Micro-Raman Spectroscopy Study of 32 Kinds of Chinese Coals

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Micro-Raman Spectroscopy Study of 32 Kinds of Chinese Coals: Second-Order Raman Spectrum and Its Correlations with Coal Properties Jun Xu, Hao Tang, Sheng Su,* Jiawei Liu, Hengda Han, Liangping Zhang, Kai Xu, Yi Wang, Song Hu, Yingbiao Zhou, and Jun Xiang* State Key Laboratory of Coal Combustion, Huazhong University of Science and Technology, 430074 Wuhan, Hubei China ABSTRACT: Coal property and structures of 32 kinds of Chinese coals were investigated from the insights of second-order Raman spectrum using micro-Raman spectroscopy. A new deconvolution method for the second-order Raman spectrum of coal has been established, and the spectrum from 2100 to 3400 cm−1 was curve-fitted by eight Gaussian bands successfully. The results indicate that the bands at 3060 and 2810 cm−1 are sensitive to the volatiles content in coal and the bands at 2925, 2670, and 2480 cm−1 are related to the more ordered structures of coal. Reasonable correlations between the second-order Raman bands area ratios and coal property parameters have been found, and an effectively comprehensive method for evaluating the coal property based on a second-order Raman spectrum has been built. The results reveal that the C−H and amorphous carbon structures increase with the increase of volatile content in the coal but have no obvious relationship with the fixed carbon content. Besides, the order degree of coal structure has a good positive correlation with the ratio of fixed carbon to volatiles content in the coal. This study demonstrates that the second-order Raman spectrum can reveal useful structure information on coal and provide a new approach for evaluating coal properties. band), and 1500 cm−1 (D4 band) were attributed in the firstorder Raman spectrum.16−18 Sheng et al.16 and Sadezky et al.17 summarized the assignment of these bands and used these five bands to deconvolute the first-order Raman spectrum of highly ordered carbon materials successfully. For poorly ordered carbon materials, especially for coal or low rank coal char, more bands in the first-order Raman spectrum were attributed.29−32 Li et al.31 proposed that ten Gaussian bands were more suitable to deconvolute the first-order Raman spectrum of coal or low rank coal char as there were actually no significant graphitic crystallites but a wide variety of amorphous structures and cross-linking structures. In the second-order Raman spectrum of the highly ordered carbon materials, the bands were generally attributed to the overtone or combination of the bands in the first-order Raman spectrum.21−25 A band located at about 2670 cm−1 (2D band) was attributed to the overtone of D1 band at around 1350 cm−1.23−26 A band defined as the addition of D1 band and G band appeared at around 2925 cm−1 and an overtone band of D2 band was also found at around 3240 cm−1.23−25 In some studies, a minor band at about 2450 cm−1 was also found.17,21,22,33,34 For poorly ordered carbon materials, Péron et al.35 found that several bands involving C− H stretching vibration regarding the methyl and methylene appeared at around 2845 cm−1 in the second-order Raman spectrum of the polycyclic aromatic hydrocarbon (PAH). Colangeli et al.36 found C−H stretching vibration of aromatic appeared at about 3060 cm−1 in the second-order Raman spectrum of PAH. In addition, Wang et al.23 studied the second-order Raman spectrum of low rank coal char. They

1. INTRODUCTION Nowadays, coal is the main source of energy, and it will remain in a very important position in the energy mix in the foreseeable future, especially in developing countries such as China.1−3 Coal is known to be a highly heterogeneous carbon material with complex structures.1−7 In order to facilitate the utilization, commercially and analytically, coal is characterized by coal property parameters based on proximate and ultimate analysis (such as volatiles, fixed carbon, ash, moisture, carbon and hydrogen content, etc.), which can greatly influence the coal conversion processes including pyrolysis, gasification, liquefaction, and combustion since the rate and path of coal conversion can vary drastically with these property parameters.1−5 Qualitative/quantitative characterization of the detailed structures related to these property parameters and setting up the correlations between coal property parameters and coal structures are always of interest to researchers.4−6,8−11 An efficient method for evaluating coal properties can provide a potential way to analyze coal online, which can remarkably improve the production efficiency and lower the cost of production.10 Micro-Raman spectroscopy has been demonstrated to be a useful tool to characterize the microstructure of carbon materials due to its high-efficiency, high-precision, and nondestructive nature.9−20 In the Raman spectrum of carbon materials, there are mainly two regions. One is between 800 and 1800 cm−1 (first-order region), and another one is between 2100 and 3400 cm−1 (second-order region).17,21−26 In the firstorder Raman spectrum of the single crystals of graphite, just one band at about 1580 cm−1 (G band) was found and defined as the E22g mode of graphite.16−20,27,28 With the existence of defects and heteroatoms in the graphite crystals, four other bands at about 1350 (D1 band), 1620 (D2 band), 1150 (D3 © XXXX American Chemical Society

Received: April 7, 2017 Revised: June 12, 2017 Published: June 25, 2017 A

DOI: 10.1021/acs.energyfuels.7b00990 Energy Fuels XXXX, XXX, XXX−XXX

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Energy & Fuels proposed that a band located at about 2350 cm−1 could reflect the cross-linking density of the char and more bands should be attributed to the second-order Raman spectrum of the poorly ordered carbon materials. Unfortunately, few studies have been done to systematically investigate the second-order Raman spectrum of the raw coals, especially no detail deconvolution of the second-order Raman spectrum for the coal has been proposed. In the past decades, Raman spectroscopy was widely applied in studying coal structures and properties.9,11−15,37−41 Among these studies, the first-order Raman spectrum was mainly applied and analyzed. Some studies investigated the first-order Raman spectra of the coals with different ranks and found there were correlations between the full width at half-maximum (fwhm) of G and D1 bands with the vitrinite reflectance (Rf) of the coal.14,37,38,40−42 Generally, the fwhm of the G and D1 bands would decrease with the increase of Rf, revealing these two Raman parameters can be used as maturity indicators in coal petrography. However, the reflectance analysis of the coals is usually time-consuming and the correlation between the Rf and volatile matter content in the coal is not always good.4 On the contrary, the property parameters of proximate and ultimate analysis can be obtained more easily and they are widely used to reflect the coal property during thermal conversion processes.2,4 Some studies also have been done to try to set up the correlations between the first-order Raman spectral parameters and the coal property parameters based on proximate and ultimate analysis.9,12,15,39,43,44 Kwiecinska et al.43 and Marques et al.9 studied the correlations between the firstorder Raman spectral parameters and property parameters of high rank coals and graphite. They found that the G band fwhm would increase with the increase of hydrogen and carbon atom ratio in the coal. Morga et al.15 found that the G band fwhm and the ratio of the G band area to the total Raman band area (AG/AAll) would increase with increase of the volatiles content on a dry ash-free basis (Vdaf) of the coal. Konchits et al.44 found the intensity ratio of D1 band and G band (ID1/IG) would decrease with the increase of Vdaf in the coal, and Ulyanova et al.12 found ID1/IG would increase with the increase of fixed carbon contents in air-dry basis of coal. Baysal et al.39 also used Raman spectroscopy to study the structures of the western Anatolia coals, but the results showed that there were no reasonable correlations between the first-order Raman spectral parameters and coal property parameters. In these literature sources, some tendencies of the correlations between first-order Raman spectral parameters and coal property parameters were revealed, but the relationships were not good enough; few comprehensive correlations between Raman spectral parameters and coal property parameters have been set up especially based on a large number of samples. Moreover, the secondorder Raman spectra of the coals have not been resolved, and half of the useful data was discarded. Actually, with the development of Raman spectrum analysis techniques, the second-order Raman spectrum attracted more and more attentions. Some works have been done to resolve the second-order Raman spectroscopy to further characterize the carbon materials structures.21−25,28 Zaida et al.21 found that there was a better linear correlation between the bandwidth of the 2940 cm−1 band and the reactivity of the cellulose chars obtained at high temperature than that between the first-order Raman spectral parameters and reactivity. Lee et al.24 applied the second-order Raman spectrum to study the crystallinity changes under heat treatment and found that the second-order

Raman spectrum was effective to clearly quantify the difference in crystallinity. Thomsen et al.25 also indicated that the secondorder Raman spectrum was more sensitive to the change of graphite ordering than the first-order Raman spectrum. Antunes et al.22 studied the second-order Raman spectra of carbon nanotubes and indicated that high quality second-order Raman spectrum can be obtained by using the visible laser, and the 2D band in second-order Raman spectrum was more sensitive to the three-dimensional graphite. López-Honorato28 found that second-order Raman bands could be used to quantify the texture of pyrolytic carbon. These studies indicate that the bands in the second-order Raman spectrum can give additional and useful structure information to the first-order Raman spectra of carbon materials. However, all these studies mainly focus on the highly ordered carbon materials, and the second-order Raman spectrum of the poorly ordered carbon materials especially coal is rarely studied. Moreover, the secondorder Raman spectra of highly ordered carbon materials are simple and can be deconvoluted into three or four bands reasonably.17,21,22 But it is no longer appropriate for the deconvolution of the second-order Raman spectrum of the coal as the coals are poorly ordered and more bands would exist.23 It has been demonstrated that C−H and amorphous carbon structures widely exist in the raw coal and can greatly determine the volatiles content in the coal.45,46 The C−H and amorphous carbon structures are Raman active in the first-order Raman region,20 but the D1 and G band are too strong to cover up the bands of them.16,17,31 It thus gives a big barrier to accurately obtain the structures parameters of the C−H and amorphous carbon structures through the first-order Raman spectrum. Fortunately, some studies showed that C−H structures were also Raman active and had strong bands in the wavenumber between 2800 and 3100 cm −1 in the second-order region.23,35,36,47 Besides, some bands in the second-order Raman spectra are the overtones of the bands in the firstorder region,21−23 and thus, the distance between some bands in the second-order region would be larger than that in the firstorder region, which can be beneficial for more bands to expose in the second-order region and also the deconvolution of the spectrum. Therefore, it is meaningful to further resolve the second-order Raman spectrum of the coal and set up the correlations between the second-order Raman spectral parameters and the coal property parameters, which may give a good way to characterize the coal property and coal structures effectively. The purpose of this study was to establish a new deconvolution method of the second-order Raman spectrum of the raw coals and try to set up the correlations between the second-order Raman spectral parameters and coal property parameters, proposing a new assessment method of coal property and coal structure based on the second-order Raman spectrum.

2. EXPERIMENTS AND METHOD 2.1. Coal Characterization. Thirty-two kinds of Chinese coals ranging from anthracite to lignite were studied. A kind of graphite (spectrum pure) and a typical kind of coal ash were also analyzed for comparison. Twenty-seven kinds of coals are from different coal basins in China that are Leiyang (LY), Jingping 1 (JP1), Xingqiao (XQ), Jingping 2 (JP2), Zhicheng (ZC), Xiwujiang (XWJ), Sicuan (SC), Maanshan (MAS), Shanxi 2 (SX2), Xiangmei (XM), Liupanshui (LPS), Pingdingshan (PDS), Shanxi 1 (SX1), Xingaoshan (XGS), Hongshaquan (HSQ), Bingxin (BX), Wucaiwan (WCW), Huolinhe (HLH), Nantun (NT), Honghe (HH), Huangning (HN), JiangjunB


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Figure 1. Distribution of the coal basins selected for this study in a map. miao (JJM), Jiyuan 2 (J2), Shengli (SL), Cangzhou (CZ), Shenfu (SF), and Xiaolongtan (XLT). The location of the coal basins are shown in Figure 1, and the longitude and latitude details and geological age are also shown in Table 1. Five coals named as MeiKu 1−5 are selected from the coal bunker of State Key Laboratory of Coal Combustion to obtain more coal samples with different coal properties though their coal basins are uncertain. Before analysis, all the raw coals were ground and sieved to obtain the samples with a particle size between 74 and 105 μm. The ultimate analysis of the coal sample was obtained in a Vario MAX (Elementar Analysensysteme GmbH), and the proximate analysis was tested following the Chinese National Standard GB212-2001.16 The main property parameters of the coal samples are shown in Table 1. The Raman spectra of the coals were obtained in a micro-Raman spectrometer (Jobin Yvon Lab RAM HR800), which was equipped with an Nd:YAG laser (excitation line λ0 = 532 nm). A 50× objective lens of an Olympus BX41 optical microscope was employed to focus the laser beam on the sample surface, and the beam diameter on the sample surface was about 2 μm. It is known that the Raman spectrum intensity is proportional to the laser power reaching on the sample surface. A higher laser power is beneficial for the spectrum quality, but it would induce higher thermal emission and thermal degradation of the coal.31 Therefore, different laser power was applied before experiments to obtain a best experiments condition. It was found that a suitable spectrum can be obtained and no significant thermal degradation was observed on the sample surface through the objective lens for most of the coals when the laser power was controlled at about 5 mW. In addition, in order to reduce the experiment system error, the Raman spectrometer was calibrated before measurement using standard silicon (the band position is at 520 cm−1). The spectra were all recorded in the range of 800−3400 cm−1, and the resolution of the spectrum was better than 1 cm−1. The acquisition time for the Raman signal was 10 s for each test, and about 10−15 grains were randomly chosen and tested for each coal sample to obtain the Raman spectral parameters statistically. 2.2. Second-Order Raman Spectrum Characteristics and Deconvolution Method. Figure 2 shows the second-order Raman spectra of the graphite and coals with typical ranks. All the spectra were first baseline corrected and normalized to the band of the highest intensity. The second-order Raman spectrum of the typical coal ash was not shown in the figure as no true band was found and could not

be normalized in this study. For the graphite, as shown in Figure 2, it can be seen there are mainly three bands located at about 2480, 2670, and 3240 cm−1 in the second-order Raman spectrum. No obvious overlap exists between these bands, indicating the second-order Raman spectrum of graphite is simple, which is in accord with the results of the references.17,22 But for the coals, it can be seen that the second-order Raman spectra are complex and they are significantly different from that of the graphite. As shown in Figure 2, there are another four strong bands located at about 2810, 2925, 3060, and 3180 cm−1 and two minor bands located at about 2300 and 3320 cm−1. It can be seen that there are overlaps between the bands in the secondorder Raman spectra of the coal, but the intensity of these bands is not significantly different from each other. In other words, the bands can be distinguished from each other, which is different from the situation in the first-order region where two strong bands (G band and D1 band) mainly exist and some bands are overlapped and hard to identify.16,17 In addition, no obvious band shift was observed for all the bands with increasing the coal rank. In order to obtain more detail and semiquantitative structure information from the Raman spectra of carbon materials, further deconvolution of the spectra is needed,16,17,31 and also the deconvolution of the second-order Raman spectrum was carried out. In this study, all the second-order Raman spectra were curve-fitted by eight bands appearing in the spectra of the coals that are shown in Figure 2. Before curve-fitting, a linear baseline was first subtracted from the spectra. During the curve-fitting, the Gaussian curves were applied and the band position was fixed while the band widths were restrained to different maximum limits. The R2 value was calculated for each curve-fitting to evaluate the accuracy of a fit. The results showed that R2 was all higher than 0.995, indicating a successful curve-fitting can be achieved using this method. Figure 3 shows an example of the curve-fitting for a typical Raman spectrum of the raw coal, and the positions and assignments of the eight bands are summarized in Table 2. As shown in Figure 3, the 2D band is a main band with strong intensity, and it is the overtone of the D1 band located at about 1350 cm−1 in the first-order region.21−23 For the highly ordered carbon materials, the 2D band is believed to be related to the number of graphene layers and does not reflect any disorder or defect structure of the graphite crystal as the D1 band reflects.22,23 But for the poorly C


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Energy & Fuels Table 1. Characteristics of the Coal Samples Selected for This Studya name

long (E)

lat (N)

age

Mad %

Vad %

FCad %

Aad %

FCdaf %

FC/V

C/H

LY JP1 XQ JP2 ZC XWJ SC MAS SX2 MK2 XM LPS PDS SX1 MK1 MK5 XGS MK4 HSQ BX WCW HLH MK3 NT HH HL JJM J2 SL CZ SF XLT graphite ash

112.9818 112.9427 116.3033 112.7378 111.4513 112.8864 104.3842 111.3189 113.1873 uncertain 112.4023 105.3786 113.2777 112.1861 uncertain uncertain 112.8855 uncertain 90.3733 108.0542 88.8650 119.7644 uncertain 116.8955 116.8126 108.9300 89.9809 116.6824 116.0841 107.2378 110.2800 103.1500

26.3490 36.0053 33.8443 35.6085 30.1373 35.4549 27.8534 27.6921 37.9304 uncertain 28.2480 26.0575 33.7805 39.4165 uncertain uncertain 40.0167 uncertain 44.5454 35.0737 44.7868 45.4688 uncertain 35.4029 35.4028 35.6651 44.6064 35.3537 44.0505 36.6358 38.3950 23.3500

Upper Permian Lower Permian Lower Permian Lower Permian Lower Permian Lower Permian Upper Permian Upper Permian Carboniferous−Triassic uncertain Upper Permian Upper Permian Carboniferous−Permian Carboniferous−Permian uncertain uncertain Lower Jurassic uncertain Middle Jurassic Middle Jurassic Middle Jurassic Jurassic−Cretaceous uncertain Carboniferous−Permian Carboniferous−Permian Middle Jurassic Middle Jurassic Carboniferous−Permian Lower Cretaceous Triassic−Jurassic Upper Jurassic Neogene period

1.28 4.48 1.83 1.75 1.61 2.84 1.39 2.59 2.06 3.29 1.62 4.12 1.50 1.64 12.76 1.90 13.50 15.83 14.34 3.17 12.47 26.46 9.61 3.01 3.97 3.07 4.98 2.68 10.53 7.02 8.77 22.10

4.85 5.99 7.53 9.72 10.07 10.91 11.81 12.70 17.80 18.88 19.05 21.69 22.74 22.86 22.94 23.66 24.24 24.87 24.91 25.04 25.78 27.28 27.71 28.27 28.61 28.92 29.59 30.02 30.26 30.37 32.25 34.93

62.02 68.55 67.49 68.13 57.94 32.18 67.78 66.59 33.95 65.28 48.88 47.97 47.40 47.85 42.36 49.68 41.52 35.92 53.91 57.06 57.11 29.03 33.73 43.08 46.10 51.39 61.69 41.43 55.52 46.87 54.38 35.47 100

31.85 20.98 23.15 20.40 30.38 54.07 19.02 18.12 46.19 12.55 30.45 26.22 28.36 27.65 21.94 24.76 20.74 23.38 6.84 14.73 4.64 17.23 28.95 25.64 21.32 16.62 3.74 25.87 3.69 15.74 4.60 7.50

92.75 91.96 89.96 87.51 85.20 74.68 85.16 83.98 65.60 77.56 71.95 68.86 67.58 67.67 64.87 67.74 63.14 59.09 68.40 69.50 68.90 51.55 54.90 60.38 61.71 63.99 67.58 57.98 64.72 60.68 62.77 50.38

12.79 11.44 8.96 7.01 5.76 2.95 5.74 5.24 1.91 3.46 2.57 2.21 2.08 2.09 1.85 2.10 1.71 1.44 2.16 2.28 2.22 1.06 1.22 1.52 1.61 1.78 2.08 1.38 1.83 1.54 1.69 1.02

2.43 1.99 1.70 1.86 1.38 1.41 1.60 1.73 1.40 1.55 1.66 1.21 1.28 1.29 1.22 1.31 1.21 1.22 1.19 1.48 1.28 0.88 0.98 1.24 1.26 1.36 1.47 1.17 1.39 1.22 1.22 0.85

100

Long: longitude. Lat: latitude. Mad: moisture content in air-dry basis. Vad: volatiles content in air-dry basis. FCad: fixed carbon content in air-dry basis. Aad: ash content in air-dry basis. FCdaf: fixed carbon content in dry ash-free basis. FC/V: the ratio of fixed carbon content to the volatiles content. C/H: carbon and hydrogen atom ratio. The longitude and latitude details and age of the coal samples selected in this study are from the geological survey of China. a

Figure 3. Example of curve-fitting for the second-order Raman spectrum. Figure 2. Second-order Raman spectra for typical ranks of coal. ordered carbon materials, the 2D band is still thought to be from the same vibration mode of the D1 band as there is no significant graphite crystal.23 For the low rank coal char, the D1 band is mainly attributed

to the C−C structures between aromatic rings and the aromatic rings system with not less than six rings.29−31 Therefore, the 2D band can be D


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Energy & Fuels Table 2. Summary of the Band Assignments band name

band position (cm−1)

description

refs

(2G)L 2G (2G)R D+G (2D)L 2D (2D)R 2S

3320 3180 3060 2925 2810 2670 2480 2300

overtone of the band at 1670 cm−1, carbonyl group CO overtone of the G band at 1590 cm−1, aromatic rings aryl C−H stretch vibration combination of D1 band and G band, large aromatic rings system C−H stretch of methyl and methylene, amorphous carbon structures overtone of the D1 band, C−C between aromatic rings, large aromatic rings system large aromatic rings system overtone of the band at 1150 cm−1, CaromaticCalkyl, CO structures

29, 31; this work 23, 24 23, 36, 47; this work 21−24 23, 35, 47; this work 21−24 this work 29, 31; this work

Figure 4. Correlations between the second-order Raman spectral parameters and volatiles content on an air-dry basis. mainly assigned to the aromatic rings especially for large aromatic rings system in this study. As another strong band, the D + G band is the combination of the D1 band and G band in the first-order region.22−24 It has been demonstrated that the D + G band can bring the similar information as the D1 band.22 So the D + G band can be also attributed to the relatively large aromatic rings systems in the coal. The other two bands, (2G)R and (2D)L, are generally not found in graphite-like materials. It has been found that these two bands are associated with the C−H stretch vibration in PAH. The (2G)R band is attributed to the C−H stretching vibration of aromatics, and the (2D)L band is more related to the C−H stretching vibration of the methyl and methylene.23,35,36,47 The attribution of the (2D)R band at about 2480 cm−1 is hard to interpret since its origin is still controversial.17,21,33,34 Some researchers attribute it to the overtone of a Raman inactive graphitic lattice vibration mode at 1220 cm−1 in the first-order region.17,33 Other researchers attribute it to the combination of the 1100 cm−1 and D1 band.21,34 Our results in this study cannot confirm the vibration mode of this band but suggest that it is more related to

the more ordered structures in the coal such as large aromatic rings, which will be discussed below. The other three bands (2G)L, 2G, and 2S bands are mainly attributed to the overtone of the corresponding bands at about 1670, 1590, and 1150 cm−1 in the first-order region.29,31 Their intensity changes little for different coals, and thus it can be said that they are less sensitive to the change of the coal structures. After curve-fitting, the total second-order Raman spectrum area (A2) was calculated as the sum of the area for the eight curve-fitted bands. The ratios of the band area to the A2 were calculated to reflect the relative intensity of the band since the band area can not only take into account the band height but also the bandwidth.16 The main average Raman spectral parameters were correlated with the coal property parameters to obtain a relationship between the coal structures and properties. E


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Figure 5. Correlations between the second-order Raman spectral parameters and fixed carbon content on an air-dry basis.

3. RESULTS AND DISCUSSION 3.1. Correlations between Volatiles Content and Second-Order Raman Band Area Ratios. Figure 4 shows several correlations between the second-order Raman band area ratios and the volatiles content of coal on an air-dry basis (Vad). In Figure 4a and b, it can be seen that the ratio of the (2G)R band area to A2 (A(2G)R/A2) and the ratio of (2D)L band area to A2 (A(2D)L/A2) both increase with the increase of Vad in the coal. It indicates that the relative intensity of the (2G)R and (2D)L bands would both increase with the increase of Vad in the coal. It is known that the aromaticity of coal and average size of aromatic rings in the coal would generally increase with the decrease of volatiles content in the coal (with increasing coal rank).3,4 With increasing aromatic ring size, the relatively small aromatic rings would condense and the C−H of aromatics would decrease significantly.3,4 As summarized in Table 2, the (2G)R band mainly reflects the C−H stretching vibration of aromatics.35,36,47 Therefore, the relative intensity of the (2G)R band would increase extensively with the increase of volatiles content in the coal. Besides, it has been proven that the volatiles in the coal are related to the aliphatic, alkane structures in the coal,45,46 and there is a positive correlation between the volatile yield of the coal and aliphatic hydrogen content.8,45 Therefore, generally more methyl and methylene would exist in the coal with higher volatiles content, resulting in higher relative intensity of the (2D)L band. As described in Table 2, the 2D band and D + G band can mainly reflect the structures that are more ordered in the coal

such as large aromatic rings, while the (2G)R and (2D)L band can mainly reflect the poorly ordered structures such as C−H structures that inclined to exist in the small aromatic rings system or side chains. Thus, the Raman band area ratio A(2D+(D+G))/A((2G)R+(2D)L) can partly reflect the order degree of coal structure. A higher value of the ratio A(2D+(D+G))/ A((2G)R+(2D)L) for the coal is corresponding to a higher order degree of the coal structure. From Figure 4c, it can be seen that the ratio A(2D+(D+G))/A((2G)R+(2D)L) decreases with increase of the volatiles content in the coal. This indicates that coal with higher Vad has a lower order degree and contains more small aromatic rings or side chains while less large aromatic rings. As shown in Figure 4d, a negative correlation between the ratio of the (2D)R band area to A2 (A(2D)R/A2) and Vad is found. In other words, the relative intensity of the (2D)R band would decrease with the increase of volatiles content in the coal. Thus, it is reasonable to say that the structures reflecting by (2D)R band in the coal would be less with the increase of volatiles content in the coal, and it is more probably attributed to more ordered structures. So, though the attribution of the (2D)R band is still controversial,17,33,34 the results of the data in this study suggest that the (2D)R band is more probably related to the structures that are more ordered in the coal such as large aromatic rings. In order to evaluate the correlations, different equations were tried to fit the points in the figure and a cubic equation was applied at last as it was simple and the curve-fitting was also suitable. The empirical formulas were all shown in Figure 4. It F


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Figure 6. Correlations between A(D+(D+G))/A((2G)R+(2D)L) and fixed carbon content on a dry ash free basis and the ratio of fixed carbon content to volatiles content in the coal.

Figure 7. Correlations between the second-order Raman spectral parameters and C/H atom ratio in the coal.

can be seen that the R2 values of the correlations are all larger than 0.7, and those for A(2G)R/A2, A(2D+(D+G))/A((2G)R+(2D)L), and Vad are even larger than 0.9. This indicates that the secondorder Raman spectral parameters especially A(2G)R/A2 and A(2D+(D+G))/A((2G)R+(2D)L) can act as good indicators for volatiles content in the coal. 3.2. Correlations between Fixed Carbon Content and Second-Order Raman Band Area Ratios. As another important index for the organic components in the coal, the fixed carbon content in air-dry basis (FCad) was also correlated with the second-order Raman band area rations. As shown in

Figure 5a and b, there are no reasonable correlations between the FCad and second-order Raman band area ratios A(2G)R/A2 and A(2D)L/A2. This reveals that the fixed carbon content in the coal is not directly related to the C−H structures and amorphous carbon structure in the raw coal. From Figure 5c and d, it can be seen there are general positive correlations between A(2D+(D+G))/A((2G)R+(2D)L), A(2D)R/ A2, and FCad, though some singular points exist. This indicates the order degree of the coal structure would generally increase with the increase of fixed carbon content in the coal. In other words, the fixed carbon content in the coal would be more G


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Energy & Fuels Table 3. Summary of the Comprehensive Method for Evaluating the Coal Properties Y Vad FC/V FCdaf C/H

X

a

b

A(2G)R/A2 A(D+(D+G))/A((2G)R+(2D)L) A(D+(D+G))/A((2G)R+(2D)L) A(2D)R/S2

2.482 × 10 9.510 × 101 8.172 × 102 −8.273 × 100 2

c

−5.761 × 10 −1.344 × 102 −1.299 × 103 3.977 × 102 3

R2

d

4.321 × 10 5.865 × 101 7.112 × 102 −5.677 × 103 4

−9.896 × 10 −7.109 × 10° −1.232 × 102 2.826 × 104 4

0.94 0.94 0.88 0.85

H atom ratio in the coal, indicating that the relative intensities of the (2G)R and (2D)L bands decrease with the increase of the C/H atom ratio. It is not hard to understand that the C−H structures would generally decrease with the increase of the C/ H atom ratio in the coal, and thus, the intensity of the (2G)R and (2D)L bands would also decrease as these two bands are both involved with the C−H vibration.35,36,47 Besides, A(2D+(D+G))/A((2G)R+(2D)L) and A(2D)R/A2 also increase with the increase of the C/H atom ratio, indicating that the order degree of the coal structure would also generally increase with the increase of C/H atom ratio in the coal. Among all the correlations, the correlation between A(2D)R/A2 and the C/H atom ratio is the best, and R2 is about 0.88. A(2D)R/A2 is more suitable to be an indicator for the C/H atom ratio in the coal. 3.4. Comprehensive Method for Evaluating Coal Properties. Considering the obtained results above, there are mainly three key second-order Raman spectral parameters: A(2G)R/A2, A(2D+(D+G))/A((2G)R+(2D)L), and A(2D)R/A2, which can be related to the coal property parameters. It is possible to propose a comprehensive method for evaluating coal properties based on the second-order Raman spectrum of coal. The coal property parameters were plotted with these Raman spectral parameters, and cubic functions were also used to fit the points. All the functions obtained can be expressed as follows:

related to the relatively high order degree structures such as large aromatic rings. Comparing with the R2 for the correlations between A(2D+(D+G))/A((2G)R+(2D)L) and A(2D)R/A2 with Vad, it is obviously lower for the correlation between A(2D+(D+G))/ A((2G)R+(2D)L) and A(2D)R/A2 with FCad as shown in Figure 5c and d. This reveals that the order degree of the coal structure would be more significantly dependent on the volatiles content in the coal compared to the fixed carbon content. In other words, the coal structure would be more sensitive to the change of volatiles content in the coal than fixed carbon content. Furthermore, the coal property parameters of the singular points in Figure 5c and d were analyzed. It has been found that the coals of these points are mainly coals of LY, ZC, JM, XWJ, HLH, SX, and MK4 listed in Table 1, which has either high ash content or high moisture content. It has been reported that the Raman intensity of the H2O is very weak,47 and also no true bands were found in the second-order Raman spectrum of the coal ash in this study. Therefore, the ash and moisture in the coal do not affect the second-order Raman spectrum intensity of the coal theoretically. Moreover, the fixed carbon content in dry ash free basis (FCdaf) was also correlated to the A(2D+(D+G))/ A((2G)R+(2D)L) as shown in Figure 6a. It can be seen the correlation is obviously better than that between FCad and A(2D+(D+G))/A((2G)R+(2D)L). This further indicates that the inorganic component in the coal has fewer effects on the second-order Raman band area ratios of the coal. Therefore, for these singular points in Figure 5c and d, these would be mainly caused by the effects of abnormal volatiles content on an air-dry basis on the coal structures when the coal has similar fixed carbon content but high moisture content or high ash content since the coal structures are very sensitive to the change of volatiles content in the coal. In Figure 6b, it can be seen there is a positive correlation between the A(2D+(D+G))/A((2G)R+(2D)L) and the fuel ratio of fixed carbon to volatiles content (FC/V) in the coal, which is a key parameter that can significantly affect the char reactivity and NOx formation during the coal conversion.5 It can be seen that, when FC/V is lower than 3, the ratio A(2D+(D+G))/A((2G)R+(2D)L) increases drastically with the increase of FC/V. This reveals that the order degree of the coal structure is significantly determined by FC/V in coal. When FC/V is larger than 3, the ratio A(2D+(D+G))/A((2G)R+(2D)L) increases moderately with the increase of FC/V, which is mainly because the volatiles content in the coal is relativity low and a slight change of the volatiles or fixed carbon content would cause a distinct change of the FC/V but the coal structures change little. The empirical formula of the fitting is shown in Figure 6, and the R2 is about 0.9. It is reasonable to say that these correlations can give an approach to estimate the FCdaf and FC/V in the coal according to the second-order Raman spectral parameters. 3.3. Correlations between the C/H Atom Ratio and Second-Order Raman Band Area Ratios. Figure 7 shows the correlations between the typical second-order Raman band area ratios and the C/H atom ratio. It can be seen that A(2G)R/ A2 and A(2D)L/A2 generally decrease with the increase of the C/

Y = a + bX + cX2 + dX3

in which Y represents the coal property parameters and X represents the second-order Raman spectral parameters while a, b, c, and d are the coefficients. The corresponding correlations and specific parameters are summarized in Table 3. It can be seen the R2 values are all larger than 0.85, indicating the reasonable quality of the correlations. Through this comprehensive method, the Vad, FC/V, FCdaf, and C/H atom ratio of the coals can be calculated reasonably based on the secondorder Raman band area ratios. It needs to be pointed out that the methods proposed in this study may be only suitable for the coals within the coal rank scope and using a similar curve-fitting method, but this provides a reasonable method for evaluating coal properties and also demonstrates that the second-order Raman spectrum can reveal some useful structural information about coal.

4. CONCLUSION Thirty-two kinds of Chinese coals were characterized with micro-Raman spectroscopy in this study. A new deconvolution method for the second-order Raman spectrum of coal has been established, and the spectrum between 2100 and 3400 cm−1 can be successfully curve-fitted by eight Gaussian bands that represent the typical chemical structures in coal. The results reveal that the C−H and amorphous carbon structures in coal will increase with the increase of volatiles content in coal but have no obvious correlations with the fixed carbon content. Besides, the order degree of the coal structure has a good positive correlation with the ratio of fixed carbon to volatiles content. There are reasonable correlations between the secondH


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order Raman spectral parameters and the coal property parameters, and the ratios A(2G)R/A2, A(D+(D+G))/A((2G)R+(2D)L), and A(2D)R/S2 can act as good indicators to evaluate the coal properties including volatiles content, the ratio of fixed carbon to volatiles content, and the C/H atom ratio. The results demonstrate that the second-order Raman spectrum can be used to characterize coal structure and evaluate coal properties effectively.

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AUTHOR INFORMATION

Corresponding Authors

*Phone: (+86) 27-87542417-8206. Fax: (+86) 27-87545526. E-mail: [email protected] (S.S.). *E-mail: [email protected] (J.X.). ORCID

Sheng Su: 0000-0003-3523-8222 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by the National Key R&D Program of China (No. 2017YFB0601802), National Natural Science Foundation of China (NSFC) (Nos. 51576081, 51576086, 51576072), Shanxi Science and Technology Major Project (Nos. MD2015-05, MD2015-03), and the Foundation of State Key Laboratory of Coal Conversion (Grant No. J17-18-904). The authors also acknowledge the extended help from the Analytical and Testing Center of Huazhong University of Science and Technology.

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Micro-Raman Spectroscopy Study of 32 Kinds of Chinese Coals

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