ORIGINAL PAPER

Impact of Ball-Milling Pretreatment on Pyrolysis Behaviorand Kinetics of Crystalline Cellulose

Amir Sada Khan1,2 • Zakaria Man1 • Mohammad Azmi Bustam1•

Chong Fai Kait4 • Muhammad Irfan Khan1 • Nawshad Muhammad3 •

Asma Nasrullah4 • Zahoor Ullah1 • Pervaiz Ahmad5

Received: 22 July 2015 / Accepted: 8 December 2015 / Published online: 30 December 2015

� Springer Science+Business Media Dordrecht 2015

Abstract Effect of ball-milling pretreatment on pyrolysis

characteristics of cellulose was studied by thermogravi-

metric analysis (TGA) at four different heating rates; 5, 10,

20, and 40 K/min. Variation in the thermal stability and

activation energy of cellulose with ball-milling were cal-

culated by TGA Kinetics using Kissinger, Kissinger–

Akahira–Sunose, Flynn–Wall–Ozawa and Starink model

free methods. Results demonstrated that ball-milling

reduced the thermal stability and activation energy of

cellulose. The original and ball-milled cellulose were

thoroughly characterized by Fourier-transform infrared

spectroscopy, X-ray diffraction, and Scanning electron

microscopy. X-ray diffraction analysis revealed that ball-

milling decreased the crystallinity of cellulose from 93 to

51 %. The results suggested that ball-milling pretreatment

led to effective disruption of crystalline cellulose to

amorphous cellulose. It is, therefore, concluded that the

ball-milled cellulose can easily become a useful source of

chemicals and energy than crystalline cellulose.

Keywords Cellulose � Ball-milling � Crystallinity index �Thermokinetics � Activation energy

Abbreviations

TGA Thermogravimetric analysis

KAS Kissinger–Akahira–Sunose

FTIR Fourier-transform infrared spectroscopy

XRD X-ray diffraction

NMR Nuclear magnetic resonance spectroscopy

CV Calorific values

CC Crystalline cellulose

BMC Ball-milled cellulose

b Heating rates

Tmax Temperature of the peak

Ea Activation energy

cm-1 Wavenumber

CI Crystallinity index

a Conversion factor

n Reaction order

A Pre-exponential factor

R Ideal gas constant

Introduction

Industrial revolution is largely dependent on energy

resources, and existing natural energy resources such as

natural gas, oils, and coal are exhaustible. Besides the rapid

consumption of fossil fuel, these conventional energy

Electronic supplementary material The online version of thisarticle (doi:10.1007/s12649-015-9460-6) contains supplementarymaterial, which is available to authorized users.

& Amir Sada Khan

aamirsada_khan@yahoo.com

& Nawshad Muhammad

nawshadchemist@yahoo.com

1 Centre of Research in Ionic Liquid, Department of Chemical

Engineering, Universiti Teknologi PETRONAS,

31750 Tronoh, Malaysia

2 Department of Chemistry, University of Science and

Technology, Bannu 28100, Khyber Pakhtunkhwa, Pakistan

3 Interdisciplinary Research Centre in Biomedical Materials,

COMSATS Institute of Information Technology, Lahore,

Pakistan

4 Fundamental and Applied Science Department, Universiti

Teknologi PETRONAS (UTP), 31750 Tronoh, Perak,

Malaysia

5 Department of Physics, Faculty of Science, University of

Malaya, 50603 Kuala Lumpur, Malaysia

123

Waste Biomass Valor (2016) 7:571–581

DOI 10.1007/s12649-015-9460-6

resources also threaten our ecosystem by emitting haz-

ardous gases during their combustion. Thus, the demand

and search for alternative energy resources are important to

meet vast energy requirements [1, 2]. Recently, lignocel-

lulosic biomass is mainly composed of cellulose, has been

introduced as an alternative to fossil fuel because of its

abundance, environmental friendliness, and sustainability.

Therefore, cellulose which is most abundant component of

biomass can contribute to energy and chemical demands in

the future [3–6].

Cellulose is the homo-polymer consists of glucopyra-

nose repeating unit. The repeating units are linking toge-

ther by b-(1?4) glycosidic bonds formed between C-1 and

C-4 of the adjacent glucose. The chemical formula of

cellulose is (C6H10O5) n and structurally it consists of long

straight chains without branching. The long-chains are

interlinked through hydrogen bonding (results from inter-

action of hydrogen atom of one chain with hydroxide group

of another chain) and van der Waals forces, which cause

the cellulose to be packed into microfibrils [5, 7]. These

close packing of chains via intermolecular and

intramolecular hydrogen bonding limit the solubility and

conversion/hydrolysis of cellulose into energy and chemi-

cals [8]. Cellulose is containing both crystalline and

amorphous components. The amorphous component is

more important than the crystalline region because of its

easy degradation and conversion into chemicals and fuels.

The higher reactivity of amorphous cellulose than crys-

talline cellulose (CC) can be attributed to the lower cohe-

sive energy density of the former than the latter [4].

In the last few years, various chemical and physical

methods have been applied to decrease the crystallinity

and molecular weight of cellulose for efficient conversion/

hydrolysis to glucose and others chemicals. In chemical

methods, strong acids [9–12] and ionic liquids [13–15] are

usually used to decrease the crystallinity of cellulose and

ultimately its hydrolysis to chemicals. Acid and ionic

liquid treatments decrease the crystallinity and facilitate

the conversion of cellulose. However, the applications of

such treatments are limited by the high cost, toxicity,

corrosive nature, and environmental pollution of ionic

liquids. Physical treatments are more environmental

friendly than chemical treatments because the former does

not need any solvent. Ball-milling is a powerful physical

technique used to modify the structure of cellulose [16–

18].

Pyrolysis is one of the most efficient methods in con-

verting cellulose into valuable chemicals and fuels. It is

thermal process and conducted in the absence of oxygen.

During pyrolysis, the molecules of cellulose are broken

down to low molecular weight gases (volatiles), liquids

(tars) and solid char. The volatile gases and liquids are both

very important from energy point of view because of their

high calorific value (CV). Thermogravimetric analysis

(TGA) is a rapid and effective quantitative method used to

understand the pyrolysis under nonisothermal and isother-

mal conditions, and to determine the kinetic parameters of

the thermal decomposition of cellulose. These kinetic

parameters include activation energy (Ea), reaction order

(n), and pre-exponential factor (A). The activation energy is

a dominant factor that gives considerable information

about cellulose reactivity. Determining kinetic parameters

via TGA is essential to design and establish efficient, safe,

and reasonable processes. Kissinger [19], Ozawa [20],

Flynn–Wall [21], and Friedman [22] proposed model free

kinetics methods. The model-free methods are extensively

used because of their simplicity and low error risk. The

model free kinetics methods are used to evaluate simple

and complex kinetic reactions without prior knowledge of

the reaction mechanism [18]. These all models are based

on the following general expression;

dadt

¼ Ae �EaRTð Þf að Þ ð1Þ

To the best of our knowledge, there is a very little

information available on the effect of mechanical treatment

on the pyrolysis process of cellulose. This study is the first

systematic study to investigate the effect of a mechanical

treatment (i.e., ball-milling) on the kinetics of thermal

decomposition of cellulose. Kinetic parameters were

determined by using Kissinger, Kissinger–Akahira–Sunose

(KAS), Flynn–Wall–Ozawa (FWO) and Starink methods.

The effect of ball-milling on the crystallinity and mor-

phology of cellulose was thoroughly characterized by

Fourier-transform infrared spectroscopy (FTIR), X-ray

diffraction (XRD, and scanning electron microscopy

(SEM). The calorific values (CVs) of the cellulose sample

before and after ball-milling were determined. Investigat-

ing the effect of ball-milling on the crystallinity and ther-

mal decomposition kinetics of cellulose using various

model free methods is a significant contribution.

Experimental

Ball-Milling of Cellulose

The crystalline cellulose (CC) was supplied by Merck

Malaysia. The cellulose was milled using planetary ball

mill (Fristch, Germany, S. No: 05.6000/00594) for 2 h with

a milling frequency 600 rpm. A 20 g cellulose sample was

placed in a zirconium oxide bowl (500 mL) with 25 zir-

conium oxide balls (1 cm diameter) during milling. To

prevent overheating of cellulose, 5 min of interval was

provided between every 30 min of milling. This ball-milled

cellulose (BMC) was used for further analysis.

572 Waste Biomass Valor (2016) 7:571–581

123

Characterizations of Cellulose

The FTIR spectra of crystalline and ball-milled cellulose

were recorded using FTIR spectroscopy (Perkin–Elmer

spectrum one, US). FTIR spectra were recorded within the

wavenumber range of 4000–450 cm-1 with a resolution of

5 cm-1. The CV of cellulose samples was determined by

using a bomb calorimeter (Ika-Werke of Gmbh& Co Kg).

XRD analysis of untreated and BMC samples was carried

out with a Philips powder diffractometer using a Ni-filtered

Cupper K-alpha radiation (wavelength 1.5418 A). The

diffracted intensities were measured within the range of 5�to 40� (2h). The thermal characteristics or weight-loss

profiles of CC and BMC were investigated using a ther-

mogravimetric analyzer (Perkin Elmer, STA 6000) over the

temperature range of 373–723 K at various heating rates of

5, 10, 20, and 40 K/min. The analysis was conducted using

N2 gas with a flow rate of 50 mL/min and sample weight of

5–7 mg.

Kinetic Study

Kissinger Kinetic Method

This method allows to obtain the value of activation energy

from a plot of ln(b/Tmax2 ) against 1000/Tmax for experiments

performed at different heating rates (b), where Tmax is the

temperature of the peak of the DTG curve, representing the

maximum decomposition point. The equation can be

expressed as

lnb

T2max

� �¼ ln

A � REa � g að Þ

� �� E

RTmaxð2Þ

Using this equation, the activation energy (Ea) can be

calculated from the slope of the plot of ln bT2max

� �against

1000/Tmax, which is equal to � Ea

R.

Ozawa Method

The simple mathematical form of the Ozawa method can

be expressed as

ln bð Þ ¼ lnAE

Rg

� �� 5:331 � 1:052

E

RTð3Þ

where g(a) represents mechanism and is considered as a

unity and constant at a given value of conversion. The

subscript a denotes the value of conversion. The activation

energy Ea can be calculated from the slope (-1.052Ea/R)

of plot of ln(b) against 1000/Tm at different heating rates

[20].

Kissinger–Akahira–Sunose Method (KAS)

The KAS method is also called the generalized Kissinger

method [19] and is based on the following expression:

lnbiT2ai

� �¼ ln

AaR

Eaga

� �� Ea

RTaið4Þ

where the subscript i denotes the ordinal number of a non-

isothermal experiment conducted at the heating rate bi and

the subscript a denotes the quantity evaluated at a specific

conversion fraction. This method allows us to calculate the

apparent activation energy from a plot of ln(bi/Ta,i2 ) versus

1000/Ta,I for a given value of conversion, a, where the

slope is equal to -Ea/R.

Starink Method

In Starink method [23], both FWO method and KAS

method can be transferred into the following formula.

lnb

T1:92

� �¼ Const � 1:0008

E

RTð5Þ

where b is the heating rate, R is the universal gas constant

and T is the absolute temperature. In 1996 Starink devel-

oped new method by adjusting the value of s and B used in

FWO and KAS methods. In Starink method the apparent

activation energy calculated from the slope of each line by

plotting ln bT1:92

� �versus 1000/T.

Results and Discussion

Energy Transfer During Ball Milling

During ball-milling, the energy is transferred to materials.

The transfer of energy can be explained by considering a

simple collision theory; that is, the mechanical energy of

planetary ball mill is transferred via vial wall–ball and

ball–ball collision [24–27]. This transfer of energy depends

on various variables, such milling time, ball weight ratio,

ball number, and angular velocity of the ball mill plate. The

transfer of kinetics energy to the powder occurs when the

powder comes between the balls, converting cellulose into

small pieces [28–30].

FTIR Analysis

To study the effect of ball-milling on the crystallinity of

cellulose, FTIR spectra were recorded before and after ball-

milling (supplementary Fig. 1). The spectra show that ball-

Waste Biomass Valor (2016) 7:571–581 573

123

milling can affect the spectra of cellulose. The changes in

spectra were observed in the 1190–850, 1520–1190, and

3700–2800 cm-1 regions. Various FTIR-based methods

can be used to determine the ratio of crystalline and

amorphous celluloses in samples. The ratio between

absorbance values of bands centered at approximately 1430

and 895 cm-1 (A1430/A895), and at 1372 and 2900 cm-1

(A1372/A2900) has been used to evaluate the crystallinity

index [31, 32]. The broad band in the 3600–3100 cm-1

region is due to the OH-stretching vibration. The change in

this peak position gives considerable information about

hydrogen bonding and ultimately cellulose crystallinity. In

amorphous cellulose, this peak became sharper and shifts

toward higher wavenumber [33]. The increase in the

amorphous domain with ball-milling can also be confirmed

by the shifting of the band at 2900 cm-1 (corresponding to

C–H vibration) to high number and decrease in its inten-

sity. Similarly, the band at the 1500–899 cm-1 region

greatly reduced with ball-milling. The increase in the

intensity of band occurred at 898 cm-1 [C–O–C stretching,

b-(1,4) glycosidic linkages] in amorphous cellulose as

compared with the un milled cellulose [4, 33, 34].

XRD Analysis

To investigate the effect of ball-milling on the crystallinity

of cellulose, XRD spectra were recorded before and after

ball-milling. Figure 1 shows the existence of three major

peaks (101, 002, and 040), which characterize CC. The CC

showed a sharp peak at 22�, which can be assigned to the

crystallinity of cellulose. After ball-milling, this peak

became less intense and broader, indicating the breakdown

of the original CC to amorphous cellulose. The result

shows that ball-milling decreased the crystallinity of cel-

lulose because of the decrease in the intensity of peaks

assigned to the crystallinity of cellulose and increased the

broad peak representing amorphous cellulose [35, 36].

After ball-milling, the characteristic shape of the cellulose

crystal structure has been lost. The decrease in crystallinity

can be ascribed to the ball-milling-imposed mechanical

stress, which disrupted the crystalline order of cellulose.

The decrease in the degree of polymerization and crys-

tallinity of cellulose improve the degradability of cellulose

and its ultimate conversion to chemicals [1, 37, 38]. The

crystallinity index (CI) for CC and BMC were also cal-

culated from XRD data using CI = (I002 - Iam)/I002 for-

mula. CI was calculated from the height ratio between the

intensity of the crystalline peak (I002 - Iam) and total

intensity (I002) after subtraction of the background signal

measured without cellulose [39, 40]. The result showed

that the CI decreased from 93 to 51 %.

Calorific Value (CV)

To study the effect of ball-milling on the CV, the CV was

recorded before and after ball-milling. Table 1 shows the

CVs of the CC and BMC. The data represent that the CV

value of cellulose considerably decreased with ball-milling.

This decrease in CV can be attributed to the breakage of

glycosidic bond with ball-milling and ultimate decrease in

its CV. No research group has studied the effect of ball-

milling on cellulose CV.

Morphological Analysis

The morphologies of native cellulose and BMC were

observed via SEM. After ball-milling, the cellulose fibrous

structure completely disappeared and changed into small

particles of quasi-circular shape (Fig. 2). This change in

the morphology of cellulose with ball-milling suggests that

the mechanical stress promoted the change in fiber cellu-

lose into particles.

Thermal Analysis

To elucidate the effect of ball-milling on the thermal sta-

bility, the CC and BMC samples were subjected to TGA at

various heating rates (5, 10, 20, and 40 K/min). Figure 3a,

b shows the effect of heating rate (b) on the TG curve and

DTG peak of the untreated and ball milled cellulose. The

result indicated that ball-milled sample degraded at a lower

temperature than the CC sample. The decrease in the

5 10 15 20 25 30 35 40 45

20

40

60

80

100

120

140

160

180

(021)

(040)

(002)

(101 )

Inte

nsity

2 Theta

(101)

(CC)(BMC)

Sample Cr.I (%)CC 92.85BMC 51.56

Fig. 1 XRD patterns of CC and BMC

Table 1 Calorific value (KJ/g) of CC and BMC

Species Average calorific

value (KJ/g)

Crystalline cellulose 16.361

Ball mill cellulose 15.646

574 Waste Biomass Valor (2016) 7:571–581

123

Fig. 2 SEM images of CC and BMC

(a)

(b)

Fig. 3 a TG of weight loss curves of CC and BMC recorded at 5, 10, 20 and 40 K/min. b DTG curves of CC and BMC recorded in nitrogen at 5,

10, 20 and 40 K/min

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123

decomposition temperature of cellulose with ball-milling

can be attributed to the mechanical degradation during ball-

milling that disrupted the crystallinity of cellulose into

amorphous cellulose [41]. The DTG curve of the cellulose

sample shows that the peak temperature depended on

heating rate. The graph showed that the DTG peak shifted

toward higher values without changing the thermal profile

as the heating rate was increased from 5 to 40 K/min. The

peak temperature of the sample is important because it

provides information about the point where the maximum

weight loss occurs because of fast and rapid volatilization

by the formation of carbonaceous residue [42–44]. The

sample of low heating rate have good ignition and vice

versa. The maximum weight loss in CC was recorded at

approximately 598, 609, 621, and 639 K, whereas that in

BMC occurred at 584, 595, 610, and 627 K at heating rates

of 5, 10, 20, and 40 K/min, respectively. Table 2 also

shows that the maximum decomposition temperature

(Tmax) was lower for BMC than for CC at each heating rate.

The lower Tmax value for BMC than for CC can be ascribed

to the decrease in the crystallinity of cellulose with ball-

milling. This result can be ascribed to the smaller size of

BMC than CC that leads a better heat transfer to the inner

part of cellulose.

The increase in peak temperature with heating rate is

due to heat transfer limitation. High heating rate has short

reaction time; therefore, the temperature needed for sample

decomposition is also higher. At a lower heating rate, a

large thermal energy is provided to the sample; therefore,

efficient decomposition is achieved and fewer amounts of

char are formed at a low heating rate. This phenomenon is

the main reason for the shift of DTG peak toward high

temperature [1, 45, 46]. In addition, cellulose particles have

got enough time to become uniformly heated and slow

reactions has taken place at a low heating rate. Excessive

heat is supplied to the sample in a short time at a high

heating rate.

The intensity of DTG peaks decreased with increasing

heating rate, where the width of DTG peaks increased with

heating rate. This result may be due to the delayed

decomposition that diffuses more heat in the cellulose for a

short interval of time [46, 47]. Furthermore, the DTG curve

of BMC was sharper and narrower than that of CC. This

decrease in intensity is due to the decrease in the particle

size of BMC, which simplified the pyrolysis of BMC as

compared with that of CC. This change in the pyrolysis

behaviors of cellulose can be ascribed to the increase in the

amorphous domain in BMC, which does not require much

energy to overcome the energy barrier of the crystal

structure to decompose [48].

Kinetic Studies

The kinetic parameters of both crystalline cellulose and

BMC were determined using Kissinger (differential), KAS,

FWO and Starink methods. The value of conversion (a)

was taken in the range of 0.1–0.7 for all curves at various

heating rates and corresponding temperatures. Because of

low correlation value, conversion degree below 0.1 and

above 0.7 were not included.

In the Kissinger method, ln(bi/T2) was plotted against

1000/T for the experiment performed under various heating

rates ranging from 5 to 40 K/min (Figs. 4a, 5a). The Kis-

singer method was controlled by changing the DTG tem-

perature peaks with changing heating rate.

In the KAS method, the apparent Ea values for CC and

BMC were calculated from the slope of linear fit of ln(bi/T2) versus 1000/T for different values of conversion

ranging from 0.1 to 0.7. Figures 4a and 5a shows regres-

sion lines for CC and BMC using Kissinger method,

respectively. Apparent activation energy, average activa-

tion energy and regression coefficient values for CC and

BMC using KAS method are displayed in Table 3. The

value of regression coefficient is very high indicating that

the activation energy calculated for CC and BMC using

KAS method is accurate.

Figures 4c and 5c shows regression lines obtained for

CC and BMC using FWO method, respectively. The value

of activation energy Ea was calculated from the slope

(-1.052Ea/R) of the plot of ln(b) against 1000/Tm at dif-

ferent heating rates at given conversion value. Apparent

activation energy, average activation energy and regression

coefficient values for CC and BMC using FWO method are

listed in Table 3. The value of regression coefficient is very

high indicating that the activation energy calculated for CC

and BMC using KAS method is very precise.

Figures 4d and 5d shows the regression line obtained for

CC and BMC using Starink method, respectively. The

value of activation energy Ea was calculated from the slope

(-1.0008 Ea/R) of plot of ln(b.T-1.92) against 1000/Tm at

conversion value ranging from 0.1 to 0.7. Apparent acti-

vation energies, average activation energy and regression

coefficient values for CC and BMC using FWO method are

listed in Table 3. The value of regression coefficient is very

high indicating that the activation energy calculated for CC

and BMC using KAS method is very accurate.

Table 2 Temperature (Tmax) at maximum degradation rate for CC

and BMC obtained for different heating rates

Heating rate (K/min) Tmax(K) for CC Tmax(K) for BMC

5 598 584

10 609 595

20 621 610

40 638 627

576 Waste Biomass Valor (2016) 7:571–581

123

Based on the results of activation energies calculated by

Kissinger, KAS, FWO and Starink methods, it was con-

cluded that the apparent activation energy Ea are not in

close agreement for all conversions (Table 3). The apparent

value of Ea calculated for CC and BMC by KAS method

varied from 180.82 to 157.96 and 133.02 to 162.12 kJ/mol,

respectively. The average values of Ea obtained for CC and

BMC from the Kissinger method were 165 and

145.57 kJ/mol, respectively. The apparent value of Ea

calculated for CC and BMC using FWO method varied

from 180.81 to 159.88 and 117.20 to 144.23 kJ/mol

respectively. Similarly, the apparent value of Ea calculated

for CC and BMC using Starink method varied from 180.09

to 158.34 and 122.90.20 to 152.02 kJ/mol, respectively.

Theses results indicated that solid-state pyrolysis involved

complex multi-step mechanisms with a large number of

parallel reactions. The trend in changing of Ea for CC and

BMC for conversion ranging from 0.1 to 0.7 was almost the

same, but the Ea for BMC is lesser than that for CC. The

different values of Ea suggest that the mechanism of reac-

tion during the thermal decomposition of cellulose is not the

same as that during the entire decomposition process.

The Ea values calculated by using Kissinger, KAS,

FWO and Starink methods are listed in Table 3. The result

clearly showed that the Ea for BMC was lower than CC,

this decrease in activation energy for ball mill cellulose is

due to more porous nature and low crystallinity index

which favor the decrease in activation energy and thermal

stability. Activation energy can be used to evaluate the

reactivity of original and ball milled cellulose. Lower the

value of Ea, higher is the reaction rate and vice versa.

Isoconversional Analysis

Table 3 and Fig. 6 shows the variation in the apparent

activation energies (Ea) with conversion factor (a). Chan-

ges in Ea with the conversion factor were observed using

KAS, FWO, and Starink methods. Variation in the value of

(a) (b)

(c) (d)

Fig. 4 Kinetic plot for CC a Kissinger, b KAS, c FWO and d Starink methods

Waste Biomass Valor (2016) 7:571–581 577

123

activation energies was observed for both CC and BMC

with increase of a from 0.1 to 0.7. The apparent Ea for CC

decrease when a changed from 0.1 to 0.6 and increase when

conversion value changes from 0.6 to 0.7. The higher value

of apparent Ea at lower value of conversion is due to high

crystallinity index and close packing structure of original

cellulose as compared to BMC. The initial thermal

decomposition of BMC was faster than that of CC. In case

of BMC the increase in the value of Ea was observed when

a changes from 0.1 to 0.2. The lower value of Ea at a = 0.1

represented the fast thermal decomposition of amorphous

content of BMC, which approaches balance after 0.2 [20,

49]. The apparent Ea was stable in the conversion ranging

from 0.2 to 0.6. The result in Table 3 represented that value

of apparent activation and average activation energy for

BMC is lower than CC in the conversion (a) ranging from

0.1 to 0.7. This lower value of apparent Ea for BMC than for

CC can be ascribed to the decreased in crystallinity index of

cellulose with ball-milling. As a result, lower value of Ea at

beginning of pyrolysis process of ball mill cellulose could

be assigned to the thermal decomposition of amorphous

cellulose and then increase in value started. The region from

a = 0.1 to a = 0.7 is kinetically important and this pyr-

olytic region include the temperature range of 603–673 K

[50–52]. In this region, the major degradation of cellulose

occurred because of unzipping of cellulose molecules. As a

result of this fast unzipping, the original structure of cel-

lulose molecules disappeared [53–55].

This decrease in activation energy and crystallinity index

is very important for effective hydrolysis of cellulose into

chemicals (e.g. glucose, 5-hydroxymethylfurfural and

levulinic acid) and energy. The effect of ball-milling pre-

treatment on cellulose conversion into levulinic acid is

studied by our research group [37]. Zaho et al. [56] found

that the ball mill cellulose easily hydrolyze compared to the

original cellulose because of mechanically disruption of

cellulose. Yeh et al. [57] found that with ball-milling the

crystallinity and particle size of cellulose decreased which

(a) (b)

(c) (d)

Fig. 5 Kinetic plot for BMC a Kissinger, b KAS, c FWO and d Starink methods

578 Waste Biomass Valor (2016) 7:571–581

123

increase the rate of enzymatic hydrolysis of cellulose.

Ribeiro et al. [58] found that ball-milling decrease the

crystallinity index of cellulose and the catalytic conversion

of cellulose to sorbitol increased with the increase in mall-

milling time and frequency.

Conclusions

This study showed that the ball-milling significantly

decrease the crystallinity and thermal stability of cellulose.

The decrease in thermal stability assessed by TGA was

ascribed to the crystallinity of cellulose samples because a

significant amount of energy is required to disrupt crys-

talline domains. The activation energies calculated for CC

by using Kissinger, KAS, FWO and Starink methods were

165, 162.71, 164.03, and 162.94 kJ/mol, respectively.

Similarly, the activation energies calculated for BMC by

using Kissinger, KAS, FWO and Starink methods were

145.57, 156.06, 140.64 and 147.94 kJ/mol, respectively.

This lower value of Ea for BMC can be attributed to the

ball-milling that changed CC to amorphous cellulose. The

crystallinity index of cellulose decreased from 92.85 to

51.56 with ball-milling. SEM result confirmed that ball-

Table 3 Apparent activation energies and correlation factors different values of conversion calculated using Kissinger, KAS, FWO and Starink

methods for CC and BMC

Sample a EKAS(KJ/mol) R2 EFWO(KJ/mol) R2 EStarink(KJ/mol) R2 EKiss(KJ/mol) R2

CC 0.1 180.82 0.964 180.81 0.968 181.09 0.965 165 0.987

0.2 171.43 0.995 172.22 0.996 171.72 0.998 165

0.3 160.54 0.998 161.95 0.998 160.8 0.999 165

0.4 158.79 0.999 159.95 0.999 158.61 0.999 165

0.5 156.13 0.999 158.06 0.999 156.41 0.999 165

0.6 153.31 0.999 155.35 0.999 153.63 0.999 165

0.7 157.96 0.999 159.88 0.999 158.34 0.999 165

Ea, average 162.71 kJ/mol 164.03 kJ/mol 162.94 kJ/mol 165 kJ/mol

BMC 0.1 133.02 0.960 117.20 0.954 122.90 0.954 145.57 0.988

0.2 153.80 0.997 140.59 0.993 147.87 0.997 145.57

0.3 159.62 0.999 146.21 0.997 153.68 0.998 145.57

0.4 162.12 0.999 147.15 0.998 155.09 0.999 145.57

0.5 161.29 0.999 144.07 0.999 151.19 0.999 145.57

0.6 160.46 0.999 145.09 0.999 152.85 0.999 145.57

0.7 162.12 0.999 144.23 0.999 152.02 0.999 145.57

Ea, average 156.06 kJ/mol 140.64 kJ/mol 147.94 kJ/mol 145.57 kJ/mol

(a) (b)

Fig. 6 Apparent of activation energies Ea as a function of the degree of conversion (a), determined by the KAS, FWO and Starink methods.

a crystalline cellulose, b ball mill cellulose

Waste Biomass Valor (2016) 7:571–581 579

123

milling strongly influenced the morphology of cellulose;

the original fibrous morphology of cellulose changed to

quasi-circular morphology. The results of this study pro-

vided insights into the future application of BMC as an

efficient source of chemicals and energy. Further research

work is in progress to show the effect of ball-milling on the

catalytic conversion of CC and BMC to chemicals using

ionic liquids.

Acknowledgments The authors gratefully acknowledge the Min-

istry of Higher Education, Malaysia for funding the research work

under Exploration Research Grant Scheme (ERGS:0153AB-108) and

Centre of Research in Ionic Liquid (CORIL), all the research officers

and postgraduate students for helping in all aspects.

Compliance with Ethical Standards

Conflict of interest The authors declare that they have no conflict

of interest. The research does not involve any type of animal and

human trails. The research does not involve any endangered species

of plant.

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