obesity-related health problems occur in early years of life and progress into adulthood [51]. Several chronic disease conditions in later life are associated with childhood obesity. These chronic diseases include diabetes, stroke, high blood pressure, cancers and heart disease [52]. Despite the increased prevalence of overweight and obesity in children, research evaluating treatment in these age groups is minimal. Middle-income countries such as South Africa (SA), Brazil and China have increased overweight and obesity rates across all age groups and economic levels [49]. However, over the last few years overweight has increased in every continent. It has been postulated that the number of overweight children under age five will rise from over 40 million to approximately 43 million by 2025 [53]. As of 2018, approximately half of the overweight under five children were in Asia, with a quarter in Africa. Between 2000 and 2018 in Africa, the number of overweight under five children rose by just under 44%. In children and adolescents aged 5–19 years old, the proportion of overweight in 2000 rose from one in 10 (10.3%) to just under one in five (18.4%) in 2016 [40].
\n
\n
\n
2.6 Stunting versus overweight/obesity
\n
Some developing countries such as SA are currently facing a nutrition transition with the dual burden of over and undernutrition. This nutrition transition is the replacement of traditional home cooked balanced diet meals by energy-dense foods, as well as sedentary lifestyles due to technology and urbanization. A review study highlighted the dual burden in SA in children aged 0–20 years. The prevalence of wasting and stunting was higher in younger male children and predominant in rural areas, whereas overweight/obesity prevalence was highest in females and children in urban settings. It is important for tracking of over and undernutrition in children at a district level that can also be used to prioritize, monitor and evaluate government policies regarding malnutrition [54]. More recent years have seen the double burden of malnutrition being accompanied by a triple burden of malnutrition, affecting families, communities and countries. In countries such as India and Egypt, the problem is increasing and therefore highlights the urgent need to consider child malnutrition in the greater familial and household contexts [40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55]. A study in Ghana addressed the concurrent occurrence of obesity and stunting in children aged under 5 years, providing data for the first time on such an occurrence. The study reported a stunting prevalence of 27.5%, overweight prevalence of 2.4% and an overall concurrent stunting and overweight prevalence of 1.2% [56]. A study in South Africa, with children aged 6–12 years old, reported that 9.1% were stunted, while 14.9% were overweight/obese [57]. This highlights the need for urgent targeted interventions in children to address this double burden to prevent these malnutrition issues as they transition into adulthood.
\n
\n
\n
2.7 Wasting (weight for length/height or W/H)
\n
In wasting or low weight for height the Z score is below 2 standard deviations [21]. Wasting is reflective of a body mass that is low in comparison to the age and may be due to disease or starvation. Weight loss and retardation of growth occur due to inadequate intake of food and long term it leads to wasting and becomes more severe with emaciation [58]. A child falls behind another child who is growing actively when his/her own growth is affected acutely [38], and the body height and weight become less than ideal for the age of the child [59]. Severe wasting occurs when the weight for height is less than the median by 70% to represent a standard deviation of −3SD [46]. According to the national Department of Health (DoH) height measurements in all children should be conducted at least every 3 months [60]. In measuring overall growth to compare growth standards, both height and weight measurements are essential. Globally, in 2013, in children less than 5 years of age, 51 million were wasted and 17 million severely wasted. Global wasting prevalence in 2013 approximated 8%, of which 3% accounted for severe wasting. A postulated third of wasted children were present in Africa and an estimate of the children severely wasted in Africa followed the same trend [61]. As of 2018–2019 52 million children are wasted, with an estimated 16.6 suffering from severe wasting in 2018 [62]. Children left untreated with severe acute malnutrition (SAM) are at least 12 times more likely to die than healthy children [63]. South Asia is the global wasting epicenter as 15.2% of children under five are wasted. Together with other hotspots such as Oceania, Southeast Asia and SSA, improvements regarding wasting are minimal [64] (Table 2).
\n\n
\n
\n
\n\n
\n
Classification
\n
Z score values
\n
\n\n\n
\n
Adequately nourished
\n
−2 < Z-score < +1
\n
\n
\n
Moderately malnourished
\n
−3 < Z-score < −2
\n
\n
\n
Severely malnourished
\n
Z-score < −3
\n
\n\n
Table 1.
Malnutrition classification of children based on Z scores [20].
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Country
\n
Year of last survey
\n
Wasting
\n
Overweight
\n
Stunting
\n
Underweight
\n
\n\n\n
\n
Angola
\n
2015–2016
\n
4.9
\n
3.4
\n
37.6
\n
19.0
\n
\n
\n
Benin
\n
2017–2018
\n
5.0
\n
1.9
\n
32.2
\n
16.8
\n
\n
\n
Botswana
\n
2007–2008
\n
7.2
\n
11.2
\n
31.4
\n
11.2
\n
\n
\n
Burkina Faso
\n
2017
\n
8.6
\n
1.7
\n
21.1
\n
16.2
\n
\n
\n
Burundi
\n
2016–2017
\n
5.1
\n
1.4
\n
55.9
\n
29.3
\n
\n
\n
Cabo Verde
\n
1994
\n
6.9
\n
—
\n
21.4
\n
11.8
\n
\n
\n
Cameroon
\n
2014
\n
5.2
\n
6.7
\n
31.7
\n
14.8
\n
\n
\n
Central African Republic
\n
2012
\n
7.6
\n
1.9
\n
39.6
\n
24.6
\n
\n
\n
Chad
\n
2014–2015
\n
13.3
\n
2.8
\n
39.8
\n
29.4
\n
\n
\n
Comoros
\n
2012
\n
11.3
\n
10.6
\n
31.1
\n
16.9
\n
\n
\n
The Congo
\n
2014–2015
\n
8.2
\n
5.9
\n
21.2
\n
12.3
\n
\n
\n
Cote d’Ivoire
\n
2016
\n
6.1
\n
1.5
\n
21.6
\n
12.8
\n
\n
\n
Democratic Republic of Congo
\n
2013–2014
\n
8.1
\n
4.4
\n
42.7
\n
23.4
\n
\n
\n
Djibouti
\n
2012
\n
21.6
\n
8.1
\n
33.5
\n
29.9
\n
\n
\n
Equatorial Guinea
\n
2011
\n
3.1
\n
9.7
\n
26.2
\n
5.6
\n
\n
\n
Eritrea
\n
2010
\n
15.3
\n
2.0
\n
52.0
\n
39.4
\n
\n
\n
Eswatini (former Swaziland)
\n
2014
\n
2.0
\n
9.0
\n
25.5
\n
5.8
\n
\n
\n
Ethiopia
\n
2016
\n
10.0
\n
2.9
\n
38.4
\n
23.6
\n
\n
\n
Gabon
\n
2012
\n
3.4
\n
7.7
\n
17.0
\n
6.4
\n
\n
\n
The Gambia
\n
2013
\n
11.0
\n
3.2
\n
24.6
\n
16.5
\n
\n
\n
Ghana
\n
2014
\n
4.7
\n
2.6
\n
18.8
\n
11.2
\n
\n
\n
Guinea
\n
2016
\n
8.1
\n
4.0
\n
32.4
\n
18.3
\n
\n
\n
Guinea—Bissau
\n
2014
\n
6.0
\n
2.3
\n
27.6
\n
17.0
\n
\n
\n
Kenya
\n
2014
\n
4.2
\n
4.1
\n
26.2
\n
11.2
\n
\n
\n
Lesotho
\n
2014
\n
2.8
\n
7.5
\n
33.4
\n
10.5
\n
\n
\n
Liberia
\n
2013
\n
5.6
\n
3.2
\n
32.1
\n
15.3
\n
\n
\n
Madagascar
\n
2012–2013
\n
7.9
\n
1.1
\n
48.9
\n
32.9
\n
\n
\n
Malawi
\n
2015–2016
\n
2.8
\n
4.6
\n
37.4
\n
11.8
\n
\n
\n
Mali
\n
2015
\n
13.5
\n
1.9
\n
30.4
\n
25.0
\n
\n
\n
Mauritania
\n
2015
\n
14.8
\n
1.3
\n
27.9
\n
24.9
\n
\n
\n
Mauritius
\n
1995
\n
15.7
\n
6.5
\n
13.6
\n
13.0
\n
\n
\n
Mozambique
\n
2011
\n
6.1
\n
7.8
\n
42.9
\n
15.6
\n
\n
\n
Namibia
\n
2013
\n
7.1
\n
4.0
\n
22.7
\n
13.2
\n
\n
\n
Niger
\n
2016
\n
10.1
\n
1.1
\n
40.6
\n
31.4
\n
\n
\n
Nigeria
\n
2016–2017
\n
10.8
\n
1.5
\n
43.6
\n
31.5
\n
\n
\n
Rwanda
\n
2014–2015
\n
2.3
\n
7.9
\n
38.2
\n
9.6
\n
\n
\n
Sao Tome and Principe
\n
2014
\n
4.0
\n
2.4
\n
17.2
\n
8.8
\n
\n
\n
Senegal
\n
2017
\n
9.0
\n
0.9
\n
16.5
\n
14.4
\n
\n
\n
Seychelles
\n
2012
\n
4.3
\n
10.2
\n
7.9
\n
3.6
\n
\n
\n
Sierra Leone
\n
2013
\n
9.5
\n
8.8
\n
37.8
\n
18.2
\n
\n
\n
Somalia
\n
2009
\n
15.0
\n
3.0
\n
25.3
\n
23.0
\n
\n
\n
South Africa
\n
2016
\n
2.5
\n
13.3
\n
27.4
\n
5.9
\n
\n
\n
South Sudan
\n
2010
\n
24.3
\n
5.8
\n
31.3
\n
29.1
\n
\n
\n
Togo
\n
2013–2014
\n
6.6
\n
2.0
\n
27.6
\n
16.1
\n
\n
\n
Uganda
\n
2016
\n
3.5
\n
3.7
\n
28.9
\n
10.4
\n
\n
\n
United Republic of Tanzania
\n
2015–16
\n
4.5
\n
3.7
\n
34.5
\n
13.7
\n
\n
\n
Zambia
\n
2013–14
\n
6.2
\n
6.2
\n
40.0
\n
14.9
\n
\n
\n
Zimbabwe
\n
2015
\n
3.3
\n
5.6
\n
27.1
\n
8.5
\n
\n\n
Table 2.
Joint malnutrition country estimates of anthropometric indicators in children aged 0–59 months [65].
\n
\n
\n
\n
3. Malnutrition in South Africa
\n
As a developing or middle-income country, SA is still undergoing major transitions socially, economically and in the population’s health. The country is currently facing a quadruple disease burden, with non-communicable diseases linked to diet and lifestyle; the burden of Human Immunodeficiency Virus/Acquired immunodeficiency syndrome (HIV/AIDS); infectious diseases and poverty linked to under nutrition; and deaths due to injuries [66]. As a developing country SA is in a nutrition transition where both over and undernutrition coexist [67]. The first 2 years of life are a vulnerable time frame as it is during this period that malnutrition begins. According to Faber and Wenhold [68], chronic malnutrition or stunting is more prevalent in children in SA compared to wasting. Since the post-apartheid era in 1994, SA has faced great challenges in addressing the nutritional status of infants, young children and adults [69]. However, large-scale nationwide surveys were conducted to trace the progress, failures and successes in addressing malnutrition. In 1994 the South African Vitamin A Consultative Group (SAVACG) conducted a national survey on the nutritional status of children aged 6–71 months [70]. Anthropometric results revealed that approximately 10% or 660,000 children were underweight, with one in every four children (1.5 million) affected by stunting. Severe wasting was only recorded in 0.4% of children. KwaZulu-Natal (KZN), Eastern Cape and Northern Province revealed the greatest prevalence of malnutrition [70]. In 1999 the National Food Consumption Survey (NFCS) was conducted in children aged 1–9 years [71], collecting a larger set of data in comparison to the SAVACG survey. The NFCS reported 10% underweight in children, with 20% affected by stunting and 17.1% as overweight and/or obese. The NFCS secondary analysis, focusing on children aged 1–5 years, reported underweight at 6.8%, stunting at 20.1%, overweight at 20.6% and obesity at 9.5% [69]. In 2005, the National Food Consumption Survey-Fortification Baseline (NFCS-FB) reported that of children aged 1–9 years old, 20% were affected by stunting, 9.3% were underweight, wasting was found in 4.5%, and 14% were overweight or obese [72]. The South African National Health and Nutrition Examination Survey (SANHANES) conducted in 2012 reported that in children aged 0–14 years stunting prevalence was 15.4%, with 3.8% having severe stunting. Wasting was reported at 2.9%, with severe wasting at 0.8%. Underweight was reported at 5.8%, with severe underweight at 1.1%. Regarding over nutrition, SANHANES identified 18.1% of children as overweight and 4.6% as obese [36]. The prevalence of overweight and obesity was significantly greater in females (25% and 40.1%) compared to males (19.6% and 11.6%) respectively. Underweight was significantly higher in males (13.1%) in comparison to females (4.0%) [36]. Thus, it is evident that SA is facing the malnutrition epidemic at a young age and context-specific and targeted interventions are required to prevent child malnutrition before it progresses into adulthood.
\n
\n
\n
4. Conclusion
\n
During 2012–2013, WHO member states recognized the seriousness of malnutrition and its effect on global health [3]. Thus, at the United Nation’s General Assembly in 2016, the United Nations Decade of Action on Nutrition 2016–2025 was announced. This set a time frame for all forms of malnutrition to be addressed and for diet-related and nutrition targets to be met by 2025. This also set the time frame for the Sustainable Development Goals (SGDs) to be achieved before 2030, particularly SDG 2 that aims to improve nutrition, achieve food security and end hunger, as well as SDG 3 that aims to ensure healthy living and promote well-being for all [1]. To tackle the malnutrition epidemic food fortification is important to ensure that children with good weight do not risk becoming overweight or obese [73]. All malnutrition indicators must be included in interventions, and more importantly treated together rather than stand-alone issues [74]. As part of the health system strengthening and with the goal of combatting malnutrition, existing policies on child malnutrition must be evaluated. The coexistence of stunting and overweight/obesity remains a challenge in LMICs that requires multi-sectoral action. During infancy and early childhood optimal nutrition is vital to ensure that, development and rapid growth demands are met. In the efforts to tackle the nutrition disparities, the first 1000 days of life are an important window period, presenting the opportunity to prevent both stunting and overweight/obesity [75]. Interventions must be inclusive of both linear growth and appropriate weight, beginning in early life and preferably during this important window period. To further tackle the double and triple burdens of malnutrition, early screening and identification of at risk children, including those already with malnutrition, is essential at healthcare facilities [76]. Thus, a more holistic, context-specific approach is required, whereby interventions not only take into consideration the risk factors, but also consider the inclusion of nutritionists and educating mothers on self and childcare regarding nutrition [77]. Furthermore, child malnutrition research and interventions must be up-scaled from community level to provincial and national levels so that it informs policy on the intervention strategies that can address the burden of child malnutrition. This is vital as children left untreated transition into malnourished adulthood, increasing the healthcare costs and needs, weakening the healthcare systems, and perpetuating the vicious malnutrition cycle.
\n
\n\n',keywords:"malnutrition, children, wasting, stunting, obesity",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/71665.pdf",chapterXML:"https://mts.intechopen.com/source/xml/71665.xml",downloadPdfUrl:"/chapter/pdf-download/71665",previewPdfUrl:"/chapter/pdf-preview/71665",totalDownloads:761,totalViews:0,totalCrossrefCites:1,dateSubmitted:"August 30th 2019",dateReviewed:"March 5th 2020",datePrePublished:"April 5th 2020",datePublished:"November 11th 2020",dateFinished:null,readingETA:"0",abstract:"Malnutrition is a widespread problem, affecting the global population at some life stage. This public health epidemic targets everyone, but the most vulnerable groups are poverty-stricken people, young children, adolescents, older people, those who are with illness and have a compromised immune system, as well as lactating and pregnant women. Malnutrition includes both undernutrition (wasting, stunting, underweight, and mineral- and vitamin-related malnutrition) and overnutrition (overweight, obesity, and diet-related noncommunicable diseases). In combating malnutrition, healthcare costs increase, productivity is reduced, and economic growth is staggered, thus perpetuating the cycle of ill health and poverty. The best-targeted age for addressing malnutrition is the first 1000 days of life as this window period is ideal for intervention implementation and tracking for the improvement of child growth and development. There is an unprecedented opportunity to address the various forms of malnutrition, especially the 2016–2025 Decade of Action on Nutrition set by the United Nation. This aims to achieve the relevant targets of the Sustainable Development Goals that aim to end hunger and improve nutrition, as well as promote well-being and ensure healthy lives.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/71665",risUrl:"/chapter/ris/71665",signatures:"Natisha Dukhi",book:{id:"8030",title:"Malnutrition",subtitle:null,fullTitle:"Malnutrition",slug:"malnutrition",publishedDate:"November 11th 2020",bookSignature:"Muhammad Imran and Ali Imran",coverURL:"https://cdn.intechopen.com/books/images_new/8030.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"194146",title:"Dr.",name:"Muhammad",middleName:null,surname:"Imran",slug:"muhammad-imran",fullName:"Muhammad Imran"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"311182",title:"Dr.",name:"Natisha",middleName:null,surname:"Dukhi",fullName:"Natisha Dukhi",slug:"natisha-dukhi",email:"doctordukhi@gmail.com",position:null,institution:{name:"Human Sciences Research Council",institutionURL:null,country:{name:"South Africa"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Classification of malnutrition",level:"1"},{id:"sec_2_2",title:"2.1 Undernutrition",level:"2"},{id:"sec_3_2",title:"2.2 Undernutrition/protein energy malnutrition (PEM)",level:"2"},{id:"sec_4_2",title:"2.3 Underweight (weight for age or W/A)",level:"2"},{id:"sec_5_2",title:"2.4 Stunting (height for age or H/A)",level:"2"},{id:"sec_6_2",title:"2.5 Overweight and obesity",level:"2"},{id:"sec_7_2",title:"2.6 Stunting versus overweight/obesity",level:"2"},{id:"sec_8_2",title:"2.7 Wasting (weight for length/height or W/H)",level:"2"},{id:"sec_10",title:"3. Malnutrition in South Africa",level:"1"},{id:"sec_11",title:"4. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'\nWorld Health Organization (WHO). Malnutrition [Internet] 2019. Available from: https://www.who.int/news-room/fact-sheets/detail/malnutrition\n\n'},{id:"B2",body:'\nWorld Health Organization (WHO). Nutrition [Internet] 2020. 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DOI: 10.1371/journal.pone.0154756\n'},{id:"B74",body:'\nShrimpton R, Rokx C. The Double Burden of Malnutrition in Indonesia. Jakarta, Indonesia: World Bank Jakarta. Contract No.: Report 76192-ID [Internet]; 2013. Available from: http://documents.worldbank.org/curated/en/955671468049836790/The-double-burden-of-malnutrition-in-Indonesia\n\n'},{id:"B75",body:'\nPerez-Escamilla R, Bermudez O, Buccini GS, Kumanyika S, Lutter CK, Monsivais P, et al. Nutrition disparities and the global burden of malnutrition. BMJ. 2018;361:1-8. DOI: 10.1136/bmj.k2252\n'},{id:"B76",body:'\nSteenkamp L, Lategan R, Raubenheimer J. Moderate malnutrition in children aged five years and younger in South Africa: Are wasting or stunting being treated? South African Journal of Clinical Nutrition. 2016;29(1):27-31 Available from: http://www.sajcn.co.za/index.php/SAJCN/article/view/1030\n\n'},{id:"B77",body:'\nModjadji P, Madiba S. The double burden of malnutrition in a rural health and demographic surveillance system site in South Africa: A study of primary schoolchildren and their mothers. BMC Public Health. 2019;19(1087):1-11 . Available from. DOI: 10.1186/s12889-019-7412-y\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Natisha Dukhi",address:"doctordukhi@gmail.com",affiliation:'
Human Sciences Research Council, Cape Town, South Africa
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Patients usually present with symptoms of dysfunction of VI, VII, VIII, IX, X, XI, XII nerves and sympathetic trunk. Depending on the tumor’s topography, various approaches might be used to obtain its gross total resection. Jugular Foramen’s paraganglioma classification, nuances of the approaches, pathology, postoperative complications, and outcomes are revised as follows. 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