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International Journal of
Molecular Sciences
Article
Effect of Acetyl Group on Mechanical Properties of
Chitin/Chitosan Nanocrystal: A Molecular
Dynamics Study
Junhe Cui 1 , Zechuan Yu 1 and Denvid Lau 1,2, *
Received: 12 December 2015; Accepted: 29 December 2015; Published: 5 January 2016
Academic Editor: Hermann Ehrlich
1
2
*
Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China;
junhecui2-c@my.cityu.edu.hk (J.C.); zechuanyu2-c@my.cityu.edu.hk (Z.Y.)
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge,
MA 02139, USA
Correspondence: denvid@mit.edu; Tel.: +852-3442-6829
Abstract: Chitin fiber is the load-bearing component in natural chitin-based materials. In these
materials, chitin is always partially deacetylated to different levels, leading to diverse material
properties. In order to understand how the acetyl group enhances the fracture resistance capability of
chitin fiber, we constructed atomistic models of chitin with varied acetylation degree and analyzed
the hydrogen bonding pattern, fracture, and stress-strain behavior of these models. We notice that
the acetyl group can contribute to the formation of hydrogen bonds that can stabilize the crystalline
structure. In addition, it is found that the specimen with a higher acetylation degree presents a greater
resistance against fracture. This study describes the role of the functional group, acetyl groups, in
crystalline chitin. Such information could provide preliminary understanding of nanomaterials when
similar functional groups are encountered.
Keywords: chitin; chitosan; acetyl group; fracture energy; stiffness; steered molecular dynamics
(SMD) simulation
1. Introduction
Chitin, poly (β-(1Ñ4)-N-acetyl-D-glucosamine), is a natural polysaccharide of major importance
as universal template in biomineralization [1] as well as the main structural component of invertebrates
skeletons [2]. Chitin-based biological materials attract a lot of research interest due to their huge sources
in nature and excellent material and especially mechanical properties with broad variety of applications
in bioinspired materials sciences and biomimetics [3]. It is widely known that chitin is the second
most abundant substance on our planet ranked after cellulose and the most abundant nitrogen-bearing
organic compound in nature [4]. Because of their outstanding mechanical properties, such as high
strength, high toughness and being lightweight [5,6], chitin acts as a major load-bearing component
in the exoskeleton of diatoms [7], sponges [8], corals [9] and mostly in the arthropod cuticles and
shells of crustaceans (e.g., shrimps, crabs and lobsters) [10,11]. In these stiff tissues, chitin exists as
fibers wrapped up by an extensive stabilized protein matrix which has a consistent interaction with
chitin [12], together with modicum calcium carbonate [13], silica [14], even both mineral phases [15].
In order to achieve chitin for utilization purposes, a series of extraction process is adopted [16],
including acid treatment to remove calcium carbonate, followed by alkaline treatment to remove
proteins [4,12,17] and pigments [8,9,18]. In addition to the removal of protein, alkaline treatment
can partially deacetylate chitin and produce a mixture of chitin and its most important derivative
chitosan [17] in the solvent with pH value of about 9.71 [19]. Apart from the artificial deacetylation
Int. J. Mol. Sci. 2016, 17, 61; doi:10.3390/ijms17010061
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Int. J. Mol. Sci. 2016, 17, 61
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process, chitin is naturally partial deacetylated and natural chitin fiber is a composite system with
different proportions of chitin and chitosan [20]. Compared with chitin in terms of chemical structure,
chitosan only lacks acetyl group [21]. This little structural difference leads to significant distinctions
between chitin and chitosan in many material properties (e.g., solubility, etc.) [4,22]. For instance, as a
result of the hydrophobic property of acetyl group, chitin lacks solubility while chitosan is soluble in
aqueous medium [4,23]. Likewise, it will logically bring about questions such as how acetyl group
can affect the mechanical properties of chitin and chitosan and whether there exists a critical degree
of deacetylation that distinguishes the mechanical behavior of chitin/chitosan. Therefore, attention
should be paid to the effect of acetyl group in order to get the maximum potential of chitin/chitosan
nanocrystal by manipulating the acetyl group.
In terms of mechanical properties, a lot of previous studies mainly focus on measuring
Young’s modulus by performing experimental tensile tests [24,25] on chitin-based materials.
Nevertheless, though many parts of cuticles, like insect wings, are subjected to high loads, which
cause cuticles to fail by fracture, little has been carried out to investigate fracture properties of chitin
based materials up to now [26]. Additionally, fracture and stress-strain behavior are the major
factors governing the strength of a material and determining its application [27]. This indicates
that a full-scale understanding of their mechanical properties is insufficient. Moreover, in order to
unravel the underlying mechanisms governing these properties and make full use of chitin/chitosan
nanocrystal, it is of utmost importance to examine the structure-properties relationship from the
molecular level [28]. Once we have a thorough knowledge about principles of design and construction
of composites by nature from the molecular level upwards [12], we can put it into practice and
use nanofibers, resembling chitin, in composite design for improving mechanical properties [26,29].
At an atomistic level, molecular dynamics (MD) simulation, which investigates mechanical properties
both systematically and comprehensively [5], can be used to explore the structure-property relations.
In previous studies using MD simulation, stiffness and ductility along the chitin chain direction
have been studied, revealing these properties are governed by covalent bonds [30]. In this paper,
our objective is to investigate effect of acetyl group on mechanical properties of chitin/chitosan
nanocrystal by examining fracture energy and stress-strain behavior along the directions, which
are determined by much weaker non-bonded interactions (e.g., hydrogen bond and van der Waals
interactions. To achieve this aim, we simulate the atomistic behavior of chitin nanocrystals subjected to
fracture. Acetyl group contributes to the stabilizing of hydrogen bond (H-bond) network, increasing
the resistance against fracture. Our findings will give inspiration for designing the nanomaterials with
similar functional groups.
2. Results and Discussions
In this section, we present the analysis for the simulation aforementioned, including the
nanostructure, fracture energy and stress-strain behavior of chitin/chitosan nanocrystal. Based on the
results, we show our findings about the role of the acetyl group.
2.1. Structure of Chitin/Chitosan Nanocrystal
We conduct steered molecular dynamics (SMD) simulations along the inter-chain and inter-sheet
directions, where the mechanical properties are governed by non-bonded interactions that could be
quantified by analyzing the H-bonding network through Visual Molecular Dynamics (VMD). As a
result of this, we analyze the interaction within the nanocrystal by plotting the probability density
function (PDF) for occupancy of the H-bond formed between different parts of the model under
different pulling conditions. By definition, an H-bond is formed by an acceptor, a hydrogen atom
and a donor [31]. We choose specific atoms (N, O, and F) as donors or accepters in H-bond detection
by VMD and an H-bond is detected when the distance between acceptor and hydrogen is less than
or equal to 4 Å and the angle between donor-hydrogen-acceptor is less than or equal to 35˝ [31,32].
Adopting these cut-offs, Figure 1 shows the H-bond formation for a single chitin molecule and chitosan
molecule viewing from two perpendicular directions. H-bond occupancy is defined as the percentage
Int. J. Mol. Sci. 2016, 17, 61
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of time that a hydrogen bond is considered “on” during the simulation [33], and it provides a measure
for the strength
of2016,
cohesion
along a plane. For pulling along inter-chain direction, the occupancy
of
Int. J. Mol. Sci.
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H-bonds formed between block 1 and block 2 and block 3 and block 4 are studied while H-bonds
J. Mol.
2016,the
17, 61
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chain
direction,
occupancy
of H-bonds
block 1 and
2 and
blockthe
3 and
block
betweenInt.
block
1Sci.and
block
3 and block
2 andformed
block 4between
are analyzed
for block
pulling
along
other
direction.
4 are studied while H-bonds between block 1 and block 3 and block 2 and block 4 are analyzed for
The results
of
VMD
analysis,
which
is
about
the
occupancy
of
H-bonds
within
each
model
are
plotted
chain
direction,
the
occupancy
of H-bonds
formed
between
block
1 andisblock
2 and
block 3 andofblock
pulling
along the
other
direction.
The results
of VMD
analysis,
which
about
the occupancy
Hin Figure
2. studied
4bonds
are
whilemodel
H-bonds
betweeninblock
1 2.
and block 3 and block 2 and block 4 are analyzed for
within each
are plotted
Figure
pulling along the other direction. The results of VMD analysis, which is about the occupancy of Hbonds within each model are plotted in Figure 2.
Figure 1. H-bonds formed within each model along the inter-chain direction (a,b) and inter-sheet
Figure 1.
H-bonds
within
each boxes
modelhighlight
along the
inter-chain
direction
(a,b)
andinterinter-sheet
direction
(c,d).formed
The orange
and yellow
the difference
in H-bond
pattern
along
direction
(c,d).
The
orange
and
yellow
boxes
highlight
the
difference
in
H-bond
pattern
chain
and
inter-sheet
directions
respectively.
The
dashed
lines
stand
for
H-bonds
and
the
color
Figure 1. H-bonds formed within each model along the inter-chain direction (a,b) and inter-sheet along
inter-chain
and (c,d).
inter-sheet
directions
respectively.
The the
dashed
forpattern
H-bonds
and
the color
represents
the acceptor
atom.
(a,c)
are
the
H-bond
formation
for alines
chitin
molecule;
(b,d) are
H-bond
direction
The orange
and
yellow
boxes
highlight
difference
instand
H-bond
along
interformed
for
a chitosan
molecule.
Comparing
(a,b),
we
note that
thestand
acetyl
group
does not
contribute
represents
the
acceptor
atom.
(a,c) are
the H-bond
formation
for
a chitin
molecule;
(b,d)
H-bond
chain
and
inter-sheet
directions
respectively.
The
dashed
lines
for
H-bonds
and
the are
color
thea formation
of
H-bond
linking
inter-chain
direction.
Comparing
between
(c,d), we
note
that
the
represents
the acceptor
atom.
(a,c) are
the H-bond
formation
for athe
chitin
molecule;
(b,d)
arenot
H-bond
formedto
for
chitosan
molecule.
Comparing
(a,b),
we
note
that
acetyl
group
does
contribute
molecule
without
an acetyl groupComparing
does not form thewe
blue
H-bonds
inter-sheet
direction.
formed for
a chitosan
note
that thelinking
acetyl
group does
notwe
contribute
to the formation
of
H-bondmolecule.
linking inter-chain(a,b),
direction.
Comparing
between
(c,d),
note that the
to the formation of H-bond linking inter-chain direction. Comparing between (c,d), we note that the
molecule without an acetyl group does not form the blue H-bonds linking inter-sheet direction.
molecule without an acetyl group does not form the blue H-bonds linking inter-sheet direction.
Figure 2. Probability density function (PDF) of H-bond occupancy for each pulling condition based
on the last 600 ps of equilibrium simulation. Higher occupancy indicates a stable H-bond. (a,b) Pulling
along inter-chain direction and inter-sheet direction in chitin model; (c,d). Pulling along inter-chain
Figure
2. Probability
density
function
(PDF)
of
H-bondoccupancy
occupancy for
condition
based
Figure 2.
Probability
density
function
(PDF)
ofchitosan
H-bond
for each
eachpulling
pulling
condition
based on
direction
and inter-sheet
direction
in
an 85%
model.
on the last 600 ps of equilibrium simulation. Higher occupancy indicates a stable H-bond. (a,b) Pulling
the last 600 ps of equilibrium simulation. Higher occupancy indicates a stable H-bond. (a,b) Pulling
along inter-chain direction and inter-sheet direction in chitin model; (c,d). Pulling along inter-chain
Based on the
H-bondand
formation
and PDF
of H-bond
occupancy,
comparisons
along inter-chain
direction
inter-sheet
direction
in chitin
model; some
(c,d).reasonable
Pulling along
inter-chain
direction and inter-sheet direction in an 85% chitosan model.
could be
made.
As shown
in Figure
1, some
H-bondsmodel.
linking the inter-sheet direction are refrained
direction
and
inter-sheet
direction
in an
85% chitosan
in chitosan
model
as
a
result
of
the
absence
of
acetyl
group.
Previous studies
demonstrated
that
Based on the H-bond formation and PDF of H-bond occupancy,
some have
reasonable
comparisons
the
distribution
of
acetyl
group
along
the
chain
direction
contributes
to
the
H-bond
formation
in
could be made. As shown in Figure 1, some H-bonds linking the inter-sheet direction are refrained
Based
the H-bond
formation
and PDF
of H-bond
occupancy,
someThe
reasonable
chitinon
model
[4,34]. Our
analysis results
coincide
well with
this conclusion.
occupancycomparisons
of Hin chitosan model as a result of the absence of acetyl group. Previous studies have demonstrated that
could be
made.
As shown
Figure 1,direction
some H-bonds
linking
inter-sheet at
direction
areand
refrained
bonds
formed
along theininter-chain
in the chitin
model the
are concentrated
about 20%,
the distribution of acetyl group along the chain direction contributes to the H-bond formation in
the frequency
of high
occupancy
(more
than of
70%)
H-bonds
is very
low. On the
contrary,
most
of the
in chitosan
model
as
a
result
of
the
absence
acetyl
group.
Previous
studies
have
demonstrated
chitin model [4,34]. Our analysis results coincide well with this conclusion. The occupancy of Hthat thebonds
distribution
of acetyl
group along
theinchain
direction
to the
H-bond
formed along
the inter-chain
direction
the chitin
model contributes
are concentrated
at about
20%, formation
and
themodel
frequency
of high
occupancy
thancoincide
70%) H-bonds
very this
low. conclusion.
On the contrary,
most
of the
in chitin
[4,34].
Our
analysis(more
results
well iswith
The
occupancy
of
H-bonds formed along the inter-chain direction in the chitin model are concentrated at about 20%,
and the frequency of high occupancy (more than 70%) H-bonds is very low. On the contrary, most
Int. J. Mol. Sci. 2016, 17, 61
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of the H-bonds formed along the inter-sheet direction have an occupancy of 65% to 90% while the
frequency of low occupancy H-bonds is only about 1/3 that of high occupancy ones. This distinction
in terms of H-bond occupancy will result in disparate mechanical properties (e.g., fracture energy and
stress-strain curve) along the two separate directions. However, this contrast does not apply to the
Int. J. Mol. Sci. 2016, 17, 61
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85% chitosan
model, whose H-bond occupancy distribution is similar along both of the two
directions,
and most
of its H-bonds
arethe
concentrated
at a low
region.
Apart
fromthe
H-bonds,
H-bonds
formed along
inter-sheet direction
haveoccupancy
an occupancy
of 65% to
90% while
frequencyanother
significant
component
of
non-bonded
interaction
is
van
der
Waals
interaction
[35],
depends
of low occupancy H-bonds is only about 1/3 that of high occupancy ones. This distinction inwhich
terms of
H-bond
occupancy will
result
in disparate
mechanical
(e.g., fracture
and stresslargely on
the molecular
mass.
The
molecular
mass of properties
chitin molecules
are energy
apparently
larger than
strain curve)
along thebecause
two separate
directions.
However,
this contrast
apply to
the 85% atom.
that of chitosan
molecules
the acetyl
group
is greater
in massdoes
thannot
a single
hydrogen
chitosan model, whose H-bond occupancy distribution is similar along both of the two directions,
The distinction
in terms of non-bonded interaction between chitin and chitosan model will result in
and most of its H-bonds are concentrated at a low occupancy region. Apart from H-bonds, another
diverse mechanical properties.
significant component of non-bonded interaction is van der Waals interaction [35], which depends
largely on the molecular mass. The molecular mass of chitin molecules are apparently larger than
2.2. Fracture
and Stress-Strain Behavior
that of chitosan molecules because the acetyl group is greater in mass than a single hydrogen atom.
The distinction
in terms
of non-bonded
interaction
chitin and chitosan
model
will result in
Based
on the value
of potential
of mean
force between
(PMF) computed
by SMD
simulation,
the PMF
diverse mechanical properties.
profiles (Figure 3), also known as one dimensional free energy of chitin/chitosan nanocrystal [36],
are plotted
for two
pulling directions
2.2. Fracture
and Stress-Strain
Behavior of both models. The maximum PMF for chitin model
along the inter-chain direction is about 2350 kcal{mol, which is much smaller than that along the
Based on the value of potential of mean force (PMF) computed by SMD simulation, the PMF 2
inter-sheet
direction
The
fracture energy
is calculated
to benanocrystal
0.33 kcal{pmol¨
profiles
(Figure (6135
3), alsokcal{mol).
known as one
dimensional
free energy
of chitin/chitosan
[36], areÅ q and
2
plotted for
directions ofand
bothinter-sheet
models. Thedirections
maximum PMF
for chitinAccording
model along
0.86 kcal{pmol¨
Å two
q forpulling
the inter-chain
separately.
tothe
this data,
inter-chain
direction
is
about
2350
kcal/mol,
which
is
much
smaller
than
that
along
the
inter-sheet
the chitin nanocrystal is a very brittle material because the fracture energy is much less than typical
direction (6135 kcal/mol ). The fracture 2energy is calculated to be 0.33 kcal/ mol Å
and 0.86
brittle material—glass
tointer-chain
5 kcal{pmol¨
q) [37,38].
Since separately.
there is noAccording
covalenttobond
formed
kcal/ mol Å for(3the
and Å
inter-sheet
directions
this data,
the along
the two chitin
pulling
directions,
the brittle
causes
for thebecause
differences
in fracture
stem
distinctions
in
nanocrystal
is a very
material
the fracture
energy isenergy
much less
thanfrom
typical
brittle
non-bonded
interactions
PMF profile
shown
incovalent
Figure bond
3c,d, formed
the maximum
material—glass
(3 to[38,39].
5 kcal/ From
mol Åthe) [37,38].
Since there
is no
along thePMF
two of 85%
the causes
for the
differences
fracture
energy stem
from distinctions
in nonchitosanpulling
modeldirections,
is estimated
to be 1600
kcal{mol
forin
both
inter-chain
direction
and inter-sheet
direction.
2 PMF of 85%
bonded interactions [38,39]. From the PMF profile shown in Figure 3c,d, the maximum
The corresponding values for fracture energy are computed to 0.29 kcal{pmol¨ Å q. Compared with
chitosan model is estimated to be 1600 kcal/mol for both inter-chain direction and inter-sheet
pure chitin
model,The
thecorresponding
85% chitosanvalues
modelfor
presents
fracture
energy
direction.
fracturea smaller
energy are
computed
to (approximately
0.29 kcal/ mol Å25%–65%)
.
along both
pulling
directions.
Moreover,
the
crystalline
model,
the PMF
demonstrates
a
Compared
with
pure chitin
model, thefor
85%
chitosan
modelchitin
presents
a smaller
fracture
energy
25%–65%)
alongdetach
both pulling
Moreover,
for theafter
crystalline
chitin model,
constant(approximately
value when the
two parts
from directions.
each other.
In contrast,
the amorphous
chitosan
PMF demonstrates
constant
valuethe
when
the two
parts is
detach
from each
other.
In contrast,
after before
model isthe
separated
into twoamajor
parts,
value
of PMF
increasing,
but
much
slower than
the
amorphous
chitosan
model
is
separated
into
two
major
parts,
the
value
of
PMF
is
increasing,
but from
separation, because there are still some linkages between the two parts, which can be observed
much slower than before separation, because there are still some linkages between the two parts,
the corresponding trajectory.
which can be observed from the corresponding trajectory.
PMF profiles for each pulling scenario. The “Savitzky–Golay filter” method is adopted to
Figure 3.Figure
PMF3.profiles
for each pulling scenario. The “Savitzky–Golay filter” method is adopted to
draw a smooth curve by fitting a cubic function for every 100 raw data points. The VMD snapshots
draw a smooth curve by fitting a cubic function for every 100 raw data points. The VMD snapshots
show the corresponding pulling situations. (a,b) are PMF profiles for chitin model pulling along intershow the
corresponding
situations.
PMFprofiles
profiles
model
chain
and inter-sheetpulling
directions
respectively;(a,b)
(c,d) are
are PMF
for for
85% chitin
chitosan
model pulling
pulling along
inter-chain
inter-sheet
directions
respectively;
(c,d) are PMF profiles for 85% chitosan model
alongand
inter-chain
and inter-sheet
directions,
respectively.
pulling along inter-chain and inter-sheet directions, respectively.
Int. J. Mol. Sci. 2016, 17, 61
Int. J. Mol. Sci. 2016, 17, 61
5 of 13
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We can
We
can estimate
estimate the
the elastic
elastic constant
constant and
and stress-strain
stress-strain behavior
behavior of
ofchitin/chitosan
chitin/chitosan nanocrystal
nanocrystal
according
to
the
output
values
of
pulling
force.
The
stress
acted
on
the
nanocrystal
is
according to the output values of pulling force. The stress acted on the nanocrystal is estimated
estimated
according to
to method
Figure 44 illustrates
illustrates the
the stress-strain
stress-strain curve
curve along
along each
each
according
method previously
previously mentioned.
mentioned. Figure
pulling direction for both chitin and 85% chitosan models. For
For all those curves, the stress along the
pulling direction shows a linear elastic response before reaching
reaching the
the maximum
maximum value.
value. The elastic
corresponding
ultimate
stress
andand
fracture
strain,
can
constant, or
or equivalently
equivalentlystiffness,
stiffness,together
togetherwith
with
corresponding
ultimate
stress
fracture
strain,
be
estimated
from
the
stress-strain
curves
plotted
and
the
values
are
listed
in
Table
1.
can be estimated from the stress-strain curves plotted and the values are listed in Table 1.
Figure
curves.
The curves
are initial
curves generated
by the Savitzky–
Figure 4.4. Stress-strain
Stress-strain
curves.
The curves
are stress-strain
initial stress-strain
curves generated
by the
Golay
filter
method
on
the
basis
of
the
huge
amount
of
raw
data
points.
To
generate
smooth
curvea
Savitzky–Golay filter method on the basis of the huge amount of raw data points.a To
generate
correctly
representing
the
relationship
between
stress
and
strain,
we
use
a
cubic
function
to
fit
for
smooth curve correctly representing the relationship between stress and strain, we use a cubic function
every
50 every
data points.
redThe
lines
are
linear
for fit
thefor
elastic
region,
and its
represents
the
to fit for
50 data The
points.
red
lines
are fit
linear
the elastic
region,
andslope
its slope
represents
stiffness.
The
value
of
stiffness
is
shown
in
the
legend.
(a,b)
are
stress-strain
curves
for
chitin
model
the stiffness. The value of stiffness is shown in the legend. (a,b) are stress-strain curves for chitin
pulling
along along
inter-chain
and inter-sheet
directions,
respectively;
(c,d)
arearestress-curves
model pulling
inter-chain
and inter-sheet
directions,
respectively;
(c,d)
stress-curvesfor
for 85%
85%
chitosan
model
pulling
along
inter-chain
and
inter-sheet
directions
respectively.
chitosan model pulling along inter-chain and inter-sheet directions respectively.
Table
Table 1.
1. Summary
Summary of
of stress-Strain
stress-Strain behavior.
behavior.
Model
Model
Chitin
Chitin
85% Chitosan
85% Chitosan
Direction
Direction
Inter-chain
Inter-chain
Inter-sheet
Inter-sheet
Inter-chain
Inter-chain
Inter-sheet
Inter-sheet
Ultimate Stress (GPa)
Ultimate Stress (GPa)
0.551
0.551
0.936
0.936
0.372
0.372
0.419
0.419
Fracture Strain (%)
Fracture Strain (%)
5.29
5.29
7.45
7.45
6.22
6.22
8.82
8.82
Stiffness (GPa)
Stiffness (GPa)
22.58
22.58
21.13
21.13
13.39
13.39
11.98
11.98
The elastic constants of the chitin model are 22.58 and 21.13 GPa for inter-chain and inter-sheet
The elastic
constants
oftwo
the values
chitin model
are 22.58
and 21.13
for inter-chain
inter-sheet
directions
distinctively.
The
of stiffness
are more
or lessGPa
similar
instead of aand
sharp
contrast
directions
distinctively.
The
two
values
of
stiffness
are
more
or
less
similar
instead
of
a
sharp
contrast
as
as in case of the fracture energy. The simulation results are nearly identical to the experimental
in case of the
fracture
Thestudies
simulation
results are our
nearly
identical
to the
experimental
measured
measured
results
fromenergy.
previous
[40], indicating
model
making
techniques
and simulation
results
from
previous
studies
[40],
indicating
our
model
making
techniques
and
simulation
methods are suitable for the studying purpose. However, the stiffness value is much lower methods
than the
are suitableresult
for theby
studying
the direction
stiffness value
much[30,41]
lower because
than the inter-chain
simulation
simulation
pulling purpose.
along theHowever,
chitin chain
(92.26isGPa)
resultinter-sheet
by pulling directions
along the chitin
chain direction
(92.26
GPa) [30,41]
becauseinstead
inter-chain
and inter-sheet
and
are stabilized
by much
weaker
interactions
of strong
covalent
directions
are
stabilized
by
much
weaker
interactions
instead
of
strong
covalent
bonds.
Furthermore,
bonds. Furthermore, the ultimate stress and fracture strain for pulling along the inter-sheet direction
the much
ultimate
stress
and
fracture
for pulling
along the inter-sheet direction are much larger than
are
larger
than
that
alongstrain
the inter-chain
direction.
that along
the inter-chain
direction.
However,
for the chitosan
model, the ultimate stress along inter-sheet direction is slightly
instead of significantly larger than that of inter-chain direction, which conforms the H-bond
occupancy distribution previously mentioned. When compared with the chitin model, more
distinctions can be detected. From Table 1, the stiffness and ultimate stress of the 85% chitosan model
Int. J. Mol. Sci. 2016, 17, 61
6 of 13
However, for the chitosan model, the ultimate stress along inter-sheet direction is slightly instead
of significantly larger than that of inter-chain direction, which conforms the H-bond occupancy
distribution previously mentioned. When compared with the chitin model, more distinctions can
be detected. From Table 1, the stiffness and ultimate stress of the 85% chitosan model along both
pulling directions are much smaller than the corresponding values of chitin model, indicating that the
chitosan model is less stiff. In contrast, the fracture strains are almost 1.3 times that of the chitin model,
revealing that the chitosan model is more ductile than the chitin model.
2.3. The Role of Acetyl Group
The only chemical difference between chitin and chitosan is the acetyl group. The presence
of the acetyl group causes more high occupancy H-bonds along the inter-sheet direction of chitin
model. In contrast, as there are few acetyl groups within the chitosan model, the H-bond occupancy
along two directions is similar. Additionally, van der Waals interaction within chitin crystals is
significantly enlarged due to the larger molecular mass of acetyl group. The effect of acetyl group on
these non-bonded interactions results in distinct mechanical properties between chitin and chitosan.
From the H-bonding network aforementioned, H-bond occupancy is correlated to strength of
cohesion along a plane. An H-bond with higher occupancy leads to greater fracture strength according
to stochastic theory of fracture [33,38]. Within the chitin model, acetyl groups contribute to the
formation of stable H-bonds (higher occupancy) along the inter-sheet direction. Fracture along this
direction requires more energy to break these high occupancy H-bonds. It is the presence of acetyl
group that leads to much higher fracture energy and larger ultimate stress along the inter-sheet
direction. Meanwhile, the relatively smaller fracture energy and smaller ultimate stress in the
inter-chain direction indicate a higher possibility for the chitin crystal to fail by fracture between
different chitin layers under high loading conditions. In contrast with the chitin model, there is no
significant distinction in terms of fracture and stress-strain behavior along two pulling directions
within chitosan model due to lack of acetyl group. Moreover, during the pulling process, there are some
linkages between two parts of chitosan model instead of a thorough separation. This phenomenon
is correlated to the amorphous nature of chitosan model resulted from the lack of acetyl group.
Additionally, the fracture energy and ultimate stress of chitosan model is smaller than that of chitin
model due to little contribution of acetyl group on increasing the number of H-bond and van der Waals
interaction. However, without the supporting effect of the acetyl group, the atoms are in much closer
contact in the amorphous chitosan model. The closer molecular contact leads to a shorter original
length along the pulling direction as well as a larger deformation before fracture occurs. As a result
of this, the chitosan model demonstrates a better performance in terms of ductility. To summarize,
the presence of the acetyl group demonstrates the following effects on mechanical properties of
chitin/chitosan nanocrystal: increasing the resistance against fracture while decreasing the ductility by
affecting the non-bonded interactions. In the industrial field, materials of different functions require
various mechanical properties. In some conditions, higher fracture energy material is required while
ductile material is preferred in other conditions. The findings in this paper will inspire us to obtain
the most appropriate mechanical properties and fully utilize chitin-based materials by adjusting the
acetyl group.
3. Methods
In this paper, we have constructed two models. The first one is pure chitin model and the second
one is with an 85% degree of deacetylation (i.e., 85% chitosan and 15% chitin). It is practical to extract
85% deacetylated chitosan from natural sources [42]. Many previous studies adopted 85% chitosan
as the high degree of deacetylation sample [43–45]. Therefore, we choose the 85% chitosan model to
form a sharp contrast with the pure chitin model so that the effect of the acetyl group is apparent.
In addition, these two models can reflect the degree of deacetylation of real chitin/chitosan samples.
Steered molecular dynamics (SMD) simulation has been proven as a good way for investigating fracture
Int. J. Mol. Sci. 2016, 17, 61
7 of 13
behavior in previous measurements [46–49]. In each model, SMD simulations are performed along
both inter-chain and inter-sheet directions separately. The model making techniques and simulation
Int.J.J.Mol.
Mol.
Sci.2016,
2016,
17,61
61
of12
12
details
will
be
discussed
in the following subsections.
Int.
Sci.
17,
77of
3.1.
AtomisticModels
Models
3.1.Atomistic
3.1.
Chitin
polymer
consists
of
linear
chain
of
poly
β-(1Ñ4)-N-acetyl-glucosamine
[21].
Figure
5a
Chitinpolymer
polymerconsists
consistsof
ofaaalinear
linearchain
chainof
ofpoly
polyβ-(1→4)-N-acetylβ-(1→4)-N-acetyl-DD
D-glucosamine
-glucosamine[21].
[21].Figure
Figure5a
Chitin
shows
the
chemical
structure
of
chitin
molecule.
Innature,
nature,chitin
chitinexists
existsas
asthree
showsthe
thechemical
chemicalstructure
structureof
ofchitin
chitinmolecule.
molecule.In
threekinds
kindsof
ofcrystal
crystalforms,
forms,
shows
namely
α-chitin,
β-chitin
and
γ-chitin.
Among
them,
the
most
abundant
crystal
form
is
α-chitin
[50],
namelyα-chitin,
α-chitin,β-chitin
β-chitinand γ-chitin. Among them, the most abundant crystal form is α-chitin [50],
namely
which
has
structure
of
antiparallel
chains.
Previous studies
studies have
have revealed
revealed the
the structure
structure of
of its
its
unit
whichhas
hasaaastructure
structureof
ofantiparallel
antiparallelchains.
chains.Previous
itsunit
unit
which
cell
[19,51],
which
have
been
used
by
us
to
construct
our
chitin
model.
We
divide
the
whole
model
into
cell
[19,51],
which
have
been
used
by
us
to
construct
our
chitin
model.
We
divide
the
whole
model
cell [19,51], which have been used by us to construct our chitin model. We divide the whole model
four
regions
in thein
first
in
order
to
make
easier for
future
work. The
x, y,
intofour
fourregions
regions
in
theplace
firstplace
place
inorder
order
toatom
makeselection
atomselection
selection
easier
forsimulation
futuresimulation
simulation
work.
into
the
first
in
to
make
atom
easier
for
future
work.
and
zx,axes
in zthe
picture
correspond
to the <100>,
<010>
and<010>
<001>and
directions,
respectively.
The whole
Thex,
and
zaxes
axes
inthe
the
picturecorrespond
correspond
tothe
the<100>,
<100>,
<010>
and
<001>directions,
directions,
respectively.
The
y,y,and
in
picture
to
<001>
respectively.
model
contains
55,680
atoms
in
total
and
the
dimension
of
the
model
is
84.51
ˆ
77.02
The
whole
model
contains
55,680
atoms
in
total
and
the
dimension
of
the
model
is
84.51
77.02Å,
The whole model contains 55,680 atoms in total and the dimension of the model is 84.51ˆ××82.25
77.02
××
which
is
an
optimum
size
for
studying
of
fracture
behavior
[38].
Figure
6
shows
the
final
layout
and
82.25 Å,
Å, which
which isis an
an optimum
optimum size
size for
for studying
studying of
of fracture
fracture behavior
behavior [38].
[38]. Figure
Figure 66 shows
shows the
the final
final
82.25
numbering
system
of
this
model.
layout
and
numbering
system
of
this
model.
layout and numbering system of this model.
Figure 5.5. (a)
(a)Chemical
Chemicalstructure
structure
of
chitin
molecule;
(b) chemical
chemical
structure
of chitosan.
chitosan.
The acetyl
acetyl
Figure
Chemical
structure
chitin
molecule;
structure
of
The
Figure
ofof
chitin
molecule;
(b) (b)
chemical
structure
of chitosan.
The acetyl
group
group
is
highlighted
in
the
red
box.
group
is highlighted
in the
red box.
is highlighted
in the red
box.
Figure6.
6.(a)
(a)
The
3D
view
of
the
complete
chitin
model;
(b,c)
Two
crosssectional
sectionalviews
viewsof
ofchitin
chitinmodel
model
Figure
6.
(a)The
The3D
3Dview
viewof
ofthe
thecomplete
completechitin
chitinmodel;
model;(b,c)
(b,c)Two
Twocross
cross
sectional
views
of
chitin
model
Figure
(c)
also
shows
the
model
numbering
system.
Numbers
1–4
correspond
to
the
four
regions
divided
to
(c) also
also shows
shows the
the model
model numbering
numbering system.
system. Numbers
Numbers1–4
1–4correspond
correspondto
tothe
thefour
fourregions
regions divided
divided to
to
(c)
makeatom-selection
atom-selectioneasier
easierfor
forlater
laterSMD
SMDsimulation
simulationwork.
work.
make
atom-selection
easier
for
later
SMD
simulation
work.
make
Chitosan is either
either an artificially
artificially or naturally
naturally deacetylated derivative
derivative of chitin
chitin which isis
Chitosan
Chitosan is
is either an
an artificially or
or naturally deacetylated
deacetylated derivative of
of chitin which
which is
endogenously
produced
in
vertabrates
[52].
It
is
with
linearity
in
arrangement
and
composedof
of βendogenously
produced
in
vertabrates
[52].
It
is
with
linearity
in
arrangement
and
composed
endogenously produced in vertabrates [52]. It is with linearity in arrangement and composed βof
(1→4)-linked-DD-glucosamine
-glucosamine [53].
[53]. Meanwhile,
Meanwhile, as
as isis shown
shown in
in Figure
Figure 5b,
5b, we
we can
can see
see its
its chemical
chemical
(1→4)-linkedstructure. As
As the
the deacetylated
deacetylated derivative
derivative of
of chitin,
chitin, chitosan
chitosan exists
exists together
together with
with chitin
chitin in
in
structure.
chitin/chitosannanocrystals
nanocrystalswith
withdifferent
differentdegrees
degrees of
ofdeacetylation.
deacetylation. As
As previously
previously mentioned,
mentioned, one
one
chitin/chitosan
of
the
frequently
used
experimental
samples
is
85%
deacelytated
chitosan
[42,43,54].
Moreover,
chitin
of the frequently used experimental samples is 85% deacelytated chitosan [42,43,54]. Moreover, chitin
crystal will
will lose
lose its
its crystallinity
crystallinity during
during the
the transformation
transformation process
process to
to chitosan,
chitosan, resulting
resulting in
in an
an
crystal
Int. J. Mol. Sci. 2016, 17, 61
8 of 13
β-(1Ñ4)-linked-D-glucosamine [53]. Meanwhile, as is shown in Figure 5b, we can see its chemical
structure. As the deacetylated derivative of chitin, chitosan exists together with chitin in chitin/chitosan
nanocrystals with different degrees of deacetylation. As previously mentioned, one of the frequently
used experimental samples is 85% deacelytated chitosan [42,43,54]. Moreover, chitin crystal will lose
its J.crystallinity
the transformation process to chitosan, resulting in an amorphous shape
of
Int.
Mol. Sci. 2016, during
17, 61
8 of 12
the extracted chitosan [43,55]. Therefore, our second model is constructed by replacing 85% chitin
molecules85%
by chitosan
molecules randomly
and
evenly. Inrandomly
order to build
modelIninorder
highlytoconformity
replacing
chitin molecules
by chitosan
molecules
and the
evenly.
build the
with reality,
we conformity
design it non-symmetrically
in any
direction (Figure 7).
Moreover,
this
partially
model
in highly
with reality, we design
it non-symmetrically
in any
direction
(Figure
7).
deacetylated
model
contains
47,040 atoms.
Moreover,
this
partially
deacetylated
model contains 47,040 atoms.
Figure 7.
7. (a)
(a) The
The 3D
3D view
viewof
ofthe
thecomplete
completechitosan
chitosanmodel;
model;(b,c)
(b,c)Two
Two cross
cross sectional
sectional views
views of
of chitosan
chitosan
Figure
model. (c)
(c) Model
Model numbering
numbering system.
system. Numbers
Numbers1–4
1–4correspond
correspondto
to the
the four
four regions
regions divided
divided to
to make
make
model.
atom-selection easier
easier for
for later
later SMD
SMD simulation
simulation work.
work. In
In comparison
comparison with
with the
the crystalline
crystalline structure
structure of
of
atom-selection
chitin,
this
amorphous
structure
presents
a
closer
molecular
contact,
revealing
the
unstable
nature
of
chitin, this amorphous structure presents a closer molecular contact, revealing the unstable nature of
highly
deacetylated
chitosan.
highly deacetylated chitosan.
3.2.
3.2. Simulation
Simulation Details
Details
In
Parallel
Simulator
(LAMMPS)
is used
to
In this
this study,
study, Large-scale
Large-scaleAtomic/Molecular
Atomic/MolecularMassively
Massively
Parallel
Simulator
(LAMMPS)
is used
do
simulations
forfor
thethe
twotwo
chitin/chitosan
nanocrystal
models.
We We
use use
CHARMM36
force
fields
for
to do
simulations
chitin/chitosan
nanocrystal
models.
CHARMM36
force
fields
chitin
and and
chitosan
molecules
throughout
the whole
simulation
process
[56]. A
cutoff
of 10 Å
for chitin
chitosan
molecules
throughout
the whole
simulation
process
[56].
A cutoff
of(10
10 −10
Å
´
10
m)
for the
interactions.
We We
useuse
thethe
particle-particle
(10 is adopted
m) is adopted
fornon-bonded
the non-bonded
interactions.
particle-particleparticle-mesh
particle-mesh(PPPM)
(PPPM)
method
method to
to compute
compute the
the long-range
long-range Columbic
Columbic interactions.
interactions. The
The SHAKE
SHAKE algorithm
algorithm is
is used
used to
to constraint
constraint
high-frequency
dynamics from
fromhydrogen-related
hydrogen-relatedenergy
energyterms
terms
[57].
Periodic
boundary
condition
is
high-frequency dynamics
[57].
Periodic
boundary
condition
is set
set
in all
<100>,
<010>and
and<001>
<001>directions
directionsbut
butalong
alongthe
the<010>
<010> direction, sufficient space between
in all
thethe
<100>,
<010>
between
the
the mirror
mirror images
images is reserved for future simulation work. The
The above
above settings
settings were
were adopted
adopted in
in the
the
past
research works
worksabout
aboutmechanical
mechanicalproperties
properties
chitin-based
material
[19,28,30].
Similarly,
we
past research
of of
chitin-based
material
[19,28,30].
Similarly,
we also
also
adopt
the method
from previous
the equilibrium
simulation
Firstly,
the
adopt
the method
from previous
studiesstudies
for the for
equilibrium
simulation
process. process.
Firstly, the
system
is
system
is minimized
reach a minimum-energy
status bythe
adjusting
the atom coordinates
minimized
to reach a to
minimum-energy
status by adjusting
atom coordinates
according toaccording
conjugate
to
conjugate
gradient
algorithm.
then
heated
50 ps.
to 300
K in
20 ps.
that, it
gradient
algorithm.
The
system isThe
thensystem
heatedisup
from
50 to up
300from
K in 20
After
that,
it isAfter
equilibrated
is
equilibrated
at
300
K
for
50
ps
in
a
canonical
(NVT)
ensemble
(amount
of
substance/volume
at 300 K for 50 ps in a canonical (NVT) ensemble (amount of substance/volume /temperature remain
/temperature
remain
followed
equilibration
300
1 atm for 500 ps (NPT)
in an
constant) followed
byconstant)
equilibration
at 300by
K and
1 atm forat
500
ps K
in and
an isothermal-isobaric
isothermal-isobaric
(NPT)
ensemble (amount of substance/pressure/temperature
remain constant).
ensemble (amount of
substance/pressure/temperature
remain constant). The temperature
control
The
temperature
control is achieved
using
Nose-Hoover
Finally,
the system
is
is achieved
using Nose-Hoover
thermalstat.
Finally,
the systemthermalstat.
is equilibrated
in an NVT
ensemble
equilibrated
anand
NVT
ensemble
for another
1 nsfile
and
corresponding
output fileThe
is saved
for have
later
for another 1inns
the
corresponding
output
is the
saved
for later simulations.
models
simulations. The models have achieved equilibrium state because the computed root mean square of
deviation (RMSD) value has become constant.
After equilibrium simulation, we perform steered molecular dynamics (SMD) simulation on the
two models. During the simulation process, SMD force is applied by tethering one end of a virtual
spring to a target atom while the other end is used for pulling. Two sets of SMD simulation are done
on each model along two perpendicular directions as is shown in Figure 8. For the pulling along inter-
Int. J. Mol. Sci. 2016, 17, 61
9 of 13
achieved equilibrium state because the computed root mean square of deviation (RMSD) value has
become constant.
After equilibrium simulation, we perform steered molecular dynamics (SMD) simulation on the
two models. During the simulation process, SMD force is applied by tethering one end of a virtual
spring to a target atom while the other end is used for pulling. Two sets of SMD simulation are
done on each model along two perpendicular directions as is shown in Figure 8. For the pulling
along inter-chain (<010>) direction, the center of mass of block 3 and block 4 is chosen as a target
atom tethered to the virtual spring while the center of mass of block 2 and block 4 is selected for
Int. J. Mol. Sci. 2016, 17, 61
9 of 12
simulation along the inter-sheet (<001>) direction. The momentum of the other half of the model is
reset
zero. SMD
the constant
speed
mode
is usedand
to stretch
theapproach
model and
this
SMD
approach
in
the to
constant
speedinmode
is used to
stretch
the model
this SMD
has
been
successfully
has been
successfully
used
in previous
[30,38].
Similar
to previous
research
studying
used
in previous
similar
studies
[30,38]. similar
Similar studies
to previous
research
studying
mechanical
properties
mechanical
properties
of
cellulose,
we
adopt
the
same
parameters
in
SMD
simulation
with
of
of cellulose, we adopt the same parameters in SMD simulation with speed of v = 20Å/nsandspeed
virtual
2 ), respectively [38].
v
“
20
Å{ns
and
virtual
spring
constant
of
100
kcal/(mol¨
Å
spring constant of 100 kcal/(mol Å2), respectively [38].
Figure 8. Two sets of SMD simulation. The green blocks represent different parts of the model and
Figure 8. Two sets of SMD simulation. The green blocks represent different parts of the model and
the numbers demonstrate the combination of the four parts divided previously. The blue arrows
the numbers demonstrate the combination of the four parts divided previously. The blue arrows
demonstrate the direction of pulling force. (a) Pulling along the inter-chain direction; (b) Pulling along
demonstrate the direction of pulling force. (a) Pulling along the inter-chain direction; (b) Pulling along
inter-sheet direction; (c,d) illustrate the inter-chain and inter-sheet directions, where the dotted blue and
inter-sheet direction; (c,d) illustrate the inter-chain and inter-sheet directions, where the dotted blue
orange lines correspond to the inter-chain and inter-sheet interactions respectively.
and orange lines correspond to the inter-chain and inter-sheet interactions respectively.
The trajectory of equilibrium simulation is used to analyze the H-bonding system within the
TheFrom
trajectory
of equilibrium
simulation
is used to analyze
the and
H-bonding
system within
the
models.
previous
studies, the cut-off
of donor-acceptor
distance
donor-hydrogen
acceptor
models.
studies,
the cut-off
donor-acceptor
distance
donor-hydrogen
acceptor
angle
are From
set to previous
4 Å and 35°,
respectively,
forofdetecting
hydrogen
bondsand
[19,28].
In the later 600
ps of
˝ , respectively, for detecting hydrogen bonds [19,28]. In the later 600 ps of
angle
are
set
to
4
Å
and
35
equilibrium simulation, the information of H-bond is collected every 10 ps by VMD. The occupancy
equilibrium
simulation,
theps
information
ofby
H-bond
10 ps by VMD.
The
occupancy
of
of
H-bond over
the last 600
is analyzed
meansisofcollected
plottingevery
its probability
density
function
(PDF)
H-bond
over
the
last
600
ps
is
analyzed
by
means
of
plotting
its
probability
density
function
(PDF)
using MATLAB. During the SMD simulation process, LAMMPS makes a record every 100 fs for
using MATLAB.
During
the potential
SMD simulation
LAMMPS
makes
a record
every
100 (CM)
fs for
several
useful values,
namely
of meanprocess,
force (PMF),
distance
between
center
of mass
several
useful
values,
potential
of the
mean
forcedirection.
(PMF), distance
between
center
massthese
(CM)
of
two half
models
andnamely
spring force
along
pulling
It is very
significant
to of
record
of
two
half
models
and
spring
force
along
the
pulling
direction.
It
is
very
significant
to
record
these
values for analyzing the simulation results in the later stage. We use potential of mean force (PMF)
to represent work done by the virtual spring during the SMD simulation process [58]. We calculate
the displacement of the end of virtual spring x(t) and model strain ( ) along the pulling direction
using the distance between CMs of the pulling part and stable part of the model. By plotting PMF
against displacement of spring end, we can generate PMF profile of which the maximum constant
value can be used to compute the fracture energy. The stress applied by the virtual spring is estimated
Int. J. Mol. Sci. 2016, 17, 61
10 of 13
values for analyzing the simulation results in the later stage. We use potential of mean force (PMF) to
represent work done by the virtual spring during the SMD simulation process [58]. We calculate the
displacement of the end of virtual spring x(t) and model strain (σ) along the pulling direction using
the distance between CMs of the pulling part and stable part of the model. By plotting PMF against
displacement of spring end, we can generate PMF profile of which the maximum constant value can
be used to compute the fracture energy. The stress applied by the virtual spring is estimated from the
force applied along the pulling direction. Based on the values calculated above, stress-strain curve is
plotted and the stiffness is estimated as the slope of this curve in the linear elastic range.
4. Conclusions
In this research, the effects of acetyl group on two mechanical properties—fracture energy
and stress-strain behavior—are studied due to the load-bearing function of chitin fibers in natural
chitin-based materials. We construct two typical atomistic models, namely pure chitin model and
85% chitosan model. The chitosan model is built amorphously to fit the realistic structure of chitosan,
which has not been taken into account in previous molecular dynamics studies. In each model, we
performed two sets of steered molecular dynamics (SMD) simulations along inter-sheet direction and
inter-chain direction, respectively, to measure the fracture energy and study the stress-strain behavior.
For the chitin model, the fracture energy for pulling along inter-chain direction is lower, indicating the
fracture is more likely to occur along this direction. The fracture energy of 85% chitosan model is about
25% to 65% of chitin model, and this difference is the result of stronger non-bonded interactions within
the chitin model due to the presence of the acetyl group. The stiffness of chitin model is estimated
to be 21.13 to 22.58 GPa, which is identical to experimental results. In contrast, the 85% chitosan
model has a lower stiffness but larger strain, revealing the effect of acetyl group on increasing stiffness
and decreasing ductility. Our findings could provide preliminary understanding of nanomaterials
with acetyl groups and could further inspire us to design composite materials by appropriately
introducing the acetyl group to achieve better mechanical performance. Our models are limited to
demonstrating the mechanical behaviors at the atomistic level. In reality, materials exhibit diverse
mechanical properties at different length scales. This study focuses on an atomistic investigation, and
questions about acetyl groups at a large length scale remain unanswered. Future studies could adopt
coarse-grained models and establish multiscale understanding of chitin-based materials.
Acknowledgments: The authors are grateful to the support from Croucher Foundation through the Start-up
Allowance for Croucher Scholars with the Grant No. 9500012, and the support from the Research Grants Council
(RGC) in Hong Kong through the Early Career Scheme (ECS) with the Grant No. 139113.
Author Contributions: Junhe Cui carried out the molecular dynamics simulations and drafted the manuscript.
Zechuan Yu and Denvid Lau conceived of the study and participated in its design and coordination. All authors
read and approved the final manuscript.
Conflicts of Interest: The authors declare no conflict of interest.
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