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; [email protected] (J.C.); [email protected] (Z.Y.) Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA Correspondence: [email protected]; 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

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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

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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. 17, 61 3 of 12 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 3 of 12 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

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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 4 of 12 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.

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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

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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

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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 , and and directions, respectively. The whole Thex, and zaxes axes inthe the picturecorrespond correspond tothe the, , and directions, directions, respectively. The y,y,and in picture to 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

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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 , and and directions directionsbut butalong alongthe the direction, sufficient space between in all thethe , 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-

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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 () 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 () 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 = 20 Å/ns andspeed 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

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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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