Evolution from graphite to graphene elastomer composites

Progress in Polymer Science 39 (2014) 749–780

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Progress in Polymer Science journal homepage: www.elsevier.com/locate/ppolysci

Review

Evolution from graphite to graphene elastomer composites Kishor Kumar Sadasivuni a,b,∗ , Deepalekshmi Ponnamma b , Sabu Thomas b,c,d,e , Yves Grohens a a b c d e

LIMATB laboratory, Université de Bretagne Sud, Rue St Maudé, 56100 Lorient, France School of Chemical Sciences, Mahatma Gandhi University, Kottayam, 686560 Kerala, India Centre for Nanoscience and Nanotechnology, Mahatma Gandhi University, Kottayam, 686560 Kerala, India Universiti Teknologi MARA, Faculty of Applied Sciences, 40450 Shah Alam, Selongor, Malaysia Center of Excellence for Polymer Materials and Technologies, Tehnoloski park 24, 1000 Ljubljana, Slovenia

a r t i c l e

i n f o

Article history: Received 30 October 2012 Received in revised form 15 July 2013 Accepted 22 July 2013 Available online 8 August 2013

Keywords: Elastomer Graphene Graphite nanoplatelets Sensors Gas permeability Thermal conductivity

a b s t r a c t Elastomer composites have established a unique position among technologically important materials because of their extensive and potential applications. Considerable interest has been devoted to graphite derived elastomer composites, known as new generation materials, due to their exceptional electrical, mechanical and permeability properties. The discovery of graphene opened a promising aspect towards the synthesis of elastomer nanocomposites. A thorough investigation of the properties of various graphitic fillers, such as natural graphite flakes, expanded graphite (EG), graphite nanoplatelets (GNP) and graphene is undertaken in this review. The dependence of these fillers on the rheological, electrical (sensing), mechanical, thermal, dielectric and barrier properties of elastomer composites is discussed, giving special emphasis to particle size and mode of interactions with the matrix. A systematic evolution from microcomposites to nanocomposites is shown to give definitive evidence of the importance of graphene nanocomposites. Most preparation methods of these composites are covered, including, solution blending, latex compounding, in situ polymerization, and melt intercalation. Graphene exhibits very good dispersion in most elastomers and substantially improves the mechanical and electrical properties of the matrix compared to all other graphite derivative composites. A review of the potential applications of these composites and current challenges is provided in order to guide future progress on the development of more promising materials. © 2013 Elsevier Ltd. All rights reserved.

Contents 1. 2.

3.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Graphite derivatives and graphene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Synthesis of graphite derivatives and graphene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1. Bottom-up processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2. Top-down processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Characterization of graphite derivatives and graphene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elastomer/graphitic filler nanocomposites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

∗ Corresponding author at: LIMATB laboratory, Université de Bretagne Sud, Rue St Maudé, 56100 Lorient, France. E-mail address: kishor [email protected] (K.K. Sadasivuni). 0079-6700/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.progpolymsci.2013.08.003

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3.1.

4.

5. 6.

Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1. Melt intercalation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2. Solution dispersion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3. In situ polymerization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Quantifying dispersion of elastomer/graphene and graphite derivative composites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Cure kinetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1. Self-curing effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Characteristic properties of elastomer/graphene and graphite nanocomposites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Mechanical properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Electrical properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1. Temperature sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2. Piezoresistive effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Thermal behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4. Dielectric properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5. Gas barrier properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Nomenclature A/C Af AGs AGT AFM AGS AGTS

acid–graphite and coupling agent aspect ratio acid graphite platelets acid graphite with thermal shock atomic force microscopy acid graphite with sonication acid graphite with thermal shock and sonication BYK-9076 alkylammonium salt of high molecular weight copolymer CNF carbon nano fibers CB carbon black carbon nanotube CNT CVD chemical vapor deposition CRG or GE chemically reduced graphene cetyltrimethyl ammonium bromide CTAB CuPc copper phthalocyanine DMF dimethyl formamide expanded graphite EG FGS functionalized graphene sheet GNP or GN graphite nano platelets GIC graphite intercalation compounds graphene oxide GO GONP graphite oxide nanoplatelets HR-TEM high resolution-transmission electron microscopy high abrasion furnace black HAF HXNBR hydrogenated carboxylated nitrile–butadiene rubber hexadecyl trimethyl ammoniumbromide HTAB iGO isocyanate treated graphene oxide IIR poly(isobutylene–isoprene) rubber latex compound method LCM MMT montmorillonite

MLGS MG MM NR NGs NMR NGT NGS NGTS

multilayer graphene sheets modified graphene melt mixing natural rubber (poly isoprene) natural graphite nuclear magnetic resonance natural graphite with thermal shock natural graphite with sonication natural graphite with thermal shock and sonication natural flake graphite NFG NBR nitrile–butadiene rubber XNBR carboxylated nitrile–butadiene rubber NBR-PVC nitrile butadiene rubber with poly(vinyl chloride) PMN-PT lead magnesium niobate–lead titanate polydimethylsiloxane PDMS PAC polyaluminium chloride PHT poly(3-hexylthiophene) Ph-iGO phenyl isocyanate treated graphene oxide RTVSR room temperature vulcanising silicone rubber RGO reduced graphene oxide SWCNT single wall carbon nanotube SEM scanning electron microscopy SDS sodium dodecyl sulfate SR silicone rubber styrene–butadiene rubber SBR TEGO thermally expanded graphene oxide TEM transmission electron microscopy thermally reduced graphene TRG TPU thermoplastic polyurethane ULMR ultrasonically assisted latex mixing and in situ reduction

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1. Introduction New generation materials, including smart materials exhibiting high performance and multifunctionality have become a topic of interest. As one of the most important branches of current nanotechnology and composite science, the fabrication of elastomer nanocomposites is significant in producing such materials. Their advantageous applications have triggered detailed studies in theoretical as well as applied research. In order to synthesize elastomer nanocomposites, nanofillers such as carbon black (CB), silica, titanium dioxide (TiO2 ), layered silicates, carbon nanotubes (CNTs), polyhedral oligomeric silsesquioxane (POSS), graphene and graphite intercalation compounds have been incorporated into various elastomer matrices to provide efficient reinforcement and functional properties. Graphite intercalation compounds (GICs) include expanded graphite, graphite nanoplatelets and graphene. Among the various nanocomposite systems, those of graphitic based fillers are significant due to their multi-functional behavior. They can improve mechanical and tribological properties, thermal stability, microwave absorption, electrical and thermal conductivities, dielectric performances and gas barrier properties of all elastomer matrices. In this context, a detailed discussion about their structures and properties is essential, and this review aims at providing a thorough understanding of them. Natural graphite flakes (NFG) are polycrystalline forms of carbon comprising layered planes containing hexagonal arrays of carbon atoms to form an atomically flat stacked material in three dimensional. Covalent bonds bind the carbon atoms in the same plane together, with van der Waals forces between successive layers, separated by 0.337 nm. Because of the very weak van der Waals forces, it is quite easy for small atoms, ions and molecules to intercalate between the layers to form expanded graphite (EG) [1], graphite nanoplatelets (GNP) [2,3] and graphene [4–10], the properties of which are given in Table 1. These GICs containing intercalating agents thus have increased interplanar spacings compared to NFG, and are themselves considered to be nanocomposites. Expanded graphite (EG), one kind of GIC is fabricated from NFG through chemical or thermal expansion. It is reported that chemical or electrochemical expansion [11] using strong acids increased the d-spacing of expandable graphite from 0.335 to ∼0.789 nm [12–14]. The average pore diameter, surface area and the pore volume of chemically produced EG, was observed to be ∼2 mm, 30–40 m2 /g and ∼4–8 mL/g, respectively [15–17]. Rapid heating of GICs can produce highly porous (pore size ranging from micro to nano) thermally expanded graphite with greater interplanar spacings. Thin sheets with large areas can be produced when the multi-layered graphite is exfoliated. The resulting graphite

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nanosheets or platelets (GNPs) have proved their significance as strong, versatile and inexpensive fillers in composite materials [18] even at low concentrations. The thickness, diameter and surface area of GNPs can be tuned by various techniques, such as intercalation, oxidation, heat treatment, microwave irradiation, ultrasonic treatment, etc. [19–22] Exfoliation of graphite, EG and/or GNPs (GNPs are themselves bi-, tri- or multi-layers of graphene) into much thinner nanoplatelets, in other words, to single graphene sheets, [23] is another important area. Even though the production of graphene nanosheets was first reported in 1970, [24] isolation of single-layer graphene sheets (nano sized) from natural graphite (micro sized) using micromechanical cleavage (Scotch Tape method) was not reported until 2004 [10]. Graphene is a twodimensional (2-D) single-atom-thick sheet of graphite with carbon–carbon (c–c) bond length of 0.142 nm. It has a strength of 130 GPa, Young’s modulus 1 TPa, thermal conductivity ∼5000 W/(mK) and electrical conductivity up to 6000 S/cm [25,26]. Its superior electrical conductivity [30] is evident from its enhanced oxygen to carbon ratio (O/C) (Table 1). Compared to the other contemporary nanofillers, graphene possesses extremely high surface area, superior gas impermeability [27] and unique functional properties [28,29]. The natural abundance, low cost and multifunctionality of graphitic fillers gave rise to keen interest in the manufacture of a large numbers of elastomer composites. The research groups of Hamed and Zhang explained the importance of graphite derivatives (particularly graphene) over other kinds of nanofillers in their ability to impart mechanical [31,32] and other functional properties to a rubber matrix, especially when the filler is finely dispersed in the matrix with improved interfacial interaction. Generally, elastomer/graphene and graphite derived composite fabrication can be done by melt blending, solution mixing and in situ polymerization methods. However, it is difficult to incorporate rubber macromolecular chains directly into the graphite interlayers. Various preparation processes are discussed in the following. For the preparation methods discussed, the dispersion of platelets in the composite is ensured by the level of exfoliation of the platelets prior to, or during, mixing. In this aspect, solution mixing offers the simplest route to disperse graphite derivatives and graphene platelets into an elastomer matrix, even if some restacking of the platelets may occur. A large number of surfactants also facilitate graphene dispersion [3,33–36]. A schematic representation showing all kinds of graphitic derivatives and their inter dependence is given in Fig. 1. The scheme also represents elastomer nanocomposites of expanded graphite, graphite nanoplatelets and graphene.

Table 1 Structural characterization of EG, GNP and graphene. Material

Thickness

Surface area (m2 /g)

O/C ratio

Electrical conductivity (S/m)

EG GNP Graphene

0.50 mm [1] 2–150 nm [2] 0.34 nm [4–10]

∼15 to 90 [1] 15–2630 [2] ∼2630 [4–10]

<0.006 [1] 0.006 [30] 0.188 [30]

<5.98 ± 0.11 × 104 [1] 5.98 ± 0.11 × 104 [30] 1.28 ± 0.04 × 102 [30]

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Fig. 1. Schematic representation of graphitic based filler systems and elastomer nanocomposite containing (a) expanded graphite, (b) graphite nanoplatelets and (c) graphene.

The modification of graphitic fillers usually enhances their interfacial interaction with elastomer chains, thereby leading to better properties. For example, the acid modified expandable graphite reinforced styrene butadiene rubber (SBR) nanocomposite shows good improvement in thermal, mechanical and fatigue properties [34] compared to unmodified graphite and carbon black fillers. Following this study, the effect of various concentrations and particle sizes of graphite filler on the physicomechanical and rheological properties of SBR were explored by Ismail and Khalaf [37]. Investigations showed dramatic improvement in the properties depending on dimensions (size and shape) of the filler particles. In a similar study the influences of the size and shape of graphite particles on the tribological properties of acrylonitrile–butadiene rubber (NBR) [38] were investigated, and a kind of graphitic friction material based on NBR with high friction coefficient, high capacity of energy absorption and low wear was developed [39]. Mahmoud and Al-Ghamdi studied the material behavior of graphite nanoplatelets/NBR nanocomposites [40] and obtained identical results. Evidence supports the synergistic effect of (NBR)/expanded graphite (EG)/carbon black (CB) systems and the mechanical and tribological properties are compared among their micro- as well as their nano-composites [41]. Apart from these mechanical aspects, graphitic fillers extend their applicability to various other fields. The composite of graphite and silicone rubber (SR) is a useful electrode material with excellent mechanical resistance and easy surface renewing [42] properties. The SR/GNPs nanocomposites reported by Chen et al. [43] show piezoresistivity (pressure-sensitive behavior) with much lower percolation threshold. The high thermal conductivity of silicone/EG composites fabricated by solution intercalation was also reported [17]. In short, the size, shape, nature of dispersion and interfacial interactions of graphitic fillers are responsible for the improved properties of their rubber composites. The nanodimension and aspect ratio of graphene make its elastomer nanocomposites superior to all other graphitic derived composites, provided better dispersion

of the filler is achieved. Significant property improvement is obtained for natural rubber (NR)/graphene (GE) composites synthesized by Zhan et al. [44]. Similar to all other nanofillers, the rate of dispersion and interfacial interaction of graphene can be regulated by proper surface modification techniques. This is evidenced by the dramatic enhancement of mechanical properties of NR, IIR (butyl rubber), SR, SBR, polyurethane (TPU) and elastomers upon the addition of functionalized graphenes [3,45–52] It was also found that the functionalized graphene can enhance the dielectric properties of elastomer nanocomposites approximately about tenfold when compared to CNTs, while simultaneously preserving the low dielectric loss and good tensile strength values [49]. Recently, the tribological properties of graphene oxide reinforced nanocomposites [53] were explored by Li et al., comparing the methods of dry sliding and wet lubrication. Graphite derivatives and graphene/elastomeric compounds are widely used, e.g., in automotive, electronics, packaging, aerospace, biomedical and shape memory applications [54–57]. Since the composite properties are highly influenced by the filler–elastomer interactions, making well-exfoliated systems by chemical as well as physical modifications of filler particles has a critical role in material fabrication. This review aims at providing a comprehensive understanding of recent researches on elastomer/graphite, EG, GNP and graphene composites, including their fabrication, curing behavior, mechanism of reinforcement and various properties. The qualitative and quantitative features of the nanocomposites are addressed in the following, with special emphasis to molecular interactions. 2. Graphite derivatives and graphene 2.1. Synthesis of graphite derivatives and graphene Investigations on the preparation and properties of graphite derivatives and graphene have become a subject of keen interest because of the great potential

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of these materials as nanocomposites. Their important synthesis methods include two-zone vapor transport technique, liquid intercalation, electro-chemical and co-intercalation techniques. Synthesis of graphite sheets can be accomplished by simply treating the reactants, hexachlorobutadiene (C4 Cl6 ) and sodium (Na) at 500 ◦ C [48]. It is found that the large amount of heat generated during this reaction facilitates the formation of graphite sheets. EG is prepared from natural graphite using nitrating mixture and KMnO4 at 25 ◦ C [58]. Rapid expansion and/or thermal exfoliation of graphite flakes at high temperature (>600 ◦ C) also results in EG formation. Alkali metals and their compounds are useful intercalants to prepare GICs [2,59]. All these methods are inappropriate for the synthesis of graphitic fillers in nanodimensions. The two main fabrication approaches mostly preferred for GNPs [2,48,50,59–69] and graphene [3,5,26,47,68,70–136] include bottom-up processes and top-down processes. 2.1.1. Bottom-up processes These techniques involve the conversion of carbon to graphite derivatives. A large number of methods such as chemical vapor deposition (CVD) [60,70,71,73–75], chemical conversion [85–87], epitaxial growth on SiC [79–84], reduction of CO [88], arc discharge [21,77,78], unzipping carbon nanotubes [89–91] and self assembly of surfactants [92] are employed for this process. CVD and epitaxial growth on a metal substrate, generally copper, has the additional advantage – over the mechanical cleavage method – of producing large-size, defect-free graphene sheets, and is the most common and effective method of preparation. Both single layer and bi-layer graphene sheets, of specific area upto 1 cm2 for industrial and electronic applications can be well produced by this method. But these methods fail to synthesize bulk quantities of graphene. 2.1.2. Top-down processes In this process, graphene and GNPs are prepared from natural graphite by following physical and chemical approaches [120,137]. Physical methods include mechanical milling [10,62] in which bulk graphite layers are mechanically detached by breaking the van der Waals forces binding the layers. The micromechanical exfoliation of graphite is proved to be easy and can yield high quality graphene sheets with large surface area (∼1 mm2 ) [10]. But the large particle size and a broad particle size distribution of the obtained GNPs are considered to be the demerits of this method. The invention of graphite intercalated compounds (GIC) through intercalation approach has overcome this problem. By following this approach, Drzal and Fukushima successfully produced exfoliated graphite nanoplatelets (xGNP) with 5–10 nm thickness and 100–1000 nm diameter [69]. Certain metals [2,94] can also impart a double intercalation/exfoliation effect to produce thinner GNPs, having lengths of 2–20,000 ␮m [66]. In addition to mechanical milling, direct exfoliation techniques of graphite such as sonication [138] in the presence of dispersing agents [102,103], electrochemical functionalization of graphite in the presence of ionic liquids [104] and dissolution in super acids [105] are also practiced to obtain single and multi- layered graphene sheets. Sonication of aqueous

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dispersion of graphite in the presence of non-ionic surfactants [139] produces pristine graphene in bulk. It is also observed that the ultrasonication power breaks the flakes and ultimately influences the size of GNPs and graphene even though the fillers are well dispersed. The expansion of GICs could be done using aqueous exfoliating agents, such as water and alcohol as well. Chemical syntheses of graphene and GNPs from graphite derivatives are scalable and provide processable material with new functionalities. Acid intercalation procedure followed by ultrasonic treatment is observed to be capable of exfoliating graphite into isolated graphite nanosheets [63]. The acid intercalation can also be carried out by vapor phase reaction and electrochemical methods. Graphite oxide and graphene oxide are synthesized according to Brodie [140], Staudenmaier [100] and Hummers and Offeman [68] or Improved Graphene Oxide [7,121] processes in which graphite is oxidized using strong oxidants such as KMnO4 , KClO3 , and NaNO2 in the presence of nitric acid alone or nitrating mixture. Similar to the graphite morphology, graphene oxide sheets are also stacked with an interlayer spacing of 0.6–1 nm, depending on the hydroxyl groups [106] present. The functional groups present in the graphene oxide such as ketone, hydroxyl and epoxy groups [101,107] are very useful in making covalent bond linkages with the matrix back bone [107–117,141–144]. Both graphite oxide and graphene oxide have similar chemical properties due to these same surface functional groups, but their structures are entirely different, the former being three dimensional and the latter two dimensional. During oxidation, both of these oxide sheets undergo unzipping, leading to size reduction [119]. Rapid pyrolysis and surface modifications of graphene oxide or graphite oxide result in the formation of graphene or GNPs. These two methods are notable due to the relatively high yield of obtained single graphene sheets, and are considered as the most efficient routes for the exfoliation of graphite. Surfactant functionalization of graphene sheets [47,49,122–124] provides efficient dispersion in the elastomer matrices by significantly reducing the particle re-aggregation [30,95–97]. Chemical methods were proved to be effective and successful for synthesizing graphene oxide and graphite oxide from various precursors at low cost and in bulk [94]. Both these oxides can be reduced by chemical or thermal processes. The chemical reduction can be carried out using hydrazine [49,124,125], dimethyl hydrazine [96], sodium borohydride followed by hydrazine [126], hydroquinone [127] and UV-irradiated TiO2 [128] to produce chemically reduced graphene (CRG) or GNPs [122]. Stankovich et al. [97] applied hydrazine assisted reduction for graphene oxide marked by the simultaneous enhancement in electrical conductivity compared to unreduced GO [122]. Though the chemical reduction is an effective method to prepare CRGs from graphene oxide, the use of chemicals and their high cost usually limit their application. Because of this reason, alternative reduction methods like dehydration [129–131] are practiced on graphene oxide at high temperature (120–200 ◦ C) and pressure. Thermally reduced graphene or graphite nanoplatelets (TRG) can be produced by rapid heating of dry graphene oxide or graphite oxide under inert gas atmosphere at

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Fig. 2. (a) XRD patterns of GNP, GONP and graphene (b)XRD Pattern of FGS, GO, and EG (FGS = functionalized graphene sheets, GO = graphite oxide, EG = exfoliated graphite, GNP = graphite nanoplatelets, GONP = graphite oxide nanoplatelets). [30] Copyright 2009. Reproduced with permission from Elsevier Ltd.; [64] Copyright 2009. Reproduced with permission from John Wiley & Sons.

high temperature [132,135]. This method leads to the production of reduced exfoliated graphene sheets. The pressure generated by the evolved carbon dioxide gas due to the decomposition of the epoxy and hydroxyl groups on graphene oxide cause exfoliation due to the breakage of interlayer van der Waals forces, and makes the sheets highly wrinkled [22,133,134]. About 80% of the TRG sheets obtained are in the form of single layers in the 500 nm range, independent of the starting material size [134]. TRG reduced at 1000 ◦ C, 30 s has a C/O ratio of about 10/1 compared to 2/1 for graphene oxide, [95] and this ratio can be high up to 660/1 [136] during the high temperature (1500 ◦ C) treatment for long period. The surface area of thermally reduced graphene sheets is observed to be of the order of 1700 m2 /g, from methylene blue adsorption experiments. The thermal reduction method discussed so far has the extra benefit over CRGs in not requiring organic solvent for dispersion, as well as in the obtained high electrical conductivity (6000 S/cm), particularly for the defect-free single graphene sheets [26,133]. Moreover the dispersion of TRGs in matrices is possible even by applying simple mechanical stress or solution mixing, [3] and is much easier than exfoliation of chemically reduced graphene, where the number of stacks formed is high. Microwave irradiation can also provide sufficient energy to promote the expansion of GICs, with a larger volume exfoliation ratio and less sulfur residue [33,65]. An environmentally friendly and easy to scale-up route to synthesize reduced graphite oxide (RGO) hydrogel from graphite oxide with excellent mechanical and electrical properties, using excess of vitamin C is also reported [67].

order to demonstrate the intercalation of graphite, X-ray diffraction (Fig. 2) is used [30,64,72,145,146]. In Fig. 2, the sharp reflection at 2 = 26.3◦ (Cu K␣ radiation, X-ray wavelength = 0.154 nm) in graphite shifts to 14.1–14.9◦ region in graphite oxide, [146] whereas the disappearance of Xray diffraction peak is observed upon the exfoliation of graphite oxide sheets [133,134] in to graphene. Raman spectroscopy is a powerful tool to quantify the transformations from sp3 to sp2 hybridization through the intensity variation of bands in the spectrum [49,72,147]. The spectra can also give the information about the number of stacked layers (Fig. 3) and the disordered stacking in graphite samples [148,149]. Using the D peak value (splitting value 28.9) the number of synthesized graphene layers was found to be 6–7 [150]. The specific surface area and thickness of graphene layers extracted from graphite are confirmed by following N2 or methylene blue adsorption and atomic force microscopy (AFM) measurements. N2 adsorption results can vary based on the preparation methods of graphene such as CVD, CRG, TRG, etc. [133] Atomic force microscopy imaging provides visualized and more reliable measurements of sheet dimensions. Both contact and tapping mode AFM can be used to probe the morphology of the surfaces, cracks, defects, surface irregularities

2.2. Characterization of graphite derivatives and graphene After finishing the synthesis, it is essential to verify that the obtained product satisfies all the expected requirements. Moreover, information on the size of graphene sheets and the number of attached functional groups is important for dispersing the fillers in elastomers. A number of techniques are applied to characterize graphite derivatives and graphene. These include visual inspection, weight uptake, chemical analysis, c-axis dilatation, diffraction measurements, electron microscopy and so on. In

Fig. 3. Comparison of Raman spectra at 514 nm for bulk graphite and graphene. They are scaled to have similar height of the 2D peak at 2700 cm−1 . [148] Copyright 2010. Reproduced with permission from John Wiley & Sons.

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Fig. 4. AFM image of graphene, line scan of the selected individual graphene. [30] Copyright 2009. Reproduced with permission from Elsevier Ltd.

and bending behavior [49,117]. Using this technique, Lin et al. [150] investigated friction and wear characteristics of multilayered graphene films deposited on a silicon substrate by mechanical exfoliation. The thickness of graphene specimen was found to be 1.153 nm [30] as given in Fig. 4. Scanning electron microscopy (SEM) is another imaging technique that is capable of giving qualitative insight into the 3-D structure of particles [134] but with low resolution. Transmission electron microscopy (TEM) can provide images of single graphene sheets on a carboncoated copper grid with high resolution [103]. In addition to morphology, TEM also provides size determination. Fig. 5 illustrates the clear differentiation between single sheets from bilayer sheets (GNPs), [100] similar to Raman spectroscopy results. High-resolution TEM (HR-TEM) has additional importance in identifying the atomic bonds and defects on the surface of graphene sheets [117]. The aspect ratio of graphitic filler suspensions in dilute systems can be determined using viscosity measurements within certain limits. In addition to these, static light scattering measurements of dilute graphene oxide dispersion reveal its fractal dimensions. There are reports on the existence of nearly flat sheets (df = 2.15) [151] and crumpled membranes (df = 2.54) [152] in graphene oxide structure. However these results were found to be sensitive to solvent polarity [151,152]. Electrical conductivity measurement offers a simple tool to identify the percentage of reduction from graphene oxide to graphene from the variation in hybridization [49,153–155]. Chemical modification on graphene fillers can be identified by several methods. X-ray photoelectron spectroscopy (XPS), infrared spectroscopy (IR) and nuclear magnetic resonance spectroscopy (NMR) are a few among them. XPS is effective in finding out the amount of oxygen present in the surface functional groups and in identifying the types of carbon oxygen bonds as illustrated in Fig. 6. The existence of C–O, C O, or –O–C O bonds on graphene oxide and other functional groups derived from these groups [122,123,153] are observable from the chemical shift values in XPS spectra, but their quantification is limited. It is reported that 13 C NMR is the most direct and suitable method to distinguish the total number of oxygen functional groups in graphene [107,109,111,146] overcoming the limitations of the XPS and absorption [156–158] methods [109]. The above mentioned characterization techniques have their own significance and provide information about the nature

of fillers, their mode of dispersion, modification of surfaces and interaction effects. 3. Elastomer/graphitic filler nanocomposites 3.1. Synthesis The dispersion of graphene and graphite derivatives in an elastomer is the most important step during the fabrication of a composite. Elastomer properties change significantly if the filler particles acquire high level and homogeneity in terms of dispersion. Among the various factors influencing dispersion, the nature of interaction between the filler and matrix at the interface has substantial implication on the final composite properties. Thus, efforts to improve the interfacial interaction are a principal focus in all manufacturing techniques. In general, elastomer nanocomposites can be synthesized in one of the three ways, viz., melt intercalation, solution mixing, and in situ polymerization. These techniques are useful for graphene and graphite/elastomer composites fabrication as well. It is important to mention about the rubber processing equipments also in this section. Different instruments such as two roll mill, three roll mill, etc., are used to masticate the elastomer composites mechanically. In the case of latex suspensions, mechanical stirrers, magnetic stirrers, sonicators, etc., also work for this process. Melt mixing devices for elastomers include Haake devices, extruders, injection molding devices, etc. Depending on the method of mixing, instruments are selected and processing is done accordingly. 3.1.1. Melt intercalation Melt blending/mechanical mixing is the most economically attractive and scalable method for industries to fabricate elastomer nanocomposites. During this process, fillers are dispersed in the polymer matrix by applying a shear force. The advantage of this method lies in the absence of utilization of organic solvents, and its applicability to both polar and non-polar elastomers. Among all graphitic filler-reinforced composites, most research reports melt mixing process with TRG, when compared to CRG because of its thermal stability. Prud’homme et al. observed the enhanced properties for NR/graphene nanocomposites prepared by the melt compounding technique [45] over the solution mixing

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Fig. 5. TEM images of (a) GNP, five layers with an interlayer spacing of 0.334 nm (b) graphene sheets at low magnification, inset showing the folded area (c) high resolution image of the folded area in (b). [30] Copyright 2009. Reproduced with permission from Elsevier Ltd.

process, and patented the results. Kim et al. prepared TPU/FGS (functionalized graphene sheets)/GO (graphene oxide) composites following the same technique [3]. Composites of styrene–butadiene rubber with graphite powder having different sizes are also reported using melt mixing [37]. Song et al. synthesized SBR compounds with various kinds of graphitic fillers such as natural-graphite platelets (NGs) and acid-graphite platelets (AGs). They modified graphite by following thermal shock (NGT and AGT), sonication (NGS and AGS), and sonication after thermal shock (NGTS and AGTS) with coupling agents [159]. These coupling agents were found to be effective in modifying the surface chemistry of acid–graphite, and melt blending resulted in their homogeneous dispersion in SBR matrix. Al-solamy et al. prepared piezoresistive NBR/graphite nanoplatelets (GNP) composites using melt mixing [29]. Yang et al. mixed powdered graphite of different particle sizes with NBR using melt mixing at room temperature [38]. There are also reports showing the effective synthesis of graphite/PVC (40) –NBR (60) blend composites [36] and acrylonitrile butadiene rubber (NBR)/high abrasion furnace black (HAF)/graphite hybrid nanocomposite [160] using the melt mixing method. 3.1.2. Solution dispersion Though the conventional direct blending method provides sufficient torque to disperse the fillers in rubber matrices, the high viscosity of the material often

causes non-uniform dispersion of graphite platelets [33,34,36–38,44,45]. Solution mixing has been widely reported as an effective fabrication technique due to the ease of processing graphite derivatives and graphene in water or organic solvents [33,44–47,163,164]. This process generally involves the mixing of colloidal suspensions of graphene-based materials with the desired elastomer, either itself already in solution or by dissolving the elastomer in the same solvent used for filler dissolution, by simple stirring or shear mixing [72,145]. In order to get better dispersion of graphitic fillers, sonication is often practiced. Bai et al. compounded hydrogenated carboxylated nitrile butadiene rubber (HXNBR) with exfoliated graphene oxide by a solution-blending method using THF as solvent with the aid of ultrasonication [46] and obtained better dispersion [145]. Zhan et al. prepared NR/GE (graphene) composites by ultrasonically assisted latex mixing and an in situ reduction process [44]. However, they could not avoid degradation of polymer during the in situ reduction step. The possibility of restacking of the platelets in solution mixing process can be further prevented by using certain surfactants which have the ability to stabilize particle suspensions. Chemical modification of GO with isocyanate or amine in aprotic solvents prior to composite manufacturing has been reported. Butyl rubber (IIR)/graphene nanocomposites using the surfactant cetyltrimethylammonium bromide were fabricated by Lian et al. [47] using solution processing and the method followed by them is

Fig. 6. (a) XPS general spectra and curve fit of C1s spectra of (a) GNP, (b) GONP and (c) graphene. 1: 284.5 Cg sp2; 2: 285.6 Cd sp3; 3: 285.9 C–O; 4: 286.7 C–N; 5: 287.8 C O; 6: 289.6 COO . [30] Copyright 2009. Reproduced with permission from Elsevier Ltd.

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Fig. 7. Schematic representation for the fabrication of graphene-IIR nanocomposite membrane. [47] Copyright 2011. Reproduced with permission from John Wiley & Sons.

schematically represented in Fig. 7. Kim et al. also prepared TPU/FGS (functionalized graphene sheets)/GO (graphene oxide) composites via solvent blending. They dispersed TRG, Ph-iGO, and GO into TPU using the solvent DMF [3]. Solvent casting has also been reported for elastomer/graphite composites. Yang et al. fabricated NBR latex/EG (expanded graphite) composite using the surfactant sodium dodecyl sulfate (SDS) in H2 O [33] and compared the dispersion of the filler and the melt mixing methods. They observed that the surfactant prevents restacking of the flat expanded graphite sheets. Hexane was used as the solvent to prepare SR/graphite nanosheets composites, and both mechanical stirring and ultrasonic treatments were used to obtain uniform dispersion of GNPs within the matrix [43]. Mu and Feng used toluene to prepare methyl vinyl silicone/EG composites [17]. Vulcanized silicone rubber (RTVSR)/graphite nanosheets (GNP) nanocomposite were fabricated by Soltani et al. using an alkyl ammonium salt as an interfacial compatibilizer at room temperature. They made nanocomposite samples by incorporating dried GNP powder into the RTVSR/n-hexane solution and then applying shear mechanical mixing [165]. The advantage of using only one solvent [168] throughout the whole preparation process of graphite nanoplatelets (GNP) filled thermoplastic polyurethane (TPU) nanocomposites was introduced by Quan et al. [166]. Comparison between the solvent mixing and melt blending processes show the better possibilities of the former. Since most rubbers naturally exist in latex form, the latex compounding method (LCM) is comparatively easy, and it maintains very good performance/cost ratio. The

partial ionic nature of certain graphite derivatives due to the presence of certain functional groups (epoxide and hydroxyl) on their surface can cause an easy and enhanced intercalation with those elastomers having ionic nature [33,44,46,146,167,169]. A modified solution process is used by Kim et al. for preparing multi-layered graphene sheet/SBR nanocomposites. They used heterocoagulation between negatively charged SBR latex particles and positive surface modified multi-layered graphene in aqueous medium using flocculant, polyaluminium chloride [170]. The hexadecyltrimethylammonium bromide (HTAB) and CTAB surfactants impart positive charge to the filler, and this helps in the improved reinforcement effect between the filler and the elastomer. Even though solution mixing provides better dispersion effect in the liquid state, the suitable solvents, surfactants, sonication, mixing time are the essential criteria to be considered for maximum dispersion efficiency. 3.1.3. In situ polymerization In situ polymerization methods have also been reported in the preparation of graphite derivatives and graphene/elastomer composites [3,17,171,172]. In this, unlike solution mixing, a high level of dispersion of graphene-based filler has been achieved without a prior exfoliation step. The filler is first mixed with neat monomers (or multiple monomers), or a solution of monomers, followed by in situ polymerization. This process helps to increase the interlayer spacing, and exfoliates the layered structure of graphite into graphite nano plates and the intercalation of monomers generate polymer. Kim

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Fig. 8. TEM images of NRL containing graphene after (A) 10 times, (B) 15 times and (C) 20 times dilution. [44] Copyright 2011. Reproduced with permission from John Wiley & Sons.

et al. reported the synthesis of TPU/graphene derived composites following in situ polymerization [3]. Polyisoprene/graphene and GIC composites are produced by the polymerization of isoprene monomers initiated by the negatively charged fillers in the presence of alkali metals [170]. In situ polymerization method is quite useful for the fabrication of elastomer composites, but it is not free from limitations. It is found that this method is not suitable if the polymerization takes place at the surface of the GICs or between the layers [17,172]. This method also requires monomer units as well as lot of reagents for the polymerization procedure, and thus less applicable in the case of naturally existing polymers. 3.2. Quantifying dispersion of elastomer/graphene and graphite derivative composites Investigation of the level of dispersion of fillers in a polymer matrix is a difficult task while manufacturing composites or after sample preparation. Scanning electron

microscopy (SEM), transmission electron microscopy (TEM), X-radiography (XRD), Raman spectroscopy and surface measurements (AFM) are generally used to assess the mode of dispersion. This is completed by image analyzes that explore composite structure, number of particles in a specific area, aggregate size, etc. Mu et al. observed the difference between melt and solution processing of silicone/EG (10 phr) composites by SEM photographs [17]. Nanocomposites prepared by solution intercalation had multiple network structure composed of particles, boards or sheets, and nanosheets at different scales. On the contrary, the authors did not observe such multiple networks in the normal composites prepared by melt mixing. Though graphite has a lower atomic number contrast with polymers, it can be imaged by TEM technique without staining [3,135,173] whereas in graphene, the smaller thickness of isolated sheets makes it difficult to obtain satisfactory image resolution. As already indicated in the previous sections, chemical modifications and the surface defects arising from thermal treatment

Fig. 9. TEM images of (a) SBR and (b) NR nanocomposites with 5 phr of graphite. [33] Copyright 2007. Reproduced with permission from Elsevier Ltd.

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respectively, represents the integrated 1D and 2D wide angle X-ray diffraction (WAXD) scattering as a function of the strain before failure. Reflections from all crystalline regions contribute to the total intensity, which gives evidence of a similar crystallinity at maximum extension for all composite samples. 3.3. Cure kinetics

Fig. 10. X-ray diffraction patterns: (c1) unfilled NBR vulcanizate at small angle (0.5–10◦ ); (c2) EG powder pretreated with ultrasonic irradiation with SDS (surfactant) intercalated (c3) NBR/EG (5 phr) nanocomposite prepared by latex compounding at small angle. [33] Copyright 2007. Reproduced with permission from Elsevier Ltd.

also distort two-dimensional graphene sheets into a highly wrinkled form. Despite these difficulties, attempts to quantify graphene dispersion in elastomers directly by TEM have been reported. Fig. 8 represents the TEM images of natural rubber latex (NRL)/graphene composites at different dilutions. It was observed that with 20-fold dilution, exfoliated GE has an average width of 1–2 mm and a thickness of 1–3 nm [44]. Yang et al. quantified expanded graphite dispersion in SBR and NR matrices using TEM. They succeeded in obtaining well dispersed EG at 5 phr loading, [33] as characterized by the TEM image in Fig. 9. The dispersion of graphite in elastomers as well as the crystallinity of nanocomposites with different filler concentrations was characterized by Lian et al. [47] using XRD, including natural graphite-butyl rubber (NG-IIR) and modified graphite-butyl rubber (MG-IIR). The diffraction peak at 2 ≈ 26.5◦ observed for NG and NG-IIR composites confirmed retention of stacking order of NG in the composite. On the other hand, no peaks appeared in the diffraction pattern of MG-IIR composites, indicating a complete exfoliation of MG in the IIR matrix [47]. Similar XRD patterns have been reported for graphene/elastomer composites [44–46,170]. Yang et al. investigated the effect of surfactant on EG dispersion in NBR latex by the same technique. The XRD pattern in the small angle range (0.5–10◦ ) of the ultrasonic and SDS (sodium dodecylsulfate, surfactant) pretreated EG powder is shown in Fig. 10 (curve c2). The small percentage of intercalated NBR/EG composite structure is evidenced by the shift in the diffraction peak of graphite to the much lower level of 1.02◦ (curve c3). The peak at 2.89◦ is an indication of change in the surfactant intercalation structure while processing via latex compounding and molding [33]. The strain induced crystallization behavior of natural rubber has been studied using the X-ray diffraction coupled with tensile test (Fig. 11) [98]. The influence of stress at the commencement of crystallization on the degree of crystallinity and orientation of the crystallites in nanocomposites are clear from XRD. Fig. 11(a) and (b),

Vulcanization is a chemical process of elastomer chain crosslinking. The kinetics of curing or vulcanization of rubber materials is rather complex as it depends upon several factors, such as the composition of the rubber compound, temperature and method employed to compound the material. Addition of fillers causes variation in the values of torque and scorch time. The dispersion effect of fillers in composites can be explained using minimum and maximum torques measured during the cure. The minimum torque corresponds to the original viscosity of the unvulcanized elastomer/filler blend and the maximum torque corresponds to high surface area of fillers, which induce strong interfacial interactions with the matrix. As a result, the vulcanization reaction proceeds completely and facilitates the formation of a crosslink network, which in turn yields effective load transfer between the filler and rubber matrix [44]. The kinetic studies of crosslinking are helpful in characterizing various concomitant reactions that take place during vulcanization processes in rubber compounds. Table 2 represents the curing properties of elastomer/graphene and graphite derived composites. The changes in the rheometric torque with filler loading is a measure of the filler–matrix interaction or reinforcement represented by the reinforcing factor (˛f ) and can be calculated from the rheographs [174] using Eq. (1). ˛f =

Lmax (max) − Lmax (gum) . Lmax (gum)

(1)

where Lmax (filled) and Lmax (gum) are the changes in torque during vulcanization of the filled and gum compounds, respectively. An increase in ˛f values with increasing graphite content in SBR composites was observed by Ismail and Khalaf [37]. The value of ˛f also increased with decrease in particle size, indicating increasing reinforcement. The t90 values of the samples filled with graphite were lower than those of the unfilled samples, decreasing with increasing graphite concentration as graphite accelerated the reaction between the sulfur and rubber compounds [37,175]. These aspects appear clearly in Table 2 and Fig. 12. Among the vulcanization characteristics of NR composites with three different fillers GE, CB and MWCNT shown in Table 2, the minimum and maximum torque of NR/(2 wt%) GE composites were observed to be higher. In the NBR/graphite system (Table 2), the curing processes for all kinds of composites were found to be quite similar. This is because of the chemical inertness of the graphite fillers during the curing reaction [38]. Song et al. observed typical curing curves for graphite filled SBR compounds as shown in Fig. 13. It was found that the curing of rubber composite using acid–graphite and coupling agent (A/C) was faster than that of other rubber composites. The

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Fig. 11. Coupled WAXD and tensile tests for neat NR and NR filled with 1 and 4 wt% FGS, and 16 wt% CB. (a) 1D WAXD patterns for unstretched neat NR, and all samples shortly before failure in the tensile test. Small peaks from 22 to 26 nm−1 are from ZnO in the base rubber formulations. (b) 2D WAXD patterns at strain = 2 (air scattering is subtracted as background). Stretch direction is vertical. [98] Copyright 2012. Reproduced with permission from John Wiley & Sons.

Fig. 12. Rheographs of SBR vulcanizates filled with graphites of different particle sizes (53–150 ␮m). [37] Copyright 2011. Reproduced with permission from John Wiley & Sons.

Fig. 13. Curing curves of SBR/graphite compound at 160 ◦ C. [34] Copyright 2010. Reproduced with permission from Springer.

6.50/7.20 6.00/7.20 6.50/7.20 6.50/7.20 36.10/27.20 35.50/27.20 35.40/27.20 37.20/27.20 7.28/5.08 7.60/5.08 6.77/5.08 7.61/5.08 40 phr 40 phr 40 phr 40 phr – – – – Graphite, ␮m Graphite, sub␮m EG Graphite, spherical

Melt Melt Melt Melt

16.00/27.00 17.00/27.00 17.00/27.00 16.00/27.00 136.00/63.00 134.00/63.00 127.00/63.00 116.00/63.00 12.00/8.00 13.00/8.00 14.00/8.00 14.00/8.00 140 phr 140 phr 140 phr 140 phr – – – – Graphite (<53 ␮m) Graphite (53–90) ␮m Graphite (90–125) ␮m Graphite (125–150) ␮m

Melt Melt Melt Melt

37.20/35.50 37.80/35.50 53.80/54.60 55.60/54.60 16.60/19.10 17.80/19.10 4.76 wt% 4.76 wt% – bis-(3-Triethoxy silylpropyl) tetrasulfane AG

Melt Melt

5.13/5.53 5.05/5.53 5.20/5.53 2.44/2.20 2.21/2.20 2.25/2.20 0.33/0.21 0.21/0.21 0.18/0.21 Solution Solution Solution 2 wt% 2 wt% 2 wt% – – – GE CB MWCNT

Content Compatabilization Filler

761

reason for the shorter cure time of the rubber composite using A/C is probably due to the higher specific surface area due to acid treatment and the increase of thermal transition of SBR in the presence of A/C, facilitating vulcanization via filler–filler and filler–matrix interactions [34]. 3.3.1. Self-curing effect An important curing behavior known as self-curing is observed in certain nanocomposite systems. Self-curing is usually initiated by the free radicals present on the fillers at high temperature. This can happen in two ways, one way is through the direct reaction of radicals with the double bonds of the rubber chains, and the other is through allylic hydrocarbon abstraction. Finally, the combination of polymeric free radicals or chain reactions involving radical to double bond polyadditions, lead to crosslinking. Yang et al. [33] investigated the self-curing effect of SBR and NR nanocomposites containing graphite nanosheets using the latex compounding method. They observed the selfcuring effect of GNP to be temperature dependent (Fig. 14). The kinetics of the effect are clear from Fig. 14(a). At 5 phr graphite filler loading, above 120 ◦ C temperature, the torque of the composite rapidly increases with time, and thereafter reaches a steady state gradually. No crosslinking occurs when the temperature is below 100 ◦ C, whereas at 110 ◦ C and above, the increase in the rate of torque change with time indicates the initial steps of crosslinking. A large increase in torque is observed in the case of NBR/EG composites, due to the faster crosslinking reaction caused by EG. The behavior of SBR/EG system is different from this, and gives a clear cure dynamics when the temperature approaches 160 ◦ C (Fig. 14b). It is impossible to completely cure neat SBR without curing agents. The self-crosslinking ability and its rate are lower for SBR composites than for the NBR composites, but the torque increases rather quickly with temperature. In the case of natural rubber nanocomposites, since there is a chance for the radicals on EG to react with the isoprene units, the abstraction pathway predominates, and crosslinking therefore mainly occurs through the coupling of polymeric radicals, as already discussed [176–187]. However, the abstraction reaction occurs at the points of contact where the radicals on EGs meet the allylic hydrogens on rubber macromolecules, thus limiting the possibility of the reaction. This is the reason NR nanocomposites have lower curing efficiency [33]. The investigation on the self-curing effect is important in the case of elastomer/graphitic filler nanocomposites due to the possibility of radical formation of the fillers, and since this effect avoids the use of curing agents. 4. Characteristic properties of elastomer/graphene and graphite nanocomposites

NBR [38]

SBR [37]

SBR [34]

NR latex [44]

4.1. Mechanical properties

Elastomer

Table 2 Curing properties of elastomer/graphene and graphite derivatives composites.

Processing

Minimum torque, N m (composite/pure matrix)

Maximum torque, N m (composite/pure matrix)

Optimum vulcanization time (min) (composite/pure matrix)

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The promising mechanical strength of all graphitic fillers offers potential for the development of affordable, high quality composites [45]. Modulus improvement in elastomer/graphene composite is more significant than other polymer/filler nanocomposites, which indicates

762

Table 3 Mechanical properties of elastomer/graphene and graphite derivative nanocomposites. Filler

Compatibilizer

Content

Processing

Modulus (MPa) (composite/pure matrix)

Tensile strength (MPa) (composite/pure matrix)

Elongation at break (%) (composite/pure matrix)

NR latex [44]

CRG in situ reduction

–

2 wt%

Solution Melt

M 300 6.6/2.4 2.47/2.4

25.20/17.10 18.80/17.10

564/579 600/579

NR [45] SBR [50] SR [48]

TRG FGS FGS

–

1.2 (vol%) 2 wt% 0.05 wt% 3 wt%

Melt/Solution – – –

1.3/– – 1.42/1.33 4.8/1.33

– 11.00/2.00 0.52/0.57 3.43/0.57

– – 66/74 112/74

HXNBR [46]

GO

–

0.44 (vol%) 1.3 (vol%)

Solution Solution

M 200 3.4/1.7 6.5/1.7

22.40/14.80 10.30/14.80

419/534 248/534

IIR [47]

MG

CTAB

1 wt% 10 wt%

Solution Solution

∼0.5/0.17 ∼3.5/0.17

∼0.22/0.20 ∼0.50/0.20

∼320/600 ∼300/600

SBR [45]

FGS

–

2 phr

–

5/1

11.00/1.80

600/400

SBR [34]

AG

– bis-(3-triethoxy silylpropyl)tetra sulfane

5 phr 5 phr

Melt Melt

M300 22.6/21.9 25.3/21.9

29.00/25.70 30.00/25.70

397/342 395/342

SBR [161]

Graphite:HAF

–

30:20 phr

Melt

M100 2.70/–

13.40/–

511/–

SBR [37]

Graphite (<53 ␮m) Graphite (125 ␮m)

– –

140 phr 140 phr

Melt Melt

– –

4.35/1.03 3.25/1.03

80/235 67/235

TPU [3] TPU [166]

TRG GNPs

– –

1.6 (vol%) 2.7 (vol%)

Solution Solution

6.1–7.1/– 35/10

– 25.00/28.00

– –

NBR latex [33]

EG

–

10 phr

Solution Melt

11.5/1.1 1.8/1.1

11.80/4.00 5.80/4.00

110/410 610/410

NBR [38]

Graphite (diameter < 2 ␮m, thickness ∼ 130 nm) EG Graphite (<30 ␮m) Nickel coated graphite 40:60) EG

–

60 phr

Melt

M100 4.3/1.0

10.20/3.00

563/480

SDS – Vinyltriethoxy silane –

5 phr 70 phr 200 phr 15 wt%

Solution Melt Melt Solution

M100 2.4/1.3 25/5 M100 3.26/1.03 1/– (220% increase)

12.20/7.40 4.50/1.80 3.87/4.56 –

590/590 53/56 142/475 –

PDMS [49]

FGS CNT

– –

2 wt% 2 wt%

Melt Melt

M100 0.99 ± 0.03/0.33 ± 0.05 M100 0.69 ± 0.06/0.33 ± 0.05

– –

528 ± 32/842 ± 23 583 ± 14/842 ± 23

NBR [188]

EG (micro) EG (nano)

– –

10 phr 10 phr

Melt Melt

– –

6.00/5.80 10.00/5.80

250/300 220/300

NBR [41]

EG/CB (micro) EG/CB (nano)

– –

5/40 phr 5/40 phr

Melt Melt

4.30/1.70 7.60/1.70

19.80/2.80 18.80/2.80

381/300 218/300

XNBR [35] NBR-PVC (60:40) [36] SR [162] PDMS [164]

–

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Elastomer

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enhanced elastomer–graphene interaction [3]. Even though the modulus increases significantly, the ductility of elastomers is compromised by the incorporation of rigid fillers and the graphene-filled elastomers often show a decline in tensile strength. A summary of the mechanical properties of graphite derivative and graphene reinforced elastomer nanocomposite is given in Table 3. The properties vary significantly with the nature of fillers and elastomers, size and content of fillers, mode of dispersion, influence of coupling agents and composite fabrication methods. Upon the addition of graphite, the tensile strength of SBR is remarkably improved, and this verifies the reinforcing effect of graphite fillers [37]. However, the tensile strength and the elongation at break of the composites were found to be decreasing as particle size was increasing. An increase of about 32% in modulus and approximately 18% increase in tensile strength in the AG (acid–graphite platelets) composites as compared to the unmodified one were demonstrated by Song et al. [159]. The reasons for these increased mechanical properties include the greater specific surface area, and both physical and chemical interactions between graphite and elastomer through the coupling agent. They also found a decrease in fatigue crack growth of composites when acid graphite is used, due to the functional groups assisted uniform dispersion of acid–graphite in SBR matrix. The authors also reported [34] a slight increase in the hardness of SBR/acidic–graphite composites indicating that small additions of filler do not largely influence the rubber matrix. The composite reinforced with acidic–graphite using coupling agent showed an increase in mechanical properties over graphite as evidenced from Table 3. Dependence of filler particle size on the mechanical properties of NBR composites was investigated using micrometer, submicrometer, expanded, and spherical graphite fillers [38]. In all cases, the tensile strength, modulus at certain elongation (e.g., 100%), and hardness of NBR increased as filler contents increased. The Young’s modulus was highest for expanded graphite reinforced composites among the different graphitic filler composites studied at the same loading level. This was in accordance with the hardness data since both were measured at low strain. In such a low strain range, bigger filler particles can effectively

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carry the load. The reason behind expanded graphite showing the highest Young’s modulus is its smallest size leading to improved reinforcement compared with that from the larger particles with lower surface area. High-performance NBR latex nanocomposites with combined mechanical and functional properties [33] have been reported. To fabricate these composites, graphite sheets are dispersed in NBR matrix by following a simplistic approach of latex compounding (LCM). Dispersion of nanofillers plays an important role in regulating the composite behavior, and this compounding method influences the dispersion to a great extent. The tensile properties of NBR/EG vulcanizates fabricated following two routes – LCM and direct blending – varies significantly depending on the quality of dispersion of EG. Latex compounding results in fine dispersion of fillers in the matrices, more filler–elastomer interfacial interaction and thus better reinforcement. The typical stress–strain curves of rubber/EG composites with different filler loadings and rubber/carbon black or silica at 10 phr loading following different mixing methods are compared in Fig. 15(a) [33]. The substantial increase in tensile strength with 0–10 phr EG loading is observed for composites synthesized by following LCM. The stress at small strain (under 100%) also significantly increases with increasing EG (at 10 phr) for LCM rather than direct blending (Fig. 15a). A high level of reinforcement is obtained in the case of NBR/10 phr EG composite prepared by LCM technique, as compared to carbon black or silica composites. This stronger reinforcement is due to the high aspect ratio as well as the enlarged surface areas of graphite sheets along with the interfacial interactions between functional groups (–OH and –COOH) present on the EG surface and the rubber chains. In a similar work by Ozbas et al. almost the same level of reinforcement was observed with NR and PDMS elastomers, generalizing the effect of property enhancement [50]. The relative enhancement in the modulus is much lower for carbon black filled composites, as observed from Fig. 15(b). In this case of CB-filled NR and SBR composites, filler loading of about 16 wt % produces the same modulus enhancement as achieved with 1 wt % FGS addition. Moreover it is clear that better reinforcement for elastomers can be obtained by FGSs rather than CNTs and clay platelets, as

Fig. 14. Temperature dependence of self-curing reaction of (a) NBR/5 phr graphite and (b) SBR/5 phr graphite nanocomposites. [33] Copyright 2007. Reproduced with permission from Elsevier Ltd.

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Fig. 15. Tensile stress vs. strain curves for (a) composites with different fillers like carbon black and silica at 10 phr loading. (b) Normalized modulus values with respect to neat rubber for FGS-filled NR, SBR, and PDMS and CB-filled NR and SBR (c) Stress strain curves for Modified Graphene-IIR nanocomposites (1–10 wt%). [33] Copyright 2007. Reproduced with permission from Elsevier Ltd.; [50] Copyright 2012. Reproduced with permission from John Wiley & Sons; [47] Copyright 2011. Reproduced with permission from John Wiley & Sons.

demonstrated in Fig. 15(b). In the case of NR composites, the strain induced crystallization also contributes towards an enhanced modulus. Synthesis of NBR/EG nanocomposites following melt mixing [187] also increased the tensile strength by 78% and storage modulus by 90% at a loading of 5 wt% below glass transition temperature. Zhan et al. [44] obtained an increase of 47% and 50% in the tensile strength and tear strength respectively for the natural rubber latex (NRL)/GE (Chemically Reduced Graphene, CRG) composites with 2 wt% filler content. In contrast, the tensile strength of NR/CB (carbon black) and NR/MWCNT (multi-walled carbon nanotube) composites was increased by only 6% and 9%, respectively. The reasons for the better reinforcing effect or adhesion between GE and NR matrix are assigned to their higher specific surface area, high strength and excellent tensile modulus [189]. As illustrated in Fig. 15(c), the greater level of dispersion in MG (Modified Graphene with surfactant) –IIR nanocomposites results in a higher mechanical strength compared to NG (Natural Graphite)-IIR composites [47]. The highest value for Young’s modulus (3.4 MPa) is exhibited by the 10 wt% MG nanocomposites, which is about 16 times higher than that of pure IIR (0.21 MPa) (Table 3). Since the mode of dispersion of fillers in the matrix is directly related to fabrication methods of nanocomposites, mechanical properties are strongly influenced. Kim et al. [3] compared mechanical properties of thermoplastic polyurethane (TPU)/functionalized graphene composites by varying mixing methods, and concluded that solvent mixing is effective than melt mixing for the enhancement of TPU properties. Melt mixing results in a lower modulus for the composite due to the possibility of reaggregation of graphene flakes during compounding. Thermally exfoliated GO (TEGO)/polyurethane composites prepared via in situ polymerization showed less improvement in modulus than solution mixed composites, despite good dispersion [3]. An increase in modulus of over two orders of magnitude (from approximately 10 MPa–1.5 GPa) at 55 wt% GNP [180] have been reported for polyurethanes. Bai et al. [46] observed an increase of 50% and 100% in tensile strength and in the modulus at 200% elongation of the HXNBR when the GO content was 0.44 vol%. As shown in Table 3 the modulus value of HXNBR consistently increased from 1.7 to 6.5 MPa as GO

content increased at the expense of elongation at break. The tensile strength also enhanced from 14.8 to 22.4 MPa, by the addition of 0.44 vol% GO and thereafter decreased to 10 MPa when the GO content was 1.3 vol%. [46]. GO/HXNBR composites showed higher tensile strength (22.4 MPa) than their CNT counterparts (15.7 MPa) at 0.44 vol% filler loading indicating better reinforcement effect of GO. The authors correlated the experimental observation with the Halpin Tsai model, which is helpful in determining the orientation of fillers in matrices. The theoretical values can be derived by starting with the values of Young’s moduli of the composites containing randomly oriented (Er ) and or unidirectional (Eu ) GO sheets parallel to the surface, in HXNBR matrix using Eqs. (2) and (3), respectively.

  3 8

Er = Em

 Eu = Em

1 + L Vg 1 − L Vg

1 + L Vg 1 − L Vg



+

5 8



2T Vg 1 − L Vg



(2)

 (3)

with Er and Eu the moduli of the composites and Vg the volume fraction of GO in the composites. The density of HXNBR is 0.97 g cm−3 and the density of GO is 2.28 g cm−3 . The terms L ,  and T can be defined by Eq. (4). L =

T =

(Eg /Em )−1 (Eg /Em )+ (Eg /Em )−1 (Eg /Em )+2

where

=

21 3d

(4)

(5)

Here Eg and Em are the Young’s moduli of the GO and neat HXNBR. The calculated and experimental moduli of the composites with different distributions of the GO sheets [185,186] are compared in Fig. 16. It may be seen that the experimental results are close to the theoretical modelling results for the composite with random distribution of GO sheets, and thus their random dispersion throughout the HXNBR matrix is confirmed. Pott et al. explored the influence of orientation of GO platelets in NR matrix by a theoretical analysis to draw a correlation between the morphology, mechanical and processing of the nanocomposites [190]. However, they did not provide an explanation of

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Fig. 16. Young’s moduli of the composites and Halpin–Tsai theoretical models for both random orientation and unidirectional distribution of GO sheets in the HXNBR matrix. [46] Copyright 2011. Reproduced with permission from Elsevier Ltd.

the equations used for the modelling studies. In short, the mechanical analysis give not only the information about the tensile properties, but also the factors influencing the properties and physical aspects of composites. Dynamic mechanical measurements also have a significant role in determining the composite properties. Chen et al. [43] investigated the mechanical properties of silicone rubber nanocomposites with various GNP content. The dynamic mechanical properties such as the elastic and viscous moduli vary with the mechanical property improvement. The elastic modulus of the nanocomposite is enhanced by increasing GNPs, and further by the addition of Al2 O3 nanoparticles. The mechanical strength also improves with nano alumina addition even at a very low loading level. Mu and Feng [17] observed higher storage modulus E for silicone/EG composites prepared by solution intercalation than their melt mixing counterparts at 10 phr EG content as a function of temperature. This is because of the more dramatic reinforcement effect obtained in the solution mixing process. In general when the filler particles are incorporated in the elastomer matrices, the storage modulus at a temperature above the glass transition temperature Tg increases resulting in an increased G compared to the neat matrix [62]. The value further increases as the filler concentration increases. Also Tg will increase if the filler imparts crystallinity to the matrix. The remarkable reduction in the molecular mobility of elastomer chains around the graphitic filler sheets increases Tg . In addition, the area under the tan ı peak is greatly reduced with the filler concentration reflecting the reduction in damping properties [33]. 4.2. Electrical properties Electrically conductive elastomer composites are made by dispersing a conductive phase (carbon black, graphite powder, carbon fibre, micro-particles of metals, CNT, EG, GNP and graphene) in an elastomer, and the conductivity is a function of filler loading, as described by percolation theory [191,193]. Addition of graphite

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derivatives to insulating elastomer matrices can change them into electrical conductors with high level of electron delocalization at significantly lower loading compared to CNTs [135]. This is mainly due to the larger surface area of graphite sheets than nanotubes. It is the most suitable alternative to conventional carbon black fillers, where a decrease in properties for CB-filled polymer composites is often observed due to the high amount of filler used [163,194,195]. Graphite, an abundant resource, has established a unique position among conductive fillers [96,196,197], and possesses excellent electrical conductivity of ∼100 S/cm. At low levels of filler loading, the average distance between the filler particles is more than their size range, and so the fillers exist as individual units rather than connected networks. Due to this, the conductivity of the nanocomposite becomes very close to that of the pure insulating matrix. For current flow, the fillers need not be in direct contact with each other, but rather conduction can take place via tunnelling between thin polymer layers surrounding the filler particles, and this tunelling resistance is the limiting factor in the composite conductivity [191,192]. At a sufficient concentration level, the filler forms a percolation network, allowing charge transport within the composite. This critical filler concentration is called the percolation threshold and is marked by a rapid increase in conductivity. The value of the percolation threshold varies from filler to filler [198] as it depends on geometry and orientation. Other than the 2D structure and aspect ratio of GNP, the number of GNP particles also has a key role in the percolation behavior of elastomer/GNP nanocomposites. It has been found that conductivity of GNPs improves by doping/modification [53,89]. This is done by adding electrons to the conduction band, or holes to the valence band, and forming a charge–transfer complex. Table 4 presents the electrical conductivity values for graphene and graphite derivative elastomer nanocomposites. After achieving the percolation, the conductivity increase as a function of filler loading can be modelled by a simple power-law expression represented by Eq. (6): t

c = f [( − c ) ]for  > c

(6)

where  is the filler volume fraction, c the percolation threshold,  f the filler conductivity,  c the composite conductivity, and t is a scaling exponent. Of these, c ,  f and  c may be determined experimentally. Chen et al. compared the electrical properties of SR/GNPs and SR/conventional graphite composites with various filler contents [43]. The decrease in resistivity observed for SR/graphite composites with graphite concentration is illustrated in Fig. 17(a). The figure indicates that the percolation threshold values for SR composites filled with GNP and two kinds of mesh graphites (represented as 8000 and 2000) are about 0.009, 0.053, and 0.07 respectively. The excluded volume theory [199,200] accounts for the formation of the conductive percolation network at low loading level, which is due to the specific geometry of GNPs with an aspect ratio of about 100–500 higher than that of conventional graphite. As mentioned earlier, a compatibilizer causes better dispersion of filler particles in the matrix, and this can again improve electrical conductivity, like all other properties. An example of

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Table 4 Electrical conductivity of elastomer/graphene and graphite derivative nanocomposites. Elastomer

Filler

Compatibilizer

Processing

Electrical percolation threshold

NR latex [44]

TRG

– –

Melt Solution

>2.00 (vol%) 0.80 (vol%)

TPU [3]

TRG

– –

Solution In situ polymerization

1.00 (vol%) 1.60 (vol%)

SBR latex [170] NBR [29] SR [48] SR [145]

MLGS GNP FGS Graphene

HTAB – –

Solution Melt – Solution

0.50–1.00 wt% 0.50 phr 0.10–0.20 wt% 2 wt%

SR [43]

GNP 8000 mesh grpahite 2000 mesh graphite

– – –

Solution Solution Solution

0.009 (v/v) 0.053 (v/v) 0.07 (v/v)

PDMS [164] NBR:PVC (60:40) [36]

Exfoliated graphite Graphite

– –

Solution Melt

3.00 wt% 40–50 phr

RTVSR [165]

GNP GNP

– BYK-9076 (30 wt%)

Solution Solution

3.00 wt% 1.00 wt%

SR [162]

Nickel coated graphite (40:60)

Vinyltriethoxy silane

Melt

∼15 to 16 (vol%)

this is provided in the study of Soltani and Katbab [165] who showed the effect of compatibilizer on the electrical resistivity of the SR/graphite sheets nanocomposites. The decrease in percolation threshold while using the compatibilizer is exhibited in Fig. 17(b). The value decreased from 3 to 1 wt% graphite sheets upon the addition of 30 wt% compatibilizer, shown by the decrease in resistivity at those levels, whereas above this compatibilizer concentration the resistivity remain unchanged. This is attributed to the maximized dispersion of the graphite sheets at 30 wt% of the compatibilizer and, hence, to fewer chances for the formation of more filler conductive networks. In a comparison of the electrical properties of natural graphite and acid modified exfoliated graphite/SBR, Song et al. [159] observed an increase in conductivity of approximately 60% with the exfoliated graphite. The reasons given in their explanation was the higher specific surface area of graphite platelets, the increase in probability of particle–particle contacts, and the improved interactions between rubber and graphite. Kim et al. also studied the

change in electrical conductivity of multi-layer graphite (MLGS) containing SBR nanocomposites fabricated by heterocoagulation, to obtain the data shown in Fig. 17(c) [170]. The conductivity of the composite increased from 4.52 × 10−13 to 4.56 × 10−7 S/cm as the MLGS concentration changed from 0.1 to 5 wt%. It is also noted that the concentration of the filler that is required to achieve the same electrical conductivity from carbon black is lower because of the high aspect ratio and electrical conductivity of MLGS [201]. The reasons for the observed low electrical percolation threshold were attributed to the efficient mixing process, without damaging fillers and effective network formation in the matrix [43], an effect the authors explained by the segregated network concept [202]. Al-solamy et al. [29] obtained the best electrical property for NBR/graphite nanoplatelets composite at 0.5 phr level (Table 4), much less than the usual percolation range of 5 phr EG. Similar to MLGS, EG also enhances the conductivity to a great extent compared to the conventional carbon black fillers [203,204]. EG imparts very

Fig. 17. Electrical resistivity of (a)SR/graphite and graphite nanoplatelets (GN in the figure) composite as a function of filler content; (b) nanocomposites as a function of graphite sheet concentration with and without 30 wt% compatibilizer; (c) electrical conductivity as a function of MLGS (Multi layer graphene) concentration (wt%) in SBR. (a) [43] Copyright 2008. Reproduced with permission from John Wiley & Sons; (b) [165] Copyright 2010. Reproduced with permission from Elsevier Ltd.; (c) [170] Copyright 2011. Reproduced with permission from Elsevier Ltd.

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767

Fig. 18. DC surface resistance of melt-blended graphite/TPUcomposites (closed symbols, also in inset) and melt-blended, solution-mixed, and in situ polymerized TRG/TPU composites (open symbols). [3] Copyright 2010. Reproduced with permission from the American Chemical Society.

good electrical conductivity at 10 phr loading [35] to a similar system (carboxylated acrylonitrile butadiene rubber (xNBR)/expanded graphite (EG) nanocomposites). The influence of graphite and TRG on the electrical conductivity of TPU was reported by Kim et al. The DC surface resistance of graphite and TRG composites prepared via different methods are compared in Fig. 18. Both graphite and TRG effectively reduce the resistance, but they differ greatly in the percolation concentration (>2.7 vol% for untreated graphite and <0.5 vol% for TRG) [3]. Among the TRG composites, the resistance decreases even at <0.3 vol% of TRG in the case of solvent-mixed samples, whereas it requires >0.5 vol% for melt intercalation because of the possibility of platelet aggregation in the latter.

Fig. 19. Variation of electrical conductivity with temperature for NBR loaded with different concentrations of GNPs (indicated as GN). The solid line represents the fit using the Mott equation. [40] Copyright 2012. Reproduced with permission from John Wiley & Sons.

by using the Mott Eq. (7) which explains the dependence of conductivity on temperature.  = 0 exp

  1/4  T0 −

T

(7)

The constants T0 and  0 are given by T0 =

˛3 kB N(Ef )

and

0 = e2 R2 (T ) 0 N(Ef )

where R(T) is the hopping distance 4.2.1. Temperature sensing Temperature has a substantial impact on the conductivity of materials, and this property is often used in finding out temperature variations (sensing). The influence of temperature on the electrical conductivity of different NBR loaded GNPs has been investigated by Mahmoud et al. They used different concentrations of graphene nanosheets, ranging from 1% to 5%, and observed the dependence of both temperature and filler concentration on conductivity [40]. This increase in conductivity is due to the decrease in the hopping path between GNP layers as the amount of GNP in the rubber matrix increases. The variation of interparticle distance with GNP concentration [205,206] can be clearly understood from Table 5. In a conductive nanocomposite, the inter-particle distance between conductive layers can be determined [207]

Table 5 The calculated values of inter-particle distance between conductive layers at different GN concentrations [40]. GNP concentration (phr) R (nm)

0.1 0.5 1.0 2.0 5.0 101 ± 12 85 ± 7 71 ± 3 68 ± 2 61 ± 1

R(T ) =



9 8˛kB TN(Ef )

1/4

Here ˛−1 is the radius of the localized wave function, e the electron charge, kB the Boltzmann constant, N(Ef ) is the state density at the Fermi level, is a dimensionless constant having a value ∼18.1, and 0 is the jump rate prefactor. Mahmoud et al. plotted the evolution of electrical conductivity with temperature for the same composite samples, and fitted the results using the Mott equation [40] as illustrated in Fig. 19. These results provide evidence for the dependence of inter particle distance on conductivity. 4.2.2. Piezoresistive effects The piezoresistive effect of an electrical resistor is the change in its resistance when subjected to a strain and/or deformation. Piezoresisitivity can provide simple and direct energy/impulse dependence relative to the mechanical and the electrical domains. Piezoresistive materials are used in a wide variety of sensing applications, including accelerometers, pressure sensors, gyro-rotation rate sensors, tactile sensors, flow sensors and chemical/biological

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Fig. 20. A schematic model for the change of conductive structure in the composites under pressing: the conductive fillers disperse randomly in the composite. [208] Copyright 2007. Reproduced with permission from John Wiley & Sons.

sensors. Elastomer/graphite derivatives have extensive possibilities as piezoresistive materials [29,43,165,208], where the electrical resistance depends on both the resistance of each conducting particle and of the polymer matrix. When an external pressure is applied (compression), the inner conducting network of electrically conductive composites changes, and this results in resistance variation. During the compression process, destruction and formation of conductive networks simultaneously occur in the composites (Fig. 20). If the compression is small, the experimental data are consistent with the tunnelling conductance model. But for larger deformations, destruction of the conductive network and decrease of the number of conducting pathways have to be considered. Chen et al. [43,208] fabricated piezoresistive SR/GNP composites with 0.0136 vol% filler loading which is close to the percolation threshold, and they observed finger pressure sensitivity (0.3–0.7 MPa). This is a sharp and positive pressure variation tendency with electrical resistivity especially at very low pressures. This rapid transition behavior is due to the compressive-stress-induced deformation of the conducting network. This is attributed to the high state of dispersion GNPs throughout the SR matrix, thus making insufficient conductive paths between the filler particles under applied pressure. Soltani et al. [165] also succeeded in preparing piezoresistive material from SR and GNPs. They used RTVSR, GNP and an alkylammonium salt as interfacial compatibilizer and solution mixing process for the fabrication of composites. The compatibilizer decreased the conductivity threshold but, in addition, pressure sensitivity was reduced. Later the piezoresistivity of NBR filled with GNPs (10 nm thickness) at percolation limit of 0.5 phr [29] showing pressure sensitivity was reported by Al-solamy et al. Fig. 21(a) shows the change in resistivity with applied pressure for all nanocomposites. It has been found that the applied pressure can increase the resistivity for entire composites, but not by the same order. The sample at the percolation concentration, GNP2 (0.5 phr), is the most sensitive to the pressure variation because, at this concentration, the aspect ratio of the GNP after mixing with rubber did not change, and these platelets tend to align parallell to the composite surface. The conductivity is increased by more than five orders upon 60% compression and more than two orders for 6 MPa pressure for NBR/GNPs. The relative resistivity against compressive strain for the same nanocomposite is shown in Fig. 21(b). The authors explained the conductivity behavior of composites by using a model based on the conductive

surface network. They considered the distance between the particles as the determining factor. If particles are far away from each other, no current flows through the composite and, if they are close, tunnelling currents arise. The total electrical resistance R of the composite can be calculated using Eq. (8) [112]:

 R=

8hsL 3A2 s2 N

 e s

(8)

where L is the number of particles forming a single conducting path, N the number of conducting paths, h the Plank’s constant, s the least distance between conductive particles, A2 the effective cross-section where tunnelling occurs, e the electron charge, and is calculated using Eq. (9) [118]:



=

8(2m) h

1/2



(9)

where m is the electron mass and w is the height of potential barrier between adjacent particles. When stress is applied to a composite sample, the resistance changes due to the particle separation and, if this change is from S0 to S, the relative resistance (R/R0 ) can be shown as Eq. (10): R = R0

S S0

e (S−S0 )

(10)

where R0 is the initial resistance, and s0 and s are the initial and final particle distances. For an elastomer composite, the separation under tensile strain is calculated by Eq. (11): S = S0 (1 + ε)

(11)

where ε is the tensile strain of the elastomer matrix, L the deformation of the composite sample, and L0 is the initial length of the sample. Substitution of Eq. (6) into Eq. (5) yields:



ln R = ln R0 + ln 1 +

L L0



+ S0

 L 

(12)

L0

At large deformations L/L0 is related to the destruction of the conducting network, i.e., with the decrease of the number of conducting paths N:



N = N0 e

− ˛(L/L0 )+ˇ(L/L0 )2 +( L/L0 )3 +ı(L/L0 )4

 (13)

where N0 is the initial number of conducting path and ˛, ˇ,  and ı are constants. The substitution of Eq. (13) into Eqs.

K.K. Sadasivuni et al. / Progress in Polymer Science 39 (2014) 749–780

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Fig. 21. (a) Resistivity of NBR/GNP composites perpendicular to the direction of orientation of GNPs as a function of applied pressure. GNP1, 0.1 phr; GNP2, 0.5 phr; GNP3, 1 phr; GNP4, 2 phr; and GNP5, 5 phr (b). Relative resistivity versus compressive strain for NBR loaded 0.5 phr of GNP. Dashed line represents data fitting using Eq. (12) and solid line using Eq. (14). [29] Copyright 2012. Reproduced with permission from John Wiley & Sons.

(8) and (11) yields the final Eq. (14):



ln R = ln R0 + ln 1 + +

 L 3 L0

 L L0

+˛

 L 4

+ı

L0

.

 L  L0

+ˇ

 L 2 L0 (14)

The experimental data are fitted with Eq. (14) in Fig. 21(b), depicting the relation between ln(R/R0 ) and (l/l0 ) at low and high pressures for GNP2 composites. It is observed that the model of tunnelling currents, Eq. (12), correctly describes the experimental data at small deformations l/l0 < 0.1 with s0 = 6.491 and R0 = 2.31 × 105 . For large deformations, l/l0 > 0.1, a good agreement between the theoretical, Eq. (14), and experimental data is achieved at ˛ = 6.71; ˇ = 83.51;  = 743.11; ı = 9832.43 and R0 = 2.12 × 105 V. From the above discussion it is clear that the elastomer/graphitic fillers nanocomposites are excellent piezoresistive materials. As usual, the dispersion effect and interfacial interaction between the fillers and matrices influence the pressure sensitivity. Studies also revealed the mechanism of electrical conductivity variation with applied pressure by means of tunnelling paths. 4.3. Thermal behavior Thermally conductive elastomer composites have offered several applications, including power electronics, electric motors and generators, heat exchangers, etc., and these materials are replacing heavy metal parts [209–213]. The ability of 2-D platelet-like GNPs and graphene (5000 W/(m K) [214,215]) fillers over 1-D, rods like CNTs (MWCNT (3000 W/(m K) [216]) or CNF [205,206,217] to improve thermal conductivity of elastomers is already established. It is the lattice vibration (phonons) that transfers the thermal energy through the matrix, and poor

coupling at the filler–polymer and filler–filler [218] interfaces cause significant thermal resistance [219]. This is really important as it can hinder the transfer of phonons [220], without which heat conduction in polymers is impossible. Reducing the large interfacial thermal resistance between the filler and the surrounding matrix is the main task while synthesizing the thermally conductive elastomer composites. Generally, the Debye equation (Eq. (15)) is used to calculate the thermal conductivity of polymers: =

Cp vl 3

(15)

where Cp is the specific heat capacity per unit volume, v the average phonon velocity, and l is the phonon mean free path. The thermal conductivity k is calculated according to Eq. (16) using the non steady-state methods such as the hot wire and hot plate methods, the temperature wave method and laser flash techniques [181]: k = ˛Cp 

(16)

where ˛, Cp and  are the thermal diffusivity, heat capacity and density, respectively. Two basic models are employed to find the thermal conductivity of the composites: the series and the parallel models. In the parallel model – also referred to as the mixture model – each phase in the composite is assumed to contribute independently to the overall conductivity, proportionally to its volume fraction. This is clear in Eq. (17): kc = kp p + km m

(17)

where kc , kp and km are respectively the thermal conductivities of the composite, filler and the elastomer matrix, with p and m the filler and matrix volume fractions. The parallel model gives more emphasis to the conductive phase contribution, and assumes a perfect and complete particle network formation. The same theory

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has been used to explain the parallel and continuous orientation of fibers in fiber reinforced composites as well. Compared to the parallel model, the series model assumes no contact between filler particles and, thus, the particle contribution is limited to the region of the filler embedded matrix alone. The conductivity of composites according to the series model is predicted by Eq. (18): kc =

1 (m /km ) + (p + kp )

(18)

Unlike electrical conductivity, no rapid increase was observed in the thermal conductivity percolation threshold, but yet the percolation model can be applied to these nanocomposites and suspensions because of the similarity of the thermal conduction system with the electrical conduction system. Foygel et al. [95] applied Monte Carlo simulations for classical percolation to estimate thermal conductivity percolation parameters based on Eq. (19): k(; (Af )) = ko [ − c (Af )]

t(Af )

(19)

where k is the thermal conductivity, k0 is a pre-exponential factor related to the conductivity of fillers and their contacts with each other,  the volume fraction, c the critical volume fraction for percolation, Af the aspect ratio and t is a factor accounting for the percolating network characteristics. It is possible to control Af by using different thermal expansion temperatures, and a higher Af of reinforcing platelets results in higher thermal conductivity [137]. The thermal conductivity of the polymer composite is influenced by the geometry of fillers [222,223], the degree of exfoliation, the orientation and interfacial interaction between the filler particles and the matrix. When the particles are very close, the interfacial resistance of the filler particles will reduce the thermal conductivity of the composite in accordance with the percolation theory [223]. The use of SWNTs with GNPs (at 3:1 ratio of GNPs:SWNTs) reported a synergistic improvement in the thermal conductivity, correlated with the morphology of the composite. SWNTs bridge across adjacent GNP platelets, forming an extended network of filler in direct contact [206]. Table 6 demonstrates the thermal conductivity values for graphene and graphite derivative/elastomer nanocomposites. The thermal properties of NGST and AGST filled SBR composites were analyzed [159] and found to exhibit an increase of approximately 20% compared to pristine SBR. As with electrical conduction, this is due to the increased interfacial interaction. Various studies have been done to achieve large thermal conductivity gains at low filler loadings, to minimize the interfacial phonon scattering by covalent interface coupling, and to modify the surface without reducing the intrinsic thermal conductivity [224–226]. The modification of filler particles enhances the dispersion and the physical and chemical interactions between the filler and the matrix. The use of acid–graphite and coupling agents resulted in 19% higher thermal conductivity than the pure matrix in SBR nanocomposites [34]. Functionalization of EG with amine silyl groups also improved the thermal conductivity by up to 20% over unmodified EG at the same loading [227]. The thermal conductivity of

nitric acid treated GNP (1 vol%) has better modification efficiency [228] due to the presence of polar groups on GNPs surface. The fabrication method of the composites is another factor influencing the thermal conductivity of composites. High thermal conductivity has been observed for NBR/EG composites (Table 6) synthesized by following the LCM technique rather than the direct blending method, and the value has been found to be increasing upon EG addition [33]. Again, this enhancement in the value has been ascribed to the fine dispersion of EG sheets in the matrix and the formation of conductive network, as discussed before. For SBR/GNP composites produced via in situ polymerization, the thermal conductivity improved 30 times as compared with neat SBR at 33 vol% [137,221]. The thermal conductivity of NR/GE (graphene) composite synthesized by ultrasonic latex mixing is reported to be higher than that for NR [44], even at a low concentration of GE. Zhamu and Bor [229] observed a large improvement in thermal conductivity of nearly 21.3 (W/mK) for NR with nano graphene platelets (thickness < 0.8 nm), which varied with the thickness (0.8–300 nm) and weight percentage of graphene platelets. Haiqing et al. examined the synergistic effect of grahene and CNT on silicone rubber, and obtained enhanced thermal diffusivity at 1 wt% graphene and 3 wt% CNTs [145] filler loading. Mu et al. investigated the mechanism of thermal conductivity improvement of SR/EG composites by changing the processing conditions. They introduced EG with different morphologies and internal microstructures into the matrix and focused on the mechanism of conducting path formation (Fig. 22). For nanocomposites prepared by solution intercalation (Fig. 22(a)), the EG particles with large surface-to-volume ratio can contact each other to form a conducting network even at lower EG contents. This is due to the intercalation of rubber chains into EG, and the formation of EG/SR nanoscale and microscale networks, which protect the EG particles from destruction during compression (Table 6). In the composites prepared by melt mixing (Fig. 22b), the shape of EG particles is drastically changed, and this causes the surface-to-volume ratio to reduce. Consequently conducting paths are formed only at higher EG concentrations [17]. Among various graphitic fillers, GNPs and graphene have exceptional thermal conductivity, thermal stability and dimensional stability as compared to EG composites. Also higher conductivity is observed in the direction of graphite alignment than in the perpendicular direction [205,221]. The influence of GNPs while enhancing the thermal stability of GNP composites is explained by Li and Zhong [111] through several mechanisms. They narrated the possibility of heat extraction by GNPs from the matrix. The GNPs prevent the accumulation of heat within the polymer matrix, thereby eliminating the possibility of oxidation at the early stages of degradation [230]. These fillers can also serve as mass transfer barriers against the volatile pyrolized products [96,197], and can enhance the thermal stability. Finally, processing techniques such as extrusion or solvent casting lead to orientation effects of GNPs and graphene platelets in the composites, and can influence the conductivity [64]. Rigid fillers can restrain

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Table 6 Thermal conductivity of graphene, graphite derivative/elastomer nanocomposites. Elastomer

Filler

Compatibilization

Content

Processing

Thermal Conductivity (W/mK) (Composite/pure matrix)

NR latex [44]

CRG in situ reduction

–

2.00 wt%

Solution

0.19/0.17

NR [229]

Nano graphene platelets (thickness < 0.8 nm) Nano graphene platelets (thickness < 6 nm) Graphite nanoparticles (thickness = 350 nm)

– – –

2.00 wt% 2.00 wt% 2.00 wt%

– – –

21.30/0.13 2.11/0.13 0.85/0.13

SBR [34]

Graphite Acid graphite

– – bis-(3-Triethoxy silylpropyl) tetra sulfane (0.8 phr)

4.76 wt% 4.76 wt% 4.76 wt%

Melt Melt Melt

0.34/0.30 0.34/0.30 0.36/0.30

SBR [159]

NG AG NGST NGST

– – – –

4.76 wt% 4.76 wt% 4.76 wt% 4.76 wt%

Melt Melt Melt Melt

0.33/0.30 0.34/0.30 0.36/0.30 0.36/0.30

NBR latex [33]

EG

–

9.09 wt%

Solution Melt

0.30/0.19 0.23/0.19

SR [17]

EG

–

8.25 wt%

Solution Melt

0.24/0.17 0.32/0.17

the thermal expansion of the elastomer matrix due to their confinement effect. 4.4. Dielectric properties The dielectric properties of filled polymers are related to the structure–property relationships at the morphological level [163]. The molecular motions or dynamics of nanocomposites in response to various applied fields have an intense connection with the macroscopic properties. Upon exposure to an electric field, nanocomposites are subjected to ionic, interfacial, and dipole polarization. This polarization mechanism is the main reason why dielectric spectroscopy is used for the study of nanocomposite dynamics. Elastomer composites with high dielectric constant have various functional applications such as energy storage materials, capacitors, transistors and in flexible electronics [49,231,232]. Dielectric spectroscopy analysis is associated with a number of measurements, and an attempt has been made here to explain the various parameters used in this technique. The complex permittivity ε* of a given sample is related to the complex impedance Z* , which is determined by using Eq. (20). Z ∗ (ω) =

U ∗ (ω) I ∗ (ω)

(20)

where U* and I* are the voltage and current circulating through the sample at a certain angular frequency ω. By knowing the impedance, ε* may be calculated by Eq. (21): ε∗ (ω) = ε − iε =

Fig. 22. Structural models of silicone/EG composites prepared by (a) solution intercalation and (b) melt mixing, showing the formation of conducting paths. [17] Copyright 2007. Reproduced with permission from Elsevier Ltd.

1 iωZ ∗ (ω)C0

(21)

where ε and ε are the real and imaginary parts of the complex permittivity, and C0 corresponds to the capacity of the empty sample holder. The complex permittivity of the nanocomposites can be measured over a wide frequency window like 10−1 < F/Hz < 107 (F = ω/2 is the

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K.K. Sadasivuni et al. / Progress in Polymer Science 39 (2014) 749–780 Table 7 FoM calculated for several types of high dielectric constant filler/silicone elastomer composites [49].

Fig. 23. Variation of ε of the SBR vulcanizates with the graphite loading for different particle sizes (53–150 ␮m) at 100 Hz. [37] Copyright 2011. Reproduced with permission from John Wiley & Sons.

frequency of the applied electric field) during an extensive temperature range. The imaginary part of the obtained dielectric permittivity was analyzed by the phenomenological Havriliak–Negami (HN) function [61,233] as given by Eq. (22): ε∗ (ω) = ε∞ +

ε b c

[1 + (iωHN ) ]

(22)

where ε = εS − ε∞ ; ε∞ and εS are the unrelaxed and relaxed values of the dielectric constant,  HN is the characteristic relaxation time and b and c are shape parameters (0 < b, c ≤ 1) which respectively describe the symmetric and the asymmetric broadening of the equivalent relaxation time distribution function. The relative enhancement observed in the dielectric permittivity for polymer nanocomposites in accordance with the weight fraction w2 of the filler are usually expressed by Figures of Merit (FoM) values calculated from Eq. (23) [194]: FoM =

(εc

− ε1 /ε1 ) w2

.

(23)

where εc and ε1 are the composite and polymer matrix dielectric permittivity, respectively. Ismail and Khalaf [37] measured ε values of SBR composites filled with graphite particles of different sizes at different concentrations. Measurements were done at room temperature and at 100 Hz, and the obtained result is depicted in Fig. 23. The values of ε increased with increasing graphite content. This increase in ε is a typical response of all heterogeneous systems where the conductivity and relative ε of the constituent phases differ, and is a result of an interfacial polarization phenomenon that occurs at the interfaces of dissimilar materials at low frequency. Moreover, it is interesting to observe that for samples containing up to 70 phr graphite, ε was inversely proportional to the particle size as evidenced in Fig. 23. Recently Romasanta et al. compared the dielectric permittivity of poly(dimethyl) siloxane (PDMS)/FGS and poly(dimethyl) siloxane (PDMS)/CNT nanocomposites at room temperature (Fig. 24). The dielectric permittivity spectra of PDMS/FGS with 0.5–1 wt% FGS loading shows the

Filler

Filler Loading (Wt%)

FoM

TiO2 TiO2 PMN-PT BaTiO3 PHT CuPc CNT FGS FGS

70.00 30.00 70.00 70.00 1.00 20.00 0.50 0.50 2.00

3.33 (at 1 Hz) 1.11 (at 10 Hz) 2.38 (at 1 Hz) 8.09 (at 1 Hz) 21.42 (at 10 Hz) 5.00 (at 1 Hz) 14.80 (at 10 Hz) 157.77 (at 10 Hz) 366.29 (at 10 Hz)

values of composites to be twice as much compared to the PDMS matrix, thereby suggesting its smooth and frequency independent behavior. At 2 wt% of FGS, the permittivity constant is increased (ε = 23) to about ten times higher than the pure matrix at low frequencies, whereas only a six-fold increase is observed for CNT composites at the same concentration [49]. The reason for this behavior is explained in terms of compatibilization. The functional groups present on the graphene sheet surface reduced the polarization process and, thus, improved the compatibility of nanofiller/polymer at the interface [234]. Also, not much variation is found in the loss tangent values with frequency, again attributed to the homogeneous dispersion of FGS in the matrix and the presence of functional groups on the filler surface. The functional groups can interrupt the ␲conjugation occurring in the graphene layers and, thus, can favour enhanced filler/polymer compatibility [194]. The authors also compared the FoM values of PDMS composites with different fillers (Table 7). As evidenced from Eq. (23), the composites containing FGS shows the highest permittivity enhancement (1 or even 2 orders of magnitude) with the lowest amount of filler when compared to all other composites. 4.5. Gas barrier properties One of the most significant applications of rubber nanocomposites is in improving the barrier properties of tyre inner tubes. Since the soft, rubbery materials have a large free volume and, thus, very low gas barrier properties [35], nanocomposites are widely used to obtain good barrier materials. One-dimensional fillers such as CNTs limit their effectiveness in improving the barrier properties of a composite relative to the neat polymer [3]. Fillers having a sheet morphology are the most acceptable in imparting the excellent gas retention properties to rubber. The two-dimensional fillers form a network of platelets inside the rubber matrix, and provide a tortuous path which can inhibit the molecular diffusion through the matrix and, thus, yields significantly reduced permeability (Fig. 25). Barrier properties are influenced by the orientation effects of the platelets as well. It is established that both the perpendicular alignment and higher aspect ratios of filler platelets can provide highly tortuous paths (Fig. 25), thus correlating with an increased barrier resistance [235]. The influence of EG, GNP and graphene on the barrier properties of rubber composites prepared by different processing methods is given in Table 8. EG platelets impart

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Fig. 24. Dielectric permittivity as a function of frequencyat room temperature, for (left) CNT/PDMS and (right) FGS/PDMS composites at various filler concentrations. [49] Copyright 2011. Reproduced with permission from Springer.

Fig. 25. Illustration of formation of a ‘tortuous path’ of platelets inhibiting diffusion of gases through an elastomer composite (a) without alignment and (b) with alignment.

similar gas barrier properties with the layered silicates to NBR and XNBR matrices [33,35]. Here also, the dispersion of EG in the matrix (NBR) and the interfacial interaction of EG/NBR synthesized via a latex compounding method plays the key role. Results indicate a reduction in nitrogen

permeability by 62% for NBR/10 phr EG nanocomposite as opposed to that of the unfilled NBR vulcanizate (Table 8). On the other hand, the permeability of the composite manufactured following the direct blending technique was decreased by 43%. The surfactants and mode of dispersion

Table 8 Gas permeability of graphene, graphite derivative/elastomer nanocomposites. Elastomer

Filler

Content

Processing

Permeant

Relative reduction

NR [45]

TRG

1.70 (vol%)

Solution/melt

Air

60

TPU [3]

TRG

1.60 (vol%) 1.60 (vol%) 1.50 (vol%) 1.60 (vol%) 1.50 (vol%)

Melt Solvent In situ polymerization Solvent In situ polymerization

Nitrogen Nitrogen Nitrogen Nitrogen Nitrogen

52 82 71 94–99 62

IGO GO SR [48]

FGS

0.43 (vol%) 1.31 (vol%)

– –

Nitrogen Nitrogen

7.3 49

NBR [33]

EG

10 phr 10 phr 5 phr

Melt Solution Solution

Nitrogen Nitrogen Nitrogen

43 62 38

XNBR [35]

EG

5 phr

Surfactant Aq-solution

Nitrogen

52

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also influence the permeability of EG composites [35]. The capability of EG sheets in making the rubber electrically and thermally conductive has been reported, and this is the additional advantage of graphitic fillers over layered silicates [33]. If the orientation of the nanosheets is in a random mode, Eq. (24) can be used to model the dependence of the relative gas permeability (P/P0 , where P is the gas permeability and P0 is the initial gas permeability) on the filler volume fraction () and the aspect ratio (r/d, where r is the radius of the nanosheets and d is the thickness) [236]. The experimental data are well located around the line predicted by Eq. (24) with the value of r/d at 90, and this indicates that the average aspect ratio of the graphite nanosheets was about 180. This was also beneficial for the gas-barrier properties.

FGS and TRG, and they correlated the barrier properties with modulus improvements. They suggested better filler alignment and higher aspect ratio for the functionalized graphene composites. From the above discussions it is clearly understood that graphene and GNPs are capable of decreasing the gas permeability at low level of loading as compared to EG, even though they have the same sheet-like morphology. The reason might be the larger surface area of graphene and GNPs compared to EG. This obviously causes the gas molecule to take more time to diffuse through the membrane (the width and length of the tortuous path are more in the case of graphene and GNP nanocomposites), and results in the best barrier properties.

1− P = Po 1 + (r/d)(/3)

5. Applications (24)

Reports emphasize the combined barrier property with the mechanical integrity of graphene and GNP fillers on the polymeric hosts in large scales, with significant advantage over fillers such as carbon nanotubes or clay at similar loading and all the more so if graphene sheets having zero defects are impermeable to all kinds of gas molecules [3,27]. Compared to clay platelets, crumpled graphene sheets show ∼25–130 times improvement even at low concentrations [235,237] based on the predictions by the Nielsen, Cussler and Bharadwaj theories [182–184]. However, to fulfill these expectations, the fillers have to be well dispersed in the elastomer matrix. Fig. 26 demonstrates the reduction in air permeability for PDMS/FGS nanocomposites as a function of filler loading for two types of functionalized graphene sheets having different surface areas: 525 and 320 m2 /g [50]. It has been found that the gas permeability decreases significantly for FGS sheets with high surface area 525 m2 /g (hence, high aspect ratio) due to the long, tortuous path for gas diffusion when compared to the case with lower aspect ratio (low surface area 320 m2 /g). The authors calculated the aspect ratio of fillers by following the Nielsen model. Similarly Kim et al. observed relative helium (He) and nitrogen (N2 ) permeability at 35 ◦ C for TPU filled with different kinds of graphitic fillers following different processing conditions. They proposed a model in which the relative permeability versus volume fraction of graphene were fitted for monodispersed parallel flakes in random array by considering Af as an adjustable parameter [3]. The unidirectionally aligned (Af = 400–500) flat impermeable flakes of iGO at 1.6 vol% (3 wt%) level can decrease the gas permeability up to 90%. Considering the possible layer misalignment which reduces the barrier enhancement, [182] the actual particle aspect ratio Af can be even greater than 400–500. Moreover the same amount of Ph-iGO leads to a remarkable decrease in permeability of nitrogen gas from 80 to 1. Since the barrier performance of 2-D platelets mostly depends on the particle aspect ratio Af , the iGO having larger diameter minimize the gas permeation to a great extent. Moreover, disk-like particles tend to adopt a parallel orientation in nematic transition as the shape anisotropy and particle concentration increase [179,238]. Prud’homme et al. [45] studied relative permeability (P/P0 ) of NR and SR with

The versatility of elastomer/EG, GNPs and graphene nanocomposites makes them potentially applicable in various fields. The low permeability property of elastomer/GNPs and graphene were useful for industries related to tyres, inner tubes, microwave absorbers [72] as well as in aerospace applications [45]. These superior properties of graphene [239] and graphitic based fillers makes superior to the conventional fillers, such as carbon black and silica widely used in tyre industry. The high electrical, dielectric and thermal conductivity of graphene [240,241] and GNPs/elastomer nanocomposites satisfy conditions for heat or electricity activated shape memory, making them highly applicable in artificial muscles, charge-storage capacitors, transistors, electromagnetic interference shielding, high-K gate dielectrics [49,231,232] as well as in sensing applications such as accelerometers, pressure sensors, and sensors for monitoring structural integrity of mechanical elements, etc. Especially at the percolation limit, the composites show dramatic change in the relative resistance upon solvent attack [204], temperature change [203], pressure change [43,208], and external strain [235]. The on–off phenomenon in electrical conductivity by external stimuli (pressure, strain, vapors, etc.) can be used in sensor applications [124]. Other significant applications of elastomer/GNPs and graphene are hoses, belts, matting, flooring and dampeners (antivibration mounts) for the automotive industry because of the excellent reinforcement. In addition to providing reinforcement and conductivity, graphitic fillers help the elastomer to achieve thermal stability, orientation flexibility, photo sensitive properties etc. Applications based on this nature of graphene fillers vary from super capacitors to solar cells. Exploiting the optical properties of graphene, its PU composite is used as an activator for infrared light [213]. Some of the novel areas where the graphene nanocomposites are applicable include pigments, fuel cells, food packaging, gaskets, conductive inks, etc. [242]. The highly significant functions of elastomer graphene composites are not limited to technology and industry, but extends to biological applications. It is reported that the silicone rubber-biocompatible graphene oxide nanocomposite is helpful in promoting osteoinductive signalling of surface adherent osteo cells and thus for joint reconstruction [190]. Of course the

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Fig. 26. Influence of surface area (525 and 320 m2 /g) of FGS on the relative permeability of PDMS-FGS nanocomposites as a function of filler concentration. The solid lines represent the predictions of the Nielsen model for isotropically oriented sheets, where the key parameter of the impermeable filler is itslength-to-height ratio (L/H). [50] Copyright 2012. Reproduced with permission from John Wiley & Sons.

tremendous possibilities of graphitic based elastomer composite’s applications and use cannot be covered completely as it can be the topic of yet another review, a short and brief outline is provided here, aiming to trigger the interest of the reader. 6. Conclusions and perspectives The changes of elastomer composite properties while changing the fillers from graphite derivatives – such as EG or GNP – to graphene are illustrated in this review. Graphite derivatives such as GNPs and graphene are multifunctional reinforcement materials that can improve the electrical, piezoresistive, dielectric, thermal, mechanical, and gas barrier properties of elastomers even at extremely low loadings. Because of the exceptionally high surface area, as compared to other graphite derivatives, an enormous improvement in properties is observed for graphene composites. Correspondingly, they exhibit unique advantages, as compared with all other organic and inorganic fillers, and are thus useful in many applications. Finally it may be concluded that graphene can be applied to improve the gas permeability (like layered silicates), electrical and thermal conductivity (like carbon nanotubes) of elastomer composites. However, in some cases, GNPs shows competing effect with graphene. Major conclusions drawn from the investigations on composite behavior can be summarized into a few points. 1. The interfacial interaction between the matrix and graphitic fillers – especially graphene – plays a major role in significantly improving properties. Hydrogenbonding interaction with modified graphene surfaces containing functional groups and elastomers is the reason for the surprisingly high modulus and other mechanical properties observed. 2. Processing techniques such as sonication or thermal treatments, commonly used to exfoliate graphene, can reduce the aspect ratio of platelets, which in turn can affect reinforcement as well as electrical and thermal properties.

3. Manufacturing techniques regulate the level of dispersion of graphene-based fillers and have a significant impact on reinforcement and, thus, in material properties. 4. The functional groups present on graphitic fillers interrupt the ␲-conjugation in filler layers even at low loading levels, and reduce the surface charge. This favors the filler/polymer compatibility leading to high dielectric properties for the composites. 5. The electrical percolation concentration correctly indicates an effective graphene dispersion since it is inversely proportional to the aspect ratio platelets. 6. The orientation of fillers plays major role in composite properties. In parallel, oriented graphene sheets at the surface of elastomer films can reduce gas permeation much more effectively than randomly oriented ones. 7. Advanced intelligent tyres made of graphene elastomer composites – which are capable of measuring the deformation using sensing technology, and have good permeability – are anticipated. Acknowledgements The authors would like to acknowledge the Department of Science and Technology, Delhi, India and EU FEDER, French Ministry for Research and the Brittany Region for financial support. We are also thankful to the financial support from the Department of Atomic Energy Consortium, India and Ministry of Higher Education, Science and Technology of the Republic of Slovenia (through contract No. 3211-10-000057, Center of Excellence in Polymer Materials and Technologies). References [1] Shornikova ON, Kogan EV, Sorokina NE, Avdeev VV. The specific surface area and porous structure of graphite materials. Russ J Phys Chem 2009;83:1022–52. [2] Viculis LM, Mack JJ, Mayer OM, Hahn HT, Kaner RB. Intercalation and exfoliation routes to graphite nanoplatelets. J Mater Chem 2005;15:974–8. [3] Kim H, Miura Y, Macosko CW. Graphene/polyurethane nanocomposites for improved gas barrier and electrical conductivity. Chem Mater 2010;22:3441–50.

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