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Thermally induced structural transitions in cotton fiber revealed by a finite mixture model of tenacity distribution Sunghyun Nam, Daniel Ahmed Alhassan, Brian Condon, Alfred D. French, and Zhe Ling ACS Sustainable Chem. Eng., Just Accepted Manuscript • DOI: 10.1021/ acssuschemeng.7b04919 • Publication Date (Web): 09 Apr 2018 Downloaded from http://pubs.acs.org on April 9, 2018
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Thermally induced structural transitions in cotton fiber revealed by a finite
2
mixture model of tenacity distribution
3 Sunghyun Nam,*,† Daniel Ahmed Alhassan,‡ Brian D. Condon,† Alfred D. French,† and Zhe Ling†,§
4 5 †
6 7
‡
8 9 10 11 12
United States Department of Agriculture, Agricultural Research Service, Southern Regional Research Center, 1100 Robert E. Lee Boulevard, New Orleans, LA 70124, USA.
§
Department of Mathematics, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA 70148, USA.
Beijing Key Laboratory of Lignocellulosic Chemistry, Beijing Forestry University, Tsinghua East Road, Beijing, China.
13
ABSTRACT
14
Much processing of cotton fibrous materials involves heat treatments. Despite their critical influence
15
on the properties, the structural responses of cotton fiber to elevated temperatures remain uncertain. This
16
study demonstrated that modeling the temperature dependence of the fiber tenacity distribution was a new
17
approach to uncovering the details of the thermally induced structural transitions of cotton fiber at low
18
and intermediate temperatures. As the temperature increased, the tenacity probability density developed a
19
unique pattern—periodic evolution/degeneration of bimodality—which was successfully parameterized
20
by the mixed Weibull model. Interpretation of the variation of the model’s five parameters indicates that
21
cotton fiber underwent the following sequence of transitions: glass transition at 160-220 °C, dehydration
22
at 240-260 °C, and chain scission at 280-300 °C. The crystallographic and thermogravimetric analyses
23
showed the coexistence of thermal crystallization at 180-360 °C. The decomposition of the crystalline
24
cellulose was predominant along the fiber axis, preserving the lateral crystalline structure in the remains
25
even after a 90% weight loss.
26 27 28 29 30 31
KEYWORDS: cotton cellulose; tenacity; glass transition; mixed Weibull model; crystallinity; X-ray diffraction; Rietveld refinement Corresponding Author * Sunghyun Nam. E-mail:
[email protected]. Tel.: +15042864229. Fax: +15042864390 1
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INTRODUCTION
33
Under heat, cotton fiber undergoes a series of physical and chemical reactions that alter the structure
34
and ultimately the properties of the fiber.1 The structure of cotton fiber is complex. The cellulose, a linear
35
polymer of β-D-glucopyranose containing about 20,000 glucose units, is imperfectly aligned and forms
36
very small crystallites.2 Considering that the length of a crystallite (∼300 Å) is much smaller than that of
37
cellulose (∼10 µ), a cellulose chain is considered to pass through several crystallites and periodically form
38
a noncrystalline (or amorphous) phases between crystallites (i.e., the “fringed micelle” model);2 however,
39
there is considerable uncertainty regarding a complete picture of the cellulose configuration. The
40
complexity along with the inherent imperfections of the cotton structure hampers the unraveling of the
41
concurrent and consecutive thermal responses of the constituent phases. In particular, the response of the
42
amorphous phase to low or intermediate temperatures is little known. With respect to high degrees of
43
crystallinity and intra- and inter-molecular hydrogen bonds, the question remains whether cotton fiber has
44
a distinctive glass transition, at which glass-like amorphous cellulose becomes rubbery.
45
While numerous studies have examined the glass transition of synthetic polymers, there have been
46
relatively few reports regarding that of cellulose. Various wood and regenerated cellulose samples were
47
reported to have undergone glass transitions in the range of 220-250 °C by various methods.3-10 On the
48
other hand, the glass transition temperature of ramie was 160 °C in a torsion pendulum test.11 The
49
molecular dynamics modeling of the temperature effect on the specific volume of amorphous cellulose
50
estimated its glass transition temperature to be 377 °C.12 These varied results show the difficulty of
51
determining the glass transition of cellulose. Differential scanning calorimetry, which is the most widely
52
accepted technique for synthetic polymers, is not suitable for cellulose because of its small changes in
53
heat capacity.13 As an alternative, indirect methods using plasticizer or varying degrees of polymerization
54
have also been employed.3, 7
55
Regarding heat-induced structural changes in cotton, a limited number of studies14-16 have been
56
conducted. Those studies measured the glass transition temperature of cotton in a way that is similar to
2
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examining its mechanical deformation in tensile tests. However, their results were not consistent: > 240
58
°C,14 no evidence of thermal softening,15 and ca. 200 °C.16 This discrepancy was partly due to less
59
distinctive changes in tensile properties at low temperatures. A simple summary statistic, namely an
60
average, on which those studies relied, seemed to be insufficient for elucidating the thermal effects on the
61
cotton structure. Wide variations of the properties intrinsic to natural fibers are likely to mask the subtle
62
changes associated with the chain segmental motion. A complete description of the properties, therefore,
63
is necessary based on the entire distribution. Another concern is that all of the above mentioned studies
64
used cotton yarns. One of their authors11 pointed out that “it will be difficult to use such measurements to
65
obtain an accurate determination of Tg (glass transition temperature) since the mechanical properties of
66
cotton yarn are influenced by inter-fiber as well as intra-fiber forces.”
67
Motivated by the incomplete and contradictory data in the literature, we have measured the tensile
68
property of cotton single fiber after heat treatments and parameterized the distribution of tenacity using
69
the Weibull model.17 Based on the weakest-link theory, the Weibull model describes the probability
70
distribution of the strength by assuming that inhomogeneous flaws are randomly dispersed in the volume
71
of fiber, and its fracture is triggered by the largest flaw present. The utility of the Weibull model has been
72
demonstrated by its good fits for a variety of brittle fibers including natural lignocellulosic fibers.18-19 The
73
Weibull distribution function also well described the fracture data of nano-sized materials, i.e., carbon-
74
nanotubes,20-22 and their statistical behavior, when being incorporated into a Monte Carlo model that
75
effectively simulates the shear load transfer in different contact modes of two adjacent fibers, provided
76
good predictions of the strength of carbon-nanotube yarns.23-24
77 78
The two-parameter Weibull cumulative distribution function (CDF) can be expressed as: x x m F ( x; λ , m ) = ∫ f ( x; λ , m )dt =1 − exp− , x > 0, λ > 0, m > 0 0 λ
(1)
79
where F(x) is the probability of failure of a fiber subjected to a stress of x, λ is the scale parameter, which
80
represents the 63.2 percentile of the distribution, and m is the shape parameter (Weibull modulus), which
3
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indirectly measures the distribution of flaws within the fiber. The corresponding probability density
82
function (PDF) is given by:
83
f ( x; λ , m ) =
m x λ λ
m−1
x m exp− λ
(2)
84
The two parameters can be determined using the maximum likelihood estimation (MLE) method, which
85
has enabled precise estimation of the Weibull parameters.25 For this method, the likelihood function (L) of
86
n random sample data is first obtained as:
87
m−1 n x m m n 1 m x L( x1 ,..., xn ; λ , m ) = ∏ i exp − i = m exp − m i =1 λ λ λ λ λ
n m m−1 x ∑ i ∏ xi i =1 i =1 n
(3)
88
Here λ and m are determined when the value of the measurement is most likely to occur, that is, where L
89
is maximized. This optimization can be obtained easily using the log-likelihood function.
90
91
ln L( x1 ,..., xn ; λ , m ) = n ln (m ) − nm ln (λ ) −
λm
n
n
i =1
i =1
∑ xim + (m − 1)∑ ln (xi )
(4)
The partial derivatives of ln L with respect to λ and m, respectively, are set at zero.
92
∂ ln L nm m n =− + m+1 ∑ xim = 0 ∂λ λ λ i =1
93
∂ ln L n ln λ n 1 = − n ln (λ ) + m ∑ xim − m ∂m m λ i =1 λ
94
1
(5) n
n
i =1
i =1
∑ xim ln (xi ) + ∑ ln ( xi ) = 0
(6)
Equations (5) and (6) yield the following simplified equations, respectively, for m and λ:
95
n m ∑ xi ln ( xi ) 1 n m = i =1 n − ∑ ln ( xi ) n i =1 xim ∑ i =1
96
1 n m λ = ∑ xim n i =1
−1
(7)
1
(8)
97
From the determined parameters, the mean and variance of a Weibull distribution can be calculated by the
98
following equations:
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µ = λΓ 1 +
1 m
σ 2 = λ2 Γ1 +
(9)
2 1 2 − Γ 1 + m m
(10)
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In this study, we have demonstrated that the tenacity of cotton fiber was well described by the
102
Weibull model; however, when heating the fiber, its statistical behavior changed, departing from the
103
single Weibull distribution. The distributions of fibers heated over a temperature range of 160-280 °C was
104
successfully described by a finite mixture model—a mixture of two Weibull distributions. The determined
105
five parameters, which characterized a complex pattern of the distribution, were interpreted in terms of
106
the thermal reactions of cotton fiber. To assist and support the interpretation, the results of
107
crystallographic and thermogravimetric analyses were consulted. These analyses also aided in revealing
108
changes in the crystalline phase at higher temperatures (300-500 °C).
109 110
EXPERIMENTAL SECTION
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Materials and sample preparation. American Upland raw cotton fiber was acquired from the
112
national registry. To remove noncellulosic components, which were found to alter the thermal reactions of
113
cellulose,26-27 the scouring of cotton fiber was carried out. Using an overflow-jet dyeing apparatus
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(Werner Mathis USA Inc., Concord, NC), cotton fiber was circulated in an aqueous solution containing
115
NaOH (1.8 g/L) and Triton X-100 (0.2 g/L) with a liquid-to-fiber ratio of 22:1 at 100 °C for 60 min. The
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fiber was then washed in circulating water at 100 °C for 20 min, followed by cold-water washing for 20
117
min. The scoured fiber was neutralized in an aqueous solution of acetic acid (0.25 g/L) for 10 min, rinsed
118
with cold water, and air dried.
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The scoured cotton fiber was heated using a TGA Q500 thermal gravimetric analyzer (TA
120
Instruments, New Castle, DE) under a nitrogen atmosphere. The nitrogen flow into the furnace was
121
maintained at a rate of 90 mL/min. When the furnace reached the desired temperature with a heating rate
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of 10 °C/min, the sample was cooled to room temperature. The control sample (no heat treatment) was
123
denoted as fiber at a temperature of 25 °C.
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Characterization. The linear density (LD) and tensile properties of heated cotton fiber—elongation,
125
force to break, tenacity, modulus, time to break, and work to rupture—were measured using a Favimat
126
tester (Textechno H. Stein GmbH). A single fiber was clamped with a gauge length (l) of 12 mm and pre-
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tensioned with a force (T) of 0.5 cN. According to the vibroscopic technique (ASTM D 1577), the LD
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(g/cm = 1/9×10-5 denier) was determined from the resonant frequency of the transverse vibration of the
129
fiber using the following equation:
130
LD = ρA =
T
(11)
4l 2 f 2
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where ρ, A, and f are the density of fiber (g/cm3), the cross-sectional area of fiber (cm2), and the resonant
132
frequency (Hz), respectively. The same fiber section was extended with a load cell of 210 cN and a cross-
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head speed of 2 mm/min until the fiber broke. The precision for measuring tensile force was within 1 mN.
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For each sample, 100 fibers were tested.
135
X-ray diffraction (XRD) measurements were conducted using an XDS 2000 diffractometer (Scintag
136
Inc.). Cotton fiber was ground to a powder using a Mini Wiley Mill (Thomas Scientific, Swedesboro, NJ)
137
with a 40 mesh screen (0.42 mm). Approximately 0.15 g of the ground sample was pressed with 127 MPa
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of pressure in a hydraulic press, cut into a 2.5 cm diameter circular disc, and mounted on the sample
139
holder. The diffraction pattern of the sample was recorded using Cu-Ka radiation generated with 43 kV
140
and 38 mA (1.54056 Å). Angular scanning was conducted from 8° to 38° with a scanning rate of 0.6°/min.
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No background correction was made. The obtained X-ray diffractograms, after 9-point smoothing and
142
normalization of intensity, were analyzed using the Rietveld powder diffraction method in the MAUD
143
program (Materials Analysis Using Diffraction, version 2.7). For crystalline phase, the cellulose Iβ crystal
144
information file28-29 was employed. The cellulose II information was to generate an amorphous pattern by
145
using a very small crystallite size (12 Å).30 Eleven parameters—scale factor, three parameters of a 2nd
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order polynomial function for the background, crystallite size, three parameters for the dimensions of the
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Iβ unit cell (a, b, and γ), two parameters for the March-Dollase preferred orientation along the (001) plane
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of cellulose Iβ (coefficient and weight), and the volume fraction of the amorphous phase—were included
149
in the Rietveld refinement. For the 400 °C sample, which underwent a significant loss of crystallinity,
150
additional parameters for the preferred orientation of the amorphous phase and the anisotropy of the
151
crystallites (i.e., Popa’s Rules31) had to be included to achieve a good fit. The amount of amorphous
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cellulose was calculated from the area of the calculated pattern for amorphous cellulose divided by the
153
sum of the areas for crystalline cellulose and amorphous cellulose. The d-spacing was calculated using
154
Bragg’s Equation:
155
nλ = 2d sin θ
(12)
156
where n is an integer, λ is the wavelength of the X-ray radiation, d is the spacing between the planes, and
157
θ is the diffraction angle of the peak.
158 159
For thermogravimetric (TG) analysis, the TG and differential TG thermograms collected from the TGA Q500 analyzer were analyzed using Universal Analysis 2000 software (TA Instruments).
160
Data analysis. Analyses of the tenacity data were carried out using R software.32 The parameter
161
estimates of the mixed Weibull distribution were obtained by performing non-linear least squares
162
optimization using the Levenberg-Marquardt algorithm. To visualize the classification of the temperature
163
effect, principal component analysis (PCA) was applied to the data. The PCA provided a general
164
overview plot by converting 14 experimental variables from tensile, crystallographic, and
165
thermogravimetric analyses—which might be correlated—into two linearly uncorrelated variables
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(principal components: PC1 and PC2) that maintain about 85% variability. The determination of the
167
number of principal components was verified using the leave-one-out cross-validation method.
168 169
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RESULTS AND DISCUSSION
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Tensile properties. Favimat, which can differentiate single fibers based on tensile properties and
172
fineness, has been usefully used in cotton testing.33 Figure 1a shows force-elongation curves for control
173
cotton fiber. As expected for natural fibers, cotton exhibited wide variations in the response to external
174
force. The force-elongation curve of cotton fiber has, however, been known to be distinct from those of
175
other natural fibers—wool and silk—due to its lower extensibility (determined as the elongation at break
176
in the curve).34 The stiffness of cotton fiber is attributed to its high crystallinity;35 that is, it contains a
177
small amount of flexible amorphous cellulose, which is characterized by disorder in the orientation of
178
cellulose chains.36-37 Therefore, the amorphous content is one of important factors to influence the tensile
179
behavior of fibers.
180
In this study, the heat treatment was conducted in the range of 160-500 °C, but only the fibers that
181
were heated to 300 °C were strong enough for tensile tests. The heat treatment did not change greatly the
182
force-elongation curve shape of cotton fiber, i.e., a short, linear regime followed by a long, slightly
183
nonlinear regime extending until break, but the treatments above 220 °C greatly shrunken the curve
184
toward origin (Figures 1b and S1). A considerable drop in the number of successful tests was observed at
185
260 °C. The heat effect was also manifest in the fracture morphology. The micrograph of fractured
186
control fiber showed the frayed separation of microfibrils along the fiber axis (inset of Figure 1a). As the
187
temperature increased, this irregular axial splitting was less observable (inset of Figure 1b). At 300 °C,
188
clean fractures across the fiber diameter were dominant (Figure S1g).
189
The average values of linear density and tensile properties—elongation, force to break, tenacity,
190
modulus, time to break, and work to rupture—at increments of 20 °C are presented in Table 1. Since the
191
variances across the samples were inhomogeneous, a nonparametric multiple comparison test (Mann-
192
Whitney U test with Holm’s correction) was conducted. No significant change in linear density was
193
observed until 300 °C. On the other hand, tensile properties coherently exhibited significant reductions at
194
220, 240, and 260 °C. 8
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9.0
9.0
b
a 7.2
Force (g)
7.2
Force (g)
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5.4
3.6
5.4
3.6
1.8
1.8
0
0 0
4
8
12
16
0
20
4
12
16
20
Elongation (%)
Elongation (%)
195
8
196
Figure 1. Selected force–elongation curves obtained by Favimat testing and fiber fracture morphology:
197
(a) control cotton fiber and (b) cotton fiber heated at 260 °C. Scale bars are 5 µm.
198 199
Table 1. Linear density and tensile properties of cotton fiber heated at incremental temperatures. Temperature (°C)
No. of successful tests out of 100
Linear density (denier)
25 (control)
88
160
Elongation (%)
Force to break (cN)
Tenacity (cN/denier)
Modulus (cN/denier)
Time to break (s)
Work to rupture (µJ)
1.70A b (0.38)
a
9.30A (2.78)
4.17A (1.79)
2.43AB (0.97)
23.65A (8.06) c (45)
5.84A (1.66)
24.0A (12.8)
95
1.66A (0.41)
9.37A (3.20)
4.37A (1.88)
2.66A (1.04)
23.09A (6.48) (47)
5.89A (1.91)
25.3A (13.8)
94
1.55A (0.29)
9.40A (2.74)
4.00AB (1.83)
2.55A (1.00)
23.39A (8.54) (46)
5.90A (1.63)
23.7A (13.1)
94
1.62A (0.31)
8.31AB (2.67)
4.02AB (1.76)
2.49A (0.96)
22.34A (9.44) (31)
5.25AB (1.62)
21.7AB (11.5)
220
91
1.61A (0.29)
8.13B (2.65)
3.36B (1.58)
2.07B (0.83)
18.31B (9.38) (25)
5.13B (1.58)
18.2B (10.5)
240
91
1.65A (0.35)
5.43C (2.16)
2.68C (1.15)
1.64C (0.66)
13.34B (11.44) (4)
3.52C (1.29)
10.7C (6.9)
180
200
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2.84C (1.07)
6.9D (4.0)
-
2.73C (1.25)
0.06D (0.05)
-
1.77C (0.76)
0.03D (0.02)
260
57
1.62A (0.32)
4.27C (1.84)
2.16CD (0.77)
1.35CD (0.46)
-
280
37
1.67A (0.26)
4.12C (2.08)
1.70D (0.79)
1.01D (0.40)
300
6
1.69A (0.14)
2.52C (1.23)
1.27D (0.50)
0.74D (0.27)
d
a
Averages followed by different letters are significantly different (p < 0.05) based on Mann-Whitney U multiple b c d comparison tests with Holm’s correction; standard deviation; number of successful measurements; could not be determined.
205
Single Weibull model. Summary statistics (averages and standard deviations) do not give any
206
information about the shape of the distribution. Examination of alteration patterns in the distribution with
207
a proper parametric model is expected to help in understanding the underlying thermal process of cotton
208
fiber. We first applied the single Weibull model to the tenacity data for all samples except the one that
209
was heated to 300 °C, whose sample size was too small to be modeled. Two parameters estimated by the
210
MLE (Equations 3-8) and the calculated means (Equation 9) and coefficients of variation (Equation 10)
211
are presented in Table 2. In the variation of λ, there were two slope changes at 160 and 200 °C: a slight
212
increase upon heating to 160 °C and a rapid linear drop above 200 °C. The effect of temperature on m was
213
relatively less notable except for a large increase at 260 °C. The theoretical means agreed well with the
214
experimental average values of tenacity. To visualize the fit of the single Weibull model, the empirical
215
density is plotted with the respective Weibull density, as seen in Figure 2. It was found that the empirical
216
densities formed a complex shape—multimodality. The modality of the tenacity distribution depended on
217
the heating temperature; for example, bimodality was apparent at 240 °C but was dramatically dissipated
218
at 260 °C.
219
Concerned with the observed departure of the empirical density from unimodality, the goodness of fit
220
of the single Weibull model was quantitatively evaluated using the Kolmogorov-Smirnov (K-S) test.
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Under the hypothesis that the data follow the Weibull distribution, the test statistic (D), which is the
222
largest vertical distance between the empirical CDF and the Weibull CDF, can be measured as
223
D = sup Fe ( xi ) − F ( xi )
(13)
1≤i ≤ n
224
where n is the number of data points, Fe(xi) is the empirical CDF at the ith x value (tenacity)—a step
225
function that increases by 1/n at the value of each increasingly ordered data—and F (xi) is the determined
226
Weibull CDF. In the hypothesis test, a new data set was resampled from the original data with
227
replacement, and the corresponding empirical CDF was obtained. If the test statistic (D) calculated by
228
Equation (13) is smaller than the critical value ( = 1.358 / n ) at a significance level of 0.05, the
229
hypothesis was accepted. The percentage acceptance (A) and the average value of D obtained from 100
230
resampling procedures are presented in Table 2. The A for the control cotton was approximately 85%,
231
showing a relatively good fit of the single Weibull model. Its goodness of fit, however, gradually
232
deteriorated for the fibers heated until reaching 220 °C, and further heating at higher temperatures
233
substantially reduced the A.
234 235
Table 2. Single Weibull parameters, means, and coefficients of variation for the tenacity of cotton fiber
236
heated at incremental temperatures and the Kolmogorov-Smirnov goodness-of-fit test results. Temperature (°C)
Single Weibull Parameters
µ (cN/denier)
CV
K-S test
a
λ (cN/denier)
m
25
2.72 b (0.11)
2.71 b (0.24)
2.42
39.8
0.113 d (0.6391)
84.8
160
2.99 (0.11)
2.84 (0.23)
2.66
38.2
0.116 (0.5740)
80.4
180
2.87 (0.11)
2.77 (0.22)
2.55
39.1
0.1203 (0.5437)
79.4
200
2.80 (0.11)
2.84 (0.23)
2.49
38.1
0.1163 (0.5821)
81.0
220
2.33 (0.10)
2.68 (0.21)
2.07
40.3
0.1098 (0.6467)
81.8
A (%)
D c
11
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237 238 239
240
1.85 (0.07)
2.75 (0.23)
1.64
39.3
0.136 (0.4362)
56.4
260
1.51 (0.07)
3.17 (0.32)
1.35
34.6
0.162 (0.4964)
73.2
280
1.14 (0.07)
2.66 (0.32)
1.01
40.5
0.222 (0.4011)
55.2
CV (coefficient of variation) = σ/µ; standard error; average value of D from 100 resampling procedures; average p-value from 100 resampling procedures.
a
b
c
d
Probability density
1.2
a
b
c
d
e
f
g
h
Empirical Single Weibull
1.0 0.8 0.6 0.4 0.2
Probability density
1.2 0.0 1.0 0.8 0.6 0.4 0.2 1.2 0.0 1.0
0
0.8 0.6 0.4 0.2
0
1
2
3
4
5
0 6
1
2
3
4
5
Tenacity (cN/denier)
Tenacity (cN/denier)
2
3
4
5
6
Tenacity (cN/denier)
0.0
240
1
Probability density
Probability density
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 12 of 29
6
2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0
i
0
1
2
3
4
5
6
Tenacity (cN/denier)
241
Figure 2. Empirical density and predicted single Weibull probability density of the tenacity of cotton
242
fiber heated at incremental temperatures: (a) control, (b) 160 °C, (c) 180 °C, (d) 200 °C, (e) 220 °C, (f)
243
240 °C, (g) 260 °C, (h) 280 °C, and (i) 300 °C.
244
12
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245 246 247
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Mixed Weibull model. Improved expression of the tenacity distribution of heated cotton fibers was attempted using a mixture of two Weibull functions. The PDF of a mixed Weibull distribution is: f ( x; α , λ1 , m1 , λ2 , m2 ) = αf1 ( x; λ1 , m1 ) + (1 − α ) f 2 ( x; λ2 , m2 )
(14)
248
where fj(x; λj, mj) is the PDF of a Weibull distribution with j = 1, 2, and α is the relative abundance of the
249
jth component with a constraint of 0 ≤ α ≤ 1. The corresponding CDF of the mixed distribution is:
250
F ( x; α , λ1 , m1 , λ2 , m2 ) = αF1 ( x; λ1 , m1 ) + (1 − α )F2 (σ ; λ2 , m2 )
(15)
251
The five parameters, α, λ1, m1, λ2, and m2, defining the functions in Equations (14) and (15), were
252
determined by the non-linear least squares optimization. The mean and variance for the mixed Weibull
253
distribution can, respectively, be calculated by:
254
µ m = αµ1 + (1 − α )µ 2
(16)
255
σ m2 = α (σ 12 + µ12 ) + (1 − α )(σ 22 + µ 22 ) − [αµ1 + (1 − α )µ 2 ]2
(17)
256
where the µi and σ i2 are, respectively, the mean and variance of a Weibull distribution defined by λi and
257
mi with i = 1, 2. The determined parameters of the mixed Weibull model and its goodness of fit test
258
results are presented in Table 3. The A for heated fibers greatly increased, particularly for those treated at
259
high temperatures. Figure 3 shows the mixed Weibull densities plotted with the corresponding two
260
component densities (designated as Weibull 1 and Weibull 2). Clearly, almost all experimental data points
261
fell right on the mixed Weibull prediction. It is interesting to see how the shape and location of the
262
component densities systematically varied with temperature. This variation pattern was examined by
263
plotting the five parameters as well as the distance between the two modes as a function of temperature,
264
as seen in Figure 4.
265
The control cotton itself showed bimodality, i.e., appearance of the second component (5% Weibull
266
1) at lower tenacity, signifying intrinsic inhomogeneity of the population. The source of the Weibull 1 is
267
likely to be a small group of immature (weak) cotton fibers and/or damaged fibers during the mechanical
268
cleaning process. Therefore, an increase in α (abundance of the Weibull 1) is associated with the extent of
13
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269
fiber damage by the heat treatment. The α considerably increased above 220 °C. Below 220 °C, the
270
parameters of the Weibull 1 (λ1 and m1) increased whereas those of the Weibull 2 (λ2 and m2) remained
271
relatively steady. These results indicate that the Weibull 1 responded more sensitively to low
272
temperatures than the Weibull 2. Also, the weaker dependence of the Weibull 2 on the temperature, i.e.,
273
maintaining the initial density, suggests that the low-temperature thermal reaction occurred randomly
274
throughout the population. At 220 °C, the Weibull 2 shifted to lower tenacities (drop in λ2) to merge with
275
the Weibull 1 (as indicated by a decrease in the distance between the two modes). This degeneration of
276
bimodality toward unimodality suggests that the corresponding thermal reaction propagated beyond
277
complete consumption of the initial component density.
278 279
Table 3. Mixed Weibull parameters, means, and coefficients of variation for the tenacity of cotton fiber
280
heated at incremental temperatures and the Kolmogorov-Smirnov goodness-of-fit test results. Mixed Weibull Parameters Temperature (°C)
281 282
a
α
λ1 (cN/denier)
λ2
m1
(cN/denier)
K-S test m2
µ (cN/denier)
CV
a
A (%)
D c
25 (control)
0.05 b (0.01)
1.10 (0.03)
3.03 (0.30)
3.00 (0.01)
2.82 (0.03)
2.58
41.2
0.124 d (0.5454)
72.8
160
0.04 (0.01)
0.95 (0.08)
2.79 (0.64)
3.17 (0.01)
2.86 (0.04)
2.75
40.7
0.117 (0.5679)
81.5
180
0.06 (0.01)
1.34 (0.04)
3.39 (0.36)
3.03 (0.01)
2.90 (0.05)
2.61
40.3
0.117 (0.5670)
82.2
200
0.08 (0.01)
1.67 (0.01)
4.55 (0.20)
2.98 (0.01)
2.80 (0.03)
2.56
40.4
0.111 (0.6206)
86.0
220
0.02 (0.00)
1.81 (0.02)
11.44 (1.75)
2.39 (0.01)
2.78 (0.01)
2.12
38.9
0.105 (0.6933)
87.6
240
0.40 (0.01)
1.18 (0.01)
3.13 (0.02)
2.29 (0.01)
4.28 (0.05)
1.67
41.9
0.110 (0.6410)
85.2
260
0.76 (0.19)
1.48 (0.02)
3.48 (0.14)
1.79 (0.24)
2.72 (0.22)
1.39
35.4
0.169 (0.4966)
72.6
280
0.87 (0.02)
0.97 (0.01)
3.37 (0.06)
1.84 (0.05)
7.15 (1.69)
0.98
41.3
0.169 (0.6675)
87.8
b
c
d
CV: coefficient of variation; standard error; average value of D from 100 resampling procedures; average pvalue from 100 resampling procedures. 14
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Probability density
1.50
a
b
c
d
e
f
g
h
1.25 1.00 0.75 0.50 0.25
Probability density
1.50 0.00 1.25 1.00 0.75 0.50 0.25
1.50 0.00
Probability density
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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1.25
0
1
2
3
4
5
6
Tenacity (cN/denier)
1.00
Empirical Mixed Weibull Weibull 1 Weibull 2
0.75 0.50 0.25 0.00 0
283
1
2
3
4
Tenacity (cN/denier)
5
6 0
1
2
3
4
5
6
Tenacity (cN/denier)
284
Figure 3. Empirical density and estimated mixed Weibull probability density of the tenacity of cotton
285
fiber heated at incremental temperatures: (a) control, (b) 160 °C, (c) 180 °C, (d) 200 °C, (e) 220 °C, (f)
286
240 °C, (g) 260 °C, and (h) 280 °C.
287 288
Higher temperatures induced a similar pattern—bimodality was developed at 240 °C, dissipated at
289
260 °C, and redeveloped at 280 °C. The development of new bimodality indicates the initiation of another
290
type of thermal reaction. The aggressive thermal effects on the fiber strength in these regimes were
291
reflected by the larger variations of the parameters. Compared with the low-temperature stage (below 220
292
°C), the weight of the Weibull 1 (α) increased, and the life span of the bimodality shortened. For example,
293
the first bimodality survived for 60 °C increments; the second one for 20 °C increments; and the third one, 15
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294
upon development, had already degenerated to show unimodal-like appearance. Another feature is that
295
not only λ1 and m1 but also λ2 and m2 were functions of temperature. Such a complex pattern, whereby
296
both of the component densities varied, implies that the thermal reactions at 220-280 °C depended on the
297
original strength of the fiber. The variation of m suggests that the more uniform distribution of less
298
variable flaw size was induced in the Weibull 1 at 220 °C and in the Weibull 2 at 280 °C.
299 1.0
a
0.8
α
0.6 0.4 0.2 0.0
12
b
Weibull 1 Weibull 2
10
m
8 6
5
4 2
c 3
4
2 3 1 2 0 1
-1 -2 0
50
100
150
200
250
0 300
Distance between modes (cN/denier)
4
λ (cN/denier)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 16 of 29
300
Temperature (°C)
301
Figure 4. Variation of the mixed Weibull parameters as a function of temperature.
302 303
Thermally induced structural transitions. The structure of cotton fiber is generally described by the
304
fringed micelle model,2 in which the cellulose chains pass through both crystalline and amorphous 16
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305
regions. When an external force is applied to the fiber, it is concentrated mostly on weak elements in the
306
structure, i.e., amorphous segment. Therefore, the fiber strength and elongation are sensitive to changes in
307
the amorphous structure, showing their coherent dependence on the temperature in the isodensity contours
308
of the tenacity-elongation bivariate distribution (Figure 5).
0.0752
0.0658
0.0564
0.0470
0.0376
0.0282
0.0188
0.00940
0.00
309
Elongation (%)
20
a
b
c
d
e
f
g
h
15 10 5
200
Elongation (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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15 10 5 0 0
310
1
2
3
4
5
Tenacity (cN/denier)
6 0
1
2
3
4
5
Tenacity (cN/denier)
6 0
1
2
3
4
5
Tenacity (cN/denier)
6 0
1
2
3
4
5
6
Tenacity (cN/denier)
311
Figure 5. Isodensity contour plots of the tenacity-elongation joint empirical density for cotton fibers
312
heated at incremental temperatures: (a) control, (b) 160 °C, (c) 180 °C, (d) 200 °C, (e) 220 °C, (f) 240 °C,
313
(g) 260 °C, and (h) 280 °C.
314 315
For the examination of the crystalline region, crystallographic and thermogravimetric (TG) analyses
316
were conducted. Figure 6 shows the X-ray diffraction patterns of cotton fibers heated from 160 to 500 °C.
317
As shown by the selected calculations (Figures 6b and 6c), the Rietveld refinement produced an excellent
318
fit with the experimental pattern; the correlation coefficients between calculated and experimental
319
diffraction peak intensities were higher than 0.99 for all samples studied. The calculated crystallite size,
320
d-spacing, and amorphous content as a function of temperature as well as the selected crystallite models 17
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are presented in Figure 7. Figure 8 shows the weight loss and weight loss rate of the fiber heated at a rate
322
of 10 °C/min.
a
500 °C
Experimental Calculated Cellulose Iβ Amorphous Background
b
400 °C (200)
10000
380 °C
Intensity
8000
360 °C 340 °C
Calculated intensity
321
10000
R2 = 0.9980
8000 6000 4000 2000 0 0
2000 4000 6000 8000 10000
Measured intensity
6000 4000
320 °C
(1-10) (110)
2000
300 °C
0 12
280 °C
16
20
24
28
32
36
2θ (°)
260 °C
Calculated intensity
c
240 °C
10000
220 °C
8000
200 °C
Intensity
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 18 of 29
180 °C 160 °C
10000
R2 = 0.9986
8000 6000 4000 2000
6000
0 0
2000 4000 6000 8000 10000
Measured intensity
4000 2000
25 °C
0
10
323
15
20
25
30
12
35
16
20
24
28
32
36
2θ (°)
2θ (°)
324
Figure 6. (a) X-ray diffraction patterns of control cotton fiber (25 °C) and cotton fibers heated to from
325
160 to 500 °C. Selected calculated diffraction patterns with the Rietveld powder diffraction method for
326
cotton fibers heated to (b) 260 °C and (c) 400 °C. The inset shows the correlation between measured
327
and calculated diffraction peak intensities.
328 329
Collecting all 14 variables from tensile, crystallographic, and thermographic data, PCA was
330
conducted. Figure 9 shows the loading of the variables in the bidimensional space defined by PC1 and
18
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331
PC2, which explained 61.8% and 22.8% of the total variance of the original data set, respectively. For
332
PC1, tenacity, elongation, work to rupture, number of successful tensile tests, amorphous content, and λ2
333
showed negative loadings, whereas weight loss, α, and crystallite size showed positive loadings,
334
indicating their close association with the extent of the thermal impact—the higher the score, the greater
335
the thermal damage. On the other hand, PC2, which has positive loadings of λ1, m1, and crystallite size,
336
but negative loadings of m2, d-spacing, and distance between the modes, was related to the progress of
337
thermal reactions—the higher the score, the closer to the fullest extent the corresponding thermal reaction.
338
Taking all analyses into account, five thermal responses of cotton fiber can be proposed, whose
339
schematics are included in Figure 9.
340
1) Glass transition at 160-220 °C: At 160 °C, slight decreases in α and λ1 as well as a slight increase
341
in λ2 indicate that there was a release of the internal stresses that were locked within the fiber during fiber
342
development or storage. The tenacity of the minor group of inferior fibers with less crystallinity (denoted
343
as a smaller size of the fiber schematic in Figure 9) was more sensitive to this chain relaxation. The
344
resulting moderate improvement in the tenacity of the immature, weak fibers diluted the intrinsic
345
inhomogeneous characteristic of the population. In the schematic in Figure 9, such thermal softening is
346
denoted by coloring the amorphous segments with a lighter shade of yellow. At 180-200 °C, increases in
347
α as well as noticeable increases in λ1 and m1 but relative steadiness in λ1 and m1 suggest that the thermal
348
softening randomly propagated throughout the population. At 220 °C, the degeneration of bimodality
349
indicates that the glass transition proceeded to the fullest possible extent. This broad range of glass
350
transition temperatures was characterized by negative values on the PC1 axis. The PC1 score of 220 °C is
351
close to zero. Its location between the temperatures with negative PC1 values (25-200 °C) and those with
352
positive PC1 values (240-280 °C) indicates a transitional temperature between thermal softening and
353
thermal decomposition.
354
2) Dehydration at 240–260 °C: Development of a new bimodality at 240 °C and its dissipation at 260
355
°C indicate the occurrence of the second thermal response: the dehydration of cellulose including 19
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356
intramolecular reactions, which involves the loss of water and causes the thermochemical transformation
357
of cellulose.1 This dehydration temperature was in excellent agreement with that determined by FT-IR.38
358
The resulting dehydrocellulose was denoted in red in the schematic (Figure 9). The variations of the
359
parameters of both the component densities in this temperature regime indicate that the dehydration
360
reaction was not random but rather depended on the strength of the fiber. In the PCA plot, 240 and 260 °C
361
were located on different quadrants, signifying the level of the dehydration.
362
3) Chain scission at 280-300 °C: Development of a new bimodality but with severe transformation
363
toward the unimodality at 280 °C suggests the occurrence of an aggressive thermal event—chain scission
364
by decomposition of dehydrocellulose or depolymerization. The chain scission was also supported by
365
steep drops in the number of successful tensile tests out of 100 as well as the clean fracture morphology
366
(Figure S1). At 300 °C, only six samples were successfully tested (Table 1), indicating that those fibers
367
were too weak to withstand the pretension of the tensile test.
368
4) Thermal crystallizations at 180-360 °C: The analyses of the X-ray diffraction patterns revealed that
369
thermal crystallization occurred concurrently with thermal softening and decomposition. Figure 7b shows
370
that the amorphous content decreased periodically, reaching the local minima at 200, 260, and 320 °C. It
371
is also apparent from the d-spacing calculation (Figure 7a) that the crystallites expanded and shrunk with
372
a similar pattern observed in the amorphous content. Approximately 20% reductions in amorphous
373
content were observed at 200 and 260 °C as compared with the content of control cotton. One may
374
question whether such reductions would have resulted from the loss of the amorphous cellulose. The
375
weight-loss profile (Figure 8) shows that after a 3.6% reduction due to the loss of moisture, there were no
376
obvious weight reductions until 220 °C and a negligible reduction (0.1%) at 260 °C. Further evidence of
377
crystallization is that crystallite size gradually increased (Figure 7a). When reaching 360 °C, one more
378
chain layer was incorporated into the original 22 layers in the (200) lattice plane (Figure 7c). One source
379
of the additional layer could be paracrystalline cellulose (an intermediate phase between crystalline and
380
amorphous regions). Another source could be amorphous cellulose decomposing in the previous stage.
20
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Page 21 of 29
381
With free chain ends, amorphous cellulose could be more easily crystallized than when it was bound
382
between crystallites.
b
3.92
400
3.88
380 360 24 22 20 18 16 14
Number of (200) plane Crystallite size
40
12 10
35 50
320 300 280 260 240 220 200 180
100 150 200 250 300 350 400
160
Temperature (°C)
b
340
Temperature (°C)
3.84 94 92 90 88 86 84 82 80
Number of (200) plane
a
d-spacing (Å)
383
Crystallite size (Å)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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25
o
10
c
15
20
25
30
60
65
Amorphous cellulose (%)
a
400 °C 25 °C
360 °C
384 385
Figure 7. (a) The variations of d-spacing, crystallite size, and number of the (200) lattice plane as a
386
function of temperature. (b) percentage amorphous content calculated using the Rietveld powder
387
diffraction method. (c) crystallite models for control and heated cotton fibers by diagonal truncation,
388
which terminates along the (1-10) and (110) planes using the Mercury program39 with the published
389
coordinates.28-29 The numbers of glucose units in width for control, 360 °C, and 400 °C were 198, 213,
390
and 60, respectively.
391 392
5) Decomposition of crystalline cellulose at 340-500 °C: Above 340 °C, the weight loss exceeded the
393
initial amount of amorphous cellulose, indicating the deconstruction of crystalline cellulose, which
21
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394
yielded amorphous residues. At 380 °C causing about 90% weight loss, the production of amorphous
395
cellulose overtook its consumption to increase the amorphous content (Figure 7b). One may assume that
396
such drastic destruction would result in no crystalline structure subsisting in the remains. Surprisingly,
397
however, the X-ray diffraction pattern of the fiber heated to 380 °C was as detailed as that of control
398
cotton (Figure 6a); moreover, its crystallite size and the number of the (200) planes were comparable to
399
those of control fiber. This manifests the unzipping depolymerization reaction along the c-axis (fiber axis).
400
Even at 400 °C, where the major decomposition ended, the characteristic diffraction peaks of cotton were
401
still detectable. At 400 °C, the amorphous content increased to 61% (Figure 7b), and the width of
402
crystallites decreased by more than half (Figure 7c). Finally, no distinctive X-ray diffraction could be
403
collected for the sample heated to 500 °C (Figure 6a).
404
5.3
100
9
a
b
320 °C
8
5.1
5 4
5.0
3 2
4.9
354 °C
Weight (%)
Weight (mg)
3.0 80
7 6
50
100
150
200
250
300
2.5
60
2.0
40
1.5 1.0
20
380 °C
1 4.8
3.5
0 100
0 350
200
300
400
500
0.5
900
Temperature (°C)
Temperature (°C)
405 406
Figure 8. (a) Weight and percentage weight loss of cotton fiber at 30-320 °C. (b) Profiles of percentage
407
weight loss and weight-loss rate in the range of 100-980 °C, showing a rapid, major weight loss of
408
cotton cellulose occurring between 320 and 380 °C.
409 410
22
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0.0 1000
Weight loss rate (%/°C)
5.2
Weight loss (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 22 of 29
Page 23 of 29
240 °C
260 °C
PC2 (22.8) 4 220 3
220 °C
280-300 °C
2 200 260
1 180 -6
180-200 °C
-5
-4
-3
-2
-1
1
2
3
4
5
6
240
-1
PC1 (61.8)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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320-340 °C
25 160
-2 280 -3
160 °C
360-380 °C
-4
400 °C
25 °C
411 412
Figure 9. PCA scores of the heated cotton fibers at different temperatures presented in the space
413
defined by the first two principal components and the schematic of the structural transformation of
414
cotton fiber as increasing the temperature.
415 416
CONCLUSIONS
417
Due to the complexity of cotton structure, identifying structural transformation under heat treatments
418
is not a trivial task. In particular, the glass transition of cotton fiber has been a controversial topic. In this
419
study, the stepwise thermal response of cotton fiber to elevated temperatures was revealed by
420
parameterizing the periodic pattern of bimodality in the tenacity distribution using the mixed Weibull
421
model. Analyzing variations of the five parameters identified the glass transition at 160-220 °C. This
422
broad glass transition temperature could not be detected by the simple summary statistics reported in the
23
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423
literature. Two subsequent thermal responses—dehydration at 240-260 °C and chain scission at 280-300
424
°C—were also identified. Unlike the glass transition, which was randomly propagated throughout the
425
population, the latter reactions depended on fiber strength. The analyses of the X-ray diffraction patterns
426
using the Rietveld refinement method provided information on thermal crystallization and the destruction
427
of the crystalline structure. The results of this study demonstrate that a finite mixture model not only fully
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described the complex statistical behavior of the tenacity of heated cotton fibers but also provided clues
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regarding the thermal responses of cotton fiber and their characteristics. Identification of such structural
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alterations induced by heat would contribute to enhancing the thermal processing sustainability and
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efficiency of cotton fibrous materials.
432 433
ASSOCIATION CONTENT
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Supporting Information
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The supporting Information: the force–elongation curves and fiber fracture images of cotton fibers heated
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at incremental temperatures is available.
437
AUTHOR INFORMATION
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Corresponding Author
439
*
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Present Address
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Daniel Ahmed Alhassan: Department of Mathematics, Missouri University of Science and Technology,
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Rolla, MO 65409, USA.
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Notes
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This research received no specific grant from any funding agency in the public, commercial, or not-for-
445
profit sectors. The USDA is an equal opportunity provider and employer. The authors declare no
446
competing financial interest.
Sunghyun Nam: Tel.: +15042864229. Fax: +15042864390. E-mail:
[email protected].
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ACKNOWLEDGEMENTS We thank Teresa Morgan for her tensile testing and thank Tanya Goehring and Mohammad
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Saghayezhian for their XRD measurements.
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For Table of Contents Use Only
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TOC graphic
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f ( x; α , λ1 , m1 , λ2 , m2 ) = αf1 ( x; λ1 , m1 ) + (1 − α ) f 2 ( x; λ2 , m2 )
1.0
1.0
0.8
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Probability density
Probability density
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0.6 0.4 0.2 0.0
0.6 0.4 0.2 0.0
0
1
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0
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Tenacity (cN/denier)
Tenacity (cN/denier)
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1
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A finite mixture model described the fracture behavior of heated cotton fibers and revealed their thermal
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responses for the improved sustainability of heat processing.
Synopsis
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