The University of New South Wales Faculty of Science School of Materials Science and Engineering
Molecular Dynamics Simulation of ODTMA-Montmorillonite and Nylon 6 Nanocomposites
By
Lei WANG
Submitted in Partial Fulfilment of the Requirements For the Degree of
Master of Engineering By Research
February 2007 II
CERTIFICATE OF ORIGINALITY
I hereby declare this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, nor materials which to a substantial extent has accepted for the award of any other degree or diploma at UNSW or any other institutes, except where due acknowledgment is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis.
I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.
(Signed) ……………………………...... ….. III
Acknowledgement
I am sincerely indebted to my supervisors, Professor Aibing Yu and Dr. Qinghua Zeng, not only for their invaluable guidance, constant support and encouragement, but also for their believing in me through various difficult periods. They have taught me the importance of perspective, in both research and life. I consider myself very fortunate to have worked with both mentors.
I would like to thank the members in the our research lab (SIMPAS), past and present, for their help and friendship, and many interactions, either work or non-work related, during the studying period of my work, and the staff in the School of Materials Science and Engineering for their supports. Especially thanks to Dr Ruiping Zou for her extensive help and assistance, Dr Kejun Dong for his kindly help to the computer and network setup related issues, Mr Shibo Kuang for his valuable advices and encouragements.
I am also grateful to the University of New South Wales and the University of Queensland to provide me this opportunity of doing the nanocomposites research project.
Most importantly, I would like to express acknowledgment to my mother Yueling Liu and my uncle Zhiyu Liu for their understanding and continuing support during these two years. IV
Abstract
Polymer materials stand on a very significant position in the materials industry area. The presence of organoclay nanocomposites reinforces polymer materials on many properties like strength, tensile and so on. Most previous studies on the characteristics of organoclays and polymer nanocomposites were based on the experimental approaches such as XRD (X-ray Diffraction) and NMR (Nuclear Magnetic Resonance). These methods have achieved successfully on the basic analysis of chains and layering structures of polymer nanocomposites. However, information on the molecular level cannot be provided by those approaches. MD (Molecular Dynamic) simulation method could be employed to develop further information on the molecular level about organoclays and interlayer structure polymer nanocomposites.
In the research of ODTMA-MMT (Octadecyltrimethylammonium-Montmorillonite) organoclay simulation, we find that the strong layering behaviour of interlayer ODTMA molecules is present with the same minimum distance between nitrogen atoms and MMT surface in different T/O (Tetrahedral vs. Octahedral) ratio cases. Nitrogen atoms sit right above the corresponding hexagonal cavities, which is in agreement with the previous research. The interaction energy between surfactants and MMT clay will reach the lowest point when substitution ratio of tetrahedral and octahedral (T/O) is equal to 1:1. Moreover, MSD (Mean Square Displacement) and diffusion coefficient of different models under same CEC (Charge Exchange Capacity) condition are inverse ratio to the T/O proportion.
In nylon6 polymer nanocomposites, sodium cations which exist originally in ensemble as charge balancer are absorbed much closer to MMT surface than the organic components in the nylon 6 ODTMA-MMT ensemble. Sodium atoms or nitrogen atoms in surfactants both have higher MSD and coefficients than those atoms V in the organic-modified clays. In the exfoliated nylon 6 ODTMA-MMT nanocomposites, pair correlation has been analysed instead of density profile. Layering packing structure is also shown through this analysis, which is also consistent with previous work. TABLE OF CONTENTS
Title page …….……………………………………………...... I Certificate of Originality …………………..……………...... II Acknowledgement …………….…………………………… III Abstract …………………………………………………….. IV Table of Contents ………………………………………….. VI List of Figures ……………………………………………… IX List of Tables …...………………………………………… XIV Chapter 1 Introduction …………………………….……… 1 Chapter 2 Literature Review ……………………………... 3 2.1 Clay minerals …………………...……………………. 3
2.1.1 Classification ……………...…………………………...…. 3
2.1.2 Organoclays ………………………………………………. 7
2.2 Polymer nanocomposites …………..……….……… 10
2.2.1 Structure ……………………………….…………….….. 10
2.2.2 Fabrication methods ………..………..………………….. 13
2.2.3 Commercial applications ……………..…..…………….. 16
Chapter 3 MD Simulation on Organoclays: Effect of Atom Substitution ………………………….……………………… 21 3.1 MD simulation theory …………………………….... 21 VII
3.1.1 Introduction …………………………………………….. 21
3.1.2 Algorithm ..…………………………………..………..…. 22
3.1.3 Software and forcefield ……………...………………..… 24
3.2 Experimental setup …………………………………. 28
3.2.1 Models with substitutions in octahedral ……....………... 28
3.2.2 Models with substitutions in both octahedral and tetrahedral
…………………………………………………………... 31
3.3 Energy setup, minimization and dynamic simulation ……………………………………………………….. 34 3.4 Results and discussion ..……………….…………… 35
3.4.1 Trajectory profiles …………………………………..…… 35
3.4.2 Density profiles ………………………………………….. 39
3.4.3 Interaction energy ………………..……………………… 44
3.4.4 MSD and diffusion coefficient ………………..………… 46
3.5 Summary ..…………………….……….…………… 49 Chapter 4 MD Simulation on Organoclay Nylon6 Nanocomposites …………………….…………………..….. 51 4.1 Introduction ………………………………………… 51 4.2 Model construction ………………..……………..…. 52
4.2.1 Intercalated ODTMA-MMT nylon6 nanocomposites …... 52
4.2.2 Exfoliated ODTMA-MMT nylon6 nanocomposites ……. 54
4.3 Results and Discussion ……………………………... 56 VIII
4.3.1 Intercalated ODTMA-MMT nylon6 nanocomposites …... 56
4.3.1.1 Trajectory profile ………………………………….. 56
4.3.1.2 Density profile …………………….………………. 58
4.3.1.3 MSD and diffusion coefficient ……………………. 59
4.3.2 Intercalated Na-MMT nylon6 nanocomposites ……….… 61
4.3.2.1 Trajectory profile ………………..………………… 61
4.3.2.2 Density profile …………………………………….. 64
4.3.2.3 MSD and diffusion coefficient …………….……… 65
4.3.3 Exfoliated ODTMA-MMT nylon6 nanocomposites ……. 67
4.3.3.1 Trajectory profile ………………………………….. 67
4.3.3.2 Pair correlation profile …………………………….. 67
4.3.3.3 MSD and diffusion coefficient ………………….… 70
4.4 Summary ……………….…………………………... 71 Chapter 5 Conclusions and Future Work ……………… 73 5.1 Conclusion …..………………………………………. 73 5.2 Future work …………………………………………. 76
Appendix References …………………………………….. 77 IX
List of Figures
Fig. 2.1 Kaolin clay structure with different OH inner surface group.
Fig. 2.2 Illite/Mica group general atoms structure.
Fig. 2.3 Formation of mesoporous synthetic clays.
Fig. 2.4 Comparison of thermal gravimetric analysis curves of (a) neat PP,
(b)PP/Na-MMT, (c) PP/ao-MMT and (d) PP/xo-MMT nanocomposites.
Fig. 2.5 Binding energy between nylon6,6 and clay platelet (left graph) and sum
binding energy between nylon6,6 and other two components respectively
(right graph).
Fig. 2.6 Formation of polymer nanocomposites.
Fig. 2.7 Exfoliated nanocomposite type.
Fig. 2.8 Storage modulus (left) and stress-at-break (right) under different
Organic-modified MMT wt %.
Fig. 2.9 Possible gas or water trajectory through the nano-platelet.
Fig. 2.10 Variation in the area of carbonyl band of different samples.
Fig. 3.1 Difference between two argon atoms with time steps 10 fs and 50 fs.
Fig. 3.2 Front view (left) and side view(right) of montmorillonite supercell lattice.
Fig. 3.3 Initial model of ODTMA-MMT with CEC of 85 meq/100g: blue sticks X
represent nitrogen atoms; grey sticks represent carbon atoms; white sticks
represent hydrogen atoms; red lines represent oxygen atoms; yellow
represents silicon atoms; pink represents aluminium atoms; green balls
represent magnesium substations.
Fig. 3.4 Initial model of ODTMA-MMT with CEC of 102 meq/100g.
Fig. 3.5 Front view and top view of modified case 1.
Fig. 3.6 Front view and top view of modified case 2.
Fig. 3.7 Front view and top view of modified case 3.
Fig. 3.8 Front view and top view of modified case 4.
Fig. 3.9 Snapshot of ODTMA-MMT model with CEC 85=meq/100g at 100k steps: In
top view (right) blue balls is nitrogen atoms in ODTMA. Red and yellow line
type represents oxygen and silicon atoms in tetrahedral layers while purple and
green polyhedron show aluminium and magnesium atoms in octahedral layer.
Fig. 3.10 Snapshot of ODTMA-MMT sub_1 model with CEC=85 meq/100g at 100k
steps: the red tetrahedral atoms represent the Al substitution for Si in
tetrahedral layers.
Fig. 3.11 Snapshot of ODTMA-MMT sub_2 model with CEC=85 meq/100g at 100k
steps.
Fig. 3.12 Snapshot of ODTMA-MMT sub_3 model with CEC=85 meq/100g at 100k
steps.
Fig. 3.13 Snapshot of ODTMA-MMT sub_4 model with CEC=85 meq/100g at 100k
steps. XI
Fig. 3.14 Snapshot of ODTMA-MMT model with CEC=102 meq/100g at 100k steps.
Fig. 3.15 Corresponding position of N atoms to the hexagonal cavities on the
tetrahedral layer, top view and side view.
Fig. 3.16 Density profile of Model CEC_85 with all substitutions in the octahedral
Fig. 3.17 Density profile of CEC_85 Sub_1 (T/O ratio 1:1.5).
Fig. 3.18 Density profile of CEC_85 Sub_2 (T/O ratio 1:1).
Fig. 3.19 Density profile of CEC_85 Sub_3 (T/O ratio 1:4).
Fig. 3.20 Density profile of CEC_85 Sub_4 (T/O ratio 4:1).
Fig. 3.21 Density profile of CEC_102 with all substitutions in octahedral.
Fig. 3.22 Snapshot of model CEC_102 with c =30 嘤
Fig. 3.23 The dependence of interaction energy on MMT substitution ratio.
Fig. 3.24 MSD of carbon atoms in the simulation cases with both tetrahedral and
octahedral substitutions.
Fig. 3.25 MSD of carbon atoms in CEC=85 meq/100g model which has none
substitution in the tetrahedral layer compared to those 4 cases with
tetrahedral substitution.
Fig. 3.26 MSD of carbon atoms in different CEC models with none substitution in the
tetrahedral layer.
Fig. 4.1 Molecular model of nylon 6 chain (red balls represent oxygen atoms, other
colors are same as those in ODTMA molecular model).
Fig. 4.2 Snapshot of front and side view of nylon 6 intercalated nanocomposites. XII
Fig. 4.3 Amorphous cell control panel.
Fig. 4.4 Initial configurations exfoliated model.
Fig. 4.5 Snapshot of 10k steps simulation of intercalated ODTMA-MMT nylon 6
model, molecules shown in Corey-Pauling-Koltun (CPK) are nylon 6
polymer atoms, thin sticks are ODTMA alkyl chains and stick network is
MMT layer.
Fig. 4.6 Snapshot of 10k simulation of intercalated ODTMA-MMT nylon 6 model,
showing isolated Nylon6 polymer chains.
Fig. 4.7 Snapshot of 10k simulation of intercalated ODTMA-MMT nylon 6
nanocomposite (top view): yellow balls are nitrogen atoms absorbed to the
bottom of surface of MMT, thus, higher space of ensemble. Blue balls are
left nitrogen atoms, locating in lower space of ensemble.
Fig. 4.8 Atoms density profile of intercalated ODTMA-MMT nylon 6 nanocomposite.
Fig. 4.9 Mean square displacement of intercalated ODTMA-MMT nylon 6 polymer
nanocomposites.
Fig. 4.10 Initial intercalated Nylon6-Na-MMT model (front view and side view).
Fig. 4.11 Snapshot after energy minimization.
Fig. 4.12 Snapshot of 20k (left) and 100k (right) steps simulation.
Fig. 4.13 Snapshot of top view of Na-nylon6-MMT model at 100k steps, atoms in
blue ellipse are sodium atoms which apart further to the MMT.
Fig. 4.14 Density profile of atoms in the Na-nylon6-MMT model.
Fig. 4.15 Mean square displacement of atoms in Na-nylon6-MMT model. XIII
Fig. 4.16 Snapshots in different period of dynamic simulation of exfoliated model
Fig. 4.17 Pair correlation judgement.
Fig. 4.18 Pair correlation analyse of Nylon 6 atoms in exfoliated model.
Fig. 4.19 Pair correlation analysis of surfactants atoms in exfoliated model.
Fig. 4.20 Pair correlation analysis of all atoms in exfoliated model.
Fig. 4.21 Mean square displacement of surfactants’ atoms in exfoliated model. XIV
List of Tables
Table 2.1 General type of clays.
Table 2.2 Selected clay-polymer nanocomposites and their fabrication methods.
Table 3.1 Partial charges used for clays.
Table 3.2 Interaction energy between ODTMA and MMT in the different cases.
Table 3.3 The diffusion coefficient of different simulation cases.
Table 4.1 Diffusion coefficient of different atoms in the intercalated ODTMA-MMT
nylon 6 nanocomposite model.
Table 4.2 Diffusion coefficient of atoms in the Na-nylon6-MMT Model. Chapter 1 — Introduction
Chapter 1
Introduction
Nanocomposites, as one of the most promising materials, have been applying to the most aspects of the industrial and domestic usage. By adding inorganic materials into polymer materials, some desired properties such as high stiffness, strength, gas barrier properties and fire retardancy can easily surpass the conventional materials. At the same time, lower weight could save the energy and protect the environment.[1]
The “Nanocomposites” concept comes from the definition as following: “they are nanomaterials that combine one or more separate components in order to obtain the best properties of each component. In nanocomposite, nanoparticles (e.g. clay, metal, carbon nanotubes) act as fillers in a matrix, usually polymer matrix.” Since 1990 when Toyota Company synthesized the clay/nylon6 nanocomposites and used as the timing belt-cover, more and more industries and customers realized the importance of developing this sort of material. So far, there are a few methods to produce such materials. However, the detailed information at the molecular level could hardly be achieved. Another point is that when we synthesize and characterize a new type of materials, sustainable improvement of its property should be taken into account. Most of the researches on nanocomposites are based on lab experimental process, while it can only attempt to combine different component materials or process, methods or related parameters, for example, time and temperature. Undoubtedly, experimental
1 Chapter 1 — Introduction method would be costly. By using the computer modelling (i.e., molecular dynamic simulation), the information at the detailed nano-level could be obtained, so as to predict proper characteristic of polymer nanocomposites. It could also offer the useful theoretical references to manufacturing other similar nanostructured materials. It is the fact that octahedral to tetrahedral substitutions ratio in MMT layer varies from different raw materials. At the same time, effects of origin of charge deficiency
(tetrahedral vs. octahedral sheet) have not been fully understood. Furthermore, little information at molecular level regard interaction and interfacial structure are available so far. Such information will also provide details for mechanical reinforcement of such nanocomposite. So this project is necessary and significant to carry out.
This thesis presents my research on molecular dynamic simulation of organoclays and clay-based polymer nanocomposites. Chapter 2 will mainly introduce some history of nanocomposites, and review the previous works and analysis as well as current industry applications, tendency and challenges. In Chapter 3, it will mention the relevant concepts of molecular simulation method. Then, model setup and research results of organically modified clays (i.e. MMT-ODTMA) are discussed. Detailed information about its nitrogen head group in ODTMA, density profile, interaction energy and mean square displacement will be described, as well as their dynamic simulation evolution. In Chapter 4 nylon6 polymer nanocomposites are built both in intercalated and exfoliated structures, the corresponding density profile and pair correlation profile are analysed as well as mean square displacement. Chapter 5 will conclude the total research and present possible future work.
2 Chapter 2 — Literature Review
Chapter 2
Literature Review
2.1 Clay minerals
2.1.1 Classification
Clay can be seen as a family of crystal minerals which usually contain silicon and metallic elements like Al, Fe and Mg. According to Utracki’s book in 2004, clays originated from hydrothermal alteration of alkaline volcanic ash and rocks of the
Cretaceous period. After thousands years modification and composition by the nature, clays are modified to be ultra fine crystals [2].
Clay has many groups of minerals like Kaolins, micas and phyllosilicate. They have similar layered structure yet distinguished characteristics. The Table 2.1 shows many groups of clays as well as their formula and structure type.
3 Chapter 2 — Literature Review
Table 2.1 General type of clays.
Type of clay Formula Type
Kaolins
kaolinite Al4Si4O10(OH)8 1:1
Endellite Al4Si4O10(OH)8·4H2O 1:1
Dickite Al2Si2O5(OH)4 1:1 1:1 Nacrite Al2Si2O5(OH)4 (different Axial Ratios)
Smectites or Phyllosilicates
Montmorillonite Mx(Al2-xMgx)Si4O10(OH)2·n(H2O) 2:1
Hectorite Mx(Mg3-xLix)Si4O10(OH)2·n(H2O) 2:1
Beidellite Mx(Si3.5-xAlx)O10(OH)2·n(H2O) 2:1
Saponite MxMg3(Si3-xAlx)O10(OH)2·n(H2O) 2:1
Micas
Phlogopite KMg3(AlSi3)O10(OH)2 2:1
Eastonite K(Mg2Al)(AlSi2)O10(OH)2 2:1
Muscovite KAl2(AlSi3)O10(OH)2 2:1
3 layer phyllosilicate Chlorites and separated by Mg(OH)2 Vermiculites interlayer
Sepiolite, Palygorskite None octahedral layer and Attapulgite sheet
4 Chapter 2 — Literature Review
Kaolinite, dickite, and nacrite are most common in kaolin group. Kaolin crystal lattice mainly consists of one octahedral layer and one tetrahedral layer so as to form a 1:1 type clay mineral. Each layer of kaolinite are translated horizontally by –a/3, however, there are normal single tetrahedral and octahedral layer in the structure of dickite and nacrite with a OH plane in between.[3]
Fig. 2.1 Kaolin clay structure with different OH inner surface group.
Micas group normally has flat six sided monoclinic crystals with a perfect basal cleavage which is a most prominent character of mica. The layer structure is quite similar as phyllosilicate group such as Montmorillonite (MMT), with two tetrahedral layer sandwich an octahedral layer. However, the maximum charge deficiency happens in the tetrahedral layer not the octahedral layer like MMT. The potassium ions in the crystal are held tightly, so that they are not easy to be exfoliated [2], which is a disadvantage using for synthesis of nanocomposites. This speciality also makes mica easy to block the water molecular to penetrate through. Moreover, mica could be used for manufacturing stove windows class because of its outstanding
5 Chapter 2 — Literature Review heat-resistibility, or capacitors because of its strong dielectric strength.
Fig. 2.2 Illite/Mica group general atoms structure.
The smectites group is one of the most used clay minerals for industry applications in polymer nanocomposites. They are abundant in many countries and relatively easy to be intercalated or even exfoliated. The charge imbalance are usually occur both in octahedral and tetrahedral layer. Some cations like Na+, K+ could be absorbed into the interlayer space and could be easily replaced by other organic segments or surfactants with positive charges. MMT has varies composition depending on the layer charges, which can be seen from Table 2.1. The ability to exchange of ion on the surface of layer silicate is a superior characteristic for developing polymer nanocomposite as well as the ability to disperse into nanosize platelets under specific condition. The surface area of MMT is normally between 750 - 800 m2/g, and aspect ratio of individual clay platelet ranges between 100- 1500. MMT need to be purified before being used to synthesise the polymer nanocomposites. Normally, it should not have more than 5% non-smectite component [2]. It can be found a modern method to
6 Chapter 2 — Literature Review purify not only MMT but other common clays from the patent of Clarey et al. in 2000
[4]. There are many other reviews of synthesis methods from previews literatures
[5-8]. And also researches on related MMT nanocomposite morphology and some specific characteristic[9-15].
After purification, clays need to be intercalated to produce polymer nanocomposite. In this circumstance, because kaolin group or mica group clay cannot provide a sufficient cationic exchangeable capacity (CEC) to complete the intercalation process, the MMT or other smectite group clays become the first choice in the industry applications to produce polymer nanocomposite. During this process, the exchange reaction happens in the gallery of interface of layers. Finally, other cations in the platelet will be replaced by organic chains or groups to make the modified clay more hydrophobic and organophilic.
2.1.2 Organoclays
Natural clays are not easily to interact with polymer. The specifically designed features of final production can not be easily controlled if none catalyst or other modification is applied. The clay organic modified process is to improve the organophilic property of clays so that polymers are easily intercalated into the layer spacing in the later nanocomposites fabrication. In 1997, Carrado synthesized the organo-hectorite with natural Li-hectorite clay and tetraethyl ammonium (TEA) [16].
It distinctively changed the microstructure of natural clay. Later in 2004, more surface
7 Chapter 2 — Literature Review function and organo-tailoring of this clay are discovered[17]. High protein loading leads to a high concentration of enzyme which is a tremendous improvement for this commercial hectorite material.
Also, according to the Carrado’s review[6], the organoclays have at least two applications. On the one hand, it can be commonly used as the component of nanocomposites fabrication. On the other hand, when organic chains are removed, the modified clay with larger spacing can be used as porous material for potential catalysts (Fig. 2.3).
Fig. 2.3 Formation of mesoporous synthetic clays.
More different cases have been done to show the importance of the organic-modification of clay. In 2006 Ding[18] introduces the 1-methyl-
+ - 3-tetradecylimidazolium chloride ([C14mim] Cl ) as the surfactants into the Na-MMT
8 Chapter 2 — Literature Review so as to produce the polyolefin/clay nanocomposites. As the Fig 2.4 shown, the organic-modified nanocomposites have much better thermal stability than those unmodified onesDŽ
Fig. 2.4 Comparison of thermal gravimetric analysis curves of (a) neat
PP, (b)PP/Na-MMT, (c) PP/ao-MMT and (d) PP/xo-MMT
nanocomposites.
Another case by Vansant and Uytterhoeven[19] shows the change from hydrophilic to organophilic produced by entropic effect. It also suggests that the length of alky chain would affect the Van de Waals’ forces between molecules. However, Van de Waals’ forces are not so comparable to the hydration properties and the electrostatic interaction. Simulation also has been done to test the binding energy of PA-66 to quaternary ammonium modified MMT [20]. The binding energy of ensemble with
C18 alkyl chains are less than 30 kcal/mol. Binding energy between nylon6,6 and
MMT platelet decreased linearly with increasing of absorbed quaternary ammonium
9 Chapter 2 — Literature Review salt. At the same time, the sum binding energy between nylon6,6 and clay platelet and between nylon6,6 and alkyl chains are also dropped with no obvious characteristic
(Fig. 2.5).
Fig. 2.5 Binding energy between nylon6,6 and clay platelet (left graph) and sum binding energy between nylon6,6 and other two components respectively (right graph).
2.2 Polymer nanocomposites
2.2.1 Structure
Since early 1990’s when Toyota Company developed a layer silicate polyamide composites[21], more and more commercial applications have been turning on exploitation on this kind of new materials because of its many unique and outstanding reinforced properties. For example, in this patent, the tensile strength increases from
8.02 or 7.75 kg/mm2 to 13 kg/mm2 which are 60% more than that of conventional composites. The heat distortion temperatures (HDT) increase from 65 or 90ć to
130ć.
10 Chapter 2 — Literature Review
Fig. 2.6 Formation of polymer nanocomposites.
After the clay has been organically modified, the original hydrophilic one becomes more organophilic, so that polymer matrix could be easier intercalated into the interlayer space. From Fig. 2.6 [22], the polymer composites could have 3 categories.
The first ‘phase separated’ one in microcomposite scale can only insert the whole silicate lattice into the polymer matrix. Intercalated nanocomposite, the second kind of material, generally opens the gallery of silicate layer, and polymer chains are gradually going through. The exfoliated nanocomposite which is the most desired model, fully open the layers and they are dispersed into the polymer matrix uniformly.
Actually, the exfoliated model can still be divided into order and disorder structure
(Fig. 2.7).
11 Chapter 2 — Literature Review
Fig. 2.7 Exfoliated nanocomposite type.
Although the disordered exfoliated structure is most expected type, it is very difficulty to fully disperse the clay particle into layer platelets. The separation of tactoid crystal in smectite clay could be the most critical issue in the current application. For example, in Yasmin’s paper in 2006 [23], the graphite nanosheets cannot totally separated but still keep the multilayer structure. If a longer sonication applied to silicate layers to boost the dispersions, the mechanical property of nanocomposite will be degraded. From another example, in Kornmann’s work in 2001 [24], by SEM, there are still some aggregates and non-exfoliated layers in the interlayer spacing after synthesis the epoxy-clay nanocomposite, thought it has a finer improvement compared to conventional polymer materials. However, there are still some successful cases showing in the following. The latest one which is done by Yang [25] synthesises the PS/VC18-MMT nanocomposites by in situ emulsion polymerization method.
MMT was modified by cation exchanging process with organic surfactants vinylbenzyldimethyloctadecylammionun chloride firstly. The structure of final results which is analysed by XRD and TEM shows the fully exfoliated of montmorillonite.
12 Chapter 2 — Literature Review
The storage modulus and glass transition temperature of nanocomposite is increased compared to the original polystyrene. Also the density of copolymer is decreased due to the expansion of MMT gallery and increasing of surface areas. Moreover, the exfoliated structures could be achieved via different ways such as polymer exfoliated-absorption[26], latex blending[27], melt compounding[28] and so on[29-31]. Many mechanical and structure properties of composites can be improved significantly.
2.2.2 Fabrication methods
As mentioned before, the fabrication methods of intercalated and exfoliated nanocomposites are various. So only a few popular means are introduced here with the cases attached.
First method is “solution induced intercalation (or exfoliation) method”. Initially, the soluble polymer must be prepared and consist in the corresponding organic solvent.
Then the clay mineral can be dispersed into the solvent. After the evaporation of solvent or the precipitation of the polymer, the natural mixture of polymer nanocomposites is formed. However, this method has a disadvantage that it is hardly to control the state of mixture during the process, and ideal intercalation can not be achieved perfectly. Another drawback is that related solvents perhaps cost much.
According to the research of Zhang in 2006, the soluble solution which is consist of inorganic metal salt, surfactant, cross-linkers, organic monomers, and initiators is
13 Chapter 2 — Literature Review
evaporated under 300ć. Then it is treated by spraying compressed air N2 gas to eliminate dust and then some other process. In the results, the XRD and TEM image show clearly a nacre-like laminated final structure with average channel spacing of around 3 nm[32].
The second method is in situ polymerisation. In this process, the layer silicate is mixed with monomer but not polymer. Then, with the addition of polymerization initiator, the catalyst, or the radiation, the polymerisation will occur in the spacing gallery so as to form the intercalation of exfoliation nanostructure. For example, the ammonium persulfate (APS) and dodecylbenzene sulfonic acid are used as initiators in the Chang’s research in 2006 [33]. Another example was done in 2005 [34], the basal spacing of organic-modified clay (OZnAl-LDH) is increased from 2.63 nm to
2.85 nm after in situ polymerisations. Most of the clay platelets present as intercalated state but still some of them are exfoliated into poly methyl acrylate matrix. The tensile strength increases dramatically from 0.46 Mpa of pure PMA polymer to 3.81 Mpa of final nanocomposite. At 400 ć the clay platelets could retain 39 wt% of nanocomposite which is 26 wt% higher than the original polymer.
The last common mean of fabrication of polymer nanocomposite is melting process.
This technique is quite commonly employed in the industrial manufacturing and applications. Firstly the clay minerals have to be organic modified to make it easier to mix with polymer. Then, the compounding procedure will happened by the physical
14 Chapter 2 — Literature Review force from extruder, twin-screw or mixer. Probably this method would be most preferred for the fabrication of nanocomposite with thermoplastic [35]. There is a simple investigation [36] in which the octadecylammonium modified MMT with CEC
=119 meq/100g is mixed with polystyrene by melting process. The melting compounding process is using an extruder machine with a screw speed of 50 rpm under temperature 140 ć They find out when the wt% equals to 5 wt% the greatest thermal stability is obtained. Both storage modulus and stress-at-break have been improved as the Fig. 2.8 showing below:
Fig. 2.8 Storage modulus (left) and stress-at-break (right) under different
Organic-modified MMT wt %.
In sum, only three methods have been listed above, while in following table(Table 2.2) from Zeng’s thesis are generally showing the common fabrication methods for different polymer nanocomposites.[37]
15 Chapter 2 — Literature Review
Table 2.2 Selected clay-polymer nanocomposites and their fabrication methods.
2.2.3 Commercial applications
For Automotive industry application, which is one of the most promising fields of commercial nanocomposites, the clay-polymer nanocomposites can be utilized for barrier films, car bodies, and components of power train and energy conversion.
As it is known, the first commercial nanocomposite was invented in 1991, when the
Toyota Motor company used the clay-nylon-6 as their timing belt cover. Then, the
16 Chapter 2 — Literature Review similar applications have been reported in many aspects of automotive industry. One example is the commercialization of polypropylene nanocomposite in the 2001 when
General Motors and polyolefin producer Basell developed the step-assist successfully
[38]. Another case is that the Chevrolet Impala model in 2004 from GM Company was reinforced by nanoclay thermoplastic olefin for its trim, center bridge and etc[39].
Besides the cover or body part, the nanotechnology could also contribute to other component like fuel cell. The porous nanocompound could improve ability of dispersion layer in the fuel cell because of large surface character of this compound.
Even more, similar porous nanocomposites can be utilized to produce emission filter so as to reduce the poisoned emission by catalytic reaction [40].
Nanocomposites also have many applications in electrolyte field. The composite polymer electrolyte nanofiller could be used to replace the micro sized fillers so as to enhance the ionic conductivity and compatibility. LiN(C2F5SO2)2, polyvinylidene fluoride–hexafluoropropylene (PVdF-HFP) were employed with 2 different size aluminium oxyhydroxide (in both micro and nano scale) as lithium salt to compare the ionic conductivity, compatibility, transference number and charge-discharge character in Stephan’s work in 2006[41]. The similar related research[42, 43] could have potential application in the hybrid electric vehicle in the future.
Another area is packaging especially in food packaging application. Since the dispersion of MMT or clay platelet into the polymer, the strength or tensile modulus
17 Chapter 2 — Literature Review will increase significantly. Traditionally, the petroleum-based polymer is commonly used in the market because its low cost compared to the biodegradable plastics. While for the environment or public healthy issue, the biodegradable plastics might be the desired materials. Recently, Avella has synthesized the starch/clay sample[44]. While not only biodegradable, this material improves the mechanical proper as well as qualified European directives for food packaging sector. Another commendable character of nanocomposites for packaging is its gas barrier property (see Fig. 2.9)
Fig. 2.9 Possible gas or water trajectory through the nano-platelet.
Russo has compared the different O2 diffusion coefficients with the different silicate loading into the polymer[45]. Generally, the permeability of O2 will decrease with the tensile modulus increasing and the silicate loading enhancement.
In the aerospace area, polymer nanocomposites could also fill some shortage in related issues. The enhanced thermo-mechanical property of MMT nanocomposites with small silicate loading could stimulate and broad the selection of polymeric materials in aerospace application. Old or new fabrication methods of polymer have to be combined effectively to maximise the interfacial bonding of materials[46].
Another very significant issue in the aerospace field is the coating for materials. As
18 Chapter 2 — Literature Review it’s known, the condition of aircraft or satellites like temperature and humidity could vary during the different environment. So the life of materials will be largely reduced under counterchanged exposition. The multiphase material which combines both hard and solid lubricant carbon into the nanocomposite coating can tremendously improve the performance of hardness, good wear resistance and low friction in different condition[47].
Environment is also a key issue while materials are utilized in both industry and civil applications. The MMT clay polymer nanocomposites show the better photo-oxidative degradation quality than the pure polymer. Thus, by exposing under the UV lights, the measure of area of carbonyl band in the samples is the critical parameter regarding the degradation ability. From Qin’s case in 2005 [48], this area keep almost constant, while the area of nanocomposite samples increase significantly especially after 200 hours (see Fig.2.10). The result also shows the important roles played by compatibilizer (maleic anhydride-grafted-polypropylene) and MMT because both of them can introduce photoresponsive groups into PP matrix.
Fig. 2.10 Variation in the area of carbonyl band of different samples.
19 Chapter 2 — Literature Review
Surely the nanocomposites applications are not limited only in the areas mentioned above. Medicine, textile, fire resistant materials (in civil engineering etc.[49]) and commodity products are all realistic or potential applications in present or future.
Many scientists or engineers are concluding the polymer nanocomposites will have a promise future, as well as many industry and business communities have realized or already have been involved in the area. So that understanding and developing its special property for potential utilization is quite necessary.
20 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution Chapter 3
MD Simulation on Organoclay: Effect of Atom Substitution
3.1 MD simulation theory
3.1.1 Introduction
Molecular dynamic (MD) simulation is generated basically from Newton’s second law of motion. The trajectory is produced by solving the differential equations of
“F=ma”:
2 d xi Fxi 2 (3.1) dt mi
In this equation, Fxi is the force along coordinate (xi), mi is mass of the entity.
Normally in the simulation of atoms or molecules, the forces in the equation are related to its position relative to other atoms (with a cut-off settlement), so the calculation could be quite costly depending on the scale of assemble and cut-off setup.
It might be the first MD simulation produced by Alder in 1957[50] with period boundary condition in a rectangular box. Because the particles are all hard sphere, the case is relatively simple, all the collision happen fully elastically and forces are only sparking when the separation of the surface of particles begin. In 1964, Rahman performed a dynamic simulation of the liquid argon[51]. The result of pair correlation function and constant of self-diffusion agreed with the physical experiment very well.
21 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution In this case, force, velocity and potential energy are not calculated like the earlier model, but successively change as their position’s variation. So that’s why the results are much more optimum and closer to the realistic results. Nowadays, the dynamic method is much more complicated in both precision and scales thanks to the rapid development of hardware. Therefore, more research on particles turn from physical experiment to the computer simulation.
3.1.2 Algorithm
There are many algorithm theories until now and they are suitable for different simulation situation. For the finite difference method, all the algorithms in this field are obeying the Taylor series expansions to determine the particles route, velocity, acceleration, etc. Formulae are as below: 1 1 1 r (t Gt ) r (t ) Gtv (t ) Gt 2 a (t ) Gt 3 b (t ) Gt 4 c (t ) (3.2) 2 6 24 1 1 v(t Gt) v(t) Gta(t) Gt 2b(t) Gt 3c(t) (3.3) 2 6 1 a(t Gt) a(t) Gtb(t) Gt 2c(t) (3.4) 2 b(t Gt) b(t) Gtc(t) (3.5) r ņņ position of particle v ņņ velocity of particle (the first derivative of the positions with respect to time G t ) a ņņ acceleration (the second derivative of positions with respect to time G t ) b and c ņņ similar as acceleration but the third and fourth derivative of positions,
respectively.
22 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution The verlet algorithm[52] would be the most widely used algorithm in MD simulation.
Basically, this algorithm calculates the variable by these two equations[53]: 1 r ( t G t ) r ( t ) G tv ( t ) G t 2 a ( t ) (3.6) 2 1 r(t Gt) r(t) Gtv(t) Gt 2 a(t) (3.7) 2
Adding two equations together, it gives: r (t G t ) 2 r (t ) r (t G t ) G t 2 a (t ) (3.8)
And: v (t ) [ r (t G t ) r (t G t )] / 2 G t (3.9)
Verlet algorithm has the modest hardware requirement, while one significant disadvantage is that the adding of Gt 2 a(t ) which is quite small in scale to the term
2r(t) r(t Gt) will lose some precision. The velocity at time t could not be given until the next step when r(t Gt) has been worked out.
After Verlet algorithm, many extension versions have been established. One of them is the Leap-frog[54] algorithm which is also the main algorithm used in this thesis. 1 r (t G t ) r (t ) G tv (t G t ) (3.10) 2 1 1 v (t Gt ) v (t Gt ) Gta (t ) (3.11) 2 2 1 1 v (t ) [ v (t G t ) G ta (t )] (3.12) 2 2 The most advantage of this algorithm compared to the standard Verlet algorithm is that it avoids adding the small number terms to the difference of large numbers to increase the precision. However, its can be found that the results of velocity and position of each step are not synchronised.
23 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
The Velocity Verlet method[55] describes the velocities and positions synchronously but the same drawback as the original Verlet algorithm: addition of large numbers and small numbers term make the results not very accurate. Equations are given below: 1 r (t G t ) r (t ) G tv (t ) G t 2 a (t ) (3.13) 2 1 v (t Gt ) v (t ) Gt[a (t ) a (t Gt )] (3.14) 2
One more method is Beeman’s algorithm[56]: 2 1 r (t Gt ) r (t ) Gtv (t ) Gt 2 a (t ) Gt 2 a (t Gt ) (3.15) 3 6 1 5 1 v (t Gt ) v (t ) Gta (t ) Gta (t ) Gta (t Gt ) (3.16) 3 6 6 As it is seen, the costly computation calculation exchanges the more precise results for both velocity and position.
So it is quite important to choose a proper algorithm to help our simulation. In my experiment, because the potential is one of the most examined issues, so obtaining of synchronal velocity is not so important than the precise of results and computation time saving. So the Leap-frog algorithm becomes our choice.
3.1.3 Software and forcefield
The commercial package used for this research is Material Studio [57]. The Discover module and Amorphous cell module have been used in the simulation process and later analysis.
24 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
Before running a simulation, time step choosing is also an important preparation. It is hard to assert which time step is most appropriated. The small time step could reduce the simulation speed or even waste computation resource. The large time step will create the large energy overlap between steps. At the beginning time of simulation large time step could make the relatively large errors or possibly fail the simulation running. See the figure below (Fig. 3.1), the difference time stepG t could have huge different results. According to the Leach’s book, the time step might be set as one tenth the time of the shortest period of motion in the molecules[53]. C-H bond vibrates with a repeat period around 10 femtoseconds, and while in my work, the models are consisted by rigid molecules, flexible atom chains and flexible bonds. So in most cases 1 femtosecond is chosen as the single time step.
Fig. 3.1 Difference between two argon atoms with time steps 10 fs and 50 fs.
Another important preparing job before running a simulation is to choose a proper
25 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution forcefield. Forcefield can be defined as a molecular mechanical method for chemical calculation. Normally, one forcefield includes these parts: the equations defining the potential energy of a molecular system as a function of atomic coordinates, atom types, and parameter sets that fit the equations to experimental data[58]. For the potential energy calculation, generally, the function can be represented as following equation:
k 2 k 2 V E(rN ) i (l l ) i ( ) n (1 cos(n )) ¦ i i,0 ¦ Ti Ti,0 ¦ Z J bond 2 angles 2 torsions 2 N N V V q q (3.17) {4 [( ij )12 ( ij )6] i j } ¦¦ Hij i 11j n rij rij 4SH0rij
The first term represents the bond stretch:
ki —— the potential coefficient of bond stretch
li , li,0 —— bond length, bond reference length
Ti , Ti,0 —— valence angle, reference valence angle
The second term represents the valence angle. The third term describes the torsion potential energy. The fourth term has two terms; first part is term which calculates the potential of Van der Waals’ force by Lennard-Jones equation. The second part calculates potential created by electrostatic interactions using a Coulomb potential equation.
There have been many forcefield theory developed. In Discover module, forcefield like COMPASS, CVFF, PCFF, etc. might be used under different simulation environment and scale. COMPASS forcefield was developed by Sun in 1998 [59]. It
26 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution was initially designed for simulation of organic molecules and small inorganic molecules. Generally, COMPASS is based on ab initio data and empirical optimization techniques. This forcefield can predict various solid-state properties like crystal unit cell structures, lattice energies, elastic constants and vibrational frequencies[60]. it has been also validated by using many calculation method [61] [62].
PCFF is an initial of Polymer Consistent Forcefield based on CFF91. So normally, it applies on the polymer and organic field. It has been validated including list of
CFF91 and other polymer compounds like polysilanes, polycarbonates etc.[63] and zeolites [64]. Compared to COMPASS forcefield which is quite general one, PCFF includes many Lennard-Jones parameters for metal atoms like Fe, Cu, Li, and K.
CVFF is an initial of consistent-valence forcefield [65]. It is a generalized valence forcefield which is fit for amino acids and some small organic structure molecules. It also includes some atoms type in silicates and phosphates. CVFF_aug is an augmented version of CVFF that includes non-bond parameters for additional forcefield types that are useful for simulations of silicates, aluminosilicates, clays and aluminophosphates[60]. In fact, most cases in this research are based on clays, so
CVFF_aug becomes the most preferable forcefield to run our simulation. However, the original CVFF_aug could not provide all the necessary parameters to fit this research. So some more parameters have been added. For example, Al, Mg, Si in both tetrahedral layer and octahedral layer are based on the Heinz’s work in 2004 [66], the
27 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution charges in the surfactants are based on Mrayed’s research[67]. The additional forcefield coefficients k from Teppen’s work[68] are utilized.
3.2 Experimental setup
3.2.1 Models with Substitution in octahedral
As the structure data of American Mineralogist Crystal structure database [69], the dimension of lattice with multicell (4x4x1) was set up as in Fig. 3.2 below:
Fig. 3.2 Front view (left) and side view (right) of montmorillonite
supercell lattice.
CEC= 85 meq/100g a =5.18×4=20.72 Å b =8.98×4=35.92 Å c =20.00 Å
¢ £ ¤ e
28 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution The MMT cell is treated as rigid crystal and period boundary condition is applied.
Parameter c was chosen close to the result from the Viani’s experiment [70] but enlarged in interlayer space to let proper numbers of surfactants insert in. In this case, the entire charge deficits in MMT are derivate from the substitution of Al by Mg in octahedral layer. The cell formula of MMT is MxSi8(Al4-xMgx)O20(OH)4. When M represent by element Na, the unit cell formula weight of clay
(Na0.625Si8(Al3.375Mg0.625)O20(OH)4) is 731.25 g. so that the CEC= 0.625/731.25h
1000= 0.85 meq/g= 85 meq/100g. Similarly, when, x = 0.75, the CEC= 102 meq/100g.
In this situation, because there are 4h4=16 cells, and CEC=85, so the atoms substitution number in MMT octahedral layer equals to 0.625*16=10. Undoubtedly, the integer substitution will be the easiest to calculate and modelling. So the CEC=85
(10 substitutions) and CEC =102 (12 substitutions) come to our modelling parameter choice. Fig. 3.3 below shows the model of CEC = 85 meq/100g with 10 alkylammoniums chains octadecyltrimethyl (ODTMA):
ODTMA: octadecyltrimethyl, 18-carbon alkyl chain.
29 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
Fig. 3.3 Initial model of ODTMA-MMT with CEC of 85 meq/100g: blue sticks represent nitrogen atoms; grey sticks represent carbon atoms; white sticks represent hydrogen atoms; red lines represent oxygen atoms; yellow represents silicon atoms; pink represents aluminium atoms; green balls represent magnesium substations.
Another model with CEC 102 is shown below (Fig. 3.4).
CEC= 102 meq/100g a =5.18×4=20.72 Å b =8.98×4=35.92 Å c =22.00 Å
30 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution ¢ £ ¤ e
Fig. 3.4 Initial model of ODTMA-MMT with CEC of 102 meq/100g.
In this model, 12 Mg atoms (green balls showed in the Fig. 3.4) replace the Al atoms in the lattice which forms charge deficits. 12 ODTMA alkyl organic chains are embedded to neutralize the charge balance. Lattice parameters are unmodified except height c.
3.2.2 Model with substitutions in both octahedral and tetrahedral
To compare the effect of different substitutions’ origin to surfactants, positions of charge deficiency has been modified.
31 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
Substitution modified case 1:
Fig. 3.5 Front view and top view of modified case 1.
4 Al atoms substituted Si atoms in tetrahedral layers, which still make the same deficit in the MMT lattice with CEC 85 meq/100g. The proportion of substitution in octahedral layer and tetrahedral layers is 60%: 40%
Substitution modified case 2
Fig. 3.6 Front view and top view of modified case 2.
In this setup, 5 Al atoms substituted Si atoms in tetrahedral layers randomly. Total
32 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution charge deficiencies are still 10 electric charges with CEC 85 meq/100g. The proportion of substitution in octahedral layer and tetrahedral layers is 50%: 50%.
Substitution modified case 3
Fig. 3.7 Front view and top view of modified case 3.
Case 3 has 2 Al atoms as substitutions in the tetrahedral layers. So the ratio is 80%:
20%.
Substitution modified case 4
Fig. 3.8 Front view and top view of modified case 4.
33 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution 80% of substitutions occur in the tetrahedral layer. In fact this situation would hardly happen in the nature clays. While here it was utilized for result analysis and comparison.
3.3 Energy setup, minimization and dynamic simulation
Before running dynamic simulation, the whole ensemble needs to be firstly assigned charges, forcefield type and related parameters. MMT charges are based on the
Heinz’s work in 2004 [66] (see Table. 3.1)
Table. 3.1 Partial charges used for clays.
The partial charges of atoms in ODTMA are from Mrayed’s work [67]. Because of shortage of some torsion parameters in the forcefield, as well as saving the simulation
34 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution time consuming, the potential energy of out of plane bending terms and cross terms of bond energy are neglected. Other bond energy and all non-bond energy which include clay - surfactants, clay - nylon 6, surfactants - surfactants, surfactants - nylon 6 and nylon 6 - nylon 6 have been included. Such assumption will not affect this study and conclusions on the interfacial structure and interaction have been applied before in other publications [71-73]
3.4 Results and discussion
3.4.1 Trajectory profiles
Snapshots of different cases are shown below; the alkyl chains of surfactants are omitted in all top view to obtain a better visualization:
Model CEC_85 with all substitutions in the octahedral:
Fig. 3.9 Snapshot of ODTMA-MMT model with CEC 85=meq/100g at 100k steps:
In top view (right) blue balls is nitrogen atoms in ODTMA. Red and yellow line type represents oxygen and silicon atoms in tetrahedral layers while purple and green polyhedron show aluminium and magnesium atoms in octahedral layer.
35 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution Model Sub_1, CEC =85 meq/100g, with tetrahedral and octahedral substitutions ratio 40%: 60%:
Fig. 3.10 Snapshot of ODTMA-MMT sub_1 model with CEC=85 meq/100g at
100k steps: the red tetrahedral atoms represent the Al substitution for Si in tetrahedral layers.
Model Sub_2, CEC =85 meq/100g, with tetrahedral and octahedral substitutions ratio 50%: 50%:
Fig. 3.11 Snapshot of ODTMA-MMT sub_2 model with CEC=85 meq/100g at
100k steps.
Model Sub_3, CEC =85 meq/100g, with tetrahedral and octahedral substitutions
36 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution ratio 20%: 80%:
Fig. 3.12 Snapshot of ODTMA-MMT sub_3 model with CEC=85 meq/100g at
100k steps.
Model Sub_4, CEC =85 meq/100g, with tetrahedral and octahedral substitutions ratio 80%: 20%:
Fig. 3.13 Snapshot of ODTMA-MMT sub_4 model with CEC=85 meq/100g at
100k steps.
Model CEC_102 with all substitution in octahedral:
37 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
Fig. 3.14 Snapshot of ODTMA-MMT model with CEC=102 meq/100g at 100k steps.
From the equilibrated structure above and simulation trajectory, some conclusion could be drawn. From the front views, firstly, the nitrogen atoms in the models in which CEC equals to 85 are rapidly absorbed closed to the MMT surface. Secondly, the hydrogen atoms attached to the alkyl groups beyond the nitrogen heads are tend to be perpendicular to the MMT surface. Thirdly, most alkyl chains are presenting the gauche and twist state while chains in the intermedia parts of d-spacing cross over from top to low region after simulation. However, alkyl chains in the CEC 102 models (Fig. 3.14) do not appear similarly. Carbon backbones present less gauche tendency and do not cross over from one side of MMT to another side of neighbouring MMT slide. Furthermore, two nitrogen atoms can not be absorbed to close to the surface of MMT. Height parameter c has been modified to see whether the increasing of gallery space could change this alkyl chain arrangement, however, it still can be found that nitrogen head groups keep forming three layers. The density profile will be described this issue in the next section. From the top view of different cases,
38 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution after a period of simulation when nitrogen atoms reach their balanced state, almost all the nitrogen atoms are sitting in the corresponding cavities above the nearest hexagon hollow on the MMT surface viewing from the XY plane (Fig.3.15).
Fig. 3.15 Corresponding position of N atoms to the hexagonal cavities on the tetrahedral layer, top view and side view.
This conclusion is also agreed with the recent result of Heinz’s paper [74]. Normally nitrogen atoms will walk close to the substitution atoms probably because of the electrostatic force, for example, the Mg atoms in the octahedral layer. However, if there are some substitutions (Al atoms which replace the original Si atoms) embedded in the tetrahedral layer, the atoms tend to be attracted more by the surface charge deficit atoms rather than charge deficit in the octahedral layer.
3.4.2 Density profile
The diagrams of different cases are shown below:
Model CEC=85 meq/100g with all substitutions in the octahedral:
39 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
Carbon atoms density Nitrogen atoms density All atoms density (Include H) 40 35 34.45 30 25 26.32 22.01 20 18.05 15 12.78 10 5.33 Atoms percentage Atoms 5 0 0.2 2.2 4.2 6.2 8.2 10.2 12.2 14.2 16.2 18.2 Z axis
Fig. 3.16 Density profile of Model CEC_85 with all substitutions in the octahedral.
Model Sub_1, CEC =85 meq/100g, with tetrahedral and octahedral substitutions ratio 40%:60%:
Carbon atoms density Nitrogen atoms density All atoms density (Include H) Atoms percentage Atoms Z axi
Fig. 3.17 Density profile of CEC_85 Sub_1 (T/O ratio 1:1.5).
Model Sub_2, CEC =85 meq/100g, with tetrahedral and octahedral substitutions ratio 50%: 50%:
40 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
&DUERQDWRPVGHQVLW\ 1LWURJHQDWRPVGHQVLW\ $OODWRPVGHQVLW\ ,QFOXGH+
$WRPVSHUFHQWDJH =D[LV
Fig. 3.18 Density profile of CEC_85 Sub_2 (T/O ratio 1: 1).
Model Sub_3, CEC =85 meq/100g, with tetrahedral and octahedral substitutions ratio 20%: 80%:
&DUERQDWRPVGHQVLW\ 1LWURJHQDWRPVGHQVLW\ $OODWRPVGHQVLW\ ,QFOXGH+
$WRPVSHUFHQWDJH =D[LV
Fig. 3.19 Density profile of CEC_85 Sub_3 (T/O ratio 1: 4).
Model Sub_4, CEC =85 meq/100g, with tetrahedral and octahedral substitutions ratio 80%: 20%:
41 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
&DUERQDWRPVGHQVLW\ 1LWURJHQDWRPVGHQVLW\ $OODWRPVGHQVLW\ ,QFOXGH+
$WRPVSHUFHQWDJH =D[LV
Fig. 3.20 Density profile of CEC_85 Sub_4 (T/O ratio 4: 1).
Model CEC=102 meq/100g with all substitution in octahedral:
&DUERQDWRPVGHQVLW\ 1LWURJHQDWRPVGHQVLW\ $OODWRPVGHQVLW\ ,QFOXGH+
$WRPVSHUFHQWDJH =D[LV
Fig. 3.21 Density profile of CEC_102 with all substitutions in octahedral.
From the diagram above, it can be seen clearly that in all the cases both nitrogen and carbon atoms in surfactants are strongly represented in layering behaviour. Nitrogen atoms form into 2 layers and carbon atoms form into 3 layers which have much less
42 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution polar aggregated density curves. For the nitrogen atoms in different cases, it can be seen the case sub_1 and sub_3 which have less tetrahedral to octahedral substitution ratio (T/O ratio) that are 1:4 and 2:3 appear sharper and more average than sub_2 and sub_4 (ratio 1:1, 4:1) for the density profile of nitrogen atoms. The peak of density profile close to the up surface of MMT seems to be direct proportion to the T/O ratio, while the peak close to the bottom surface inverse proportion to the T/O ratio. For the carbon atoms, it is hardly to see the evident tendency by the effect of T/O ratio. For the model CEC=102 meq/100g, we can see two nitrogen atoms do not move close to the surface but keep dynamic in the intermediate area. The carbon atoms appear less gauche and twist state than those in the cases of CEC 85 meq/100g. We suspect that it is possible that the space for surfactants may not large enough for inserting in two more nitrogen head groups. Because the CEC has to be kept invariable on 102 meq/100g, so a, b parameter in XY plane can not be changed under the condition that no more surfactants are added. So the parameter c in Z direction is increased to 30 嘤
(the value chosen can not be contrast too much to the experiment result [75]) to test whether that issue is related to the space. As the Fig. 3.22 shown, nitrogen atom (blue ball) still could not be absorbed to the surface of MMT. They are forming a “trilayer” structure gradually. Thus, with the increase of CEC, the structure of surfactants in the d-spacing would change from “bilayer” to “trilayer” which also quite agrees with the
Hackett’s experiment results in 1998 which concludes the D-spacing and layers are increased with the increase of CEC[76]. This agreement also confirms the simulation system has reliable outcome to a certain extent.
43 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
Fig. 3.22 Snapshot of model CEC_102 with c =30 嘤
3.4.3 Interaction energy
Interaction energy is also a useful parameter for researching the composite ensemble system. Interaction potential energy of all cases are calculated and compared. Because in our ensemble, the main interaction occurs between the layered silicate and surfactants ODTMA, interaction energy is derived by following equation:
Eint eraction Etotal (E surface E polymer ) (3.18)
After calculation, the results are showing below:
44 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution Table 3.2 Interaction energy between ODTMA and MMT in the different cases
Simulation system CEC_85 Sub_1 Sub_2 Sub_3 Sub_4 (T/O ratio) (0/10) (2/3) (1/1) (1/4) (4/1)
Surface Energy -19676.3 -19737.4 -19664.0 -19692.5 -19823.5 (kj/mol) Polymer energy 1017.5 1017.5 1017.5 1017.5 1017.5 (kj/mol) Total Energy -19713.5 -19762.6 -19846.1 -19735.6 -19850.0 (kj/mol) Interaction Energy -1054.7 -1042.7 -1199.6 -1060.6 -1044.0 (kj/mol)
From the Table 3.2 we can draw the interaction energy curve:
CEC 85 7HWUDKHGUDO2FWDKHGUD/D\HU5DWLR
0.0% 50.0% 100.0% 150.0% 200.0% 250.0% 300.0% 350.0% 400.0% 450.0% -800
-900
-1000 0.0% 66.7% 400.0% 25.0% -1100
(QHUJ\ .MPR/ -1200 100.0%
-1300
Fig. 3.23 The dependence of interaction energy on MMT substitution ratio.
For polymer potential energy, they are all the same because there are same 10
ODTMA chains in any ensemble. The surface energies are inverse proportion to the
45 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution T/O ratio except model sub_2. Total energy is inverse proportion to the T/O ratio too with no exception. Then, it can be seen from Fig. 3.23 that when T/O Ratio equals to
1:1, the ensemble reach its lowest interaction energy. When the T/O ratios are at other
4 cases, the interaction energies do not variate much but around 1050 kj/mol.
3.4.4 Mean square displacement and diffusion coefficient
Mean square displacement (MSD) and diffusion coefficient are also important characteristics while we study the diffusion and distribution profiles of surfactants.
Because from the trajectory file the single nitrogen atom position can be specified approximately whereas carbon atoms are not in such a detailed position requirement, hereby, carbon atoms in the backbone are examined to see how the substitutions in different layers affect its MSD.
Mean square displacement is calculated by following equation:
>@r(t) r(0) 2 a (3.19) N D
ND : Number of diffusive atoms in the system. r(t) : Specific atom position function.
The diffusion coefficient of atoms is simply to calculate the slope by MSD vs. time and divided by 6 in the 3D ensemble.
46 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
ND a 1 d 2 D Lim >@r(t) r(0) (3.20) tof ¦ 6't 6ND dt iof
Considering the time when the whole ensemble reaches its steady state, the time period used for calculation of MSD is from step 60k to 80k. After collecting the data the following diagrams are obtained:
Mean square displacement Sub_3 T/O=1/4 Sub_1 T/O=2/3 Sub_2 T/O=1/1 Sub_4 T/O=4/1
1.5
1.25 ) 2 1
0.75
0.5 Mean Square Displacement(Å 0.25
0 60.5 63 65.5 68 70.5 73 75.5 78 Time steps (ps)
Fig. 3.24 MSD of carbon atoms in the simulation cases with both tetrahedral and octahedral substitutions.
47 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution
Sub_3 T/O=1/4 Sub_1 T/O=2/3 Mean square displacement Sub_2 T/O=1/1 Sub_4 T/O=4/1 CEC 85 Model 18 ) 2 CEC 85 model with all 15 octahedral substitutions 12
9 Both Tetra. & Octa. 6 Substitution series
3
0 Mean Square Displacement(Å 60.5 63 65.5 68 70.5 73 75.5 78 Time steps (ps)
Fig. 3.25 MSD of carbon atoms in CEC=85 meq/100g model which has none substitution in the tetrahedral layer compared to those 4 cases with tetrahedral substitution.
Mean Square Displacement CEC 85 Model CEC 102 Model
18
15 CEC 85 Model ) 2 12
9
6 Mean Square Mean CEC 102 Model Displacement(Å 3
0 60.5 63 65.5 68 70.5 73 75.5 78 Time steps (ps)
Fig. 3.26 MSD of carbon atoms in different CEC models with none substitution in the tetrahedral layer.
48 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution From the diagrams above, it can be concluded that in all the cases, MSD represents the linear function, and different substitution series are arranged inverse ratio to the
T/O proportion. Moreover, if with none charge deficit in the tetrahedral layer, which can be treated as the T/O ratio equals to 0, the MSD increases dramatically. By comparing the different CEC model, the higher CEC will reach lower MSD at the same step. Concerning the diffusion coefficient of different cases, they are shown in the table below:
Table 3.3 The diffusion coefficient of different simulation cases.
Model CEC 85 Sub_3 Sub_1 Sub_2 Sub_4 CEC 102
(T/O ratio) (0/10) (1/4) (2/3) (1/1) (4/1) (0/12)
Coefficient 11.298 0.808 0.575 0.426 0.358 5.608 (x10-5 mm2/s)
It also can be found that the coefficients are arranged by the inverse ratio to the substitution T/O ratio. And from the preliminary results, the CEC increase leads to diffusion coefficient drops.
3.5 Summary
In briefly conclusion of this chapter, Nitrogen atoms in the head group of ODTMA are always sitting in the corresponding cavities above the nearest hexagon hollow on the
MMT surface. Most of the times they are attracted to move to the charge deficit atoms, the substitution atoms in the tetrahedral layer have stronger attraction to the N atoms
49 Chapter 3 — MD Simulation on Organoclays: Effect of Atom Substitution than in the octahedral layer due to their distances which judge the interface electrostatic force.
Both nitrogen and carbon atoms represent quite strong layering behaviour from density profiles analysis. For CEC=102 meq/100g, 2 nitrogen atoms could not move close to the MMT surface but form a third blurry layer, this analysis is also agreed with the previous results[76]. According to the visualization of results, the concentration profiles of surfactants are generally consistent with numerical experimental result through different means such as XRD [77], NMR [78] and
FTIR[79].
The interaction energy will reach its lowest point when T/O ratio comes to 1:1. When the T/O ratios are at other 4 cases, the interaction energies do not variate much but around 1050 kj/mol. This outcome agrees well with the Tanaka’s results in 2002 [20] which reconfirm the system’s reliability. The high CEC may have higher interaction energy.
Both mean square displacement and diffusion coefficient of different models under same CEC condition are inverse ratio to the T/O proportion. If with none charge deficit in the tetrahedral layer, corresponding to the T/O ratio equals to 0, the MSD increases rapidly. Lower CEC model obtains higher MSD and diffusion coefficient which is also agreed with the theoretical facts.
50 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites Chapter 4
MD Simulation on Organoclay Nylon 6 Nanocomposites
4.1 Introduction of polymer nanocomposites
The polymer nanocomposites are fabricated by dispersing some organic or inorganic clay platelet or other phase into the polymer matrix to reinforce its mechanic property and other character, for example, doubling of tensile modulus with few sacrifice of impact resistance, dramatic increasing of the heat distortion and much lighter weight while keeping comparable stiffness and strength. In the past decade, the polymer nanocomposites have been utilized for many areas in the both industry and domestic usage. They include the layered clay nanocomposites, carbon nanotube composites, etc. the first commercial nanocomposite which is also mentioned above is polyamide
6 developed by Toyota company. Another example, GE dispersed the certain nanotube into the polymer so as to obtain the high conductivity in nanocomposites [80].
Many works have been accomplished in both experimental and simulation works to improve the properties and characteristic. For example, experimentally, tensile modulus[81], permeation resistance[82], and flame retardancy[83] of nylon6 polymer nanocomposites and related products are examined. In the simulation area, it is much limited compared to the experimental works because relative high computation cost
51 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites and undefinable calculation parameters. However, because it can provide the insight the atoms behaviours and other information at atomic level which could not achieved by experimental techniques, more and more effort is expended to overcome current situation. As reported in 2002 [20] and 2003 [84], binding energy between polymeric matrix and the montmorillonite platelet will decrease while the volume of surfactants of nylon-6 organoclay nanocomposites increases. Water penetration related issue is discussed by comparing the numerical simulation and experiment study and striking similarity is obtained [85]. Monte Carlo simulation also has been employed to examine the mechanical property around the glass transition temperature[86]. The purpose of this part of my research is to study the effects of surfactants of interfacial interaction and interactions of clay-based nylon nanocomposites. This work could provide a guideline for the choice of surfactants for better structure, morphology and better mechanical properties.
4.2 Model construction
4.2.1 Intercalated ODTMA-MMT nylon6 nanocomposites
The model (Fig.4.2) is prepared for the simulation of intercalated polymer nanocomposites. Based on organoclays model before, the gallery is expanded in both
Y and Z direction. Then, the nylon6 (C6H11NO) chains which contain 9 repeat units in isotactic structure are inserted into the organic modified clay.
52 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
Fig. 4.1 Molecular model of nylon 6 chain (red balls represent oxygen atoms, other colors are same as those in ODTMA molecular model).
Fig. 4.2 Snapshot of front and side view of nylon 6 intercalated nanocomposites.
All the nylon 6 molecules are embedded in well order, and surfactants are averagely separated. Other parameters are shown below: a = 20.72 嘤 b = 71.84 嘤 c = 45.00 嘤
53 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites D E J 90q
Same as last chapter, period boundary condition is applied and nylon6 molecules are intercalated with integrated charge equals to 0.
4.2.2 Exfoliated model of Nylon6-MMT nanocomposite
Basically, the model above is setup by inserting polymer or surfactants into the clay model which is built in period boundary condition so that intercalated models have been built. The following exfoliated model is created by another concept, which is, dispersing single clay platelet into the polymer matrix.
Amorphous cell (Fig. 4.3) is another module in MS studio. It is suitable for building platelets dispersing system. More than one sort of composites are allowed to orient in the initial configuration under period boundary condition. After construction the ensemble, the system still can perform the minimization and dynamic simulation from discover module.
Fig. 4.3 Amorphous cell control panel.
54 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
The initial configuration setup is showing below (Fig. 4.4):
MMT (CEC85) =1 unit
Nylon 6 8-units polymer =15 units
ODTMA surfactant = 5 units
Crystal lattice parameter: a = 32.397 嘤 b = 32.397 嘤 c = 32.397 嘤
D E J 90q
Fig. 4.4 Initial configurations exfoliated model.
55 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites MMT platelet is still fixed. It can be seen the system has a loose packing of polymer nylon6 and surfactants. The whole ensemble does not show an average distribution of atoms.
4.3 Results and Discussion
4.3.1 Intercalated ODTMA-MMT nylon 6 nanocomposites
4.3.1.1 Trajectory profile
After 100k steps of dynamic simulation:
Fig. 4.5 Snapshot of 10k steps simulation of intercalated ODTMA-MMT nylon 6 model, molecules shown in Corey-Pauling-Koltun (CPK) are nylon 6 polymer atoms, thin sticks are ODTMA alkyl chains and stick network is MMT layer.
56 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
Fig. 4.6 Snapshot of 10k simulation of intercalated ODTMA-MMT nylon 6 model, showing isolated Nylon6 polymer chains.
Fig. 4.7 Snapshot of 10k simulation of intercalated ODTMA-MMT nylon 6 nanocomposite (top view): yellow balls are nitrogen atoms absorbed to the bottom of surface of MMT, thus, higher space of ensemble. Blue balls are left nitrogen atoms, locating in lower space of ensemble.
57 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
All the nylon 6 polymer molecules are gathering parallel close to the surface of MMT.
They appear gauche twisted state. Twin layer of nylon 6 layer appears with loose packing density. Concerning about the ODTMA location after simulation, in Fig. 4.6 in which all the nylon 6 molecules are set to be invisible, it can be found the top and bottom ODTMA in the initial configuration do not change much, but keeping parallel to the MMT surface and moving closer. ODTMA molecules which were initially placed in the intermediate space rise or drop to either side of MMT surface with a similar tilted angle. At the same time, not all the nitrogen head groups are attracted near to the surface of MMT, thus, a pseudo-trilayer mixer of polymer and surfactants are formed. In Fig. 4.7 which is a top view of system, most of the nitrogen obey the rule the same as mentioned in the organic-modified MMT section that N atoms sit corresponding to the cavities on the MMT surface, while only 2 nitrogen atoms
(showing in the blue ellipse in Fig. 4.7) which apart from the nearest MMT surface at around 10.1 嘤 (to bottom MMT surface) and 11.1 嘤 (to top MMT surface) are not following it accurately. Sometimes they overcome the bonding between Si and O atoms. The reason is speculated that they are farther away from the MMT surface
(other N atoms are apart from the surface around 3.5 嘤) and so have been less affected by the electrostatic and other force from the MMT molecule.
4.3.1.2 Density profile
The diagram of density profile of nylon 6 MMT nanocomposite after simulation is
58 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites shown below:
C atoms in surfactants N atoms in surfactants C atoms in nylon6 N atoms in nylon6 All carbon atoms All Nitrogen atoms 40 All atoms 35 33.50 31.75 30 25 25.41 20.44 20 15 10
'HQVLW\3HUFHQWDJH 5 0 0.45 4.95 9.45 13.95 18.45 22.95 27.45 31.95 36.45 40.95 =D[LV
Fig. 4.8 Atoms density profiles of intercalated ODTMA-MMT nylon 6 nanocomposite model.
Still, after adding the polymer into the system, the ODTMA surfactants behave strong layering behaviour. Compared to the ODTMA-MMT with CEC=85 meq/100g model of which both have none substitution in the tetrahedral layer, this model even has more uniform peak of nitrogen and stronger carbon atoms. Curve of density profile of nylon 6 molecules and their atoms which have no integrated charges seems much flatter than the polar molecules ODTMA. Carbon and nitrogen atoms form 4 primary layers and more bumps toward the two sides of MMT.
4.3.1.3 Mean square displacement and diffusion coefficient analysis
The mean square displacement of different atoms in the MMT nylon 6 polymer nanocomposites are examined after simulation. As well as before, time step from 60
59 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites to 80 are chosen as the data source.
1DWRPVLQVXUIDFWDQWV &DWRPVLQVXUIDFWDQWV 1DWRPVLQQ\ORQ
&DWRPVLQQ\ORQ
110 2[\JHQDWRPVLQQ\ORQ
W 100
90
80
70
60
50
40 0HDQVTXDUHGLVSODFHPHQ 60.5 63 65.5 68 70.5 73 75.5 78 7LPHVWHS SV
Fig. 4.9 Mean square displacement of intercalated ODTMA-MMT nylon 6 polymer nanocomposites.
It can be found in the diagram that surfactants averagely have higher MSD than nylon
6 atoms. Carbon atoms in the surfactants present extremely similar linear data as the oxygen atoms in nylon 6 molecules. Other atoms in the nylon 6, which are nitrogen and carbon atoms, are lower and almost same data to each other as well.
The diffusion coefficient also can be calculated as mentioned before:
N a 1 d D D Lim >@r(t) r(0) 2 tof ¦ 6't 6ND dt iof
So, following diagram is concluded:
60 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites Table 4.1 Diffusion coefficient of different atoms in the intercalated
ODTMA-MMT Nylon 6 nanocomposite model.
Atoms Nitrogen Carbon Nitrogen Carbon Oxygen
(belonged molecule) (Surfactant) (Surfactant) (Nylon6) (Nylon6) (Nylon6)
Coefficient 378.4 330.4 327.7 322.5 326.2 (x10-5 mm2/s)
The atoms in the surfactants also have higher diffusion coefficient than the atoms in the nylon 6 polymer. The overall magnitude is much higher than the coefficient of carbon atoms in the organic-modified clay.
4.3.2 Intercalated Na-MMT nylon 6 nanocomposite model
4.3.2.1 Trajectory profile
Another model has been built to compare the nanocomposite with or without surfactants. In this Na-MMT Nylon 6 model, the sodium atoms each with 1+ cation charge are embedded into the system to replace the surfactants and neutralize the integrated charge. See the figure showing below:
61 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
Fig. 4.10 Initial intercalated Nylon6-Na-MMT model (front view and side view).
The sodium atoms locate at the places which were occupied by nitrogen atoms originally. Other lattice parameters are the same as configuration in the last model: a = 20.72 嘤 b = 71.84 嘤 c = 45.00 嘤
D E J 90q
After minimization process finished, polar cation sodium atoms which locate at the top and bottom space are absorbed rapidly to the both surface of MMT clay (Fig.
4.11).
62 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
Fig. 4.11 Snapshot after energy minimization.
From the figure, the sodium atoms in the top and bottom space are nearer to the MMT surface compared to the nitrogen head groups, and the approaching speed is much quicker. After 20k steps all sodium atoms are rest steady near to the MMT surface
(Fig. 4.12, left view), and right view shows the finial snapshot of simulation.
Fig. 4.12 Snapshot of 20k (left) and 100k (right) steps simulation.
63 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
Compared to the structure of ODTMA-MMT nylon 6 model, nylon 6 molecules in this model lay flat on the MMT surface than the previous one. So it can be seen that without the surfactants the polymer tend to be more aggregate state than exfoliated state which benefit enlarging gallery and improving the property of materials.
Moreover, the aggregate of polymer and sodium atoms makes the intermediate space of ensemble empty and detract the formation of multilayer so as to weaken the related characters improvement.
The top view of simulation after 100k steps is shown below, similarly as the previous model. The sodium atoms are much closed to the MMT surface following the cavity rule. Sodium atoms apart further and sometimes overlap exiguously to the hexagonal cavities. (Fig. 4.13)
Fig 4.13 Snapshot of top view of Na-Nylon6-MMT model at 100k steps, atoms in blue ellipse are sodium atoms which apart further to the MMT
4.3.2.2 Density profile
64 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites Density profile of different atoms has been explored (Fig. 4.14). From the diagram it can be seen that the sodium atoms form an asymmetry and disuniformed peak with more atoms at the top space of ensemble. Furthermore, the nearest sodium atom to the
MMT surface is 0.758 嘤 (to top of MMT) and 0.6 嘤 (to bottom of MMT surface), the high and concentrated charge of Na cation may make them absorbed closer to the
MMT surface than the nitrogen head groups of ODTMA (the distance between N and
MMT surface is around 3 嘤) which were replaced by sodium. The empty space in the ensemble along z axis is approximately from 19 to 34.5 Å. This value is enlarged compared to the nanocomposites with the surfactants model whose low density area is from 20 to 30 嘤. Thus, in the previous nylon6 model, surfactants benefit to enlarge the system gallery and reduce the aggregation of nylon6 polymer.
Sodium atoms C atoms in the Nylon6
Nitrogen atoms in Nylon6 All atoms 35 29.00 30
25 21.75 21.82 20 19.17 18.25 15
10
$WRPVSHUFHQWDJH 5
0 0.45 4.95 9.45 13.95 18.45 22.95 27.45 31.95 36.45 40.95
=D[LV
Fig. 4.14 Density profile of atoms in the Na-Nylon6-MMT model.
4.3.2.3 Mean square displacement and diffusion coefficient
The results of mean square displacement are as following figure:
65 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
Sodium atoms Nitrogen atoms Carbon atoms Oxygen atoms )
2 100 90 80 70
60 50 40 30 Mean SquareDisplacement (Å 60.5 63 65.5 68 70.5 73 75.5 78 Time steps (ps)
Fig 4.15 Mean square displacement of atoms in Na-Nylon6-MMT model.
Data are collected from time step 60k to 80k. The linear curves are ranged from sodium, oxygen, nitrogen and carbon atoms. They are also similar as the data in the last model. According to the Equation 3.20, diffusion coefficient can be calculated as table below:
Table 4.2 diffusion coefficient of atoms in the Na-Nylon6-MMT Model.
Atoms Na Carbon Nitrogen Oxygen
Coefficient 389.4 321.2 319.5 335.4 (x10-5 mm2/s)
The diffusion coefficient of sodium atom, as the nitrogen groups which were replaced, is still higher than those atoms in the nylon6. Atoms in the nylon6 are close to each other at average 325.4 mm2/s
66 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
4.3.3 Exfoliated ODTMA-MMT nylon6 nanocomposites
4.3.3.1 Trajectory profile
After minimization and dynamic simulation process which are shown below, except the very peripheral polymer molecules, most of organic molecules are attracted moving toward to the MMT surface. The motion keeps on moving until approximately 60k steps when the ensemble reaches the steady dynamic period. The packing of atoms is much denser around the MMT surface and the tails of organic components are tending to be tilted to the MMT platelet.
Fig. 4.16 Snapshots in different period of dynamic simulation of exfoliated model.
4.3.3.2 Pair correlation profile
Because in this system it is impossible to analyse the density profile as the previous
67 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites models before, pair correlation is consider as another function to examine the packing density distribution of organic atoms in the ensemble. Since the distance we would like to examine is between surface of MMT and organic atoms, the normal pair correlation function which tackle the distance between MMT central point to the atoms does not work. At the same time, the nearest distance to some surface does not mean that the specific surface is the nearest one (see Fig. 4.17). The nearest distance from point G to the box should be a rather than b, but the nearest surface is not X surface but Y.
Fig. 4.17 pair correlation judgement.
So the distances between every atom in the MMT platelet and certain atom in organic molecules are examined to obtain the nearest distance which is also the distance to the nearest surface. The results are shown below:
68 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
10 C atoms in nylon 6 8 N atoms in nylon 6 O atoms in nylon 6 6
4
2 Percentage of atoms of Percentage 0 0.25 5.25 10.25 15.25 20.25 25.25 30.25 35.25 40.25 45.25 Distance to MMT surface
Fig. 4.18 Pair correlation analyse of Nylon 6 atoms in exfoliated model.
30 C atoms in surfactants 25 N atoms in surfactants 20
15
10
5 Percentage of atoms of Percentage 0 0.25 5.25 10.25 15.25 20.25 25.25 30.25 35.25 40.25 45.25 Distance to MMT surface
Fig. 4.19 Pair correlation analysis of surfactants atoms in exfoliated model.
10 All C atoms All N atoms 8 All atoms 6
4
2
Percentage of atoms 0 0.25 5.25 10.25 15.25 20.25 25.25 30.25 35.25 40.25 45.25 Distance to MMT surface
Fig. 4.20 Pair correlation analysis of all atoms in exfoliated model.
69 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
The correlations are divided into three diagrams for better examination of atoms in the nylon 6 and surfactants ODTMA molecules. From Fig. 4.18, the atoms percentages are fluctuated and decrease dramatically before distance less than 5 Å. Then, it keeps generally decreasing with vibration until distance around 31 Å. Because compared to the ODTMA, the nitrogen and carbon atoms in nylon6 are much greater, so surfactants are presented in another figure (Fig. 4.19). It has only two discrepant lines.
Almost half nitrogen atoms are gathering not far away from the surface of MMT surface, two peaks are formed within 7 Å. The carbon atoms have almost no obvious peak and generally scatter to outside space; atoms become exiguous after 22 Å. These two curves can be concluded as following: ODTMA surfactants have their nitrogen atoms rest near the surface of MMT, and other backbone carbon atoms with hydrogen atoms scatter reverse from the nitrogen-MMT direction. Since the surfactants atoms are much less than the nylon 6 atoms, differences between carbon atoms in nylon6 and “all carbon atoms”, nitrogen in nylon6 and “all nitrogen atoms” are very limited.
In the third figure, the curves have no much change compared to second one. The “All atoms” curve in Fig. 4.20 also represents that in the exfoliated model, the outside organic atoms may also form a pseudo-trilayer structure which is not so distinct to be observed.
4.3.3.3 Mean square displacement and diffusion coefficient
MSD of surfactants in the ensemble is also examined here (see Fig. 4.21).
70 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites
C atoms in surfactants ) 50 N atoms in surfactants 40
30
20
10
0
Mean square displacement (Å displacement square Mean 60.5 63 65.5 68 70.5 73 75.5 78 Time (ps)
Fig. 4.21 Mean square displacement of surfactants’ atoms in exfoliated model.
In surfactants, the nitrogen atoms are supposed to be less movable because MMT has stronger electrostatic attraction to them than to carbon atoms. From the figure and calculated data in which carbon and nitrogen atoms’ diffusion coefficients are 154.9 mm-5/s and 146.6 mm-5/s respectively, it can be found results are agreed well with theoretical facts.
4.4 Summary
In briefly conclusion of this chapter, models with or without organic surfactants lead to different layering structures. The sodium atoms approach much nearer to MMT surface than ODTMA, and the sodium atoms and nylon6 molecules do not form a uniform and average peak which could pose more aggregated conformation compared to the nanocomposite with ODTMA surfactants. Most sodium atoms and nitrogen atoms in surfactants’ head groups are following the same rule as those in organoclay models, except those apart quite further to the MMT surface, which means they are in
71 Chapter 4 — MD Simulation on Organoclay Nylon 6 Nanocomposites another “layer”.
Compared to the organoclay models, the mean square displacement and diffusion coefficient of polymer nanocomposites are much higher. In polymer nanocomposites themselves, the sodium atoms or the nitrogen head groups which substitute sodium as the function of surfactants have stronger MSD and diffusion coefficient than atoms in nylon 6.
Exfoliated structure model has been attempted to build in which MMT platelet is still fixed. The original loose packing nylon6 polymer and ODTMA are moving toward
MMT with a regular and average packing order. Pair correlation has been analysed instead of density profile. MSD of surfactants shows that carbon atoms have higher diffusion ability than nitrogen atoms do. Layer packing structure could also be seen from the diagram and almost half nitrogen atoms in surfactants are absorbed close to
MMT surface with backbone tail pointing outward.
72 Chapter 5 — Conclusion and Future Work
Chapter 5
Conclusion and Future Work
Although nanocomposites technology has been developing for about two decades, it is still on an early stage of development especially in MD simulation field. Many complementary methods on fabrication and composition still can not explore the immanency of nanocomposites which is the most fundamental point to develop the further usage of nanocomposites in both industrial and domestic usage. Hence, the simulation method which could discover the detailed molecular behaviour is promising to be another way to explore the future of nanocomposites.
5.1 Conclusion
In this work, MD simulations of organic-modified clay and nanocomposites based on different models have been done. Related analysis and conclusion can be listed below:
1. The trajectory profile of ODTMA-MMT organic clay shows the surfactants will
move to both top and low space of cell lattice and be absorbed near the MMT
surface. Nitrogen atoms in the head group of ODTMA are always sitting in the
corresponding cavities above the nearest hexagon hollow on the MMT surface.
Most of the times they are attracted to move to the charge deficit atoms, the
substitution atoms in the tetrahedral layer have stronger attraction to the N atoms
73 Chapter 5 — Conclusion and Future Work
than in the octahedral layer due to their distances which judge the interface
electrostatic force.
2. Density profiles of organic-modified clay is also analysed, we find that, for
CEC=85 meq/100g, both nitrogen and carbon atoms represent quite strong
layering behaviour; the data of peak of density profile close to the upper surface of
MMT seems to be direct proportion to the T/O ratio, while the peak close to the
bottom surface to be inverse ratio to the T/O ratio. For CEC=102 meq/100g, 2
nitrogen atoms could not move close to the MMT surface but form a third blurry
layer, this analysis is also agreed with the previous results[76].
3. The interaction energy will reach its lowest point when T/O ratio come to 1:1 and
for different CEC, the higher CEC would have higher interaction energy. Both
mean square displacement and diffusion coefficient of different models under
same CEC condition are inverse ratio to the T/O proportion. If with none charge
deficit in the tetrahedral layer, corresponding to the T/O ratio 0, the MSD
increases rapidly. Lower CEC model obtains higher MSD and diffusion
coefficient.
4. In polymer nanocomposites, models with or without organic surfactants lead to
different layering structures. The sodium atoms approach much nearer to MMT
surface than ODTMA, and the sodium atoms and nylon6 molecules do not form a
74 Chapter 5 — Conclusion and Future Work
uniform and average peak which could pose more aggregated conformation
compared to the nanocomposite with ODTMA surfactants. Most sodium atoms
and nitrogen atoms in surfactants’ head groups are following the same rule as
those in organoclay models, except those apart quite further to the MMT surface,
which means they are in another “layer”.
5. Compared to the organoclay models, the mean square displacement and diffusion
coefficient of polymer nanocomposites are much higher. In polymer
nanocomposites themselves, the sodium atoms or the nitrogen head groups which
substitute sodium as the function of surfactants have stronger MSD and diffusion
coefficient than nylon 6 atoms consist of N, C and O atoms.
6. Exfoliated structure model has been attempted to build in which MMT platelet is
still fixed. The original loose packing nylon6 polymer and ODTMA are moving
toward MMT with a regular and average packing order. Pair correlation has been
analysed instead of density profile. MSD of surfactants shows that carbon atoms
have higher diffusion ability than nitrogen atoms do. Layer packing structure
could also be seen from the diagram and almost half nitrogen atoms in surfactants
are absorbed close to MMT surface with backbone tail pointing outward.
The work investigates in-depth the effect of atomic substitutions of tetrahedral and octahedral sheets of clay on the molecular structure and interaction within clay gallery.
The extended structure-property relationship is another important topic which needs a
75 Chapter 5 — Conclusion and Future Work continued study in the future.
5.2 Future work
Due to the forcefield and charges for the simulation here is preliminary and limited, some none-bond energy and related forces are omitted while execute the simulation and analysis. By the development of algorithms and forcefield theory, this situation could be improved.
Currently, the MD simulation is limited in the approximately 100 嘤 range, the costly computation does not allow too many atoms while keeping accurate. So if mesoscale or even larger ensemble needs to be simulated, another strategy has to be developed to overcome the computation limit. Further more, the relation between empirical particles and small nano-sized molecules, while at current stage there are no sufficient research on these area, could be found if using the same simulation principle. Another significant and feasible research topic is that in the cooling process, the flexible molecular chains will form an ordered structure during recrystallisation. It is of interest to investigate the effect of cooling process and temperature on the interaction between organoclay and nylon 6.
76 APPENDIX — References
APPENDIX
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