Abstract
In the process of acid hydrolysis of cellulose, hydrolyzing the amorphous regions while retaining the crystalline regions is the key technology for obtaining microcrystalline cellulose products. This paper investigated the influence of FeCl3 on selective acid hydrolysis of crystalline regions and amorphous regions of cellulose. X-ray diffraction data indicated that FeCl3 can enhance the selectivity of acid hydrolysis for amorphous regions of cellulose, thus improving the crystallinity of hydrocellulose. Meanwhile, the crystalline structure did not change. Response surface methodology (RSM) was employed to optimize the crystallinity of hydrocellulose with respect to FeCl3 concentration, HCl concentration, reaction time, and temperature, and the relevant mathematical regression equation model was established. Under optimal conditions, the crystallinity of hydrocellulose was as high as 63.59% at 88.28 °C, 2.46 M HCl, 0.4 M FeCl3, and reaction duration of 64.02 min, which was in agreement with the predicted value.
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Optimization of Selective Acid Hydrolysis of Cellulose for Microcrystalline Cellulose using FeCl3
Jinbao Li,a,b,* Xiangrong Zhang,a,* Meiyun Zhang,a Huijuan Xiu,aand Hang He a,b
In the process of acid hydrolysis of cellulose, hydrolyzing the amorphous regions while retaining the crystalline regions is the key technology for obtaining microcrystalline cellulose products. This paper investigated the influence of FeCl3 on selective acid hydrolysis of crystalline regions and amorphous regions of cellulose. X-ray diffraction data indicated that FeCl3 can enhance the selectivity of acid hydrolysis for amorphous regions of cellulose, thus improving the crystallinity of hydrocellulose. Meanwhile, the crystalline structure did not change. Response surface methodology (RSM) was employed to optimize the crystallinity of hydrocellulose with respect to FeCl3 concentration, HCl concentration, reaction time, and temperature, and the relevant mathematical regression equation model was established. Under optimal conditions, the crystallinity of hydrocellulose was as high as 63.59% at 88.28 °C, 2.46 M HCl, 0.4 M FeCl3, and reaction duration of 64.02 min, which was in agreement with the predicted value.
Keywords: Microcrystalline cellulose; Amorphous regions; Hydrocellulose; Metal ions; Response surface methodology
Contact information: a: College of Light Industry and Energy, Shaanxi University of Science & Technology, Shaanxi Province Key Lab of Papermaking Technology and Specialty Paper, Xi’an 710021,China; b: State Key Lab of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510641, China;
* Corresponding authors: lijinbao@sust.edu.cn; xiangrongzhangsust@163.com
INTRODUCTION
Microcrystalline cellulose (MCC) is a type of structural material made from natural cellulose that has been hydrolyzed by inorganic acid or by enzymolysis. Acid hydrolysis is the predominant method for industrial microcrystalline production because of the lower price and higher degree of crystallinity compared to that obtained from enzymes (Adel et al. 2011; Hanna et al. 2001; Lee et al. 2009). It is a highly flowable particulate material having a short rod or granular structure, and is odourless and tasteless. The degree of polymerization of MCC is usually lower than 350, and the average particle size is between 20 and 40 μm (Abd-Allah et al. 2009). Due to the special characteristics of insolubility in water, dilute acid, and organic solvents as well as great hygroscopicity, MCC has been widely used in pharmaceuticals, foods, and chemicals (daily and industrial) (Uesu et al. 2000).
The raw material sources for MCC are predominantly wood fiber and cotton fiber. Considering the production costs and other issues, other non-wood raw materials such as soybean, bagasse, corn stalk, rice husk, peanut shell, and other agricultural wastes have also aroused attention as potential MCC sources in recent years (Adel and El-Shinnawy 2012; Okhamafe et al. 1995). Because of differences in the natural aggregation structures of crystalline and amorphous regions, the crystalline regions from high purity cellulose are used in the production of MCC, which is a high value-added product. However, current technologies have a poor selectivity between amorphous and crystalline regions in the process of acid hydrolysis, resulting in low yields and poor product properties, especially in the case of MCC made from non-wood raw materials (Abd-Allah et al. 2009). Meanwhile, the hydrolysate from amorphous regions is discarded, resulting in a lot of waste. Therefore, a method to promote the degradation of the amorphous regions by acid hydrolysis while retaining crystalline regions as much as possible is essential to MCC production. Moreover, improving the selectivity of the amorphous regions and realizing the “Orientation” hydrolysis of cellulose can allow a significant improvement on the yield and crystallinity of the MCC.
Metal inorganic salts as catalysts for enhancing the hydrolysis efficiency of cellulose has been demonstrated by many researchers. Nguyen and Tucker (2002) found that a small amount of FeSO4 can significantly improve the reducing sugar content of the cellulose hydrolysis liquid of coniferous sawdust, while the hydrolysis efficiency of cellulose can be enhanced in the presence of Fe3+ and H+ (Ren et al. 2012). Recently, Kamireddy et al. (2013) reported the mechanism of cellulose degradation by inorganic metal salts such as FeCl3, CuCl2, and AlCl3. However, many researchers have focused primarily on the preparation of MCC using different raw materials, so the reports on the efficient promotion of cellulose selective acid hydrolysis by metal ions for MCC preparation are limited. To enhance the selectivity of acid hydrolysis in cellulose amorphous regions, this study focused on the methods and mechanism of transition metal ion assisted catalytic acid hydrolysis with the purpose of obtaining a higher degree of hydrolycellulose crystallinity.
The response surface method (RSM) is an empirical modeling technique derived for evaluation of the relationship of a set of multiple variables or factors (Karunanithy and Muthukumarappan2011). RSM can be used to optimize the selective acid hydrolysis of cellulose for MCC by FeCl3 catalysis. Different parameters affecting crystallinity of hydrocellulose, including FeCl3 concentration, HCl concentration, reaction time, and temperature were examined. This work was also undertaken to develop a useful tool to predict and optimize the selective hydrolysis process of cellulose, which mainly focused on the effects of inorganic metal salt in the process of hydrolysis for MCC production. The corresponding mathematical regression model equation was used to provide some theoretical guidance for MCC preparation.
EXPERIMENTAL
Materials
Dissolving pulp from Eucalyptus sulfate pulp, the raw material for MCC in this study, was received from Shan Dong Pulp & Paper Co., Ltd. (China). The main constituents were α-cellulose (92.26%) and a small amount of hemicelluloses. The brightness was 86.8%ISO and the ash content was 0.08%. The pulp was separated and dewatered by water immersion for 24 h before use. All chemicals (e.g., FeCl3•6H2O, HCl) were of analytical grade and purchased from Beijing Chemical Reagent Co. (China).
Pulp slurry (10 g) in 500 mL three-mouth flasks was treated with varying concentrations of HCl and FeCl3 solution (solid-liquid ratio of 1:15) and stirred at 120 rpm. The flasks were heated to various temperatures and reaction times in a constant temperature water bath. Samples were taken from the reaction mixture under different reaction parameters according to the experimental design (see Table 1). Each sample from the hydrolysis solution was immediately washed with deionized water until the filtrate was at neutral pH. Then the sample was centrifuged to remove the water and air-dried. The obtained products of hydrocellulose were used in subsequent testing.
Central Composite Design (CCD)
On the basis of the single factor experimental results from previous studies (Zhang et al. 2012; Li et al. 2013), a four-factor three-level response CCD, which required 27 runs (3 replicates of the central runs, 8 stars (2n), and 16 factorial runs by 2n, n = 4) was used to optimize the FeCl3 acid hydrolysis of cellulose for MCC. Table 1 shows the range of the independent variables and experiment design levels used in this study.
The four variables and their value range were chosen based on preliminary studies. Three-dimensional surface and contour analysis were applied to investigate and validate the influence of process variables on crystallinity from the hydrolysis of cellulose. FeCl3concentration (0.2 to 0.4 M), HCl concentration (1.0 to 4.0 M), reaction time (40.0 to 70.0 min), and temperature (65.0 to 90.0 °C) were input parameters; the crystallinity of hydrocellulose was coded R in the statistical analysis as the response value. The factors were coded in levels (-1.546, -1, 0, 1, 1.546) before fitting the model.
Table 1. Coded Values of the Variables for the Central Composite Design
Analytical Methods
The fracture surface morphology of hydrocellulose was characterized with a Hitachi S-4800 (Hitachi, Tokyo, Japan) scanning electron microscope (SEM). The samples were gold coated and analyzed at an accelerating voltage of 3 kV.
The crystalline structure of samples were analyzed by X-ray diffraction (XRD) on a D/max-2200 PC automatic XRD (Rigaku Co. Ltd., Tokyo, Japan) using a Ni-filtered Cu-Kα radiation source (λ =0.1518 nm). The X-ray diffractograms were recorded from 6° to 50° 2θ with a goniometer at a scanning speed of 2°/min. The crystallinity was calculated by the total diffracted area and the area under the crystalline peaks, which were determined by integration after correcting the data for absorption. The ratio of the crystallinity of samples to the standard formless materials was taken as the relative crystallinity, which is represented as follows,
Cr = Fc /(Fa+ Fc) ×100% (1)
where Cr is the relative crystallinity, whereas Fa and Fc are the area of noncrystalline and crystal regions, respectively (Sun et al. 2008). Each sample was measured at least twice to reduce errors.
Statistical Analysis
The data were analyzed using Design-Expert software 7.1.6 (Stat-Ease, Minneapolis, MN, USA). The mathematical relationship between the response of these variables and the independent variables can be expressed by second-degree quadratic polynomial equation (Qi et al. 2009),
R = b0 + b1X1 + b2X2 + b3X3 + b4X4 + b11X12 + b22X22+b33X32 + b44X42+ b12X1X2 + b13X1X3 + b14X1X4+b23X2X3 + b24X2X4 + b34X3X4 (2)
where R is the predicted value, b0 is the constant, X1 is the FeCl3concentration, X2 is the HCl concentration, X3 is reaction time, X4 is the temperature, b0 is the offset term, b1, b2, b3, and b4 are linear coefficients, b12, b13, b14, b23, b24, and b34 are cross-product coefficients, and b11, b22, b33, and b44 are quadratic coefficients. The accuracy and general ability of the above polynomial model can be evaluated by the coefficient of determination R2. Analysis of variance (ANOVA) was employed to determine the interaction effects between the factors, and a quadratic surface plot was generated (Teh et al.2013). The adequacy of the model was tested using ANOVA, a normal probability plot, and a residual plot. An F-test was used to determine the statistical significance of the model and the significance of the regression coefficients.
RESULTS AND DISCUSSION
Effect of FeCl3 Addition on Cellulose Hydrolysis
To determine optimal acid hydrolyzing efficiency, the concentration of FeCl3 varied from 0.1 to 0.4 M, while the concentration of HCl was fixed at 3 M. The hydrolysis temperature and time were set at 90 °C and 55 min, respectively. The relationship of Fe3+ concentration, crystallinity, and cellulose yield under these conditions are shown in Fig. 1.
Fig. 1. Effect of FeCl3 dosage on the yield and crystallinity of hydrocellulose
The results in Fig. 1 clearly show that cellulose yield declined and crystallinity increased with increasing FeCl3 concentration. The H+can diffuse into the amorphous regions and surfaces of crystalline region and break the intramolecular glycosidic bonds of cellulose. These processes lead to physical swelling along with the chemical degradation of cellulose and result in the decreasing of yield. This phenomenon shows that the addition of metal ions can improve the acid hydrolyzing selectivity of amorphous regions, resulting in an improvement of crystallinity of the hydrolyzed cellulose (Li et al.2010).
A possible explanation is that cellulose in the crystalline region is more difficult to access by the acids due to its crystalline nature and tight structure (Li et al. 2013). This difference in cellulose structure determines the selectivity of acid hydrolysis. Metal ions can increase the rate of acid hydrolysis in amorphous regions. Oxygen atoms O5, and carbon atoms C2, C3, and C6 from the cellulose glucose unit have a higher reaction activity, with oxygen atoms readily adsorbing Fe3+to form an annular intermediate complex which increased the pyranose ring bond angles and bond length, and lowered the activation energy of the reaction (Zhao et al. 2011). In addition, the hydrolysis of cellulose is enhanced in acidic solution (Ma et al.2005), as shown in the following balance equation:
x Fe3+ + yH2O 
Fex (OH) y(3x-y)+ + yH+ (3)
Fe3+ can dissociate into complex ions in aqueous solvent such as water. They form coordinate covalent bond with some water molecules and more H+ was generated. Due to the increase in H+concentration in the reaction system with the increase of Fe3+concentration, H+ can effectively degrade the glycoside bond between cellulose glucose unit. Hence, the catalyst FeCl3 increased the rate of hydrolysis reaction and provided a high crystallinity of MCC.
SEM Observation
The SEM micrographs of cellulose and hydrocellulose were analyzed to investigate the structure of these fibers (Fig. 2). The samples under the experimental conditions of 0.3 M FeCl3, while the concentration of HCl was fixed at 3 M, and the hydrolysis temperature and time were set at 90 °C and 55 min, respectively. The untreated samples showed an even and smooth surface at low magnification, indicating a rigid and highly ordered surface structure (Fig. 2a).
At a higher magnification, folds and large number of cracks on the fiber surface were apparent, which provided a larger contact area and therefore higher accessibility of cellulose by acid and catalyst (Fig. 2b). Following acid hydrolysis, the fibers were degraded into short, broken fragments (Fig. 2c to Fig. 2d). Also, the degradation of the fiber caused a transverse fracture, and also appeared to have a certain degree of erosion and peeling. The average fiber length was 57 μm. After the addition of FeCl3, the degree of fiber degradation increased and the average length of particles was reduced by up to 48 μm (Fig. 2e and Fig. 2f).
Fig. 2. SEM micrographs of (a, b) normal cellulose (c, d) hydrocellulose fibers, and (e, f) hydrocellulose fibers treated with 0.3 M FeCl3
XRD Analysis
As shown in Fig. 3, the characteristic X-ray diffraction pattern of all diffractograms showed the typical crystalline structure of native cellulose or cellulose I. As indicated by the similar curves and peaks in the figure, the whole structure of cellulose was not transformed by acid hydrolysis. But the peak intensity of hydrocellulose was high, at 22.5° of diffraction, and the dispersion peak intensity of the amorphous portion was relatively low, near 18°. A possible explanation is that the glycosidic bond from amorphous regions was partially degraded and cleaved in the process of hydrolysis, while the well-organized crystalline regions changed little and thus there was an increase in crystallinity. The results show that the crystallinity of hydrocellulose with different treatments were: cellulose raw material, 49.98%; hydrocellulose without FeCl3 treatment, 53.78%; and hydrocellulose with 0.3 M FeCl3 treatment, 63.59%. This provided evidence that FeCl3 can accelerate the selective acid hydrolysis of cellulose and consequently improve the crystallinity of hydrocellulose.
Fig. 3. XRD of samples (a = cellulose; b = hydrocellulose without FeCl3 treatment; c = hydrocellulose with 0.3 M FeCl3 treatment)
Regression Models of Response
The statistical treatment combinations of the test variables along with the measured response values, expressed as the crystallinity of hydrocellulose corresponding to each combination, are summarized in Table 2.
Table 3 shows the F-test and the corresponding P-value along with the parameter estimation. The lower the P-value, the higher the significance of the corresponding P-value coefficient (Majumder and Goval 2008). The model F-value of 43.40 and values of probability (P)>F (<0.0001) showed that the model terms were significant. The coefficient of variation (CV) indicated the degree of precision with which the treatments were compared. A relatively low value of CV(1.43%) indicated a better precision and reliability of the experiments (Hou and Chen 2008). The coefficient of determination (R2) was calculated to be 0.98 for the crystallinity, indicating that the statistical model can explain 98% of the variability in the response. Normally, a regression model with an R2 higher than 0.90 is considered to have a very high correlation (Duret et al. 2013). The parameter estimates and the corresponding P-values suggested that, among the independent variables, X2, X4 and X1, X3 have significant effects on the crystallinity of hydrocellulose.
Table 2. Central Composite Design Matrix and Results
Table 3. Analysis of Variance for the Quadratic Model
*P-value less than 0.05 indicates model terms are significant. R2=0.9806, The “Pred R-Squared” of 0.9268 is in reasonable agreement with the “Adj R-Squared” of 0.9580.
The quadratic terms of X1, X2, and X4 and interactions between X2and X4 also had significant effects on the crystallinity. A statistically significant model only with significant terms can be written as follows,
R=59.16+0.61X1+2.75X2+0.57X3+2.93X4-0.26X1X2-0.093X1X3-0.32X1X4
+0.093X2X3-1.69X2X4-0.067X3X4+0.68X12-1.05X22+0.12X32-0.69X42 (4)
Figure 4 shows the response surface of the crystallinity. The crystallinity is represented as a function of FeCl3 concentration and HCl concentration, reaction time, or temperature. As shown, the optimal crystallinity was mainly influenced by the HCl concentration and the temperature. The possible explanation is that acids can diffuse into the amorphous region and small part of surfaces of crystalline region. This indicated that the intermolecular hydrogen bonds and intramolecular glycosidic bonds of cellulose are easily fractured, which led to physical swelling along with the chemical degradation of cellulose.
Fig. 4. Response surface plots and contour plots of the combined effects of FeCl3 concentration and HCl concentration (a), reaction time (b), and temperature (c) on the crystallinity of hydrocellulose while other two factors were set at corresponding center points
Swelling of the cellulose increased the contact area between acids and cellulose, and hence improved the hydrolysis efficiency. The increase of the FeCl3 concentration was beneficial to the improvement of the crystallinity when the HCl concentration was low (Fig. 4a). As can be seen from Fig. 4b, the influence of reaction time on the crystallinity was not appreciable. A significant increase in the crystallinity can be found when the temperature increased, and the contour plot showed that a high crystallinity of hydrocellulose was obtained at a higher temperature (Fig. 4c). This was in agreement with the predicted model. However, the results showed that the addition of FeCl3affected the selective acid hydrolysis of cellulose for MCC, and factors affecting the crystallinity of hydrocellulose were in the order of: reaction temperature > HCl concentration > FeCl3 concentration > time.
Effect of Independent Variables on Crystallinity and Adequacy of the Models
The second-order polynomial regression equation obtained from the experimental data can be used to predict the crystallinity of hydrocellulose under various FeCl3 concentrations, HCl concentrations, reaction temperatures, and times within the range of the experimental design. In order to confirm the validity of the statistical experimental strategies and gain a higher crystallinity of MCC by selective hydrolysis of cellulose, the optimum hydrolysis conditions were as follows: FeCl3 concentration, 0.4 M; HCl concentration, 2.46 M; reaction temperature, 88.28 °C; and reaction time, 64.02 min; the crystallinity predictive value of hydrocellulose was 62.45%. The results of three parallel tests showed that the actual crystallinity of hydrocellulose was 63.59%. The percent error between the actual and predicted values for hydrolysis was observed to be 1.79%. The predicted values and actual experimental values were compared (Table 2), and the residual and percentage error calculated. Therefore, the empirical models developed were reasonably accurate, which verified that RSM analysis is indeed a useful technique to predict and optimize the selective acid hydrolysis of cellulose for microcrystalline cellulose preparation by FeCl3.
CONCLUSIONS
- FeCl3 can be used as catalyst for selective hydrolysis of cellulose. Addition of FeCl3 helps to improve the efficiency of acid hydrolysis and enhance the hydrolysis of amorphous regions compared with no catalyst.
- X-ray diffraction results showed that the crystalline structure of cellulose was not changed by the acid hydrolysis treatment. Under the experimental conditions, the crystallinity of hydrocellulose after hydrolysis can be achieved at 63.59%, an increase of 13.61% compared to cellulose without the addition of FeCl3.
- The RSM was performed to optimize the acid hydrolysis selectivity of cellulose. The results showed that the concentration of FeCl3 plays an auxiliary role on acid hydrolysis of cellulose. The regression equation was obtained by RSM, and theoretical crystallinity was obtained under following conditions: FeCl3 concentration, 0.4 M; HCl concentration, 2.46 M; reaction temperature, 88.28 °C; and reaction time 64.02 min. The theoretical value of the crystallinity was 62.45%, while the actual value was 63.59%. Therefore, the RSM with CCD design is useful for identifying and optimizing the important factors influencing acid hydrolysis selectivity of cellulose.
ACKNOWLEDGMENTS
This project was financially supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China (grant NO.20126125130001), the State Key Lab of Pulp and Paper Engineering Open Fund (grant NO.201215), Shaanxi
Province Natural Science Fund Project (grant NO.2013JM2007) and the Doctoral Scientific Research Fund by Shaanxi University of Science & Technology (grant NO.BJ13-02).
REFERENCES CITED
Abd-Allah, M. A. N., Mohamed, Y. E. K., Essam S, A. E. S., and Fatma, M. A. (2009). “Preparation and characterization of microcrystalline cellulose (MCC),” BioResources 4(4), 1359-1371.
Adel, A. M., El-Wahab, Z .H. A., Ibrahim, A. A., and Al-Shemy, M. T. (2011). “Characterization of microcrystalline cellulose prepared from lignocellulosic materials. Part II: Physicochemical properties,” Carbohydrate Polymers 83(2), 676-687.
Adel, A. M., and El-Shinnawy, N. A. (2012). “Hypolipidemic applications of microcrystalline cellulose composite synthesized from different agricultural residues,” International Journal of Biological Macromolecules 51(5), 1091-1102.
Duret, X., Fredon, E., Masson, E., Deshamais, L., and Gérardin, P. (2013). “Optimization of acid pretreatment in order to increase the phenolic content of Picea abies bark by surface response methodology,” BioResources 8(1), 1258-1273.
Hanna, M., Blby, G., and Miladinove, V. (2001). “Production of microcrystalline cellulose by reactive extrusion,” US Patent 6,228, 213.
Hou, X. J., and Chen, W. (2008). “Optimization of extraction process of crude polysaccharides from wild edible BaChu mushroom by response surface methodology,” Carbohydrate Polymers 72(1), 67-74.
Kamireddy, S. R., Li, J. B., and Tucker, M. (2013). “Effects and mechanism of metal chloride salts on pretreatment and enzymatic digestibility of corn stover,” I&EC Research 52(5), 1775-1782.
Karunanithy, C., and Muthukumarappan, K. (2011). “Optimization of alkali, big bluestem particle size, and extruder parameters for maximum enzymatic sugar recovery using response surface methodology,” BioResources 6(1), 762-790.
Lee, S. H., Doherty, T. V., Linhardt, R. J., and Dordick, J. S. (2009). “Ionic liquid-mediated selective extractive of lignin from wood leading to enhanced enzymatic cellulose hydrolysis,” Biotechnology and Bioengineering 102(5), 1368-1376.
Li, J. B., Xiu, H., Zhang, M., Wang, H., Ren, Y., and Ji, Y. (2013). “Enhancement of cellulose acid hydrolysis selectivity using metal ion catalysts,” Current Organic Chemistry 17(5), 1617-1623.
Li, J. L., Chen, G. X., and Ye, D. Y. (2010). “Progress of research on preparation and application of nanocellulose whiskers,” Chemistry and Industry of Forest Products 30(2), 121-125.
Ma, Y., He, J., and Ma, R. (2005). “Fe(Ⅲ) behaviors in acid solution,” Hu Nan Nonferrous Metals 21(1), 36-38.
Majumder, A., and Goyal, A. (2008). “Enhanced production of exocellular glucansucrase from Leuconostoc dextranicum NRRL B-1146 using response surface method,” Bioresource Technology 99(9), 3685-3691.
Nguyen, Q. A., and Tucker, M. P. (2002). “Dilute acid/metal salt hydrolysis of lignocellulosics,” US Patent 6,423,145.
Okhamafe, A. O., Ejike, E. N., Akinrinola, F. F., and Ubane-Ine, D. (1995). “Aspect of tablet disintegrant properties of cellulose derived from bagasse and maize cob,” West African Journal of Pharmacy9(1), 8-13.
Qi, B. K., Chen, X. R., Shen, F., Su, Y., and Wan, Y. H. (2009). “Optimization of enzymatic hydrolysis of wheat straw pretreated by alkaline peroxide using se surface methodology,” Industrial & Engineering Chemistry Research 48(15), 7346-7353.
Ren, L. B., Cao, Q., and Xie, X. L. (2012). “Hydrolysis kinetics of microcrystalline cellulose catalyzed by Fe3+ and dilute hydrochloric acid,” Chemistry and Industry of Forest Products 32(4), 117-122.
Sun, Y., Lin, L., Deng, H. B., Li, J. Z., He, B. H., Sun, R. C., and Quyang, P. K. (2008). “Structural changes of bamboo cellulose in formic acid,” BioResources 3(2), 297-315.
Teh, C. C., Ibrahim, N. A., and Yunus, W. M. Z. W. (2013). “Response surface methodology for the optimization and characterization of oil palm mesocarp fiber-graft-poly (butyl acrylate),” BioResources 8(4), 5244-5260.
Uesu, N. Y., Pineda, E. A. G., and Hechenleitner, A. A. W. (2000). “Microcrystalline cellulose from soybean husk: Effects of solvent treatments on its properties as acetylsalicylic acid carrier,” International Journal of Pharmaceutics 206(1), 85-96.
Zhang, Y., Zhang, M., Li, J., and Zhang, B. (2012). “Research on the desiliconization process of wheat straw microcrystalline cellulose,” Journal of Biobased Materials and Bioenergy 5(2), 203-208.
Zhao, J., Zhang, H. M., Zheng, R. P., Lin, Z. X., and He, H. (2011). “The enhancement of pretreatment and enzymatic hydrolysis of corn stover by FeSO4 pretreatment,” Biochemical Engineering Journal56(3), 158-164.
Article submitted: December 10, 2013; Peer review completed: January 12, 2014; Revised version received: January 14, 2014; Accepted: January 18, 2014; Published: January 27, 2014.