Furfural production from rice husk using sulfuric acid and a solid acid catalyst through a two-stage process

Article abstract of DOI:10.1016/j.carres.2012.07.006

This study aimed to optimize the conditions for furfural production from rice husk via a two-stage process: acid hydrolysis followed by dehydration using an orthogonal test design and response surface methodology, respectively. Orthogonal test design was utilized in the hydrolysis step; optimum conditions were as follows: 2.5% sulfuric acid (mass fraction), 110 °C reaction temperature, sulfuric acid to rice husk (L/S) ratio of 8 (g/mL), and a reaction time of 3 h. According to the Box-Behnken design, the temperature, amount of catalyst, extractant volume, and reaction time were chosen as four important factors with three levels for the dehydration step. Conditions were further optimized by response surface analysis. The results showed that the optimal conditions were 177 °C, 120 mL extractant volume, 2.1 g of catalyst, and a reaction time of 4.8 h. Under the optimal conditions, the furfural yield reached 8.9%, which is consistent with the estimated value, 8.97%.

Full text of DOI:10.1016/j.carres.2012.07.006

Carbohydrate Research 359 (2012) 1–6
Contents lists available at SciVerse ScienceDirect
Carbohydrate Research
journal homepage: www.elsevier.com/locate/carres
Furfural production from rice husk using sulfuric acid and a solid acid
catalyst through a two-stage process
⇑
Ren Suxia, Xu Haiyan, Zhu Jinling, Li Shunqing, He Xiaofeng, Lei Tingzhou
Energy Research Institute Co., Ltd of Henan Academy of Sciences, Key Biomass Energy Lab of Henan Province, Zhengzhou, 450008 Henan, China
a r t i c l e i n f o
a b s t r a c t
Article history:
This study aimed to optimize the conditions for furfural production from rice husk via a two-stage pro-
cess: acid hydrolysis followed by dehydration using an orthogonal test design and response surface
methodology, respectively. Orthogonal test design was utilized in the hydrolysis step; optimum condi-
tions were as follows: 2.5% sulfuric acid (mass fraction), 110 °C reaction temperature, sulfuric acid to rice
husk (L/S) ratio of 8 (g/mL), and a reaction time of 3 h. According to the Box–Behnken design, the temper-
ature, amount of catalyst, extractant volume, and reaction time were chosen as four important factors
with three levels for the dehydration step. Conditions were further optimized by response surface anal-
ysis. The results showed that the optimal conditions were 177 °C, 120 mL extractant volume, 2.1 g of cat-
alyst, and a reaction time of 4.8 h. Under the optimal conditions, the furfural yield reached 8.9%, which is
consistent with the estimated value, 8.97%.
Received 28 March 2012
Received in revised form 5 July 2012
Accepted 10 July 2012
Available online 20 July 2012
Keywords:
Furfural
Rice husk
Solid acid
Hydrolysis
Response surface methodology
Optimization
Ó 2012 Elsevier Ltd. All rights reserved.
1
. Introduction
trial uses of rice husk should be developed. As a major source of
carbohydrates, including cellulose, hemicellulose and lignin, rice
Biomass is one of the world’s most important renewable energy
sources. It has been reported that the sustainable production of
husk can be used directly for furfural production, thereby greatly
reducing the production cost.
1
.3 Pg of biomass per year can be achieved without significant
Furfural can be produced through a one- or two-stage pro-
1–3
14–16
changes in agricultural practices or food supplies.
Since annually
cess.
In the one-stage process, pentosan is hydrolyzed to xy-
renewable biomass contains 75% carbohydrates, converting these
carbohydrates into organic chemicals to ultimately replace those
derived from petrochemical resources is a major challenge for
lose and dehydrated to furfural within the same reactor. The
disadvantage of this method is that it gives a low furfural yield
1
4
(0.7–3.3%, mass fraction). In the two-stage process, hydrolysis
and dehydration reactions occur in separate reactors. There are
two advantages of the two-stage process: a higher furfural yield,
and utilization of the solid residue for the production of cellulose,
4
green chemistry.
Furfural is produced from the hemicellulosic fraction of bio-
mass,5 and has been identified as one of the top 30 high-value,
bio-based chemicals. Furfural is a versatile furan platform com-
pound comprised of a heteroaromatic furan ring and an aldehyde
1
5
glucose, and ethanol via fermentation. Homogenous acids, such
as sulfuric acid and phosphoric acid, are widely-used catalysts for
6
17,18
functional group. Commercial furfural production is currently car-
the conversion of lignocellulosic materials to furfural.
How-
ried out by acid catalytic dehydration of pentosan-containing lig-
ever, this results in several problems, including difficulties in acid
recovery, complicated separation of products, and environmental
pollution. Solid superacid is a type of acid with many advantages
over a liquid acid. For example, a solid superacid is easy to separate
from a reaction mixture and easy to regenerate and reutilize. Due
nocellulosic materials in
a
batch or continuous reactor.
Lignocellulose materials from agricultural waste that are rich in
pentosans, such as rice husks, oat hulls, cottonseed hull bran, al-
mond husks, and bagasse, have generally been preferred for the
commercial production of furfural.7
–13
Rice husk is a renewable,
to these advantages, a number of studies have focused on the solid
acid-catalyzed production of furfural from lignocelluloses.1
9,20
Due
cheap, and widely available biomass. The majority of rice husk is
burnt in China, resulting in severe environmental pollution. To en-
hance the value of rice husk and to decrease pollution, new indus-
to the high pentosan content of rice husk and the employment of
functionalized solid acid catalysts, this study aimed to optimize
the conditions in both the hydrolysis and dehydration stages for
the efficient production of furfural using SBA-15, a solid superacid
with high catalytic activity, by an orthogonal test design and
response surface methodology (RSM).
⇑
Corresponding author.
E-mail address: biomass_energy@yeah.net (L. Tingzhou).
0
008-6215/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.carres.2012.07.006

2
R. Suxia et al. / Carbohydrate Research 359 (2012) 1–6
Table 2
2
2
. Results and discussion
Experimental results of rice husk hydrolysis
.1. Optimization of the hydrolysis process by orthogonal test
Experiment
Coded level
C
The yield of xylose (%)
design
A
B
D
1
2
3
4
5
6
7
8
1
1
2
3
1
2
3
1
2
3
1
2
3
2
3
1
3
1
2
1
76.02
82.18
87.42
80.24
97.04
89.94
87.97
88.54
73.18
Independent variables with three variation levels are listed in
Table 1: A (reaction temperature), B (sulfuric acid concentration),
1
1
2
2
2
3
3
3
2
3
3
1
2
2
3
1
C (reaction time), and D (L/S ratio). In the present study, all selected
4
factors were examined using an orthogonal L
9
(3) test design. The
total evaluation index was analyzed by statistical methods.
Results of the orthogonal test are presented in Table 2. Accord-
ing to the R value, the factors affecting the hydrolysis rate are listed
in decreasing order as follows: C > B > A > D. The maximum hydro-
lysis rate was obtained when the factors were A2B2C3D1 (110 °C,
9
K1
K2
K3
R
81.873 81.410 84.833 82.080
89.073 89.253 78.533 86.697
83.230 83.513 90.810 85.400
2
.5%, 4 h, and 1:8), respectively. According to the R value, hydroly-
7.200
7.843 12.277
4.617
sis time was the most important determinant of hydrolysis rate. To
reduce production costs and avoid side reactions, the optimum
parameters were: A2B2C2D1 (110 °C, 2.5%, 3 h, and 1:8). After con-
firmation, a yield of 97.89% was obtained.
Table 3
Result and design table of Box–Behnken
Trial
x
1
x
2
x
3
x
4
Yield (%)
The yield of furfural (%)
6.33
2
.2. Optimization of the dehydration process by RSM
1
2
3
4
5
6
7
8
9
A
B
C
D
0
0
1
1
0
0
1
0
1
1
1
0
0
0
1
0
0
0
0
1
The statistical treatment combinations of the test variables,
8.30
4.62
6.27
8.65
3.72
4.86
4.18
5.65
3.64
5.32
7.00
8.62
4.41
6.53
4.40
6.56
7.06
4.51
6.01
4.72
4.91
7.01
8.50
8.08
5.96
along with the measured response values, are summarized in Table
, and expressed as the yield of furfural corresponding to each
3
ꢀ1
combination. The application of RSM yielded the following regres-
sion equation, which indicated an empirical relationship between
furfural yield and the test variable in coded units:
0
0
1
0
ꢀ1
ꢀ1
0
0
0
0
0
ꢀ1
1
ꢀ1
ꢀ1
1
1
0
1
1
0
0
Y ¼ 8:59 ꢀ 0:414167X
1
þ 1:12833X
2
þ 0:401667X
3
ꢀ1
ꢀ1
0
2
2
2
3
þ 0:569167X
4
ꢀ 2:21208X ꢀ 1:52333X ꢀ 1:03833X
12
0
0
0
0
ꢀ1
1
2
13
ꢀ1
1
0
1
0
2
4
ꢀ
ꢀ
0:949583X ꢀ 0:425X
1
X
2
ꢀ 0:3775X
1
X
3
ꢀ 0:32X
1
X
4
14
0
0
0
0
1
0
1
0
1
1
1
1
1
5
6
7
8
9
ꢀ1
0:985X
2
X
3
þ 0:21X
2
X
4
þ 0:3125X ð1Þ
3
X
4
;
ꢀ1
0
0
1
0
ꢀ1
where Y was the response, and X
1
, X , X , and X were the coded val-
2
3
4
ꢀ1
0
1
0
ues of temperature, solvent volume, catalyst amount, and reaction
time, respectively. The coefficients above Eq. 1 were calculated
using RSM, and their values are listed along with the parameter
estimates in Table 4.
The significance of each coefficient was determined using Stu-
dent’s t-test and P-values. The P-values were used to determine
the significance of each coefficient, which, in turn was necessary
to understand the pattern of the mutual interactions between the
test variables. The larger the magnitude of the t-value and the
smaller the P-value, the more significant the corresponding coeffi-
cient was. From Table 4, it is evident that the first-order main effect
ꢀ1
0
0
0
20
1
0
1
ꢀ1
2
2
2
2
1
2
3
4
1
0
ꢀ1
ꢀ1
0
0
ꢀ1
0
1
0
1
ꢀ1
0
0
0
0
0
0
0
ꢀ1
25
26
0
1
27
0
ꢀ1
ꢀ1
Table 4
Significance of regression for furfural yield
2
of solvent volume (X ) was highly significant, as indicated by its P-
value. This suggested that the solvent volume was directly related
to the production of furfural. The quadratic main effects of temper-
ature, solvent volume, catalyst amount, and time were also signif-
icant, with P-values of 0.000, 0.000, 0.002, and 0.004, respectively.
The three-dimensional response surface plots represent the
regression equation, which were drawn to illustrate the main
and interactive effects of the independent variables on the depen-
dent variable (Figs. 1–6). The maximum predicted values were
Variables
Coefficient
Stand error
T
P value
Constant
X1
X2
X3
X4
X1ꢁX1
X2ꢁX2
X3ꢁX3
X4ꢁX4
X1ꢁX2
X1ꢁX3
X1ꢁX4
X2ꢁX3
X2ꢁX4
X3ꢁX4
8.59
0.3529
0.1764
0.1764
0.1764
0.1764
0.2646
0.2646
0.2646
0.2646
0.3056
0.3056
0.3056
0.3056
0.3056
0.3056
24.344
ꢀ2.348
0.000
0.037
0.000
0.042
0.007
0.000
0.000
0.002
0.004
0.190
0.240
0.316
0.007
0.505
0.327
ꢀ0.414167
1.12833
0.401667
0.569167
ꢀ2.21208
ꢀ1.52333
ꢀ1.03833
ꢀ0.949583
ꢀ0.425
6.395
2.277
3.226
ꢀ8.359
ꢀ5.756
ꢀ3.924
ꢀ3.588
ꢀ1.391
ꢀ1.235
ꢀ1.047
ꢀ3.223
0.687
ꢀ0.3775
ꢀ0.32
Table 1
Variables and levels used according to L9(3) 4 orthogonal experimental design
ꢀ0.985
Variables
Symbol
Levels
2
0.21
0.3125
1.023
1
3
Reaction temperature (°C)
Sulfuric acid concentration (%, mass fraction)
Reaction time (h)
A
B
C
D
100 110
120
3
4
2
2
8
2.5
3
10
indicated by the surface confined in the smallest ellipse in the con-
tour diagram. Elliptical contours were obtained when there was a
perfect interaction between the independent variables.21 These
L/S ratio (mL/g)
12

R. Suxia et al. / Carbohydrate Research 359 (2012) 1–6
3
Figure 1. 3D graphic surface optimization of furfural yield versus temperature and
amount of solvent.
Figure 2. 3D graphic surface optimization of furfural yield versus temperature and
amount of catalyst.
graphs were drawn by imposing two other variables at the zero
levels.
dosage, 2.1 g of catalyst, and a 4.8 h reaction time. Based on the re-
sults from the verification experiment, an actual furfural yield of
There was a relative significant interaction between every two
variables, and a maximum predicted yield, indicated by the surface
confined in the smallest ellipse in the contour diagrams. The
amount of solvent played an important role in the experiments,
as was evident from its P-value. We observed a quadratic effect
of solvent amount on the response (Figs. 1, 4, and 5), which sug-
gested that an increased amount of solvent may not be able to
boost the yield of furfural under the experimental conditions. As
shown in Figures 1–3, the reaction temperature showed similar re-
sults to that of the solvent amount. At temperatures above 180 °C,
the yield of furfural began to decrease. Although high temperatures
could accelerate the rate of conversion of carbohydrates to furfural,
unwanted side reactions may also build simultaneously. Theoreti-
cally, a higher amount of catalyst should obtain a higher yield of
furfural. However, it was determined that the yield of furfural de-
creased after a certain ratio was reached due to this factor (Figs. 2,
8
.9% was achieved. These data show that the predicted and actual
values were similar, and so indicated that the experimental model
has significance. Additional results regarding the yield of furfural
from alternate substrates are shown in Table 5.
3
. Conclusions
A two-stage process that consisted of hydrolysis followed by
dehydration was used for the production of furfural. In the first
step, the optimum conditions were 2.5% sulfuric acid and an L/S ra-
tio of 8 mL/g for 3 h. The maximum yield of xylose was 97.89%. In
the second step, we concluded that the effect of solvent amount
was highly significant for furfural production. The quadratic main
effects of temperature, reaction time, and catalyst amount were
also significant. By employing the optimum experimental condi-
tions, a furfural yield of 8.9% was achieved.
4
, and 6). Reaction time exhibited a relatively significant interac-
tion with other variables. The temperature, solvent amount, and
amount of catalyst significantly affected the time required for the
overall reaction. As shown in Figures 3, 5, and 6, there was an opti-
mal conversion process time. This suggests that if hydrolysis con-
tinued for too long, the yield would decrease again as the result
of side reactions of furfural.
According to the Minitab software response optimizer analysis,
the maximum estimate of Y was 8.97%. The values of the four main
factors were: 177 °C reaction temperature, 120 mL extraction
4. Experimental
4.1. Materials
Rice husk was obtained from Zhengzhou City (China), washed
thoroughly with distilled water to remove adhering soil and dust,
and dried at 105 °C for over 12 h and porphyrized to 60 mesh be-
fore use. The hemicellulose, cellulose, lignin, and ‘other’ contents

4
R. Suxia et al. / Carbohydrate Research 359 (2012) 1–6
Figure 3. 3D graphic surface optimization of furfural yield versus temperature and
reaction time.
Figure 4. 3D graphic surface optimization of furfural yield versus amount of
catalyst and solvent.
(
e.g., ash) of dry rice husk were 18.5%, 35.8%, 25.3%, and 20.4%,
catalyst, SBA-15 (1–3 g), were placed in the autoclave, and toluene
(50–150 mL), as a mixed solvent, was added simultaneously. The
autoclave was closed and then heated. After the reaction, the resi-
due was filtered and the liquid was collected for the determination
of furfural yield.
respectively.
4
4
.2. Experimental process
.2.1. Synthesis of functionalized solid acid catalyst SBA-15
The procedure for solid acid catalyst synthesis was as described
4.3. Optimization of furfural production
2
2
previously. Mercaptopropyltrimethoxysilane (MPTMS; Sigma Al-
drich) was added as the sulfonic group precursor. The molar com-
position of the mixture for 4 g of pluronic 123 (P123) was: 0.0328
4.3.1. Optimization of hydrolysis using an orthogonal test
design
tetraethoxysilane (TEOS), 0.0082 MPTMS, 0.0738 H
2
O
2
, 0.24 HCl,
Factors such as reaction temperature, acid concentration, reac-
tion time, and L/S ratio can greatly influence the degree of xylan
hydrolysis. Therefore, the influence of these four factors on hydro-
lysis was investigated. However, single-factor experiments neither
determined the optimal combination of the four factors, nor did
they determine which factor had the greatest influence on xylose
yield. Therefore, an orthogonal test design was employed to solve
this problem. Independent variables with three variation levels, A
(reaction temperature), B (sulfuric acid concentration), C (reaction
and 6.67 H O. The MPTMS/(TEOS + MPTMS) ratio was set to 0.2.
2
The silica precursor was hydrolyzed at 40 °C for 20 h. These mate-
rials were prepared at an aging temperature of 100 °C for 24 h.
After solvent extraction, the wet material was suspended in 1 M
sulfuric acid for 2 h at room temperature. The solid product, SBA-
3
SO H, was re-filtered, washed with ethanol, and dried.
4
.2.2. Furfural production by a two-stage process
The scheme of the two furfural production reactions is shown in
time), and D (L/S ratio) are listed in Table 1. In the present study, all
4
Figure 7. For acid hydrolysis, rice husk and dilute sulfuric acid were
mixed into a 100 mL stainless steel autoclave with a Teflon inner
lining. The autoclave was closed and placed into a pre-heated oven.
The autoclave was kept in the oven for a given period of time to
hydrolyze the xylan in the rice husk. After the reaction, the auto-
clave was removed and allowed to cool by natural convection.
The solid rice husk residue and liquid were then filtered. For dehy-
dration, the collected filtrate (50 mL) and functionalized solid acid
selected factors were examined using an orthogonal L
9
(3) test de-
sign. The total evaluation index was analyzed by statistical
methods.
4.3.2. Optimization of the dehydration process by RSM
RSM is an efficient tool for establishing the relationship of vari-
ables of interest (at least two) with the obtained responses. The
experimental data were fitted to a smooth curve, which was

R. Suxia et al. / Carbohydrate Research 359 (2012) 1–6
5
Figure 5. 3D graphic surface optimization of furfural yield versus time and amount
Figure 6. 3D graphic surface optimization of furfural yield versus time and amount
of solvent.
of catalyst.
plotted by calculating the specific predicted response. Therefore,
RSM established a relationship between the variables and re-
sponses more professionally than did traditional design. A Box–
Behnken experimental design, with four variables, was used to
study the response pattern and to determine the optimum combi-
nation of variables. The range of each parameter was: temperature
Table 5
Comparison of furfural yield produced from various substrates using a two-stage
process
Raw material
Investigator
Yield based on weight of
raw material (%)
Mansilla et al.14
Punsuvon et al.
Rice hull
Hemicellulose
(xylose) of bagasse
ꢂ10.5
ꢂ10.3
(
1
(
X
1
) 160–200 °C (central value = 180 °C), solvent volume (X
50 mL (central value = 100 mL), amount of catalyst (X ) 1–3 g
central value = 2 g), and time (X ) 2–6 h (central value = 4 h). For
statistical calculations, the variables were coded according to Eq.
2
) 50–
15
3
Hemicellulose of dPPF Wiboon Riansa-
17.34
8.9
4
ngawong et al.16
This study
Rice husk
2:
x
i
¼ ðX
i
ꢀ X
0
Þ=D
X
i
i ¼ 1; 2; 3; 4
ð2Þ
where x
i
was the coded value of the independent variable, X
i
was
0
the real value of the independent variable, X was the real value
of the independent variable on the center point, and
step-change value.
i
DX was the
The furfural yield was taken as the dependent variables or re-
sponse, Y . The proposed model for the response is:
HO
O
OH
HO
OH
i
H+
2
2
2
3
HO
OH
CHO
Y
i
¼ k þ k
þ k44X þ k12
o
1
X
2
1
þ k
2
X
2
þ k
3
X
3
þ k
4
X
4
þ k11X þ k22X þ k33
X
1
2
O
2
H O
O
O
H2O
n
X
1
X
X
2
þ k13
X
1
X
3
þ k14
X
1
X
4
þ k23
X
2
X
3
4
Figure 7. Hydrolysis of rice husk using solid acid catalyst by two-stage process.
þ k24
X
2
X
4
þ k34
3
X
4
;
ð3Þ
where Y
i
was predicted response, k
0
was the offset term, k
, k
1 2
and
k
3
were linear effect terms, k11, k22, k33, and k44 were squared
i
function (Y ), using the regression Eq. 3. The fitted polynomial equa-
effects, and k12, k13, k14, k23, k24, and k34 were interaction effects.
The behavior of the surface was investigated for the response
tion was expressed as a surface plot to visualize the relationship be-
tween the response and experimental levels of each factor, and to

6
R. Suxia et al. / Carbohydrate Research 359 (2012) 1–6
deduce the optimum conditions. The computer software used for
this study was Minitab 15.
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1
Md
The yield of xylose ¼
ꢃ 100%;
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1
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in which Md represents the mass of xylose in the hydrolyzate, and
Mx represents the mass of xylan in the rice husk.
Furfural content was then analyzed by gas chromatography
15. Punsuvon, V.; Vaithanomsat, P.; Iiyama, K. Maejo Int. J. Sci. Technol. 2008, 2,
(
GC-FID). The flow rate of helium was 1.2 mL/min. Injection and
detection port temperatures were 230 °C and 250 °C, respectively.
The injection volume was 1 L. The initial oven temperature was
0 °C for 1 min, followed by a ramp of 20 °C/min to a final temper-
182–191.
1
6. Wiboon, Riansa-ngawong; Poonsuk, Prasertsan Carbohydr. Res. 2011, 346, 103–
10.
7. Yat, S. C.; Berger, A.; Shonnard, D. R. Bioresour. Technol. 2008, 99, 3855–3863.
1
l
1
7
18. Vázquez, M.; Oliva, M.; Téllez-Luis, S. J.; Ramírez, J. A. Bioresour. Technol. 2007,
8, 3053–3060.
1
9
ature of 180 °C, which was held for 2 min. Under these conditions,
furfural had a retention time of 5.9 min. The furfural yield from rice
husk was calculated as:
9. Chareonlimkun, A.; Champreda, V.; Shotipruk, A.; Laosiripojana, N. Bioresour.
Technol. 2010, 101, 4179–4186.
20. Tomishige, K.; Ikeda, Y.; Sakaihori, T.; Fujimoto, K. J. Catal. 2000, 192, 355–362.
1. Muralidhar, R. V.; Chirumamila, R. R.; Marchant, R.; Nigam, P. Biochem. Eng. J.
001, 9, 17–23.
22. Agirrezabal-Telleria, I.; Requies, J.; Güemez, M. B.; Arias, P. L. Appl. Catal., B
012, 115–116, 169–178.
2
2
furfural contentðgÞ
Yield of Furfural ¼
ꢃ 100%
2
rice husk cententðgÞ