Powder-Activated Coke Prepared from Coal Fast Pyrolysis: Fractal Characteristics and SO2 Adsorption

doi:10.21203/rs.3.rs-1599284/v1

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Powder-Activated Coke Prepared from Coal Fast Pyrolysis: Fractal Characteristics and SO2 Adsorption

https://doi.org/10.21203/rs.3.rs-1599284/v1

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Powder activated coke is a porous material with fractal characteristics. The fractal analysis of powder activated coke prepared under different atmospheres were carried out to understand its surface irregularity and pore complexity. The Frenkel–Halsey–Hill (FHH) method was used to determined two fractal dimensions D₁ and D₂, under relative pressures of 0–0.5 and 0.5–1, respectively. The relationship between the preparation conditions and fractal dimension was investigated and the influence of the fractal dimensions on the SO₂ adsorption characteristics was also studied. The results indicate that the fractal dimensions were influenced by the concentrations of activation agents with D₁ ranging from 2.1838 to 2.8643 and D₂ ranging from 2.7485 to 2.9257. An n-shaped curve-based relationship between fractal dimensions and coke yields is observed with a peak values of fractal dimensions appearing around 64% yield. The SO₂ adsorption capacity shows a consecutively positive linear correlation with D₂, while it illustrates distinctly different linear rates with D₁ in intervals of 2–2.6 and 2.6–3, respectively.

Fractal characteristics

Powder activated coke

SO2 adsorption

Activation agent

N2 gas adsorption

SO₂ is one of the major pollutants in coal-fired power plants. At present, limestone–gypsum wet flue gas desulfurization (WFGD) is widely used in most power plants worldwide, especially in China (Zhu et al., 2015). However, this limestone scrubbing desulfurization technology has many disadvantages. The excessive exploitation of Ca-based sorbents has led to serious environmental damage. Meanwhile, the water shortage restricts its application and the difficulty in utilization of desulfurization gypsum causes to the waste of sulfur resources (Shuangchen et al., 2016). For the purpose of saving water resources and recycling sulfur products, the dry flue gas desulfurization, such as the method of SO₂ adsorption using porous adsorbents, have received more attentions (Tai et al., 2020).

Carbonaceous materials, such as activated carbon fiber, activated coke, carbon nanotubes, etc., are clean and recyclable adsorbents for SO₂ removal (Atanes et al., 2012; Gaur et al., 2006; Mochida et al., 2000; Yan et al., 2013). Among these adsorbents, low-cost powder activated coke (PAC) causes aboard attention of many researchers. In our previous study, PAC with high specific surface area and SO₂ adsorption capacity was prepared by means of fast pyrolysis in low oxygen atmosphere (Tai et al., 2020). The SO₂ adsorption capacity of PAC is put down to its physicochemical characteristics. Previous research has shown that high surface area, large pore volume, suitable microporosity and appropriate pore size distribution are the most important requirements for SO₂ adsorption (Guo and Lua, 2002; Liu et al., 2003a; Liu et al., 2003b; Lua and Guo, 2001; Raymundo-Piñero et al., 2000; Shi et al., 2015; Sun et al., 2013). In addition, several researchers suggested that active sites, such as basic oxygen surface groups, CO-derived active sites, or heteroatoms also play a significant role in SO₂ adsorption (Bagreev et al., 2002; Davini, 1990; Sun et al., 2016; Wang et al., 2018). It is worth noting that The active sites also need to be in a specific pore structure to exert effects on SO₂ adsorption. Therefore, it is of great significance to understand the pore structure formation mechanism of porous carbon material and figure out the effect of pore structure on SO₂ adsorption performance for improving the adsorption performance of carbonaceous adsorbent.

Many investigations have shown that the fractal analysis is an effective method to describe the geometric and structural properties of fractal surfaces, pore structures, surface heterogeneity, etc (Diduszko et al., 2000; Hayashi et al., 2002; Othman et al., 2010; Xu et al., 2010; Yakout and Sharaf El-Deen, 2016; Zhang et al., 2014). It was discovered that the pores of some carbon materials, such as char and coal, were fractal-like, and the preparation conditions of carbon materials affect the fractal dimension. The fractal dimension is closely related to the burn-off ratio, pyrolysis temperature and heating rate during coal devolatilization (Chen et al., 2011; Song et al., 2004; Wang et al., 2008; Xu et al., 2010). This fractal theory has also been applied in studies on gas adsorption characteristics. For instance, the CH₄ adsorption capacity is positively correlated with the pore fractal characteristics (Cai et al., 2013; Chengyang et al., 2012; Naveen et al., 2018; Yang et al., 2014; Yao et al., 2008). In previous studies, the fractal dimension was obtained via various methods, such as mercury intrusion, transmission electron microscopy, scanning electron microscopy, small-angle X-ray scattering, and N₂ gas adsorption (Pan et al., 2016; Pyun and Rhee, 2004; Wang et al., 2014; Yang et al., 2014; You et al., 2015). Among these methods, N₂ gas adsorption analysis has been shown to be an effective method for characterizing fractal dimensions (Hayashi et al., 2002; Wang et al., 2015; Xu et al., 2010).

In summary, although the pore fractal characteristics of raw coals, pyrolytic cokes, and activated carbons have been reported in previous literatures, there are few studies on the influence of preparation atmosphere on fractal dimension and the correlation of the fractal dimension with the SO₂ adsorption capacity. Therefore, the present work investigates the effects of the activation agents and coke yield on the fractal dimension in detail. In addition, the impact of the fractal dimension on the SO₂ adsorption capacity is also discussed. This type of investigation could enrich knowledge on the nature of porous solids and the related adsorption processes.

Sample preparation

Lean coal was used as a precursor material for PAC preparation. Firstly, the lean coal raw material was dried at 105°C for 8 h, and then the sample was crushed, ground and sieved, and finally the granular product ( particle size 60–90 µm) was obtained. PAC was prepared at atmospheric pressure in a drop tube reactor (DTR) system. The experimental system is described in detail in our previous work (Zhang et al., 2016). The reactor in this system is composed of 310S stainless steel tubes with an inner diameter of 80 mm and a depth of 2 m. When the reaction gas temperature reaches 850℃, nitrogen (10 L·min^-1, STP) is used as primary carrier gas to carry the pulverized coal into DTR at a mass flow rate of 0.5 g·min^-1. According to literature (Hayashi et al., 2000), coal particles in DTR were heated to 850 ℃ at high heating rate (> 10³ K·s^− 1 ). The secondary carrier gas was selected from the three gas mixtures (nitrogen / steam, nitrogen / oxygen or nitrogen / steam / oxygen) and entered the system at the rate of 10 L·min^− 1 (STP). As coal particles were continuously fed into the reactor, the volatile components released from the coal particles and the char reacted with volatile and activation gas (oxygen and steam) to form activated coke. The active coke particles generated by the reaction were collected at the bottom of DTR and further analyzed. The prepared PAC was named PAC-OxSy, where x represents the concentration of oxygen in the activator, and y represents the volume concentration of water vapor in the activator. Ox or Sy can be omitted when activation agents contained neither oxygen nor steam. In addition, the PACs prepared using nitrogen atmosphere were named as PAC-N.

Yield of PACs

The PAC yield plays an important role in adsorption performance evaluation, which is related to the economy of the process and adsorption capacity. Due to mass loss from the release of volatile substances, the yield could not be determined by direct weighing. Hence, the ash balance method was adopted for yield calculation, which defines the mass of ash in row coal and PACs is unchanged during PACs preparation. The yield x is calculated as follows:

$${\text{Y}}_{\text{PAC}}\text{=}\raisebox{1ex}{${\text{A}}_{\text{coal}}$}\!\left/ \!\raisebox{-1ex}{${\text{A}}_{\text{PAC}}$}\right.$$

where A_coal and A_PAC represent the ash content in the coal and PAC, respectively. The ash content was obtained from a proximate analysis.

Calculation of fractal dimension

Different approaches, such as fractal BET, fractal Langmuir, the thermodynamic method, and the fractal Frenkel–Halsey–Hill (FHH) method, can be used to derive the fractal dimension based on gas adsorption isotherms.(Avnir and Jaroniec, 1989; Kanô et al., 2000; Mahnke and Mögel, 2003; Neimark and Unger, 1993; Vajda and Felinger, 2014) The FHH approach has been shown to be the most effective and extensively used method for determining surface irregularity in porous materials (Naveen et al., 2018). Using the FHH method, the fractal dimension can be determined from an analysis of multi-layer adsorption onto a fractal surface according to the following equation:

$$\text{ln}\frac{\text{V}}{{\text{V}}_{\text{m}}}\text{=}\text{constant+}\text{A}\left[\text{ln}\left(\text{ln}\left(\frac{{\text{P}}_{\text{0}}}{\text{P}}\right)\right)\right]$$

where V is the volume of adsorbed gas molecules at equilibrium pressure P; V_m is the volume of monolayer coverage; A is the power-law exponent that is dependent on fractal dimension D and the mechanism of adsorption; and P₀ is the saturation pressure of the gas. The findings shown above were obtained using a low-temperature nitrogen adsorption test. N₂ adsorption isotherms of the PACs at 77 K (-196°C) were obtained using an automated gas sorption analyzer (Autosorb-iQ). The PAC samples were degassed for 12 hours under vacuum at 200°C before the gas adsorption tests. Plotting the N₂ adsorption isotherm data in the form lnV against ln(ln(P₀/P) yields the A value. The fractal dimension may then be calculated using the graph's slope (A). There are two formulas for calculating the fractal dimension: D = 3 + 3A and D = 3 + A. The former is used in a van der Waals force regime, whereas the latter is used in a capillary condensation regime(Pfeifer et al., 1989; Zhang et al., 2014). According to prior research, both formulas are often utilized, however the fractal dimensions determined with the former are generally smaller than 2. This value does not correspond to the definition of a fractal dimension, but the fractal dimensions estimated with the latter range from 2 to 3. In this study, the fractal dimension is estimated using D = 3 + A. (Liu et al., 2015; Xu et al., 2010).

SO₂ adsorption capacity of samples

In a fixed bed testing equipment (shown as Fig. 1 ), the PACs' adsorption capability was examined. The experiment setup is composed of simulated flue gas system, fixed bed reactor, and a gas analyzer. The simulated flue gas obtained via controlled mixing of 0.14vol.% SO₂, 8 vol.% H₂O, 6 vol.% O₂, and 85.86 vol.% N₂ was continuously fed into reactor at a rate of 400 mL min^-1. The steam is fed through the saturated steam carried by nitrogen. The thermostatic water bath temperature is kept at 55°C, and the pipe which the steam passes through is kept at 120°C by the heat band. The carbon bed containing 1 g PAC was used to adsorb SO₂ in a fixed bed reactor with an inner diameter of 15 mm and a length of 500 mm at 75°C. An online Fourier transform infrared gas analyzer was used to continually monitor the SO₂ concentration (GASMET-DX4000). Using the following equation, the SO₂ adsorption capacity Q_ad was estimated by integrating the SO₂ conversion versus time curves:

$${\text{Q}}_{\text{ad}}\text{=}\frac{{\text{Q}}_{\text{g}}\text{M}}{\text{22.4×}\text{m}}\int \left({\text{C}}_{\text{in}}\text{-}{\text{C}}_{\text{out}}\right)\text{dt}$$

where M_ad is the adsorption capacity per gram, Q_g is the volumetric flow rate of the simulated flue gas, C_in and C_out represent the initial and out concentrations of SO₂ in the simulated flue gas, respectively, M is the molar mass of the adsorbate, m is mass of the PAC in the experiment, and t is the absorption time. Unfortunately, SO₂ adsorption is a sluggish process, with saturation adsorption taking hundreds of hours. As a result, the adsorption time was lowered to 2 h for practical reasons(Jastrząb, 2012).

Fractal characterization of PACs

Fractal dimensions are estimated via the FHH model to linearly fit the correlation between the adsorbed volume lnV and ln[ln(P/P₀)]. According to the calculated slopes, there are different rules in the P/P₀ ranges of 0–0.5 (pore size < 10 nm) and 0.5–1 (pore size ≥ 10 nm) due to the different sorption mechanisms in pores with different sizes (Cai et al., 2013; Chengyang et al., 2012; Naveen et al., 2018; Yao et al., 2008). As shown in Fig. 2, no linear relationship was observed in the lnV versus ln[ln(P/P₀)] plot of PAC-N in the P/P₀ range of 0–0.5 and the fractal dimension is unrealistically low (D < 2) in the P/P₀ range of 0.5–1. This may be due to the amorphous carbon consumption, surface microcrystals graphitization and pore collapse of carbon materials caused by high temperature, so that they do not present fractal characteristics. The plots of PAC-Ox exhibit two distinct linear ranges and both have high degree of linearity (R² > 0.98), suggesting that the fractal characteristics are diverse in these two ranges. Hence, in the regions of P/P₀ < 0.5 and P/P₀ ≥ 0.5, the fractal dimensions were estimated and defined as D₁ and D₂, respectively. According to previous studies (Bu et al., 2015; Xu et al., 2010; Yao et al., 2008; Zhu et al., 2016), D₁ reflects the pores surface roughness of a porous carbon structure and hence, it can be used to represent the pores surface irregularity. D₂ reflects the volumetric roughness of a porous carbon structure and it can be used to represent the pore structure complexity. The other sample’s FHH plots, such as PAC-OxSy and PAC-Sy, are similar to those of PAC-Ox, which are not presented here.

(a) PAC-N, (b) PAC-O2, (c) PAC-O4, (d) PAC-O6, (e) PAC-O7, and (f) PAC-O8

The slopes (A₁ and A₂) and fractal dimension values (D₁ and D₂) of the PACs obtained by the FHH model are presented in Table 1. D₁ varies from 2.1838 to 2.4673 under an oxygen-free atmosphere, which suggests that these PACs have smooth pore surface and few micropore and mesopore structures. In the meantime, D₂ varies from 2.7455 to 2.8074 under an oxygen-free atmosphere, indicating that the PACs have irregular particle surface and several of macropores. Obviously, the D₁ and D₂ values of the PAC prepared under in oxygen-bearing atmosphere are higher than those of other PACs prepared in an oxygen-free atmosphere. This shows that oxygen acts is an vital activator for the development of pore structures and rough surfaces during PAC preparation (Yakout and Sharaf El-Deen, 2016). The PAC prepared under a 15% steam and 7% oxygen concentration has the highest D₁ and D₂ values.

Table 1

Fractal dimensions and yields of PACs
Sample	P/P0 = 0-0.5			P/P0 = 0.5-1			Yield (%)
Sample	A₁	D₁	R²	A₂	D₂	R²	Yield (%)
PAC-N	—	—	—	—	—	—	84.9
PAC-S15	-0.8162	2.1838	0.9981	-0.2515	2.7485	0.9920	83.12
PAC-S25	-0.5327	2.4673	0.9978	-0.2361	2.7639	0.9908	79.58
PAC-S35	-0.6077	2.3923	0.9903	-0.1926	2.8074	0.9591	78.35
PAC-S45	-0.7724	2.2276	0.9959	-0.2545	2.7455	0.9875	75.31
PAC-O2	-0.3414	2.6586	0.9891	-0.1820	2.8180	0.9788	73.27
PAC-O4	-0.2050	2.7950	0.9970	-0.1026	2.8974	0.9926	71.46
PAC-O6	-0.2042	2.7958	0.9911	-0.1016	2.8984	0.9808	70.56
PAC-O7	-0.1936	2.8064	0.9940	-0.0914	2.9086	0.9923	68.88
PAC-O8	-0.2136	2.7864	0.9989	-0.0923	2.9077	0.9865	64.44
PAC-O7S15	-0.1357	2.8643	0.9658	-0.0743	2.9257	0.9868	58.18
PAC-O7S25	-0.1829	2.8171	0.9874	-0.1238	2.8762	0.9957	54.92
PAC-O7S35	-0.2295	2.7705	0.9816	-0.1382	2.8618	0.9926	62.49
PAC-O7S45	-0.3032	2.6968	0.9946	-0.1603	2.8397	0.9924	55.12

Relation between fractal dimensions and activation agent concentration

The relationship between the fractal dimension and activation agent concentration is shown in Fig. 3. The D₁ value is always less than the D₂ value. As shown in Fig. 3a, D₁ and D₂ increase as the O₂ concentration increases from 2–7% and then slightly decreases as the O₂ concentration increases to 8%. D₁ exhibit similar tendencies with regard to D₂.

This accounts for the higher reactivity of O₂ with C and combustible gases in the volatile. The high reactivity contributes to rapid release of volatiles and formation of the pore structure at the initial stage of reaction, thus it increases the pore surface roughness and pore complexity of PACs. However, higher O₂ concentration causes excessive ablation of carbon surface and collapse of pore structure, resulting in the decrease of fractal dimension. Figure 3b shows the relation between the H₂O concentration and fractal dimension of the PACs prepared with H₂O activation alone. The results show that the H₂O concentration does not have much influence on D₂. However, the D₁ value changes significantly as the H₂O concentration increases and the maximum D₁ value is obtained at a H₂O concentration of 25%. With further increase of H₂O concentration, D₁ value decreased significantly. It indicates that the effect of H₂O on carbonaceous materials is mainly reflected in the ablation of carbon matrix surface and the expansion and improvement of existing pore structure. Although steam activation results in higher D₁ values, the D₁ values are still much lower than that of the PACs prepared in the oxygen-bearing atmosphere. The reason is that the rate of reaction between steam and coal is much slower than that between oxygen and coal. Moreover, when H₂O exists alone, the temperature of carbon particles declines and the release of volatiles is hindered due to endothermic reaction between C and H₂O. In this case, the creation of pore structure in the course of the initial pyrolysis stage is negatively affected, resulting in a lower fractal dimension. Figure 3c indicates the association between the fractal dimension and H₂O concentration for PACs prepared under a mixed O₂ and H₂O atmosphere with O₂ concentration fixed at 7%. D₁ increases from 2.81 to 2.86 and D₂ increases from 2.91 to 2.93 with increasing H₂O concentration from 0–15%, and then decreases at higher steam concentrations. It indicates that, under a mixed O₂ and H₂O atmosphere, the volatiles releases rapidly and the original closed pores are opened at the initial pyrolysis stage. After the devolatilization stage, O₂ and H₂O react with carbon surface to form new pore structures. Moderate steam can compete with O₂ for the reaction site. This avoids excessive ablation of carbon materials by O₂ to a certain extent, and maintain the complexity of internal surface and irregularity of pore structures. However, further increase of H₂O concentration will lead to pore size expanding and pore structure collapse, which will destroy the original micropore structure and reduce the fractal dimension.

(a) Effect of O₂ concentration on PACs prepared using O₂ alone, (b) Effect of H₂O concentration on PACs prepared using H₂O alone, (c) Effect of O₂ concentration on PACs prepared using O₂ and H₂O.

Relationship between fractal dimension and yield

The relationship between the fractal dimension of PAC and coke yield is shown in Fig. 4. It can be seen that their relationship curve is n-shaped. D₁ and D₂ reached the maximum when the yield of PAC was about 64%. This illustrates that the yield of PAC has a great influence on the fractal dimension. The relationship between fractal dimension and the yield can be expressed by the following formula:

D ₁ = -1.26×10^− 3 x² + 0.16x − 2.04 (4)

D ₂ = -4.25×10^− 4 x² + 0.054x + 1.17 (5)

When the yield is high, carbon ablation is no longer a factor affecting the fractal dimension, which is mainly affected by the release of volatile matter, which may lead to smoother pore surface and closure of some open pores inside the particles. However, when the yield decreases, a large number of micropores and mesopores will be produced with the increase of amorphous carbon and carbon crystal consumption, so the fractal dimension will also increase. When Y_PAC < 64%, the fractal dimension decreases with the decrease of yield due to the excessive consumption of amorphous carbon and carbon crystalline carbon. In other words, moderate ablation can maximize the surface complexity and pore irregularity of carbon materials.

Relation between fractal dimensions and SO₂ adsorption characteristics

The SO₂ adsorption properties of PACs were estimated using an adsorption breakthrough curve over 120 min. As observed in Fig. 5, the SO₂ adsorption breakthrough curves of the PACs varied with the O₂ and H₂O concentrations in the activation agent. The value of C/C₀ rapidly increased to 0.8 after 20 min, and saturation (C/C₀ = 1) occurred after 120 min for PAC-N prepared under a N₂ atmosphere, corresponding to the lowest adsorption capacity of 10.27 mg·g^− 1. Although H₂O activation could improve the SO₂ adsorption capacity of PAC, saturation adsorption still occurred within 120 min. This results in a limited increase in SO₂ adsorption from 13.85 mg·g^− 1 to 17.12 mg·g^− 1 with increasing adsorption capacities of four PACs prepared via H₂O activation alone, following a decreasing trend of PAC-S35 > PAC-S25 > PAC-S45 > PAC-S15. However, PAC prepared under an oxygen-containing atmosphere showed a better gas adsorption performance than PAC-N and PAC-Sy. According to Fig. 5b, the SO₂ sorption was significantly improved and the C/C₀ value decreased from 0.9 to 0.77 as the O₂ concentration increased from 2–7% but then decreased when PACs were prepared using O₂ activation alone. The SO₂ adsorption capacity of PAC-O7 activated using 7% O₂ is 39.14 mg·g^− 1, which is approximately 3.8 times than that of PAC-N. Figure 5c shows that activation with a mixture of oxygen and an appropriate concentration of steam can further improve the SO₂ adsorption capacity. With an increasing H₂O concentration from 0–15%, the value of C/C₀ decreases from 0.77 to 0.67 and then increases. Correspondingly, the SO₂ adsorption capacity of PAC-O7S15 achieves the maximum, 45.85 mg·g-1, which is approximately 1.2 times and 4.6 times than those of PAC-O7 and PAC-N, respectively. This demonstrates that PACs prepared under an atmosphere of oxygen mixed with steam are ideal for the SO₂ removal.

Figure 6 is the curves of fractal dimension D₁ and D₂ with SO₂ adsorption. It can be seen the curves in Fig. 6a and Fig. 6b are significantly different, indicating that D₁ and D₂ have different effects on SO₂ adsorption. It can be seen in Fig. 6a that there are two lines, whose fractal dimension ranges are 2–2.6 and 2.6–3. Both lines showed a good linear relationship between fractal dimension (D₁) and SO₂ adsorption capacity. At the same time, it can be seen that the slopes of the two lines were significantly different, indicating that the relationship between fractal dimension and SO₂ adsorption capacity was also different in these two fractal dimensions. The PAC with higher D₁ value has more complex microporous surface, which provides more sites for SO₂ adsorption. As mentioned above, the D₁ value of PAC prepared under anaerobic condition is lower than that of PAC prepared under oxygen atmosphere, and its SO₂ adsorption capacity increases slowly with the increase of fractal dimension. The SO₂ adsorption capacity of PAC prepared in oxygen-containing atmosphere increases sharply with the increase of fractal dimension. This indicates that the addition of O₂ promotes the heterogeneity of pore surface, and produces more functional groups that cannot be expressed in fractal dimension compared with H₂O activation. These functional groups can provide more active centers for SO₂ adsorption, thus promoting the improvement of SO₂ adsorption performance (Fu et al., 2020). As shown in Fig. 6b, the SO₂ adsorption capacity of PAC increases with the increase of D₂ value. The high value of D₂ may be due to the existence of more micropores and mesopores in PAC, and the heterogeneity of pore distribution also affects the value of D₂. The types and distribution of pores provide more space for SO₂ adsorption and more storage space for product sulfuric acid. In summary, under the premise of the same physical structure and chemical properties of carbonaceous materials, fractal dimension can fully reflect the influence of PAC performance on SO₂ adsorption (Li et al., 2016; Mahamud et al., 2003).

The FHH method was applied to investigate the fractal characteristics related to the SO₂ adsorption properties of PACs. The effects of the activation agent and yield on the fractal dimensions of PACs were studied. Furthermore, the influence of the fractal dimension on the SO₂ adsorption capacities of PACs was analyzed. The main findings are as follows:

(1) The fractal dimensions were influenced by the activation agent and concentration. Oxygen, as an activated gas, can produce higher fractal dimension than steam. When the activated gas contains H₂O, the D₁ value of PAC prepared under an oxygen-free atmosphere is much less than that of PAC prepared under an oxygen-containing atmosphere. The maximum D₁ and D₂ values were observed when PAC was prepared under 7% O₂ and 15% H₂O.

(2) The PAC yield had a significant effect on the fractal dimensions. The relationship between the fractal dimensions (D₁ and D₂) and yield can be represented by an n-shaped curve, with a maximum value at approximately 64% yield.

(3) The SO₂ adsorption characteristics differ for the PACs. PACs prepared under an atmosphere of oxygen mixed with steam are favorable for the removal of SO₂. The SO₂ adsorption capacity of PAC-O7S15 is the highest, at 45.85 mg·g-1. The fractal dimensions can comprehensively reflect the pore structure properties and the influence of the properties of coal on SO₂ adsorption.

Acknowledgements We thank Jiangwei Xue, Longzhi Li，Peiyi Liu，Shanchuan Li for helping with the experiment.

Author contribution Tai Feng: investigation, conceptualization, formal analysis, methodology. Qiwen Kong: writing—original draft, validation. Jiangwei Xue: investigation. Longzhi Li: validation project administration. Peiyi Liu: experimental operation. Shanchuan Li: experimental operation. Zhen Zhang: methodology, writing—review and editing, diagramming, .

Funding This research is supported by the Natural Science Foundation of Shandong Province (ZR2019BEE063).

Data availability All data, models, and code generated or used during the study appear in the submitted article.

Ethical approval and consent to participate. Not applicable.

Consent for publication Not applicable.

Competing interests The authors declare no competing interests.

Atanes E, Nieto-Márquez A, Cambra A, Ruiz-Pérez MC, Fernández-Martínez F (2012) Adsorption of SO₂ onto waste cork powder-derived activated carbons. Chem Eng J Adv 211–212:60–67. http://dx.doi.org/10.1016/j.cej.2012.09.043
Avnir D, Jaroniec M (1989) An isotherm equation for adsorption on fractal surfaces of heterogeneous porous materials. Langmuir 5:1431–1433. 10.1021/la00090a032
Bagreev A, Bashkova S, Bandosz TJ (2002) Adsorption of SO₂ on Activated Carbons: The Effect of Nitrogen Functionality and Pore Sizes. Langmuir 18:1257–1264. 10.1021/la011320e
Bu H, Ju Y, Tan J, Wang G, Li X (2015) Fractal characteristics of pores in non-marine shales from the Huainan coalfield, eastern China. J Nat Gas Sci Eng 24:166–177. https://doi.org/10.1016/j.jngse.2015.03.021
Cai Y, Liu D, Pan Z, Yao Y, Li J, Qiu Y (2013) Pore structure and its impact on CH₄ adsorption capacity and flow capability of bituminous and subbituminous coals from Northeast China. Fuel 103:258–268. https://doi.org/10.1016/j.fuel.2012.06.055
Chen Y, Wang X, He R (2011) Modeling changes of fractal pore structures in coal pyrolysis. Fuel 90:499–504. https://doi.org/10.1016/j.fuel.2010.10.016
Chengyang W, Shixiong H, Wenjing S, Wei C (2012) Fractal dimension of coal particles and their CH₄ adsorption. Int J Min Sci Technol 22:855–858. https://doi.org/10.1016/j.ijmst.2012.11.003
Davini P (1990) Adsorption and desorption of SO₂ on active carbon: The effect of surface basic groups. Carbon 28:565–571. http://dx.doi.org/10.1016/0008-6223(90)90054-3
Diduszko R, Swiatkowski A, Trznadel BJ (2000) On surface of micropores and fractal dimension of activated carbon determined on the basis of adsorption and SAXS investigations. Carbon 38:1153–1162. https://doi.org/10.1016/S0008-6223(99)00236-5
Fu J, Zhou B, Zhang Z, Wang T, Ma C (2020) One-step rapid pyrolysis activation method to prepare nanostructured activated coke powder. Fuel 262:116514
Gaur V, Asthana R, Verma N (2006) Removal of SO₂ by activated carbon fibers in the presence of O₂ and H₂O. Carbon 44:46–60. http://dx.doi.org/10.1016/j.carbon.2005.07.012
Guo J, Lua AC (2002) Microporous activated carbons prepared from palm shell by thermal activation and their application to sulfur dioxide adsorption. J Colloid Interface Sci 251:242–247. http://dx.doi.org/10.1006/jcis.2002.8412
Hayashi Ji, Takahashi H, Iwatsuki M, Essaki K, Tsutsumi A, Chiba T (2000) Rapid conversion of tar and char from pyrolysis of a brown coal by reactions with steam in a drop-tube reactor. Fuel 79:439–447. http://dx.doi.org/10.1016/S0016-2361(99)00179-9
Hayashi Ji, Horikawa T, Muroyama K, Gomes VG (2002) Activated carbon from chickpea husk by chemical activation with K₂CO₃: preparation and characterization. Microporous Mesoporous Mater 55:63–68. https://doi.org/10.1016/S1387-1811(02)00406-7
Jastrząb K (2012) Properties of activated cokes used for flue gas treatment in industrial waste incineration plants. Fuel Process. Technol. 101:16–22. https://doi.org/10.1016/j.fuproc.2011.05.028
Kanô F, Abe I, Kamaya H, Ueda I (2000) Fractal model for adsorption on activated carbon surfaces: Langmuir and Freundlich adsorption. Surf Sci 467:131–138. https://doi.org/10.1016/S0039-6028(00)00730-5
Li A, Ding W, He J, Dai P, Yin S, Xie F (2016) Investigation of pore structure and fractal characteristics of organic-rich shale reservoirs: A case study of Lower Cambrian Qiongzhusi formation in Malong block of eastern Yunnan Province, South China. Mar Pet Geol 70:46–57. https://doi.org/10.1016/j.marpetgeo.2015.11.004
Liu JZ, Zhu JF, Cheng J, Zhou JH, Cen KF (2015) Pore structure and fractal analysis of Ximeng lignite under microwave irradiation. Fuel 146:41–50. https://doi.org/10.1016/j.fuel.2015.01.019
Liu Q, Guan JS, Li J, Li C (2003a) SO₂ removal from flue gas by activated semi-cokes: 2. Effects of physical structures and chemical properties on SO₂ removal activity. Carbon 41:2225–2230. http://dx.doi.org/10.1016/S0008-6223(03)00230-6
Liu Q, Li C, Li Y (2003b) SO2 removal from flue gas by activated semi-cokes: 1. The preparation of catalysts and determination of operating conditions. Carbon 41:2217–2223. https://doi.org/10.1016/S0008-6223(03)00205-7
Lua A, Guo J (2001) Adsorption of sulfur dioxide on activated carbon from oil-palm waste. J Environ Eng 127:895–901 10.1061/(ASCE)0733–9372(2001)127:10(895)
Mahamud M, López Ó, Pis JJ, Pajares JA (2003) Textural characterization of coals using fractal analysis. Fuel Process Technol 81:127–142. https://doi.org/10.1016/S0378-3820(03)00004-3
Mahnke M, Mögel HJ (2003) Fractal analysis of physical adsorption on material surfaces. Colloids Surf A 216:215–228. https://doi.org/10.1016/S0927-7757(02)00577-0
Mochida I, Korai Y, Shirahama M, Kawano S, Hada T, Seo Y, Yoshikawa M, Yasutake A (2000) Removal of SOx and NOx over activated carbon fibers. Carbon 38:227–239. http://dx.doi.org/10.1016/S0008-6223(99)00179-7
Naveen P, Asif M, Ojha K (2018) Integrated fractal description of nanopore structure and its effect on CH₄ adsorption on Jharia coals, India. Fuel 232:190–204. https://doi.org/10.1016/j.fuel.2018.05.124
Neimark AV, Unger KK (1993) Method of Discrimination of Surface Fractality. J Colloid Interface Sci 158:412–419. https://doi.org/10.1006/jcis.1993.1273
Othman MR, Helwani Z, Martunus (2010) Simulated fractal permeability for porous membranes. APPL MATH MODEL 34:2452–2464. https://doi.org/10.1016/j.apm.2009.11.010
Pan J, Niu Q, Wang K, Shi X, Li M (2016) The closed pores of tectonically deformed coal studied by small-angle X-ray scattering and liquid nitrogen adsorption. Microporous Mesoporous Mater 224:245–252. https://doi.org/10.1016/j.micromeso.2015.11.057
Pfeifer P, Wu YJ, Cole MW, Krim J (1989) Multilayer adsorption on a fractally rough surface. Phys Rev Lett 62:1997–2000. 10.1103/PhysRevLett.62.1997
Pyun SI, Rhee CK (2004) An investigation of fractal characteristics of mesoporous carbon electrodes with various pore structures.Electrochim. Acta 49:4171–4180. https://doi.org/10.1016/j.electacta.2004.04.012
Raymundo-Piñero E, Cazorla-Amorós D, Salinas-Martinez de Lecea C, Linares-Solano A (2000) Factors controling the SO₂ removal by porous carbons: relevance of the SO₂ oxidation step. Carbon 38:335–344. http://dx.doi.org/10.1016/S0008-6223(99)00109-8
Shi L, Yang K, Zhao Q, Wang H, Cui Q (2015) Characterization and mechanisms of H₂S and SO₂ adsorption by activated carbon. Energy Fuels 29:6678–6685. 10.1021/acs.energyfuels.5b01696
Shuangchen M, Jin C, Gongda C, Weijing Y, Sijie Z (2016) Research on desulfurization wastewater evaporation: Present and future perspectives. Renew Sustainable Energy Rev 58:1143–1151. https://doi.org/10.1016/j.rser.2015.12.252
Song H, Min L, Jun X, Lushi S, Peisheng L, Sheng S, Xuexin S (2004) Fractal characteristic of three Chinese coals. Fuel 83:1307–1313. https://doi.org/10.1016/j.fuel.2003.12.011
Sun F, Gao J, Zhu Y, Chen G, Wu S, Qin Y (2013) Adsorption of SO₂ by typical carbonaceous material: a comparative study of carbon nanotubes and activated carbons. Adsorption 19:959–966. 10.1007/s10450-013-9504-9
Sun F, Gao J, Liu X, Yang Y, Wu S (2016) Controllable nitrogen introduction into porous carbon with porosity retaining for investigating nitrogen doping effect on SO2 adsorption. Chem Eng J 290:116–124. https://doi.org/10.1016/j.cej.2015.12.044
Tai F, Shizhen Z, Jun L, Xiao X, Longzhi L, Xiqiang Z, Chunyuan M (2020) Experimental and thermodynamic study on SO2 reduction to elemental sulfur by activated coke and pyrolysis gas: Influence of the reaction atmosphere - ScienceDirect. Int. J. Hydrogen Energy
Vajda P, Felinger A (2014) Multilayer adsorption on fractal surfaces. J Chromatogr A 1324:121–127. https://doi.org/10.1016/j.chroma.2013.11.028
Wang A, Fan R, Pi X, Zhou Y, Chen G, Chen W, Yang Y (2018) Nitrogen-doped microporous carbons derived from pyridine ligand-based metal–organic complexes as high-performance SO₂ adsorption sorbents. ACS Appl Mater Interfaces 10:37407–37416. 10.1021/acsami.8b12739
Wang F, Cheng Y, Lu S, Jin K, Zhao W (2014) Influence of coalification on the pore characteristics of middle–high rank coal. Energy Fuels 28:5729–5736. 10.1021/ef5014055
Wang M, Xue H, Tian S, Wilkins RWT, Wang Z (2015) Fractal characteristics of Upper Cretaceous lacustrine shale from the Songliao Basin, NE China. Mar Pet Geol 67:144–153. https://doi.org/10.1016/j.marpetgeo.2015.05.011
Wang X, He R, Chen Y (2008) Evolution of porous fractal properties during coal devolatilization. Fuel 87:878–884. https://doi.org/10.1016/j.fuel.2007.05.038
Xu S, Zhou Z, Yu G, Wang F (2010) Effects of Pyrolysis on the Pore Structure of Four Chinese Coals. Energy Fuels 24:1114–1123. 10.1021/ef901008a
Yakout SM, Sharaf El-Deen G (2016) Characterization of activated carbon prepared by phosphoric acid activation of olive stones. Arab J Chem 9:S1155–S1162. https://doi.org/10.1016/j.arabjc.2011.12.002
Yan Z, Liu L, Zhang Y, Liang J, Wang J, Zhang Z, Wang X (2013) Activated Semi-coke in SO₂ Removal from Flue Gas: Selection of Activation Methodology and Desulfurization Mechanism Study. Energy Fuels 27:3080–3089. 10.1021/ef400351a
Yang F, Ning Z, Liu H (2014) Fractal characteristics of shales from a shale gas reservoir in the Sichuan Basin, China. Fuel 115:378–384. https://doi.org/10.1016/j.fuel.2013.07.040
Yao Y, Liu D, Tang D, Tang S, Huang W (2008) Fractal characterization of adsorption-pores of coals from North China: An investigation on CH₄ adsorption capacity of coals. Int J Coal Geol 73:27–42. https://doi.org/10.1016/j.coal.2007.07.003
You L, Chen Q, Kang Y, Yu Y, He J (2015) Evaluation of fromation damage using microstructure fractal in shale reservoirs. Fractals 23:1540008. 10.1142/S0218348X15400083
Zhang S, Tang S, Tang D, Huang W, Pan Z (2014) Determining fractal dimensions of coal pores by FHH model: Problems and effects. J Nat Gas Sci Eng 21:929–939. https://doi.org/10.1016/j.jngse.2014.10.018
Zhang Z, Wang T, Ke L, Zhao X, Ma C (2016) Powder-Activated Semicokes Prepared from Coal Fast Pyrolysis: Influence of Oxygen and Steam Atmosphere on Pore Structure. Energy Fuels 30:896–903. https://doi.org/10.1021/acs.energyfuels.5b02488
Zhu J, Ye Sc, Bai J, Wu Zy L, Zh Y, Yf (2015) A concise algorithm for calculating absorption height in spray tower for wet limestone–gypsum flue gas desulfurization. Fuel Process. Technol. 129:15–23. https://doi.org/10.1016/j.fuproc.2014.07.002
Zhu JF, Liu JZ, Yang YM, Cheng J, Zhou JH, Cen KF (2016) Fractal characteristics of pore structures in 13 coal specimens: Relationship among fractal dimension, pore structure parameter, and slurry ability of coal. Fuel Process. Technol. 149:256–267. https://doi.org/10.1016/j.fuproc.2016.04.026

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You are reading this latest preprint version

Powder-Activated Coke Prepared from Coal Fast Pyrolysis: Fractal Characteristics and SO2 Adsorption

Status:

Version 1

Abstract

Figures

Introduction

Experiment

Sample preparation

Yield of PACs

Calculation of fractal dimension

SO₂ adsorption capacity of samples

Results And Discussion

Fractal characterization of PACs

Relation between fractal dimensions and activation agent concentration

Relationship between fractal dimension and yield

Relation between fractal dimensions and SO₂ adsorption characteristics

Conclusions

Declarations

References

Status:

Version 1

Powder-Activated Coke Prepared from Coal Fast Pyrolysis: Fractal Characteristics and SO2 Adsorption

Status:

Version 1

Abstract

Figures

Introduction

Experiment

Sample preparation

Yield of PACs

Calculation of fractal dimension

SO2 adsorption capacity of samples

Results And Discussion

Fractal characterization of PACs

Relation between fractal dimensions and activation agent concentration

Relationship between fractal dimension and yield

Relation between fractal dimensions and SO2 adsorption characteristics

Conclusions

Declarations

References

Status:

Version 1

SO₂ adsorption capacity of samples

Relation between fractal dimensions and SO₂ adsorption characteristics