ARC Hub develops test protocol to confirm quality of PureGRAPH® Graphene (ASX:FGR)



  • Researchers have developed a robust test method to detect thepresence of “fake” graphene
  • The test is based on thermogravimetric analysis (TGA)
  • Confirms that PureGRAPH® products are high-quality, pristine, lowdefect few layer graphene platelets

First Graphene Limited (ASX:FGR; “First Graphene” or “the Company”) is pleased to announce thepublication of a scientific paper written by researchers at Australian Research Council’s Graphene Research Hub (“ARC Hub”), the University of Adelaide Node, which describes a robust analytical process that can be used to detect “counterfeit” graphene materials. First Graphene’s PureGRAPH® was used as the pristine graphene that was used as a control during the test development.

The paper, titled “Accounting Carbonaceous Counterfeits in Graphene Materials Using theThermogravimetric (TGA) Approach” was written by researchers led by Professor Dusan Losic, leaderof the Nano Research Group at The University of Adelaide and Director of the ARC Hub. It was published on 28th July 2021 in Analytical Chemistry, a peer-reviewed research journal devoted to the dissemination of new and original knowledge in all branches of analytical chemistry.

The researchers have successfully demonstrated that TGA is a viable method that can be used to detect impurities in “bulk” graphene samples. This is currently not possible with other commonly usedcharacterisation techniques, such as Raman spectroscopy or powder X Ray Diffraction. TGA is a robust,simple and commonly used test method, that measures the loss in weight of a sample as it is heated under controlled conditions. It provides a unique “signature” that can be used to confirm the presence of graphene or other related carbon products (graphene oxide, reduced graphene oxide, activated carbon, carbon black) and to show whether impurities are present.

The work presented in the paper is highly relevant to the graphene industry because it can be used to give end users the confidence that they are being supplied with high-quality graphene platelets.

First Graphene’s Research and Development Team, based at the Graphene Engineering Innovation Centre, also have extensive experience of using this method. Professor Losic’s work thereforecompliments First Graphene’s extensive work in understanding, characterising and controlling theproperties of its range of graphene products. This is key to providing confidence to end users that PureGRAPH® is consistently high quality graphene platelets. Previous work by Professor Losic’s group has shown these can be “tailored” for end users by functionalising the platelets with specific chemicals. This demonstrates the versatility and unique nature of PureGRAPH® products.

Michael Bell, Chief Executive Officer of First Graphene said: “This is another excellent piece of work fromthe ARC Graphene Research Hub. It demonstrates our commitment to

providing a robust supply of high-quality graphene platelets, which has been independently validated by Professor Losic’s team of scientific experts. It is a great example of how the scientific community canhelp to support the industry at this key stage of commercialisation of graphene products.”

Professor Dusan Losic, leader of the Nano Research Group at the University of Adelaide, said: “Ourteam continues to develop simple and robust methods to support the characterisation and quality control of bulk graphene powders. We are aware of the need to prevent poor quality “fake” graphenefrom entering the supply chain and we expect that the TGA method presented in this paper will play animportant role in this process.”


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First Graphene Ltd. is the leading supplier of high-performing, graphene products. The company has a robust manufacturing platform based upon captive supply of high-purity raw materials and anestablished 100 tonne/year graphene production capacity. Commercial applications are now beingprogressed in composites, elastomers, fire retardancy, construction and energy storage.

First Graphene Ltd. is publicly listed in Australia (ASX:FGR) and has a primary manufacturing base inHenderson, near Perth, WA. The company is incorporated in the UK as First Graphene (UK) Ltd. and is a Tier 1 partner at the Graphene Engineering and Innovation Centre (GEIC), Manchester, UK.

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Accounting Carbonaceous Counterfeits in Graphene Materials Usingthe Thermogravimetric Analysis (TGA) Approach

Dusan Losic,Farzaneh Farivar, Pei Lay Yap, and Afshin Karami



Abstract Image

Counterfeits in the supply chain of high-value advanced materials such as graphene and their derivatives have become a concerning problem with a potential negative impact on this growing and emerging industry. Recent studies have revealed alarming facts that a large percentage of manufactured graphene materials on market are not graphene, raising considerable concerns for the end users. The common and recommended methods for the characterization of graphene materials, such as transmission electron microscopy (TEM), atomic force microscopy (AFM), and Raman spectroscopy based on spot analysis and probing properties of individual graphene particles, are limited to provide the determination of the properties of “bulk” graphene powders at a large scale and the identification of non-graphene components or purposely included additives. These limitations are creating counterfeit opportunities by adding low-cost black carbonaceous materials into manufactured graphene powders. To address this problem, it is critical to have reliable characterization methods, which can probe the specific properties of graphene powders at bulk scale, confirm their typical graphene signature, and detect the presence of unwanted additional compounds, where the thermogravimetric analysis (TGA) method is one of the most promising methods to perform this challenging task. This paper presents the evaluation of the TGA method and its ability to detect low-cost carbon additives such as graphite, carbon black, biochar, and activated carbon as potential counterfeiting materials to graphene materials and their derivatives such as graphene oxide (GO) and reduced GO. The superior performance of the TGA method is demonstrated here, showing its excellent capability to successfully detect these additives when mixed with graphene materials, which is not possible by two other comparative methods (Raman spectroscopy and powder X-ray diffraction (XRD)), which are used as the common characterization methods for graphene materials.

ABSTRACT: Counterfeits in the supply chain of high-value advanced materials such as graphene and their derivatives have become a concerning problem with a potential negative impact on this growing and emerging industry. Recent studies have revealedalarming facts that a large percentage of manufactured graphene materials on marketare not graphene, raising considerable concerns for the end users. The common andrecommended methods for the characterization of graphene materials, such astransmission electron microscopy (TEM), atomic force microscopy (AFM), and Ramanspectroscopy based on spot analysis and probing properties of individual graphene particles, are limited to provide the determination of the properties of “bulk”graphene

powders at a large scale and the identication of non-graphene components or purposely included additives. These limitations are

creating counterfeit opportunities by adding low-cost black carbonaceous materials into manufactured graphene powders. To address this problem, it is critical to have reliable characterization methods, which can probe the specic properties of graphene powders at bulk scale, conrm their typicalgraphene signature, and detect the presence of unwanted additional compounds, where the thermogravimetric analysis (TGA) method is one of the most promising methods to perform this challenging task. This paper presents the evaluation of the TGA method and its ability to detect low-cost carbonadditives such as graphite, carbon black, biochar, and activated carbon as potential counterfeiting materials to graphene materials and their derivatives such as graphene oxide (GO) and reduced GO. The superior performance of the TGA method is demonstrated here, showing its excellent capability tosuccessfully detect these additives when mixed with graphene materials, which is not possible by two other comparative methods (Raman spectroscopyand powder X-ray diraction (XRD)), which are used as the common characterization methods for graphene materials.


Graphene, a two-dimensional (2D) carbon material with a single atomic structure of sp2 carbon, since its discovery in 2004, has been described as the material of 21st century and a new disruptive technology, as a result of the combination of its unique properties.1 Its wide range of applications have been demonstrated in recent years ranging from lightweight composites, protective coatings, electronic devices, sensors, energy production, storage, and so on.24 Translation of these applications from academia to industry is rapidly progressing in recent years underpinning the fast growth of new emerging graphene industry across many sectors.2,5,6 Industrial manu- facturing and supply of high-quality graphene materials for industrial applications have been recognized as one of the key requirements for the growth of emerging graphene industry. Many graphene manufacturing processes have beendeveloped, and a thousand companies worldwide have claimed industrial production of graphene materials and their derivatives.69 Recent comprehensive studies on the quality evaluation of these industrially produced graphene materials revealed concerning ndings that a large percentage of grapheneavailable on market

are not graphene but a mixture of graphene, graphitic, and other carbonaceous materials.1012 These reports triggered consid- erable concerns for downstream graphene end users with a potential serious impact on the future of the entire graphene industry. Graphene is a black powder with physicalappearance not much dierent from many other low-cost commercially available carbon materials such as graphite, carbon black, biochar coal, and activated carbon. Some of these carbon materials are used or generated during graphene production, and their presence deemed as impurities maydecrease the performance of graphene materials for many applications. Owing to their similarity, their presence in graphene powders cannot be detectedvisually, which creates opportunities to

Anal. Chem. XXXX, XXX, XXX−XXX

counterfeit graphene materials and make nancial gains. The problem became more signicant when the key characterization methods recommended by International standards based on spot analysis and probing single graphene particles may fail to disriminate these additives and detect “fake” graphene,making the graphene supply chain vulnerable.1012

The graphene materials, their forms and properties are dened by the International Organization for Standardization (ISO).1315 Based on thisstandard, graphene materials can appear in dierent forms, such as powders, lms, and dispersions, and have single, double, or few layers (<10), withdierent sizes, functionalities, and other properties1618 To prove these properties and conrm that the characterized material is graphene, new ISO standards have been recently published to specify the analytical techniques for characterizing their structural properties and chemical composition such asnumber of layer/thickness, lateral ake size, level of disorder sp2 structure, specic surface area, etc.15 Most of these methods that are accepted as themost trusted, such as Raman spectroscopy, atomic force microscopy (AFM), transmission electron microscopy (TEM), and X-ray photoelectronspectroscopy (XPS), are spot characterization methods that can probe individual or few graphene particles dispersed on the substrate. Unfortunately, thesemethods have the limitations of probing a very large number of graphene particles (+500) from one sample and not able to provide representativeproperties of bulk materials in powder form at large scales (kg or tonnes). As a result, these methods, with reduced number of spot testing, could easilymiss to detect the presence of non-graphene impurities or fake additives using low-cost carbonaceous materials. Moreover, these techniques need skilled technical operators and are also very expensive, time-consuming, and not aordable for the majority of industries and the end users of graphene materials, which are usually small and medium-sized enterprise (SME) companies. Hence, there is a signicant demand to implement a more representative, simple, and low- cost analytical method that can provide information on bulk properties for industrially produced graphene materials. Several analytical methods such as thermogravimetric analysis (TGA), powder X-ray diraction (XRD), gas physisorption (Brunauer− Emmett−Teller, BET), particle sizedistribution (PSD) analysis, ultraviolet−visible (UV−vis) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, and pH titration techniques canmeet these requirements and provide complementary informa- tion about the bulk properties of graphene powder such as the crystal and graphiticstructure, surface area, chemical composi- tion, impurities, and functional groups.1318 Among them, TGA has been routinely used in the industry for thecharacterization of the thermal properties, chemical composition, and impurities of minerals, polymers, and carbon materials, but surprisingly, it has notbeen explored beyond its conventional use for advanced

characterizations and the quality control of graphene materi- als.1921

In our recent study, we demonstrated how the TGA method- based analytical approach can be used as a valuable quality control and analytical tool for the qualitative and quantitative analysis of graphene powders, not considered before.22,23 TGA is shown as a simple and reliable method that can detect “fake graphene” and the presence of nongraphene carbon impurities as a result of the manufacturing process.22,23 The main conclusion from this study revealed that the key components of nongraphene impurities from graphitic nonexfoliated particles and Graphene oxide (GO) have distinctive thermal

decomposition properties that can be elegantly distinguished from graphene by TGA measurements using the rst-derivative thermogravimetric (DTG)analysis based on a distinctive number of decomposition peaks, their shapes, and temperature of maximum mass loss rate (Tmax). Typical TGA signature of the representative few-layer graphene (FLG) material was con- rmed and related to other properties (number of layers, defects, sp2 carbon, etc.) provided by complementary methods (TEM, Raman spectroscopy, XPS, and AFM) showing the capability of the TGA method to successfully detect other carbon impurities from manufacturing process.

The aim of this study is to evaluate the use of the TGA method to detect the presence of selected carbonaceous materials such as graphite, carbon black, biochar, and activated carbon as potential counterfeiting additives for commercial graphene powder materials including FLG pristine graphene, GO, andreduced graphene oxide (rGO). These carbon materials were selected because of their large commercial availability on market, physical similarity, and low cost compared with more expensive graphene materials. The baseline comparative characterization of these carbon and graphene materials was performed by a series of methods including TEM, SEM, Raman spectroscopy, XRD, FTIR, and TGA to determine their structural and chemicalcharacteristics such as morphology, number of layers, defects, chemical compositions, and crystallinity. Articial counterfeiting model mixtures of selected four carbon additives with three commercial graphene powder materials (Gr-FLG, GO, and rGO) with additive concentrations of 10% (w/w) wereprepared. They are comparatively characterized by Raman spectroscopy, XRD, and TGA methods to evaluate their ability to detect these counterfeiting carbon additives in graphene powder mixtures. The TGA/DTG graphs of these selected graphene materials and their counterfeiting mixtures weregenerated to determine the DTG peak shape, surface area, and Tmax as the key identication parameters. Results from this study provide important information about the ability of the TGA method to be used as a fast and reliable method for detecting fake graphene generated by carbonaceouscounterfeiting additives.


  • Materials and Sample Preparation. Pristine graphene powders with few graphene layers (Gr) were obtained from First Graphene Ltd manufactured by industrial electro- chemical process. This sample represents pristine graphene (FLG) with an average particle size of ca. 5 μm with a size distribution of 2−10 μm. Commercial GO and rGO materials were supplied by The Sixth Element (China). Graphite in the form of graphite akesobtained from a local graphite company (Uley, Eyre Peninsula, SA, Australia) was sieved to ≤25 μm. Carbon black material was obtained fromChemSupply (Australia), activated carbon (Haycarb, Sri Lanka), and biochar (Permachar, Australia) was crushed and sieved below 25 μm prior to analysis. Digital photographs of these materials are presented in Figure S1 (Supporting Information). The models of articial mixtures were prepared by adding these carbon additives with 10% (w/w) concentration into commercial FLG, GO, and rGO powders, followed by physical mixing to obtain a series ofuniform mixtures.
    • Thermogravimetric Analysis (TGA). TGA measure- ments were conducted on a Mettler Toledo TGA/DSC 2 and TA InsyrumentsQ500 Series under the same conditions with a heating rate of 10 °C/min under air atmosphere with a ow rate


of 60 mL/min and 20 ml/min nitrogen used as a balance protective gas. The TGA graphs were collected from all prepared samples, in powder forms, showing typical mass loss with regard to temperature, and the related DTG graphs were generated showing mass loss rate versus temperature. The DTG graphs and Tmax values were used to demonstrate the ability of the TGA method to detect counterfeiting carbon additives in graphene materials.

  • Other Characterizations. The morphologies of

commercial FLG graphene, GO, and rGO used in this study were conrmed by eld emission scanning electron microscopy (FE-SEM, Quanta 450 FEG, FEI) at an operating voltage of 10 kV and transmission electron microscopy (TEM, Philips CM200, Japan) at 200 kV. FTIR spectroscopy (Nicolet 6700, Thermo Fisher) was used to conrm the functional groups in the samples in the range of 500−4000 cm−1. The Raman spectroscopycharacterization of graphene, GO and other carbon materials was performed using LabRAM HR Evolution (Horiba Jvon Yvon Technology, Japan) with a 532 nm laser (mpc3000) as the excitation source in the range of 500−3500 cm−1. The crystal structure of samples was analysed by powder X-raydiraction on aD4 ENDEAVOR (Bruker, Co Ka. lambda=0.178897 mm). The instrument was operated at 35kV and 30 mA with diraction data collected by scanning from 5-80 0 with a step size of 0.2 0 . Particle size distribution (PSD) of the samples was determined using a a Mastersizer 2000(Malvern Instruments, U.K.).


  • Baseline Characterization of Graphene Materials and Carbonaceous Counterfeits. Visual examination of three selected commercial graphene and four carbon powder materials used in this study showed high similarity, i.e., similar physical appearance including dark brown (GO) and black (all carbon materials investigated in this study except for GO), powder texture, lightweight, and no smell (Figure S1). Interestingly, visualexamination of counterfeiting model mixtures made of 10% graphite, carbon black, activated carbon, and biochar in three graphene materials such as graphene, rGO, and GO showed no visual dierence compared with pure graphene materials before the additions. Based on the preliminary observation,visual examination can be hardly used to detect these counterfeits; hence, instrumental character- ization is required to identify their presence in graphenematerials.

The SEM technique was used as the rst method for the baseline characterization to conrm the morphology and particle size of graphene and carbon materials used in this study, with their typical structures presented in Figure 1. From these electron micrographs, graphene materials exhibit similar micron-sized 2D sheet morphology, which is remarkably dierent from thick particles of graphite, activated carbon, and biochar, and nano-sized spherical particles of carbon black. From these results, a conclusion that can be drawn at the SEM morphological examination could be successfully used to identifythese carbonaceous counterfeits if they are added in

large quantities (>10%). It is worth noting that SEM characterization also requires testing of a large number of samples because the observation of these micron-sized or nano- sized particles can be easily overlooked by the examination of few samples or spots.

To further obtain the baseline properties of graphene materials in this work, their structural and chemical character-

Figure 1. Comparative SEM images of (a) graphene materials (pristine graphene (FLG)), rGO, and GO) and (b) potential carbon counterfeiting materials (graphite,carbon black, activated carbon, and biochar) showing their typical morphologies.

izations were performed using a broad range of characterization methods including TEM, XPS, Raman spectroscopy, AFM, XRD, and PSD, whichresults are summarized in Figure S2 and Table S1 (Supporting Information). These results conrmed the typical properties of high-quality graphene (FLG), rGO, and GO as expected for these materials compared to the literature and our previous work.911,22,23 More details and description of theirproperties are provided in the Supporting Information.

  • Evaluation of Carbon Counterfeits in Graphene

Materials by Raman and XRD Analyses. As recommended by ISO on the structural characterization of graphene from powders and dispersions, two key graphene characterization methods, Raman spectroscopy and XRD, were used here to evaluate their ability to detect selected carbonaceous counter- feits in graphene materials in this study.15 For that purpose, we collected comparative Raman spectroscopy and XRD data fromgraphene materials (Gr, GO, rGO) and selected carbon counterfeits, including graphite, carbon black, activated carbon, and biochar, which are presentedin Figure 2 and Table S2.

Raman spectra of graphene (FLG), rGO, and GO showing typical signature of these materials represented by characteristic D, G, and 2D peaks; ID/IG and I2D/IG ratios; and 2D peak shape and position are presented in Figure S2. These specic peaks, their shape, position, and peak ratios, which are presented in Table S2, indicate their structural characteristics such as the defect level, number of layers, etc. We evaluated these individual Raman spectra of graphene, GO, and rGO and compared them with the Raman spectra of carbon materials, to assess the ability of this method to detect these potential carbon counterfeits when mixed with graphene materials, which are presented in Figure 2a. An analytical similarity assessment on Raman peaksbetween graphene and selected carbon materials (>10%) is presented in Figure 2b. These results indicate a high similarity in terms of Raman peak shape and peak position between graphene and graphite and expanded graphite for D and G bands with only minor dierences captured on their 2D peaks.24All other carbon materials such as carbon black, activated carbon, and biochar have signicantly dierent Raman plots in comparison to graphene and therefore can be detected by Raman spectroscopy. With respect to rGO and GO, distinct D and G peak shapes without 2D peak can be observed,which are signicantly dierent from the Raman spectra of graphite and expanded graphite, indicating the ability to detect their additions in grapheneusing Raman analysis. However, other carbon

Figure 2. Comparative Raman and XRD spectra of individual graphene materials (pristine graphene, rGO, and GO) and potential carbon counterfeiting materials (graphite, expanded graphite, carbon black, biochar, and activated carbon). (a) Comparative Raman graphs with (b) analytical similarity assessment on key parametersof Raman graphs (D/G, 2D peaks) and the ability to detect the carbon additives in graphene powders. (c) Comparative XRD graphs with (d) analytical similarityassessment on the XRD graphs and their ability to detect these carbon additives in graphene powders. (“X” represents high similarity with lack of the detection, “?” represents high similarity with possible detection, and “tick sign” represents no similarity and high reliability for the detection of additives).

materials such as carbon black, activated carbon, and biochar showed similar hardly distinguishable Raman spectra compared to rGO and GO with the additions of these carbon additives unable to be detected by Raman spectroscopy. In this study, we did not perform and evaluate the Raman characterization of carbon counterfeit mixtures with graphene materials, which requires their dispersion in solution, deposition on substrate, andextensive examination and statistical analysis. Since Raman spectroscopy is a spot analysis, to obtain a reliable outcome and high condence detection of these carbon counterfeits, large numbers of individual particles (>500) are required to be probed, which is laborious and not practical that indicates thelimitation of the Raman spectroscopy method.

XRD is the second comparative method explored to perform direct analysis of materials in powder form with XRD graphs of graphene, rGO, andGO, as presented in Figure S2j and Table S2. These graphs showed typical signatures of these graphene materials as evidenced by their characteristic peaks at 2θ = 26.5° for graphene, 23.3° for rGO, and 9.6° for GO, which are in agreement with the literature.46,25 Individual XRD graphs of graphene materials were compared with the XRD proles of the series of carbon materials to evaluate the ability of this method to detect these potential carbon counterfeits if they were mixed with graphene materials, as depicted in Figure 2c with the analytical similarity assessment presented in Figure 2d. Theseresults indicate the high similarity between graphene and graphite and expanded graphite that is indistinguishable in terms of their peak positions. The XRD peak of rGO is discernible from graphite, but very similar to the XRD peak of carbon black, biochar and activated carbon, suggesting the limited level of their detection in the rGO sample using the XRD method. It was showed further that GO has remarkable distinctive XRD peaks

from all other carbon materials, indicating that they can be detected if these carbon additives were mixed with GO.

To further assess the capability of the XRD method for the detection of selected carbon counterfeits, a mixture of carbon additives (10%) with graphene, rGO, and GO was characterized using the XRD analysis with the results presented in Figure 3. Surprisingly, results showed that the XRDmethod can be only successfully applied in two cases (rGO + 10% graphite and GO + 10% graphite) to detect these carbon counterfeiting additives. In allother cases, signicant overlapping of characteristic peaks of graphene materials with other carbon additives was observed. This conrmed the lack of the ability of the XRD method to detect their presence at 10% concentration.

The comprehensive Raman and XRD characterization in this study clearly concluded that both methods have signicant limitations in detectionofcarbon counterfeits if they are added into graphene powder materials. In particular, the Raman technique, which is recognized as the “gold” standard forgraphene characterization, failed to discriminate dierences between D and G peaks, which are common for majority of the carbon materials. Hence, due to these limitations, alternative methods to detect these carbon additives as potential counter- feits or impurities are needed.

  • Evaluation of Carbon Counterfeits in Graphene

Materials Using the TGA Method. In our previous work, we established the baseline of TGA/DTG characteristics of graphene materials such asfew-layer graphene, GO, rGO, and graphite as their key impurities, as presented in Figure S4. These graphs show distinctive dierences in the thermaldecom- position behavior with identied characteristic parameters such as thermal stability (dened as the temperature at which the material starts todecompose), DTG peak range (position),

Figure 3. Comparative XRD graphs of graphene materials ((a−d) pristine graphene (FLG), (e−h) rGO, and (i−l) GO) and potential carbon counterfeiting materials(graphite, expanded graphite, carbon black, biochar, and activated carbon) including their mixtures with 10% concentrations.

DTG peak shape, and Tmax, which are related to their intrinsic chemical and physical properties that can be used as benchmarked parameters against other carbon materials. To demonstrate the application of TGA as a potential method and simple analytical screening tool for the detection of carbona-ceous counterfeits in graphene materials, we rst established their individual TGA/DTG characteristics as summarized in Figure 4 and Table S3. The obtained TGA and DTG graphs show distinctive dierences in their thermal oxidative

decomposition with the identied characteristic parameters such as thermal stability, DTG peak range (position), DTG peak shape, and Tmax, which represents the intrinsic chemical and physical properties of carbonaceous materials, demonstrating the dierences and similarities with graphene, rGO, and GO. Essentially, an initial assessment was performed using the DTG peak and Tmax value as key parameters in assessing their similarity to evaluate the capability of this method to detect carbon counterfeits (table inset in Figure 4). This analysis in the

Figure 4. Comparative TGA/DTG graphs of graphene (pristine graphene (FLG), rGO, and GO) and potential carbon counterfeiting materials (graphite, expanded graphite, carbon black, biochar, and activated carbon) with the inset table showing an assessment of the ability of the TGA method to detect these carbon additivesin graphene powders based on dierences in DTG peaks and Tmax values.

case of graphene showed that TGA/DTG peaks and Tmax are distinctive from all carbon materials except for carbon black showing an overlapped DTG peak at a similar position. For GO and rGO, similarities on the DTG peaks and Tmax positions with a slight overlap of peaks were observed for biochar and activated carbon, indicating a potential challenge for their detection using the TGA technique. Graphite is one of the most likelycounterfeits for graphene material, which can be inherited as a result of a poor exfoliation during the production process or articially added by thepurpose. The TGA results showed that because graphite has a very high Tmax value (>800 0C) compared to all graphene materials, it can be easily detected using the TGA method with high condence and accuracy.

To evaluate the ability of the TGA method to detect selected carbon counterfeits in this work, TGA/DTG graphs showing comparative graphs of their mixture (10%) with graphene, rGO, and GO are presented in Figure 5. Remarkably, these outcomes conrmed previous results showing that theTGA method can be successfully adopted to detect these carbon additives when added with >10% concentration into graphene materials, in almost all cases. The method not only can perform qualitative detection but also achieve their quantitative determination of the amount of these additives as tabulated in Table S4. The quantitative determination of these carbon additives was not our primary focus in this study, and we observed some dierences in quantitative values compared to 10%, which are likely results of impurities of these additives not considered in calculation. In ourprevious study, we conrmed the detection limit of 1% of graphite additives in graphene that we believe can be applied to most other carbon additives.22 The cases where carbon additives have overlapped DTG peaks with the host graphene materials are observed for graphene, carbon black, GO, and rGO with biochar and activated carbon. We found that the DTG peaks of their 10% mixture could detect these carbon additives, but withlimited peak separation in some cases having high similarity (e.g., carbon black and graphene). To improve the detection of these additives with overlapped DTG peaks, we explored several strategies including the second derivative of TGA curve


(D2TG) approach and reduced heating rate with the results summarized in Figure 6. The results showed that additional D2TG analysis in the case ofgraphene vs carbon black (Figure 6a) can be successfully used to improve their peak separation and detect these impurities with high condence. The second strategy based on the reduction of heating rate from 10 to 2.5

°C/min also showed further improvement in the separation of

these peaks (Figure 6b). Lowering the heating rate is recommended for TGA when additive components have overlapped DTG peaks, demonstrating the successful detection of carbon additives with very similar thermal properties to graphene materials. To evaluate the reliability and repeatability of this method, we performed a double-blind study and TGA analysis using two operators and two dierent TGA instruments showing no signicant dierences (Figure S5 and Table S5, Supporting information). In another study, we found the inuence of sampling method using average graphenesamples and random sample from 5 kg of powder batch showing slight dierence and importance to prepare average sample (Figure S6). The presented results clearly conrmed that the TGA method is superior that can be successfully used to achieve low- cost carbon counterfeiting in graphene materials and perform their qualitative and quantitative analysis that is not possible using other conventional characterization methods recommen- ded for their quality control. Additionally, we would like to highlight that the analysis of counterfeiting materials in graphene should not rely on single characterization method and that complementary methods are often recommended to accomplish highly reliable results.


In conclusion, it was demonstrated that the TGA-DTG method can be successfully used for the qualitative and quantitative determination of potentiallow-cost carbon counterfeiting materials such as graphite, carbon black, activated carbon, and biochar in industrially produced graphene materials such asgraphene (FLG), rGO, and GO. The method is based on the characteristic DTG peak shape and Tmax, from DTG curves that

Figure 5. Comparative TGA/DTG graphs of graphene materials ((a−d) pristine graphene (FLG), (e−h) rGO, and (i−l) GO) and potential carbon counterfeitingmaterials (graphite, expanded graphite, carbon black, biochar, and activated carbon) including their mixtures with 10% concentrations.

can clearly distinguish these carbon additives from graphene materials, not to mention that detecting them at >10% in graphene materials is challengingby other conventional

graphene characterization methods. Comparative evaluation of Raman and XRD methods showed analytical limitation to perform this task, which createsan opportunity for counter-

Figure 6. TGA/DTG analysis of graphene mixed with carbon black (10%) as the most dicult case having overlapped DTG peaks. (a) Use of D2TG peaks appliedto show successful separation between graphene and carbon black peaks and successful calculation of carbon black %. (b) Use TGA conditions with slower heating rate showing successful detection of most dicult counterfeiting material (carbon black) with similar thermal properties to graphene.

feiting materials to be undetected and pass the quality control using these methods. Prospectively, TGA shows superior performance and is a cheap, rapid, simple, and highly reliable method to prevent this potential counterfeit and will provide more condence on the quality of industrially produced bulk graphene powders that is critical for the emerging graphene industry and the end users across broad sectors.


*sı    Supporting Information

The Supporting Information is available free of charge at

Photos of materials used in this study; SEM, TEM, XPS, Raman, FTIR, AFM, and PSD analyses of graphene, rGO, and GO used in this study;characterization of graphene, rGO, and GO; and derived parameters from TGA-DTG curves of all tested materials (PDF)


Corresponding Author

Dusan Losic − School of Chemical Engineering and Advanced Materials, The University of Adelaide, Adelaide, SA 5005, Australia; ARC Hub for Graphene Enabled Industry Transformation, The University of Adelaide, Adelaide, SA 5005, Australia;; Email:


Farzaneh Farivar − School of Chemical Engineering and Advanced Materials, The University of Adelaide, Adelaide, SA 5005, Australia; ARCHub for Graphene Enabled Industry Transformation, The University of Adelaide, Adelaide, SA 5005, Australia

Pei Lay Yap − School of Chemical Engineering and Advanced Materials, The University of Adelaide, Adelaide, SA 5005, Australia; ARC Hub for Graphene Enabled Industry Transformation, The University of Adelaide, Adelaide, SA 5005, Australia

Afshin Karami − School of Chemical Engineering and Advanced Materials, The University of Adelaide, Adelaide, SA 5005, Australia;

Complete contact information is available at:

Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the nal version of the manuscript.


The authors declare no competing nancial interest.


The authors thank the funding by the ARC Research Hub for

Graphene Enabled Industry Transformation, (IH150100003). They acknowledge Australian Microscopy and Microanalysis Research Facility (AMMRF) for the access to SEM and TEM facilities.


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