Lu Qiuab,
Yan Chengab,
Chunping Yang*abc,
Guangming Zengab,
Zhiyong Longab,
Sainan Weiab,
Kun Zhaoab and
Le Luoab
aCollege of Environmental Science and Engineering, Hunan University, Changsha, Hunan 410082, P. R. China. E-mail: yangc@hnu.edu.cn
bKey Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, Hunan 410082, P. R. China
cZhejiang Provincial Key Laboratory of Solid Waste Treatment and Recycling, College of Environmental Science and Engineering, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, P. R. China
First published on 3rd February 2016
In this paper, the performance of catalytic oxidative desulfurization from model oil was studied using a catalyst of molybdenum supported on modified medicinal stone (Mo/MMS). The catalyst was successfully prepared by the sorption method and characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR) and N2 adsorption–desorption. The removal rate of dibenzothiophene (DBT) reached 97.5% within 60 min under conditions of catalyst dosage of 0.50 g, a reaction temperature of 100 °C, an oxidant/sulfur molar ratio (O/S) of 5.0 and the volume of model oil of 20 ml. The Box–Behnken design was used to evaluate the influence of the main operating parameters, including oxidation temperature (40–120 °C), oxidation time (40–80 min) and O/S (1.0–5.0) on DBT removal. The optimum values were found to be 103 °C, 62 min and 4.0, respectively. The removal rate of DBT reached a maximum at 98.1%. Statistical results also showed the degree of importance was: O/S > oxidation temperature > oxidation time. Sulfur removal dropped to 92.2% from 98.1% when the catalyst was reused 5 times. These results prove that the Mo/MMS catalyst could be cost-effective for removal of DBT from oil.
Up to now, there are many alternative deep desulfurization techniques, such as oxidative desulfurization (ODS), hydrodesulfurization (HDS), biodesulfurization, adsorption, extraction and so on.2–4 Conventional HDS is effective for thiols, sulfides and disulfides, but it can't effectively remove aromatic thiophenes, such as benzothiophene (BT), dibenzothiophene (DBT), 4,6-dimethyldibenzothiophene (4,6-DMDBT) and their alkylated derivatives,1,4–7 because of their steric hindrance.5 HDS technologies require strict operating conditions including higher temperature, higher pressure, expensive hydrogen and a large amount of active catalysts to produce low sulfur oil.5,7–9 In order to meet these requirements, costs for operating and maintenance are often too high. ODS has been considered as a promising new method for deep desulfurization of fossil oil.2 In ODS, refractory organosulfur compounds are usually oxidized to the corresponding sulfones which are then removed by extraction, adsorption, distillation, or decomposition.2,9 ODS is often carried out at the atmospheric pressure and moderate temperature as well as without using expensive hydrogen.2,10
In ODS, the final sulfur content still cannot meet the requirements of deep desulfurization without a catalyst.10 The active components of catalysts are mainly composed of transition-metals, such as palladium, iridium, nickel, platinum, molybdenum, rhodium, titanium and tungsten.3,10–14 Chica et al.14 studied the activity and stability of Ti-MCM-41 catalyst for ODS in a continuous fixed-bed reactor, and it can achieved complete oxidation of DBT into DBT–sulfone. Molybdenum has been shown as an active catalyst in ODS in the form of molybdenum trioxide. For example, Han et al.10 reported the oxidative desulfurization of DBT by phosphorous-modified MoO3/SiO2 catalysts, and the sulfur removal rate reached 98.32%. Prasad et al.6 found that Bi-modified MoO3/SiO2–Al2O3 (1% SiO2:
99% Al2O3) showed the best catalytic performance compared to all the catalysts examined in the oxidation of 4,6-DMDBT.
Supports of catalyst such as silica, activated carbon, alumina, resins and molecular sieves2,3,9–15 play an important role in ODS. These supports can improve the activity of catalysts and promote the separation of catalysts from reaction systems. However, some supports are either expensive or complex for preparation. In recent years, medicinal stone has gained much attention due to its some special properties, such as the sponge structure, special porous and relatively large specific surface area.16 The porous medicinal stone with 10 nm aperture has huge specific surface area and can be used as an excellent absorbent.17 Medicinal stone is a cheap and readily available mineral substance. The main chemical components are SiO2, Al2O3, Fe2O3, CaO, MgO, K2O, Na2O, etc.18 Then it is easy for us to infer that the medicinal stone could be used as the support of catalyst in ODS.
The aim of this work is to prepare, characterize and evaluate a cost-effective catalyst for ODS. Molybdenum was chosen as a catalyst, and modified medicinal stone (MMS) was used as the support. The influences of various factors including reaction temperature, reaction time, oxidant/sulfur molar ratio and the amount of catalyst were evaluated. The reuse of the catalyst was also examined. The Box–Behnken design was selected to determine the optimum conditions for ODS and to illustrate the relations between sulfur removal and three independent variables including oxidation temperature, oxidation time, and oxidant/sulfur molar ratio. The results are supposed to show the feasibility of the catalytic oxidative desulfurization system for DBT removal.
The catalyst was characterized by powder X-ray diffraction (XRD) using a Rigaku Dmax 2500 diffractometer equipped with a monochromator and a Cu target tube to investigate the crystal structure of the samples. A scanning electron microscope (SEM) study of the samples was performed using a Hitachi S-4800 electron microscope in order to observe the surface morphology of the Mo/MMS catalyst and MMS. The Fourier transform infrared spectrometer (FT-IR) experiments were operated on FTIR spectrophotometer (VARIAN 3100 FTIR) with the frequency range of 400–4000 cm−1. The samples were diluted with KBr and pressed into flakes. Spectra were obtained at the resolution of 4 cm−1 and room temperature. Textural properties of the samples were obtained by N2 adsorption–desorption isotherms (Micromeritics Tristar II 3020). Specific surface areas were calculated by the BET method, the total pore volume was obtained by nitrogen adsorption at a relative pressure of 0.98 and pore size distribution was analyzed from the desorption isotherms and calculated by the BJH method. The molybdenum content of the catalyst was measured by inductively coupled plasma-atomic emission spectrometry (ICP-AES) (Perkin Elmer Optima 3300DV).
η = [(C0 − C)/C0] × 100% | (1) |
The recovery of model oil was calculated using the following relationships:
ε = [(m0 − m)/m0] × 100% | (2) |
In this study, response surface methodology was used for statistical analysis of the experimental data using Design Expert software version 8.0.5. The influence of main factors included oxidation temperature X1 (40–120 °C), oxidation time X2 (40–80 min) and O/S X3 (1–5). As shown in Table 1, each variable was coded at three levels: 1, 0, and −1, which represented the high level, center point and low level, respectively. A total of 17 experiments and the results were summarized in Table 2. A second-order model in the form of quadratic polynomial equation was used for the optimization process.23
Y = β0 + ∑βixi + ∑βiixi2 + ∑βijxixj |
Independent variables | Code | Range and levels | ||
---|---|---|---|---|
−1 | 0 | 1 | ||
Oxidation temperature (°C) | X1 | 40 | 80 | 120 |
Oxidation time (min) | X2 | 40 | 60 | 80 |
Oxidant/sulfur ratio | X3 | 1.0 | 3.0 | 5.0 |
Run | Coded values | Actual values | Sulfur removal (%) | ||||||
---|---|---|---|---|---|---|---|---|---|
X1 | X2 | X3 | X1 | X2 | X3 | Actual | Predicted | Residual | |
1 | −1 | 0 | −1 | 40 | 60 | 1.0 | 82.10 | 81.40 | 0.70 |
2 | 1 | −1 | 0 | 120 | 40 | 3.0 | 94.00 | 93.53 | 0.47 |
3 | 0 | 0 | 0 | 80 | 60 | 3.0 | 96.89 | 96.94 | −0.052 |
4 | 0 | 1 | 1 | 80 | 80 | 5.0 | 94.72 | 94.37 | 0.35 |
5 | 0 | 1 | −1 | 80 | 80 | 1.0 | 84.23 | 84.46 | −0.35 |
6 | 0 | 0 | 0 | 80 | 60 | 3.0 | 96.73 | 96.94 | −0.21 |
7 | −1 | 0 | 1 | 40 | 60 | 5.0 | 87.37 | 87.25 | 0.12 |
8 | 0 | −1 | −1 | 80 | 40 | 1.0 | 83.65 | 84.00 | −0.35 |
9 | −1 | −1 | 0 | 40 | 40 | 3.0 | 86.40 | 86.75 | −0.35 |
10 | 1 | 0 | 1 | 120 | 60 | 5.0 | 96.85 | 97.55 | −0.70 |
11 | 0 | −1 | 1 | 80 | 40 | 5.0 | 93.20 | 92.97 | 0.23 |
12 | 1 | 0 | −1 | 120 | 60 | 1.0 | 84.40 | 84.52 | −0.12 |
13 | 0 | 0 | 0 | 80 | 60 | 3.0 | 97.00 | 96.94 | 0.058 |
14 | 1 | 1 | 0 | 120 | 80 | 3.0 | 94.73 | 94.38 | 0.35 |
15 | 0 | 0 | 0 | 80 | 60 | 3.0 | 96.99 | 96.94 | 0.048 |
16 | 0 | 0 | 0 | 80 | 60 | 3.0 | 97.10 | 96.94 | 0.16 |
17 | −1 | 1 | 0 | 40 | 80 | 3.0 | 87.30 | 87.76 | −0.46 |
Samples | BET area (m2 g−1) | Average pore size (nm) | Pore volume (cm3 g−1) |
---|---|---|---|
MS | 54.3 | 22.4 | 0.30 |
MMS | 75.6 | 23.1 | 0.43 |
Mo/MMS catalyst | 68.3 | 21.5 | 0.34 |
Powder XRD patterns of MMS and Mo/MMS catalyst were shown in Fig. 2. As seen in Fig. 2, all samples showed some sharp peaks at approximately 20.69° and 26.65°, which were attributed to the crystalline silica. The XRD patterns of these samples were exactly similar, and no sharp peaks of MoO3 were found in the patterns. It indicated that MMS structures didn't change and metal species were well dispersed on the surface of MMS. The results obtained on Mo/MMS catalyst agreed with the literature reported.16 However, Mo/MMS catalyst presented a significant decrease in the intensity of the diffraction peaks compared with MMS it could be due to the absorption coefficient of impregnated metal species.25
FT-IR spectra of the Mo/MMS catalyst and MMS were depicted in Fig. 3. As shown in Fig. 3, the samples supported MoO3 maintained the characteristic peaks of MMS. Typical peaks of Si–O–Si could be observed at 1088 cm−1 and 460 cm−1.19,26 This vibration corresponded to the Si–O–Si bonds in the all of the samples. Meanwhile, it can be seen that the FTIR spectrum of Mo/MMS catalyst showed three distinct absorption bands: 985 cm−1 (Mo–O–Mo symmetric stretch), 890 cm−1 (Mo–O–Mo asymmetric stretch) and 662 cm−1 (terminal MoO stretch), which could be assigned to molybdenum trioxide.12,15 It indicated that the metal might has been load in the support. This result was consistent with the observation from SEM (Fig. 1).
Some structure parameters of all samples (MS, MMS and Mo/MMS catalyst) were summarized in Table 3. The surface area is 54.3 m2 g−1 for MS. The surface area and pore volume of MMS was larger than that of MS, indicating that MS was successfully modified. Compared with MMS, the surface area of Mo/MMS catalyst decreased slightly; average pore size and total pore volume also decreased. These decrements in the textural properties may be related with molybdenum loading in MMS.15 The adsorption–desorption isotherm of Mo/MMS catalyst was presented in Fig. 4. The features of Mo/MMS catalyst isotherm can be attributed to IV adsorption isotherm according to IUPAC classification, characterizing the presence of mesopores.27 The isotherm showed a H3 hysteresis loop, typical for materials with slit shape pores of non-uniform size or shape.5 The inset of Fig. 4 illustrated the pore size distribution. A pore size distribution with maximum at 20 nm can be observed. The molecular diameter of DBT is much smaller than the pore diameter of the catalyst. Therefore, the pore of the catalyst is enough to allow DBT molecules to diffuse into the pores where most of the active sites for ODS are located.
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Fig. 7 Effect of reaction temperature on DBT removal and the yield rate of model oil. Conditions: catalyst dosage of 0.50 g, O/S of 3.0, time of 40 min and the volume of model oil of 20 ml. |
Besides, the yield rate of model oil was also affected by temperature (Fig. 7). As the temperature increased from 40 °C to 120 °C, the yield rate of model oil declined sharply from 95.1% to 86.4%. Obviously, model oil lost due to volatilization and gasification at higher temperatures. Hence, the temperature of 100 °C presented the best desulfurization result.
Y = 96.94 + 3.35X1 + 0.47X2 + 4.72X3 − 0.043X1X2 + 1.79X1X3 + 0.23X2X3 − 3.08X12 − 2.53X22 − 5.46X32 |
The results of analysis of variance (ANOVA) were presented in Table 4. The significance of each parameter was evaluated by the calculated Fischer values (F-test) and probability values (p-value). The corresponding parameter is more significant if its p-value is smaller than 0.05 at 95% confidence level.22,33 Obviously, as shown in Table 4, the model F-value of 192.08 and values of “Prob > F” less than 0.0001 indicated the model was significant. There was only a 0.26% chance that a “Model F-Value” this large could occur due to noise. The “Lack of Fit F-value” of 34.42 implied the lack of fit was significant. In this study, the independent variables of the quadratic model oxidation temperature X1, oxidation time X2 and O/S X3, the interaction between temperature and O/S (X2X3) and the interaction between time and O/S (X1X3) were quite significant because the p-value was less than 0.05. Judging by the F-values of the items in the regression model, the oxidant/sulfur ratio (X3) had the highest F-value (594.37) with lowest p-value (<0.0001) among other parameters, so the order in which the independent parameters influenced the oxidative desulfurization efficiency was: O/S X3 > oxidation temperature X1 > oxidation time X2.
Source | SS | DF | MS | F | p |
---|---|---|---|---|---|
a DF: degree of freedom of different source; SS: sum of square, MS: mean of square; F: degree of freedom; P: probability. | |||||
Model | 518.37 | 9 | 57.60 | 192.08 | <0.0001 |
Oxidation temperature, X1 | 89.85 | 1 | 89.85 | 299.63 | <0.0001 |
Oxidation time, X2 | 1.74 | 1 | 1.74 | 5.80 | 0.0469 |
O/S, X3 | 178.23 | 1 | 178.23 | 594.37 | <0.0001 |
X1X2 | 7.225 × 10−3 | 1 | 7.225 × 10−3 | 0.024 | 0.8810 |
X1X3 | 12.89 | 1 | 12.89 | 42.98 | 0.0003 |
X2X3 | 0.22 | 1 | 0.22 | 0.74 | 0.4191 |
X12 | 60.87 | 1 | 60.87 | 203.00 | <0.0001 |
X22 | 27.00 | 1 | 27.00 | 90.04 | <0.0001 |
X32 | 125.51 | 1 | 125.51 | 418.57 | <0.0001 |
Residual | 2.10 | 7 | 0.30 | ||
Lack of fit | 2.02 | 3 | 0.67 | 34.42 | 0.0026 |
Pure error | 0.078 | 4 | 0.020 | ||
Total | 520.47 | 16 | |||
R-Squared 0.9960 | Adj R-squared 0.9908 | Pred R-squared 0.9376 |
The accuracy of the model was determined by the residual analysis. The comparison between the removal rate of sulfur, obtained from the empirical model, and observed experimental data was presented in Fig. 10(a). According to previous studies,20 both of the coefficients of determination, R2 and adjusted R2 should be at least 0.80 for a better fit of a model. In this case, the coefficient of determination (R2) of the regression model was 0.9960 (Fig. 10(a)), meaning that more than 99.60% of the data deviation could be explained by the empirical model, which showed that the regression model was statistically significant. Besides, the R2-Adj value was 99.08%, indicating that the experimental results were in good agreement with the predicted values. Fig. 10(b) illustrated the normal probability plot of the residual. Obviously, the acquired data points appeared on a linear relationship consistently, which indicated the random error was independently and normally distributed. The residual plot versus run number was presented in Fig. 10(c). The random residuals were distributed around the line, which showed that model was appropriate. In addition, the adequacy of the model could be evaluated by the residuals calculated by determining the difference between the experimental and the predicted the removal rate of sulfur.
In this study, response surfaces can be visualized as contours and 3D plots which obtained from the predicted models. The resulting of both contours and 3D surface response plots demonstrated the variation of the response with two independent variables while holding the other variable fixed, as a function of (a) oxidation temperature and oxidation time (O/S = 3.0), (b) oxidation temperature and O/S (t = 60 min) and (c) oxidation time and O/S (T = 80 °C), respectively. The results were presented in Fig. 10. The elliptical form of each contour plot can help to understand the effect of various interactions on sulfur removal and also to determine optimum level of each variable.
As can be seen in Fig. 11(a), at the lower oxidation time, sulfur removal decreased gradually at the lower or higher of the oxidation temperature. Also, when a high level of temperature was applied (120 °C), the removal rate of sulfur was found to climb up and then decline by increasing time of reaction. From these results, the maximum sulfur removal (>96.03%) was observed in the region where the oxidation time was limited to 45 < t < 75 min at a moderate level of temperature (88 °C < T < 98 °C). An appropriate increase in temperature caused the molecular movement to speed up and increased the reaction probability between oxidant and sulfur compounds. Fig. 11(b) represented response surface plot of two variables oxidation temperature and O/S while oxidation time was kept constant at 60 min. The highest sulfur removal (>96.03%) occurred when O/S and oxidation temperature were kept at about 2.5–5.0 and 70–96 °C, respectively. It was obvious that the variation of O/S is more important than oxidation temperature. The reason may be that lessen of oxidant concentration would cause an incomplete conversion of the sulfur compounds to sulfone or sulfoxide. Fig. 11(c) illustrated the effect of oxidation time and O/S on sulfur removal at the oxidation temperature of 80 °C. It was obvious that at a low level of oxidant ratio, sulfur removal was consistent nearly with increasing time of reaction and similar results were obtained by Mokhtar et al.22 It has been seen that the variation of oxidant ratio has a significant impact on the removal rate of sulfur, while the variation of oxidation time was less important. From these results, it could be summarized that the degree of importance of these variables on sulfur removal was: oxidant/sulfur molar ratio > oxidation temperature > oxidation time, which was the same as the previous result.
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Fig. 11 Contours and 3D surface plots of the removal rate of DBT for: (a) oxidation temperature and oxidation time, (b) oxidation temperature and O/S and (c) oxidation time and O/S. |
The optimized conditions for three main parameters: oxidant/sulfur molar ratio, oxidation temperature and time were obtained by response optimizer. The values of the independent variables for the maximum removal rate of sulfur were presented in Table 5. The predicted response (sulfur removal) was found to be 99.0%, under the optimum conditions: oxidation temperature of 103 °C, oxidation time of 62 min and O/S of 4.0, respectively. The predicted conditions were validated by conducting an experiment thrice for the reproducibility of the data. The removal rate of sulfur of 98.1% (average of three replicates) was obtained by using optimized conditions which was nearly 0.9% lower than predicted value. The results were economically and technically feasible. Mokhtar et al.22 reported the optimization of oxidative desulfurization of diesel fuel using RSM. About 84.5% sulfur removal could be achieved for 4,6-DMDBT under the optimum conditions: 3.0 of TBHP/S molar ratio, 48 °C and 31 min. 4,6-DMDBT removal in real diesel was lower (77%). It might be real oil containing a variety of sulfur compounds that make the oxidation difficult to occur. Therefore, RSM could be successfully applied in the optimization of oxidative desulfurization experiment to maximize the sulfur removal after comprehensive consideration of the affecting factors.
Parameter | Values |
---|---|
Sulfur removal (%) | 99.0 |
X1 (oxidation temperature, °C) | 103 |
X2 (oxidation time, min) | 62 |
X3 (oxidant/sulfur ratio) | 4.0 |
Mo/MMS catalyst exhibited excellent desulfurization performance for DBT removal. DBT removal reached 97.5% in 60 min at a catalyst dosage of 0.50 g, temperature of 100 °C, O/S of 5.0 and the volume of model oil of 20 ml.
The Box–Behnken design was used to evaluate the influences of the main operating parameters, including oxidation temperature (40–120 °C), oxidation time (40–80 min) and O/S (1.0–5.0) on DBT removal in the process of ODS. The degree of importance was: O/S > oxidation temperature > oxidation time. The maximum DBT removal was 99.0% and 98.1% for the predicted and experimental data, respectively under the optimum conditions of oxidation temperature of 103 °C, oxidation time of 62 min and O/S of 4.0.
DBT removal dropped from 98.1% to 92.2% when the catalyst regenerated five rounds under the optimal removal conditions.
Mo/MMS catalyst showed the potential to be cost-effective and reusable in ODS.
This journal is © The Royal Society of Chemistry 2016 |