Characterization of Graphite Oxide and Reduced Graphene Oxide

materials

Article Characterization of Graphite Oxide and Reduced Graphene Oxide Obtained from Different Graphite Precursors and Oxidized by Different Methods Using Raman Spectroscopy Statistical Analysis

Roksana Muzyka 1, Sabina Drewniak 2,* , Tadeusz Pustelny 2, Marcin Sajdak 1 and Łukasz Drewniak 2

1 Institute for Chemical Processing of Coal, 1 Zamkowa St., 41-803 Zabrze, Poland; [email protected] (R.M.); [email protected] (M.S.) 2 Department of Optoelectronics, Faculty of Electrical Engineering, Silesian University of Technology, 2 Krzywoustego St., 44-100 Gliwice, Poland; [email protected] (T.P.); [email protected] (Ł.D.) * Correspondence: [email protected]

Abstract: In this paper, various graphite oxide (GO) and reduced graphene oxide (rGO) preparation methods are analyzed. The obtained materials differed in their properties, including (among others) their oxygen contents. The chemical and structural properties of graphite, graphite oxides, and reduced graphene oxides were previously investigated using Raman spectroscopy (RS), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD). In this paper, hierarchical clustering analysis (HCA) and analysis of variance (ANOVA) were used to trace the directions of changes of the selected parameters relative to a preparation method of such oxides. We showed that the oxidation methods affected the Citation: Muzyka, R.; Drewniak, S.; physicochemical properties of the final products. The aim of the research was the statistical analysis Pustelny, T.; Sajdak, M.; Drewniak, Ł. Characterization of Graphite Oxide of the selected properties in order to use this information to design graphene oxide materials with and Reduced Graphene Oxide properties relevant for specific applications (i.e., in gas sensors). Obtained from Different Graphite Precursors and Oxidized by Different Keywords: graphite; graphite oxide; reduced graphene oxide; Raman spectroscopy; XRD; XPS; HCA; Methods Using Raman Spectroscopy ANOVA; Hummers method; Tour method Statistical Analysis. Materials 2021, 14, 769. https://doi.org/10.3390/ ma14040769 1. Introduction Academic Editor: Soo Young Kim Graphene, obtained in 2004 [1], is characterized by its extraordinary physical and Received: 28 December 2020 chemical properties [2]. A worldwide effort has been initiated to develop efficient methods Accepted: 1 February 2021 of producing graphene and its derivatives. The most widely used chemical production Published: 6 February 2021 method for graphene is the oxidation of graphite and the exfoliation–reduction of the obtained graphite oxide. The basic preparation methods were developed by Brodie [3], Publisher’s Note: MDPI stays neutral Staudenmaier [4], Hoffmann [5], Hummers [6], Hummers and Offemann [7], and Tour [8,9]. with regard to jurisdictional claims in The last two methods (Hummers–Offemann [6] and Tour [8,9] methods) deserve special published maps and institutional affil- attention. Hummers and Offemann presented an optimized, rapid, safe method of graphite iations. oxidation, whereby GO is obtained via treatment of graphite by strong oxidizing agents. This method is currently the most used. Meanwhile, Tour et al. [9] suggested the partial replacement of nitric acid by less corrosive phosphoric acid. This limits the generation of toxic gases. Copyright: © 2021 by the authors. The literature reports that the efficiency of the oxidation processes and the resulting Licensee MDPI, Basel, Switzerland. GO structure depend on the type of graphite and its structural parameters—mainly the size This article is an open access article of the crystallites [10,11]. The obtained graphite oxide is a multilayer structure. Its color distributed under the terms and depends on the origin and size of the graphite grains and degree of oxidation (whereby conditions of the Creative Commons Attribution (CC BY) license (https:// the color changes from dark grey to green-blue) [10–13]. The obtained graphite oxides creativecommons.org/licenses/by/ contain oxygen in their structures in amounts ranging from 25% to 60% by mass, and the 4.0/).

Materials 2021, 14, 769. https://doi.org/10.3390/ma14040769 https://www.mdpi.com/journal/materials Materials 2021, 14, 769 2 of 14

materials contain different structures, compositions, and ratios of carbon to oxygen (C/O). The inﬂuence of the oxidation method on the oxygen content in the GO is shown in Table1.

Table 1. The inﬂuence of the oxidation method on the oxygen content in the GO.

Oxidation Method Material Ratio C/O [Ref.] Brodie natural graphite (Ceylon) 3.5 [3] Staudenmaier natural graphite 2.9 [4] Hofmann natural graphite 3.3 [5] natural graphite with variable grain Hummers (various) (16.0–2.0) [6] sizes smaller than 60 and at 60–90 µm Hummers–Offemann natural graphite 3.0 [7,8]

Based on the literature [14–16], we can hypothesize a relationship between the graphite precursor and the composition, morphology, and structure of the obtained graphite oxides. Moreover, the used oxidation method also affects the structure of the graphite oxides. In turn, the literature [17] shows that the origin and structure of the graphite and its oxidation method significantly impact the composition, distribution of oxygen connections, and structure of the obtained GO. The degree of comminution of the graphite is an additional factor that affects the effectiveness of the oxidation process. Deemer et al. [18] studied the influence of the oxidation method (using the Hummers [6] and Marcano–Tour [9] methods) using various sizes (smaller than 100 µm and bigger than 420 µm) of graphite flake. In the Hummers method, the graphene materials’ parameters depend on the grain size, which is correlated with the oxidation degree of GO. In [19], it is shown that the size of the crystallites, oxidation degree, and types of oxygen connections play important roles in creating composites of GO with metals. Along with increases in the oxygen content, carboxylic groups located on the edges of the graphene flakes take part in the creation of the composites. Epoxy and hydroxyl groups form bonds with metals only when the carboxylic acid content in the GO structure is very low. The graphene oxide is obtained through reduction and exfoliation. This process can be performed in many ways, one of which seems to be promising for the mass production of graphene materials—the so-called "thermal method" [20,21]. Our researchers [14,22,23] confirmed the dependence of the type of graphite precursor on the properties of reduced graphene oxides. The influence of three graphite precursors was studied, i.e., natural flake graphite (GF), natural scaly graphite (GS), and synthetic graphite (GE). The highest degree of oxidation of graphite was achieved using the modified Hummers and Tour methods. Moreover, we observed that larger graphite oxides were obtained with larger crystallite dimensions in the graphite, irrespective of the oxidation method. A distinct dependence of the degree of reduction on the graphite precursor was also observed. The highest degree of reduction and smallest number of structural defects were obtained for reduced graphene oxide prepared using flake graphite (rGO-F), whose crystallite diameter was the largest among the examined graphite materials. The rGO obtained from scalar graphite showed the smallest degree of reduction and share of carbon with C sp2 hybridization and the highest degree of structural defects. It is also worth mentioning that the largest surface area values (over 900 m2g−1) were measured for reduced graphene oxides obtained from scale and flake graphites and oxidized using a modified version of Tour’s method [9]. The mentioned papers and our research [16,24], based on RS, SEM, XPS, and XRD measurements, show that both the graphite precursor and the oxidation method determine the properties of the fabricated GO and rGO. For this purpose, it is possible to apply chemometric approaches, which have been successfully used not only for analysis of the possible relationship between the graphite precursor and oxidation method, but also for many other applications, such as for the design of polymeric sensor materials (which materials make it difficult to predict the desired properties) [25–27]. Another good example related to our study is the use of the Materials 2021, 14, 769 3 of 14

chemometric methods for the design of biological sensors, e.g., based on molecularly imprinted polymers (MIP). The chemometrics methods can be applied to investigate the effects of variables such as the type and quantity of monomers, cross-linkers, porogens, initiators, types of initiation (UV or thermal), polymerization pressure, temperature, reaction time, and reaction vial dimensions on the properties of synthesized polymers [28,29]. Chemometric methods can be used to study the relationships between the variables under investigation and for optimization of the sensor properties [25]. This paper aims to show how the graphite precursors and graphite oxide oxidation methods determine the physicochemical properties of graphene oxides (which were fabricated using different methods derived from the Hummers method (A, B, C) and a modified version of the Tour method (D). The presented analyses can help in selecting a fabrication technology for graphite oxide to obtain a material with specific physicochemical properties (for a specific practical application).

2. Materials and Methods 2.1. The Selection of Graphite for the Preparation of Graphite Oxide and Reduced Graphene Oxide In order to obtain graphite oxides and reduced graphene oxides, two natural flake (GF) and scalar (GS) graphites and one synthetic (GE) graphite were used. Each graphite (1 g) was ground and sieved to smaller than 20 µm, and in the next step was oxidized using one of four oxidation methods (A, B, C, or D; see Table2). The names of the obtained graphite oxides follow the pattern of GOX-Y, where X is the type of graphite (S-scalar, F-flake, or E-synthetic) and Y is the type of oxidation method (A, B, C, or D). The reduction and exfoliation method was the same (thermal reduction) for each sample. Graphite oxides were annealed at 900 ◦C under a nitrogen flow of 50 mL/min. The samples were annealed at the final temperature for 5 min. It should also be mentioned that methods A, B, and C are versions of the Hummers [6] method, while method D is a modification of the Tour method [8].

Table 2. GO preparation conditions [14,19].

Oxidizing Mixture Symbol Base Acid Time (Reagents)

Method A H2SO4 (20 mL) HNO3 (15 mL), KMnO4 (3 g) 24 h Method B H2SO4 (30 mL) NaNO3 (3 g), KMnO4 (3 g) 2 h Method C H2SO4 (22.5 mL) NaNO3 (0.5 g), KMnO4 (3 g) 0.5 h Method D H2SO4 (45 mL), H3PO4 (5 mL), KMnO4 (5 g), KNO3 (1.5 g) 5 h

2.2. Methods of Characterization for the Obtained GO and rGO The following characterization methods were used for the graphite oxides and graphene oxides: X-ray diffraction (XRD), X-ray photoelectron microscopy (XPS), Raman spectroscopy (RS), and elementary analysis. For XRD measurements, the samples were deposited onto glass and analyzed using Cu Ka1 radiation, with a voltage of 45 kV and a current of 30 mA. In the experiments, an X’Pert PRO PW 3040/60 diffractometer (PANalytical, Quebec, Canada) was used. (exemplary spectra are shown in SI ﬁles, Figures S4 and S5). In the XPS measurements, a PHI 500 VersaProbe spectrometer (Chigasaki, Japan) was used (Al Kα anode radiation beam: 1486.6 eV). The Raman spectra were recorded using an N-TEGRA Spectra platform (NT-MDT, Eindhoven, the Netherlands). In the measurements, a laser beam with a 532 nm wave- length was used (the exposure time was 10 s). (Exemplary spectra are shown in SI ﬁles, Figures S2 and S3). The elementary analysis results were obtained using a Vario Macro Cube automatic elementary analyzer (Elementar Analysysteme GmbH Company, Hanau, Germany). Materials 2021, 14, 769 4 of 14

2.3. Data Analysis—Chemometric Approach One of the commonly used methods for exploratory multivariate data is clustering analysis (CA). CA is one of the chemometric methods used to describe the relationships among different variables. CA allows the grouping of samples characterized by significant similarity (e.g., chemical similarity) and allows the identification of outliers. This method is often used in chemical analyses and environmental studies for the following reasons: • To distinguish between sources of emissions [30]; • To identify areas with different levels of pollution [31]; • For the analysis of solid fuels, e.g., coal [32]; • Todetermine the physicochemical properties of the pollution fractions in the environment [33]. The goal of CA is to combine tested samples or variables into clusters that indicate mutual similarities or differences. This study uses the hierarchical clustering analysis (HCA) method, in which groups are built gradually, starting with single observations that are then combined into larger clusters. Splitting of clusters, starting from the first cluster (cluster covering all objects), is performed by successive division of the first cluster into smaller, more homogeneous clusters. The first step in the analysis is to calculate the distance between features in the multidimensional data space, e.g., via Euclidean distance (as was done in the discussed studies). This allows the similarity between the tested objects or variables to be assessed, assuming that similar objects are adjacent. For this purpose, the raw data were subjected to a standardization process to obtain a data set characterized by a distribution with a mean equal to “0” and standard deviation equal to “1”. Dataset standardization is an essential stage in data preprocessing, especially in the case of variables characterized by different units and different data values, e.g., 0.0001 to 100.00. The differences between these data would make it impossible to compare the tested variables through HCA analysis. The next step in conducting HCA is to determine the rules for joining clusters, i.e., determining when two clusters are similar enough to be able to combine them. In the presented research, we applied the complete method, which is also called furthest neighbor grouping. The grouping results can be visualized as a dendrogram and clustered heat maps can show cluster merger sequences and the distances at which each merger took place. In the presented studies, the complete linkage method was applied. To determine the statistically significant impact of the graphene precursors’ studied properties and the used methods, analysis of variance (ANOVA) was applied. ANOVA helps to indicate the variables that affect the quality of the GO and rGO, e.g., the oxygen 2 3 concentration, C/O ratio, amounts of Csp and Csp bands, interlayer distance d001, and average size of the crystallites La. This approach indicates which variables are statistically significant (e.g., V1, V2, and V3, where V is a variable) and the interactions among these variables (e.g., V1V2, V1V3, V2V3, and V1V2V3). To achieve this goal, all experimental data were statistically analyzed using MATLAB (MATLAB, 2016).

3. Results The efficiency of the oxidation processes for the three graphites with four oxidation methods was 140–156% by mass. In this case, the efficiency is expressed as a percentage and determines the increase in the mass of tested graphite samples caused by the inclusion of oxygen atoms in the graphite structure during the oxidation process. The highest efficiency was obtained by applying method D, while the lowest efficiency was obtained by applying method C. This efficiency directly translated into the following oxygen contents: method C < method B < method D < method A (up to 36%). This trend is shown in Figure1 (dendrograms marked in blue) as a result of HCA. The GOs produced using methods D and A (Figure1, dendrogram marked in green) were characterized by high and homogeneous results of several parameters, such as the oxygen contents, interlayer distances d001, and contents of epoxy and hydroxyl groups. Materials 2021, 14, x FOR PEER REVIEW 5 of 15

contents: method C < method B < method D < method A (up to 36%). This trend is shown in Figure 1 (dendrograms marked in blue) as a result of HCA. The GOs produced using Materials 2021, 14, 769 methods D and A (Figure 1, dendrogram marked in green) were characterized5 of 14 by high and homogeneous results of several parameters, such as the oxygen contents, interlayer distances d001, and contents of epoxy and hydroxyl groups.

Figure 1.FigureThe clustered 1. The clustered heat map heat for map the studiedfor the studied GO samples GO samples and their and properties. their properties.

As mentionedAs earlier, mentioned cluster earlier, analysis cluster makes analysis it possible makes to determineit possible to the determine similarity the similarity between the studybetween samples the study and samples the variables and the used variables to describe used to their describe characteristics. their characteristics. In In the the clustered heatclustered map (Figure heat map1), the (Fig similarityure 1), the scale similarity is in the scale range is ofin < the− 3.3> range and of is<− a3.3> and is a consequence ofconsequence the performed of normalization the performed of all normalization variables (without of all which variables a comparative (without which a analysis of thecomparative measured variables analysis would of the be measured impossible; variables a schematic would presentation be impossible of the; a schematic normalization ofpresentation all variables of is presentedthe normalization in Figure S1). of all The variables interpretation is presented of the presented in Figure S1). The graphs in the forminterpretation of a clustered of heat the presentedmap can be graphs compared in theto linear form regression of a clustered and propor- heat map can be tionality. If thecompared tested samples to linear or variablesregression have and proportionality. comparable similarity If the tested values, samples e.g., − or3, itvariables have can be concludedcomparable that the relationshipsimilarity values, between e.g. them, −3, it is can directly be concluded proportional. that Anthe examplerelationship between is the oxygen contentthem is in directly samples proportional. oxidized by methodAn example C. The is the data oxygen obtained content using in elemental samples oxidized by analysis (the changesmethod ofC. oxygenThe data content) obtained are using directly elemental proportional analysis to (the the changes data obtained of oxygen content) using XPS spectroscopyare directly (oxygen proportional content: to C=O,the data C–O–H, obtained C–O–C, using O=C–OH XPS spectroscopy embedded (oxygen in content: the tested material).C=O, C A–O similar–H, C–O interpretation–C, O=C–OH isembedded performed in the in thetested case material of extreme). A similar values, interpretation e.g., −3, 3. Foris example, performed such in similaritythe case of valuesextreme for values, oxygen e.g. contents, −3, 3. For characterize example, such samples similarity values obtained usingfor methods oxygen A content and C,s wherebycharacterize method samples A was obtained characterized using methods by the highest A and C, whereby mean oxygen valuemethod of 35%A was (similarity characterized value by of the 3) and highest method mean C wasoxygen characterized value of 35% by (similarity the value lowest mean oxygenof 3) and value method of 22% C was (similarity characterized value by of the−3). lowest As can mean also oxygen be seen value based of on 22% (similarity CA analysis andvalue in termsof −3). of As oxygen can also content, be seen methods based on A, CA D, and analysis B can and be linkedin terms into of oneoxygen content, group (this is alsomethods confirmed A, D, and by the B can results; be linked for these into threeone group methods (this graphite is also confirmed oxides are by the results; characterized by oxygen contents higher than 30%. The statistical data analyses and the ANOVA method confirmed the significant statistical influence of the oxidation method on the oxygen content (Figure2a) for the GO, in contrast to the kind of graphite precursor (Figure2b). It also confirmed that the oxygen content depended on the oxidation method in the following order: method C < method B < method D < method A. Materials 2021, 14, x FOR PEER REVIEW 6 of 15

for these three methods graphite oxides are characterized by oxygen contents higher than 30%. Materials 2021, 14, x FOR PEER REVIEW 6 of 15 The statistical data analyses and the ANOVA method confirmed the significant statistical influence of the oxidation method on the oxygen content (Figure 2a) for the GO, in contrast to the kind of graphite precursor (Figure 2b). It also confirmed that the oxygen contentfor these depended three methods on the graphite oxidation oxides method are characterizedin the following by order:oxygen method content Cs

Figure 2. Box plots for oxygen concentrations depending on the (a) method and (b) precursor material.

During the graphite oxidation process, the interlayer distances between the graphene layers Figureincreased 2. Box plotsmore for than oxygen two concentrations-fold, from depending approximately on the (a) method 0.336 and nm (b ) (band precursor 002) material. to 0.8184 nm (band 001), as a result of adding oxygen groups between layers and adding oxygen Figure 2. Box plots for oxygenDuring concentration the graphites oxidationdepending process, on the the (a interlayer) method distancesand (b) precursor between the graphene groupsmaterial. at the edgeslayers of the increased layers. more The than graphite two-fold, oxides from approximately obtained using 0.336 nm method (band 002) A towere 0.8184 nm characterized by the(band largest 001), d as001a interlayer result of adding distances oxygen (0.8013 groups between–0.8184 layers nm) andand adding the sm oxygenallest groups dimensionsDuring the of graphite grapheneat the edgesoxidation layers of the L layers.process,a (26 The–28 the graphite nm). interlayer oxides The distances obtainedstatistical using between significance method the A were graphene of characterized this by the largest d interlayer distances (0.8013–0.8184 nm) and the smallest dimensions informationlayers increased was confirmedmore than bytwo ANOVA-fold001 , from, and approximately the results for 0.336both dnm001 and(band La 002)are presented to 0.8184 of graphene layers L (26–28 nm). The statistical signiﬁcance of this information was innm Fig (bandure 3 001),a,b, respectively. as a result of It adding was observed oxygena thatgroups the betweenlarger dimensions layers and of adding the graphene oxygen conﬁrmed by ANOVA, and the results for both d001 and La are presented in Figure3a,b , re- layersgroups in at the the graphite, edgesspectively. of the the larger layers. It was dimensions observed The graphite that were the largeroxides in dimensionsthe obtained obtained of theusing GO, graphene regardless method layers A in of thewere the graphite, oxidationcharacterized method. by the the largest larger dimensionsd001 interlayer were distances in the obtained (0.8013 GO, regardless–0.8184 nm) of the and oxidation the sm method.allest dimensions of graphene layers La (26–28 nm). The statistical significance of this information was confirmed by ANOVA, and the results for both d001 and La are presented in Figure 3a,b, respectively. It was observed that the larger dimensions of the graphene layers in the graphite, the larger dimensions were in the obtained GO, regardless of the oxidation method.

Figure 3. Box plots for (a) d001 and (b)La as functions of the applied method.

Figure 3. Box plots for (a) d001 and (b) La as functions of the applied method. The deconvolution of XPS C1s spectra of graphite oxides showed that oxygen occurred mainly (i.e., more than 50% of the total oxygen content) in the epoxy and hydroxyl The deconvolutionconnections of XPS located C1s on spectra the graphite of graphite planes (at theoxides edges showed there were that fewer oxygen carbonyl and 2 occurred mainly (i.e.,quinone more or thancarboxylic 50% groups). of the The total total oxygen amounts ofcontent) carbon within the sp hybridization epoxy and varied to a great extent in the graphite oxides (37–6%), which depended on the oxidation methods hydroxyl connections located on the graphite planes (at the edges2 there were fewer (Figure4a) in a signiﬁcant way. The carbon content with sp hybridization was inversely2 carbonylFigure 3. Box and plot quinones forproportional (a) d or001 and carboxylic ( tob) the La oxidationas groups).function yield,s of The asthe shown totalapplied in amount Figuremethod.4sb. of The carbon carbon content with spwith this hybridization variedhybridization to a great extent method inincreased the graphite when oxides the degree (37– of6%) oxidation, which decreased depended and on had the the oxidationThe deconvolution methodfollowings (Fig of ure trend: XPS 4a) C1smethod in spectraa Csignificant < method of graphite B < way. method Theoxides A,D. carbon showed content that with oxygen sp2 occurred mainly (i.e., more than 50% of the total oxygen content) in the epoxy and hydroxyl connections located on the graphite planes (at the edges there were fewer 2 carbonyl and quinone or carboxylic groups). The total amounts of carbon with sp hybridization varied to a great extent in the graphite oxides (37–6%), which depended on the oxidation methods (Figure 4a) in a significant way. The carbon content with sp2

Materials 2021, 14, x FOR PEER REVIEW 7 of 15

hybridization was inversely proportional to the oxidation yield, as shown in Figure 4b. Materials 2021, 14, x FOR PEER REVIEW 7 of 15 The carbon content with this hybridization method increased when the degree of oxidation decreased and had the following trend: method C

hybridization was inversely proportional to the oxidation yield, as shown in Figure 4b. MaterialsThe2021 , 14 carbon, 769 content with this hybridization method increased when the degree of 7 of 14 oxidation decreased and had the following trend: method C

Figure 4. Box plot of C1sp2 hybridization as a function of the applied method (a) and clustered heat map of selected variables (for the studied GO) (b).

Figure 4. Box plot of C1sp2 hybridization The Raman as a function spectroscopy of the applied confirmed method (aan) and increase clustered in heat the map share of selected of the disordered phase variablesFigure (for4. Box the studiedplot of GO)C1spcompared (b).2 hybridization to that foras a the function graphites, of the asapplied evidenced method by (a the) and increas clusterede of the D-band's intensity heat map of selected variablesin relationThe Raman(for to the the spectroscopy studied G-band. GO) confirmedIn (b the). Raman an increase spectra in the of sharethe graphite of the disordered oxides, phase both the G- and D- bandscompared increased to that for in the width graphites, and asshifted evidenced towards by the increaselower wavelengths, of the D-band’s indicating intensity an increase The Raman spectroscopyinin relationthe degree to confirmed the of G-band. defective an In increase the structures Raman in spectra thedue share to of the of graphiteintroduction the disordered oxides, of both oxygen phase the G- functional and groups. D-bands increased in width and shifted towards lower wavelengths, indicating an increase compared to that forThe the lowest graphites, ID/IG as intensity evidenced ratio by was the obtainedincrease offor the graphite D-band's oxide intensitys prepared using method in the degree of defective structures due to the introduction of oxygen functional groups. in relation to the G-band.C, which In the indicated Raman thatspectra this of method the graphite had the oxides weakest, both oxidizing the G- and potential. D- The difference The lowest ID/IG intensity ratio was obtained for graphite oxides prepared using method bands increased in widthbetweenC, which and indicated graphite shifted that towards oxides this method obtainedlower had wavelengths, the using weakest method oxidizing indicating C potential. and an theincrease The other difference s was statistically in the degree of defectivesignificantbetween structures graphite (the oxides highestdue obtainedto the variability introduction using method for the of C and oxygen examined the others functional parameters was statistically groups. was signifi- obtained for this The lowest ID/IG intensitymethod)cant (the ratio highest, as was shown variability obtained in Fig for urefor the graphite5. examined The influence oxide parameterss prepared of wasthe obtainedgraphite using for methodprecursor this method), type (GF, GS, or C, which indicated GE)thatas shown wathiss instatisticallymethod Figure5 .had The insignificant. the influence weakest of the oxidizing graphite precursor potential. type The (GF, difference GS, or GE) was statistically insignificant. between graphite oxides obtained using method C and the others was statistically significant (the highest variability for the examined parameters was obtained for this method), as shown in Figure 5. The influence of the graphite precursor type (GF, GS, or GE) was statistically insignificant.

Figure 5. Diagram of between-group variation for I /I as a function of the applied method. Figure 5. Diagram of between-group variationD G for ID/IG as a function of the applied method.

The deconvolution of the 2D band and intensity ratios I2D to IG (I2D/IG) and I2D to ID+D’ The(I2D/I deconvolutionD+D’) showed that of graphite the 2D oxides band obtained and intensity using method ratios D wereI2D to composed IG (I2D/IG of) and I2D to ID+D' (Ipackets2D/ID+D' with) showed the lowest that numbers graphite of graphene oxides layers obtained and the using highest degreesmethod of Ddefective were composed of structures compared to those oxides obtained with the other methods. The differences Figure 5. Diagram of betweenpackets- groupwith the variation lowest for number ID/IG ass a of function graphene of the layers applied and method. the highest degrees of defective in the I /I ratios of the graphite oxides obtained using method D were statistically structures2D Gcompared to those oxides obtained with the other methods. The differences in signiﬁcant in relation to methods A and C, while the I2D/ID+D’ intensity ratio for graphite The deconvolutiontheoxides Iof2D obtained /ItheG ratios2D usingband of methodand the intensitygraphite D was statistically ratios oxides I2D obtainedsigniﬁcant to IG (I2D /I onlyusingG) and in relation methodI2D to toID+D' method D were statistically (I2D/ID+D') showed thatsignificaC (Figure graphite6nt). Thein relation oxides largest numberobtained to methods of graphite using A and layersmethod C, in while the D package werethe I 2D was composed/ID+D' characterized intensity of forratio for graphite packets with the lowestoxidesgraphite number obtained oxidess obtainedof usinggraphene using method methodlayers D waand C. s statisticallythe highest degreesignificants of defectiveonly in relation to method C structures compared(Figure to those 6). oxides The largest obtained number with theof graphite other methods. layers inThe the differences package wasin characterized for the I2D/IG ratios of graphite the graphite oxides oxides obtained obtained using method using Cmethod. D were statistically significant in relation to methods A and C, while the I2D/ID+D' intensity ratio for graphite oxides obtained using method D was statistically significant only in relation to method C (Figure 6). The largest number of graphite layers in the package was characterized for

graphite oxides obtained using method C.

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Figure 6. Box plots of: (a)I2D/IG band ratio; (b)I2D/ID+D’ band ratio as a function of the applied method; (c)I2D/IG band Figure 6. Box plots of: (a) I2D/IG band ratio; (b) I2D/ID+D’ band ratio as a function of the applied ratio; (d)I2D/ID+D’ after excluding method C. method; (c) I2D/IG band ratio; (d) I2D/ID+D’ after excluding method C. Analysis of data divided according to the type of graphite precursor may show that Analysis of data divided according to the type of graphite precursor may show that the highest ID/IG ratio values and the lowest I2D/IG and I2D/ID+D’ ratio values were the highest ID/IG ratio values and the lowest I2D/IG and I2D/ID+D' ratio values were obtained obtained for graphite oxides containing synthetic graphite. This indicates that synthetic for graphite oxides containing synthetic graphite. This indicates that synthetic graphite was the mostgraphite susceptible was to the the most generation susceptible of structural to the generation defects and ofdelamination structural defectsof the and delamination Materials 2021, 14, x FOR PEER REVIEW of the graphite layers during the oxidation process. However, as shown9 of 15 from the statistical graphite layers during the oxidation process. However, as shown from the statistical analysis (ANOVAanalysis method), (ANOVA these method), differences these were differences statistically were insignificant statistically (Figure insigniﬁcant 7a–c). (Figure7a–c).

Figure 7.FigureBox plots 7. Box of: plot (as)I of:D /I(a)G I;(D/IbG)I; (b2D) /II2DG/I;(G; c(c)I) I2D2D/I/ID+D’D+D’ ratioratio as a as function a function of the of precursor the precursor material. material.

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The graphites oxidized using methods A, B, and D were selected to prepare reduced graphene oxides. The obtained graphene materials were characterized by 2–3-fold lower oxygen content than those for the corresponding graphite oxides. These differences were clearly visible when the collected data were analyzed using HCA. Figure8 shows green dendrograms, which describe samples of reduced graphene oxides and variables character- izing the degree of oxidation of the investigated materials. The oxygen contents determined by XPS ranged from 6.3% to 9.2% at and varied depending on the type of graphite in the following order: rGO-F < rGO-S < rGO-E. The degree of the reduction represented by the C/O ratio increased in the following order: rGO-E < rGO-S < rGO-F. For both parameters mentioned above, the influence of the type of precursor was confirmed by ANOVA (Figure9) and was statistically significant, thus confirming the observations made earlier. The XPS C1s spectra analysis showed that oxygen in reduced graphene oxides (similar to GO) occurred mainly in the form of epoxy and hydroxyl groups and in smaller amounts in the form of carbonyl and quinone groups. Carboxylic groups are completely decomposed in the process of thermal exfoliation–reduction, while lactone groups appear. Graphite oxides and reduced graphene oxides are essentially different in the content of carbon with sp2 hybridization. The increase of C in sp2 hybridization from 37% to 53% for graphite oxides to 70% to 80% for reduced graphene oxides confirms that the graphite structure was partial reconstructed. These differences are visible in the results obtained during data analysis using the cluster method (Figure8). The significant similarity for the number of carbon atoms with sp2 and sp3 bonds in rGO (high value of similarity ~2) compared to the 2 3 − Materials 2021, 14, x FOR PEER REVIEWnumber of sp and sp bonds in GO, for which the similarity value ranged from 0 to10 of3 15 (marked with yellow rectangles), is easy to notice.

Figure 8. The clustered heat map for the studied GO and rGO samples and their properties. Figure 8. The clustered heat map for the studied GO and rGO samples and their properties.

The oxygen contents determined by XPS ranged from 6.3% to 9.2% at and varied depending on the type of graphite in the following order: rGO-F < rGO-S < rGO-E. The degree of the reduction represented by the C/O ratio increased in the following order: rGO-E < rGO-S < rGO-F. For both parameters mentioned above, the influence of the type of precursor was confirmed by ANOVA (Figure 9) and was statistically significant, thus confirming the observations made earlier.

Figure 9. Box plots for the oxygen concentration (a) and carbon/oxygen ratios (b) depending on the precursor material.

The XPS C1s spectra analysis showed that oxygen in reduced graphene oxides (similar to GO) occurred mainly in the form of epoxy and hydroxyl groups and in smaller amounts in the form of carbonyl and quinone groups. Carboxylic groups are completely decomposed in the process of thermal exfoliation–reduction, while lactone groups appear. Graphite oxides and reduced graphene oxides are essentially different in the content of

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Figure 8. The clustered heat map for the studied GO and rGO samples and their properties.

The oxygen contents determined by XPS ranged from 6.3% to 9.2% at and varied depending on the type of graphite in the following order: rGO-F < rGO-S < rGO-E. The degree of the reduction represented by the C/O ratio increased in the following order: rGO-E < rGO-S < rGO-F. For both parameters mentioned above, the influence of the type Materialsof2021 precursor, 14, 769 was confirmed by ANOVA (Figure 9) and was statistically significant,10 ofthus 14 confirming the observations made earlier.

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carbon with sp2 hybridization. The increase of C in sp2 hybridization from 37% to 53% for graphite oxides to 70% to 80% for reduced graphene oxides confirms that the graphite structure was partial reconstructed. These differences are visible in the results obtained during data analysis using the cluster method (Figure 8). The significant similarity for the number of carbon atoms with sp2 and sp3 bonds in rGO (high value of similarity ~2) compared to the number of sp2 and sp3 bonds in GO, for which the similarity value ranged from 0 to −3 (marked with yellow rectangles), is easy to notice. XRD studies confirmed the graphite structure reconstruction in the rGO. Interlayer distances decreased from ~0.8 nm (d001 band) in the GO to ~0.4 nm (d00X band) in the rGO FigureFigure 9. 9.Box Box plots plots for the for oxygen the oxygen concentration concentration (a) and carbon/oxygen (a) and ratioscarbon/oxygen (b) depending ratio on thes precursor (b) depending material. on (Figure 10). The oxidation method's influence affected the interlayer distances in the rGO, the precursor material. XRD studies confirmed the graphite structure reconstruction in the rGO. Interlayer and this influence was statistically significant. Based on observations, it can be affirmed distances decreased from ~0.8 nm (d001 band) in the GO to ~0.4 nm (d00X band) in the The XPS C1s rGOthat spectra (Figure reduced analysis 10). graphene The oxidationshowed oxides method’s that obtained oxygen influence from in affected reduced graphites the interlayer graphene oxidized distances oxidesby inmethod A showed the thehighest rGO, and degree this influence of structural was statistically defects, significant. while those Based o onbtained observations, by method it can be B were characterized (similar to GO) occurredaffirmed mainly that reduced in the graphene form of oxides epoxy obtained and fromhydroxyl graphites groups oxidized and by in method smaller A amounts in the formshowedby of the carbonyl thelowest highest degree and degree quinone of structuralstructural groups. defects, defects. Carboxylic while Such those obtained agroups low degree by are method completely (for B reduced were graphene oxides decomposed in the characterizedpreparedprocess of usingthermal by the lowest method exfoliation degree B) of indicates structural–reduction defects. that, while reconstruction Such lactone a low degree groups (for of thereduced appear. graphite structure was Graphite oxides andgrapheneincreased. reduced oxides graphene prepared usingoxides method are B)essentially indicates that different reconstruction in the of the content graphite of structure was increased.

Figure 10. Diagram of between-group variation for d . Figure 10. Diagram of between-group variation00X for d00X. In the process of thermal exfoliation–reduction, on the one hand, the content of carbon with spIn2 hybridization the process increased, of thermal as shown exfoliation in Figure 11. Due–reduction to the signiﬁcant, on the variance one of hand, the content of thecarbon results with in the casesp2 ofhybridization the samples obtained increased, using method as shown D, it cannot in be Fig concludedure 11. that Due to the significant the differences in the carbon content with sp2 hybridization due to the applied method werevariance statistically of the signiﬁcant. results in the case of the samples obtained using method D, it cannot be concluded that the differences in the carbon content with sp2 hybridization due to the applied method were statistically significant.

Figure 11. Box plot of C1sp2 hybridization as a function of the applied method.

On the other hand, the number of structural defects due to the elimination of oxygen groups increased. Based on the values of the ID/IG and I2D/ID+D' ratios determined from the Raman spectra, it was concluded that rGO obtained from the graphites oxidized using method A showed the highest amount of structural defects, while the lowest were for

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Figure 10. Diagram of between-group variation for d00X.

In the process of thermal exfoliation–reduction, on the one hand, the content of carbon with sp2 hybridization increased, as shown in Figure 11. Due to the significant variance of the results in the case of the samples obtained using method D, it cannot be 2 Materials 2021, 14, 769 concluded that the differences in the carbon content with sp 11 hybridization of 14 due to the applied method were statistically significant.

FigureFigure 11. 11.Box Box plot ofplot C1sp of2 hybridization C1sp2 hybridization as a function ofas the a function applied method. of the applied method. Materials 2021, 14, x FOR PEER REVIEW On the other hand, the number of structural defects due to the elimination12 of of15 oxygen

groupsOn increased. the othe Basedr hand, on the valuesthe number of the ID/I ofG andstructural I2D/ID+D’ defectsratios determined due to the from elimination of oxygen the Raman spectra, it was concluded that rGO obtained from the graphites oxidized using groups increased. Based on the values of the ID/IG and I2D/ID+D' ratios determined from the method A showed the highest amount of structural defects, while the lowest were for method B. The sameRaman observation spectra, was it madewas forconcluded the values that of interlayer rGO obtained distances dfrom00X from the graphites oxidized using method B. The same observation was made for the values of interlayer distances d00X D G the XRD studies.frommethod The the observed XRD A studies.showed influence The the observed highest of the influence rGO amount method of the of on rGOstructural the method I /I onratiodefects, the wa ID/Is Gwhileratio the lowest were for statistically significantwas statistically and was significant confirmed and by was the confirmed ANOVA. by the For ANOVA. the I2D/I ForD+D' theratio, I2D /I thisD+D’ ratio, influence decreased,this influence and due decreased, to the andsignificant due to the variability significant of variability the results, of the it results, became it became statistically insignificantstatistically (Fig insignificanture 12a,b (Figure). 12a,b).

FigureFigure 12. Box 12. Boxplot plotss of ( ofa) (IaD)I/IDG /IandG and (b) (Ib2D)I/I2DD+D’/I D+D’ratioratioss as function as functionss of ofthe the applied applied method. method.

For materials obtainedFor materials from obtained flake graphite, from flake as graphite,the graphite as the layers' graphite size layers’ in the size graphite in the graphite precursor increased, the ID/IG ratio decreased and the structural defects in their structures precursor increased, the ID/IG ratio decreased and the structural defects in their structures also decreased. This was confirmed by the highest share of C sp2 being observed in the also decreased. This was confirmed by the highest share of C sp2 being observed in the reduced graphene oxides obtained from flake graphite. The ANOVA also confirmed this reduced grapheneobservation. oxides obtained The precursor’s from flake effect graphite. on the carbon The contentANOVA with also C inconfirmed sp2 hybridization this was observation. Thestatistically precursor's significant effect on (Figure the carbon 13). content with C in sp2 hybridization was statistically significant (Figure 13).

Figure 13. Box plot of C1sp2 hybridization as a function of the applied precursor material.

4. Discussion This statistical analysis allowed the following conclusions to be made for graphite oxide (GO):  Based on the HCA method, it was determined that the graphite oxides with high and homogeneous oxygen contents, interlayer distances d001, and epoxy and hydroxyl group contents were obtained using methods A and D;  Statistical analysis confirmed that the oxygen content in the graphite oxides was influenced by the oxidation method, while the graphite precursor had no significant influence on this;  The ANOVA confirmed that the GOs obtained using method A contained the greatest interlayer distances d001 and the smallest dimensions for the La graphite layers;

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method B. The same observation was made for the values of interlayer distances d00X from the XRD studies. The observed influence of the rGO method on the ID/IG ratio was statistically significant and was confirmed by the ANOVA. For the I2D/ID+D' ratio, this influence decreased, and due to the significant variability of the results, it became statistically insignificant (Figure 12a,b).

Figure 12. Box plots of (a) ID/IG and (b) I2D/ID+D’ ratios as functions of the applied method.

For materials obtained from flake graphite, as the graphite layers' size in the graphite precursor increased, the ID/IG ratio decreased and the structural defects in their structures also decreased. This was confirmed by the highest share of C sp2 being observed in the reduced graphene oxides obtained from flake graphite. The ANOVA also confirmed this Materials 2021, 14, 769 observation. The precursor's effect on the carbon content with C in sp122 of hybridization 14 was statistically significant (Figure 13).

2 FigureFigure 13. 13.Box Box plot plot of C1sp of C1sphybridization2 hybridization as a function as a of function the applied of precursorthe applied material. precursor material. 4. Discussion 4. DiscussionThis statistical analysis allowed the following conclusions to be made for graphite oxide (GO):This statistical analysis allowed the following conclusions to be made for graphite •oxideBased (GO): on the HCA method, it was determined that the graphite oxides with high and homogeneous oxygen contents, interlayer distances d001, and epoxy and hydroxyl  groupBased contents on the were HCA obtained method, using it methods was determined A and D; that the graphite oxides with high and • Statisticalhomogeneous analysis confirmed oxygen content that thes oxygen, interlayer content distance in the graphites d001, and oxides epoxy was and hydroxyl influencedgroup contents by the oxidation were obtained method, while using the methods graphite precursor A and D; had no significant influence on this; • TheStatistical ANOVA confirmed analysis that confirmed the GOs obtained that the using oxygen method content A contained in the the greatest graphite oxides was interlayerinfluenced distances by the d001 oxidationand the smallest method, dimensions while forthe the graphite La graphite precursor layers; had no significant • Theinfluence ANOVA methodon this showed; the statistical significance of the influence of the graphite  oxidationThe ANOVA method on confirmed the degree of that oxidation the ofGO GO.s obtained Method C, characterized using method by hav- A contained the ing the mildest oxidation conditions, resulted in GO samples with the least disturbed structure,greatest and interlayer thus with the distances largest share d001 of and bonds the with smallest sp2 hybridization. dimensions for the La graphite Thelayers; influence of the graphite precursors (scaly graphite GS, flake graphite GF, and synthetic graphite GE) was statistically insignificant on the change in the ID/IG ratio obtained for the graphite oxides. Research confirmed that method C had the weakest oxidizing potential. Specific applications will require a GO with specific properties. The obtained results suggest the focus should be on the process variables of the graphite oxidation method, because this has a statistically significant impact on the prepared material’s properties. This statistical study allowed the following conclusions to be made for the reduced graphene oxide (rGO): • The used cluster analysis showed the most important variables, which characterize the degree of oxidation. It was confirmed with a high probability that an increase in the C(sp2) share in rGO indicates a partial reconstruction of the graphite structure; • The statistical analysis showed the influence of the precursors (GS, GF) on the properties of the obtained reduced graphene oxides (the ANOVA analysis confirmed that the type of precursor influences the oxygen content and degree of reduction after thermal exfoliation–reduction). It is worth mentioning that there is also an influence on the ID/IG ratio and number of structure defects; • Moreover, the used ANOVA analysis showed statistically significant differences between the tested oxidation methods and the interlayer distance values d00X; • The largest specific surfaces for rGO were obtained using method D. This type of reduced graphene oxide will be better suited for further technological processes for graphene production; Materials 2021, 14, 769 13 of 14

• On the other hand, rGO particles characterized by a higher degree of oxidation seem to be more appropriate for applications in gas sensors (especially in hydrogen sensors working in air atmosphere). Apart from their cognitive value, the analyses presented above are essential for developing optimal technologies and may also have signiﬁcant application value.

5. Conclusions The results of our research and analyses using statistical methods confirmed the existence of relationships between the graphite precursor and used oxidation method related to the physicochemical properties obtained for GO and rGO. In summary, the statistical evaluation of the results has allowed the development of preliminary criteria for selecting a graphite precursor for the production (using the thermal exfoliation–reduction method) of graphite material with the required texture and structural parameters. The obtained results suggest the choice of the production technology for reduced graphene oxide to obtain the desired graphene flakes. The presented research suggests that after appropriate admixture or modification, the elaborated graphite oxide and reduced graphene oxide materials can be used in sensors of selected gases as sensing elements. The combination of reduced graphene oxides and other materials can increase the selected gas sensitivity and decrease the sensors’ operating temperature, as shown in our previous studies [24,33]. The utilitarian goal of the research presented in this paper is the use of reduced graphene oxide in hydrogen sensors with a fast reaction time (a few seconds), with great sensitivity, and working at room temperature.

Supplementary Materials: The following are available online at https://www.mdpi.com/1996-194 4/14/4/769/s1: Figure S1: The schematic presentation of normalization of all variables, Figure S2: Raman spectra of graphite oxides, Figure S3: Raman spectra of graphene oxides, Figure S4: XRD spectra of graphite oxides, Figure S5: XRD spectra of graphene oxides. Author Contributions: Conceptualization, R.M., S.D. and M.S.; methodology, R.M., S.D. and M.S.; formal analysis, T.P. ans Ł.D.; investigation, R.M., S.D. and M.S.; data curation, S.D.; writing—original draft preparation, R.M., S.D., T.P., M.S., and Ł.D.; writing—review and editing, R.M., S.D., T.P., M.S., and Ł.D.; visualization, R.M., S.D., M.S.; supervision, T.P., S.D. All authors have read and agreed to the published version of the manuscript. Funding: This work was partially financed by: Statutory Research for Department of Optoelectronics, Silesian University of Technology (BKM-759/RE4/2020); A statutory activity subsidy from the Polish Ministry of Science and Higher Education for the Institute for Chemical Processing of Coal (11.15.024). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Conflicts of Interest: The authors declare no conflict of interest.

References 1. Singh, V.; Joung, D.; Zhai, L.; Das, S.; Khondaker, S.I.; Deal, S. Graphene based materials: Past, present and future. Prog. Mater. Sci. 2011, 56, 1178–1271. [CrossRef] 2. Inagaki, M.; Kim, Y.A.; Endo, M. Graphene: Preparation and structural perfection. J. Mater. Chem. 2011, 21, 3280–3294. [CrossRef] 3. Brodie, B.C. Sur le poids atomique du graphite (On the atomic weight of graphite). Ann. Chim. Phys. 1960, 59, 466–472. 4. Staudenmaier, L. Verfahren zur darstellung der graphitsäure. Ber. Dtsch. Chem. Ges. 1898, 31, 1481–1487. [CrossRef] 5. Hofmann, U.; Holst, R. Über die Säurenatur und die Methylierung von Graphitoxyd. Ber. Dtsch. Chem. Ges. 1939, 72, 754–771. [CrossRef] 6. Hummers, W.S. Preparation of graphitic acid. U.S. Patent No. 2,798,878, 9 July 1954. 7. Dimiev, A.M.; Eigler, S. Graphene Oxide: Fundamentals and Applications, 1st ed.; John Wiley & Sons: Chichester, West Sussex, UK, 2016; pp. 1–439. 8. Chua, C.K.; Pumera, M. Chemical reduction of graphene oxide: A synthetic chemistry viewpoint. Chem. Soc. Rev. 2014, 43, 291–312. [CrossRef][PubMed] Materials 2021, 14, 769 14 of 14

9. Marcano, D.C.; Kosynkin, D.V.; Berlin, J.M.; Sinitskii, A.; Sun, Z.; Slesarev, A.; Alemany, L.B.; Lu, W.; Tour, J.M. Improved synthesis of graphene oxide. ACS Nano 2010, 4, 4806–4814. [CrossRef][PubMed] 10. Sun, L.; Fugetsu, B. Mass production of graphene oxide from expanded graphite. Mater. Lett. 2013, 109, 207–210. [CrossRef] 11. Botas, C.; Alvarez, P.; Blanco, C.; Santamarıa, R.; Granda, M.; Ares, P.; Rodriguez-Reinoso, F.; Menendez, R. The effect of the parent graphite on the structure of graphene oxide. Carbon 2012, 50, 275–282. [CrossRef] 12. Shao, G.; Lu, Y.; Wu, F.; Yang, C.; Zeng, F.; Wu, Q. Graphene oxide: The mechanisms of oxidation and exfoliation. J. Mater. Sci. 2012, 47, 4400–4409. [CrossRef] 13. Luo, D.; Zhang, G.; Liu, J.; Sun, X. Evaluation criteria for reduced graphene oxide. J. Phys. Chem. 2011, 115, 11327–11335. [CrossRef] 14. Muzyka, R.; Drewniak, S.; Pustelny, T.; Chrubasik, M.; Gryglewicz, G. Characterization of graphite oxide and reduced graphene oxide obtained from different graphite precursors and oxidised by different methods using Raman spectroscopy. Materials 2018, 7, 1050. 15. McAllister, M.J.; Li, J.L.; Adamson, D.H.; Schniepp, H.C.; Abdala, A.A.; Liu, J.; Herrera-Alonso, M.; Milius, D.L.; Car, R.; Prud’homme, R.K.; et al. Single sheet functionalised graphene by oxidation and thermal expansion of graphite. Chem. Mater. 2007, 19, 4396–4404. [CrossRef] 16. Zhang, C.; Lv, W.; Xie, X.; Tang, D.; Liu, C.; Yang, Q.-H. Towards low temperature thermal exfoliation of graphite oxide for graphene production. Carbon 2013, 62, 1–24. [CrossRef] 17. Botas, C.; Perez-Mas, A.M.; Alvarez, P.; Santamaria, R.; Granda, M.; Blanco, C.; Menendez, R. Optimization of the size and yield of graphene oxide sheets in the exfoliation step. Carbon 2013, 63, 576–578. [CrossRef] 18. Deemer, E.M.; Paul, P.K.; Manciu, F.S.; Botez, C.E.; Hodges, D.R.; Landis, Z.; Akter, T.; Castro, E.; Chianelli, R.R. Consequence of oxidation method on graphene oxide produced with different size graphite precursors. Mater. Sci. Eng. B 2017, 224, 150–157. [CrossRef] 19. Muzyka, R. Influence of Graphitic Precursor on the Composition, Morphology and Structure of Thermally Reduced Graphene Oxides. Ph.D. Thesis, Wroclaw University of Science and Technology, Wroclaw, Poland, 1–28 February 2018. 20. Botas, C.; Alvarez, P.; Blanco, C.; Santamaria, R.; Granda, M.; Gutierrez, M.D.; Rodriguez-Reinoso, F.; Menendez, R. Critical temperatures in the synthesis of graphene-like materials by thermal exfoliation-reduction of graphite oxide. Carbon 2013, 52, 476–485. [CrossRef] 21. Schniepp, H.C.; Li, J.L.; McAllister, M.J.; Sai, H.; Herrera-Alonso, M.; Adamson, D.H.; Prud’homme, R.K.; Car, R.; Saville, D.A.; Aksay, I.A. Functionalized single graphene sheets derived from splitting graphite oxide. J. Phys. Chem. B 2006, 110, 8535–8539. [CrossRef] 22. Drewniak, S.E.; Pustelny, T.P.; Muzyka, R.; Plis, A. Studies of physicochemical properties of graphite oxide and thermally exfoliated/reduced graphene oxide. Polish J. Chem. Technol. 2015, 17, 109–114. [CrossRef] 23. Drewniak, S.; Muzyka, R.; Drewniak, Ł. The structure of thermally reduced graphene oxide. Photonics Lett. Poland 2020, 12, 52–54. [CrossRef] 24. Drewniak, S.; Muzyka, R.; Stolarczyk, A.; Pustelny, T.; Kotyczka-Moranska, M.; Setkiewicz, M. Studies of reduced graphene oxide and graphite oxide in the aspect of their possible application in gas sensors. Sensors 2016, 16, 103. [CrossRef] 25. Davies, M.P.; De Biasi, V.; Perrett, D. Approaches to the rational design of molecularly imprinted polymers. Anal. Chim. Acta 2004, 504, 7–14. [CrossRef] 26. Navarro-Villoslada, F.; San Vicente, B.; Moreno-Bondi, M.C. Application of multivariate analysis to the screening of molecularly imprinted polymers for bisphenol A. Anal. Chim. Acta 2004, 504, 149–162. [CrossRef] 27. Potyrailo, R.A. Polymeric sensor materials: Toward an alliance of combinatorial and rational design tools? Angew. Chem. Int. Ed. Engl. 2006, 45, 702–723. [CrossRef] 28. Potyrailo, R.A.; Mirsky, V.M. Combinatorial Methods for Chemical and Biological Sensors, 1st ed.; Springer: New York, NY, USA, 2009. 29. Steinke, J.; Sherrington, D.C.; Dukin, I.R. Imprinting of synthetic polymers using molecular templates. Adv. Polym. Sci. 1995, 123, 81–125. 30. Abollino, O.; Aceto, M.; Malandrino, M.; Mentasti, E.; Sarzanini, E.; Barberis, R. Distribution and mobility of metals in contaminated sites. Chemometric investigation of pollutant profiles. Environ. Pollut. 2002, 119, 177–193. [CrossRef] 31. Abollino, O.; Aceto, M.; Malandrino, M.; Mentasti, E.; Sarzanini, C.; Petrella, F. Heavy metals in agricultural soils from Piedmont, Italy. Distribution, speciation and chemometric data treatment. Chemosphere 2002, 49, 545–557. [CrossRef] 32. Sajdak, M.; Stelmach, S.; Kotyczka-Morańska,M.; Plis, A. Application of chemometric methods to evaluate the origin of solid fuels subjected to thermal conversion. J. Anal. Appl. Pyrolysis 2015, 113, 65–72. [CrossRef] 33. Pérez, G.; Valiente, M. Determination of pollution trends in an abandoned mining site by application of a multivariate statistical analysis to heavy metals fractionation using SM&T–SES. J. Environ. Monitor. 2005, 7, 29–36.