ĐSTANBUL TECHNICAL UNIVERSITY INSTITUTE OF SCIENCE AND TECHNOLOGY
M.Sc. Thesis by Duygu AKSOY
Department : Polymer Science and Technology Programme : Polymer Science and Technology
JUNE 2009
A THEORETICAL STUDY ON THE ELECTRONIC, OPTICAL AND MORPHOLOGICAL PROPERTIES OF THE POLYPYRROLE-BASED
ĐSTANBUL TECHNICAL UNIVERSITY INSTITUTE OF SCIENCE AND TECHNOLOGY
M.Sc. Thesis by Duygu AKSOY (515071007)
Date of submission : 04 May 2009 Date of defence examination: 02 June 2009
Supervisor (Chairman) : Prof. Dr. Mine YURTSEVER (ITU) Members of the Examining Committee : Prof. Dr. Yusuf YAĞCI (ITU)
Assoc. Prof. Dr. Nurcan TÜZÜN (ITU)
JUNE 2009
A THEORETICAL STUDY ON THE ELECTRONIC, OPTICAL AND MORPHOLOGICAL PROPERTIES OF POLYPYRROLE-BASED
HAZĐRAN 2009
ĐSTANBUL TEKNĐK ÜNĐVERSĐTESĐ FEN BĐLĐMLERĐ ENSTĐTÜSÜ
YÜKSEK LĐSANS TEZĐ Duygu AKSOY
(515071007)
Tezin Enstitüye Verildiği Tarih : 04 Mayıs 2009 Tezin Savunulduğu Tarih : 02 Haziran 2009
Tez Danışmanı : Prof. Dr. Mine YURTSEVER (ĐTÜ) Diğer Jüri Üyeleri : Prof. Dr. Yusuf YAĞCI (ĐTÜ)
Doç. Dr. Nurcan TÜZÜN (ĐTÜ)
POLĐPĐROL ESASLI NANO YAPILARIN ELEKTRONĐK, OPTĐK VE MORFOLOJĐK ÖZELLĐKLERĐNĐN TEORĐK OLARAK ĐNCELENMESĐ
FOREWORD
I would like to express my deep appreciation and thanks for my supervisor, Prof. Dr. Mine YURTSEVER who is tenderhearted as my mother beyond the excellent teacher. I know, I will be lucky for studied and getting acquainted with her.
I am deeply indebted to my mother, who give me her ever-present love and devotion, for all the guidance and support. I would like to express my grateful thanks to my father and my sister.
I would like to express my thanks to Nurcan TÜZÜN for nice supporting.
I would like to express my thanks to Erol YILDIRIM for his help, encouragement, understanding and emotional support.
Also I want to thank my friend Filiz KAÇMAZ at Đstanbul University. She always near me and motivated me to study harder on my thesis.
Finally, I want to thank the Tubitak for financial support.
May 2009 Duygu AKSOY
TABLE OF CONTENTS
Page
ABBREVIATIONS ...v
LIST OF TABLES ... vi
LIST OF FIGURES ... vii
SUMMARY ... viii ÖZET... xvii 1. INTRODUCTION ...1 1.1 Conjugated Polymers ... 1 1.2 Polypyrrole ... 5 1.2.1 Chain structure ...5
1.2.2 The charge transport ...6
1.2.3 Synthesis ...9
1.2.4 Morphology ... 10
1.2.3 Modifying ... 11
1.2.4 Block copolymers of polypyrrole ... 16
2. METHODOLOGY... 26
2.1 Quantum Mechanical Methods ...22
2.1.1 Semi Empirical Methods ... 23
2.1.2 Ab – Initio Methods ... 23
2.1.3 DFT (Density Functional Theory) ... 25
2.2 Statistical Mechanical Methods ...26
2.2.1 Molecular Dynamics Simulation ... 27
2.2.2 Dissipattive Particle Dynamics ... 27
3. COMPUTATIONAL DETAILS... 30
4. RESULTS AND DISCUSSION ... 32
4.1 Electronic Properties of Diblock Copolymers ...32
4.2 Molecular Dynamic Studies of Diblock Copolymers ...38
4.3 Morphological Studies ...46
3.2.1 Calculation DPD Inputs ... 46
3.2.2 Calculation Solubility Parameter and Interaction Parameters ... 46
3.2.3 DPD Simulation Resulsts... 50
5. CONCLUSION ... 57
REFERENCES ... 59
ABBREVIATIONS
PPy : Polypyrrole
PCL : Poly(ε-caprolactone) PMMA : Poly(methyl methacrylate)
PS : Polystyrene
PANI : Poly(aniline)
DFT : Density Functional Theory
MD : Molecular Dynamic
DPD : Dissipative Particle Dynamic
QSPR : Quantitative Structure Relationship Properties RIS-MC : Rotational Isomeric State Monte Carlo
B3LYP : Becke, three-parameter, Lee-Yang-Parr TDDFT : Time Dependent Density Functional Theory
LIST OF TABLES
Page
Table 1.1: Polypyrrole blends with different polymer ... 10
Table 1.2: Polypyrrole graft copolymers with different polymer ... 12
Table 4.1: Oligomers with quantum mechanically obtained atomic charges ... 30
Table 4.2: Monomers with quantum mechanically obtained atomic charges ... 31
Table 4.3: The changes of m- λ and m-band gap in (Py)m-(CL)5 copolymer. ... 35
Table 4.4: The snapshots of the equilibrium structures of two PPy-b-PCL diblock copolymers ……….. 36
Table 4.5: The snapshots of the equilibrium structures of two PPy-b-PSt diblock copolymers... 37
Table 4.6: The snapshot of the equilibrium structures of two PPy-b-PMMA diblock copolymers ………..… 39
Table 4.7: The snapshots of the equilibrium structures of two PPy-b-PANI diblock copolymers... 40
Table 4.8: Potential energies of diblock copolymer systems in configurations... 41
Table 4.9: End to end distance of the side chains in the studied systems after minimization and after 2 ns simulation ... 42
Table 4.10: Solubility parameter of PPy, PCL, PANI, PSt and PMMA ... 45
Table 4.11: The parameters calculated by QSPR method ... 45
LIST OF FIGURES
Page
Figure 1.1 : Linear polyacetylene. ... 1
Figure 1.2 : The phases of the π-orbitals in the HOMO and LUMO. ... 2
Figure 1.3 : Energy band in solid. ... 2
Figure 1.4 : Reaction mechanism for the synthesis of PANI, PPy and PTs ... 4
Figure 1.5 : A pyrrole ring with the ‘α’ and ‘β’ positions marked ... 4
Figure 1.6 : Chemical structures of polypyrrole in its aromatic, polaron and bipolaron configuration ... 5
Figure 1.7 : Polymerization mechanism of pyrrole through the coupling of two radical cations ... 6
Figure 1.8 : Chemical oxidative polymerization of pyrrole. ... 7
Figure 1.9 : Copolymerization of pyrrole and aniline. ... 8
Figure 1.10 : Copolymerization of pyrrole and ethylaniline. ... 13
Figure 1.11 : Block copolymers architecture. ...13
Figure 1.12 : SEM and TEM images of PACP hollow nanospheres. ...14
Figure 1.13 : TEM images of hollow spheres synthesized at different pyrrole] [aniline] molar ratios...15
Figure 1.14 : SEM and TEM images of PACP hollow nanospheres. ...15
Figure 1.15 : Block copolymers of polypyrrole and polytetrahydrofuran. ...16
Figure 1.16 : Block copolymers of polypyrrole and polytetrahydrofuran. ...16
Figure 1.17 : Copolymer of polypyrrole and polysiloxane. ...17
Figure 1.18 : Copolymer of polypyrrole and polystyrene. ...17
Figure 2.1 : Schematic illustration of the DPD system. ...25
Figure 3.1 : Flow chart of the molecular dynamic simulation studies. ...27
Figure 3.2 : Flow chart of the DPD simulations. ...28
Figure 4.1 : The changes in the band gap of the diblock copolymer with the conjugated chain ...32
Figure 4.2 : The change of UV absorbtion sprectrum with m of (Py)m-(CL)5. ...34
Figure 4.3 : Configuration of the studied diblock copolymer system. ...35
Figure 4.4 : The amorphous cell structures for PPy, PSt, PANI, PMM and PCL.. ...44
Figure 4.5 : The morphology of PPy-PMMA and PPy-PCL sytem projected ...47
Figure 4.6 : The morphology of PPy-PANI and PPy-PSt sytem projected. ...48
Figure 4.7 : The morphology of PPy-PMMA and PPy-PCL sytem projected ...51
THEORETICAL STUDY ON THE MORPHOLOGY, SOLUBILITY, CONDUCTIVITY AND OPTICAL PROPERTIES OF THE POLYPYRROLE DIBLOCK COPOLYMERS
SUMMARY
Polypyrroles (PPy) are important member of conducting polymers and they have been studied extensively both experimentally and theoretically. In spite of their high electrical conductivity upon doping and air stability, they are not processable due to the fact that they are not soluble in common solvents. The insolubility problem restricts their processabilities and industrial applications. Block copolymerization is one of the methods used to solve this problem and enhance the properties of PPys as desired. Their industrial usage mostly include thin film applications where the morphology and the surface behavior becomes a very important issue and should be very well known in order to have a control on these properties of resulting materials. In this study, the diblock copolymers of PPy with the polymers of methyl methacrylate (MMA), aniline (ANI), ε-caprolactone (CL) and styrene (S) were modelled and studied for their electronic, optical and morphological properties. The diblocking polymers were chosen to be the softer polymers (than PPy) with different degree of polarity and solubility behavior. Ground and excited state geometries of the short oligomers of these copolymers were optimized at B3LYP/6-31g* level by DFT and TDDFT methods, respectively. The changes in the band gap values and their UV absorption spectra as a function diblock composition were observed. The structural properties and the morphologies of the copolymers which were shown to depend strongly on the interactions of the polymer chains and the solubility parameters of them, were obtained by MD simulations at micro and meso scales.
POLĐPĐROL ESASLI NANO YAPILARIN ELEKTRONĐK, OPTĐK VE MORFOLOJĐK ÖZELLĐKLERĐNĐN TEORĐK OLARAK ĐNCELENMESĐ ÖZET
Polipiroller iletken polimerlerin önemli bir üyesidir ve hem deneysel hem de teorik olarak geniş ölçüde çalışılırlar. Doplanmalarına bağlı olan yüksek elektrik iletkenliklerine ve kararlılıklarına rağmen, bilinen çözücülerde çözünmemeleri nedeniyle işlenebilir değildirler. Çözünmezlik sorunu işlenebilirliğini ve endüstriyel kullanımlarını kısıtlar. Blok kopolimerizasyon, bu sorunu çözmek için kullanılan ve polipirolün istenen özelliklerini geliştiren yöntemlerden birisidir. Endüstriyel kullanımları daha çok morfolojinin ve yüzey davranışlarının çok önemli bir konu olduğu ve sonuçta oluşan malzemenin özellikleri üstünde kontol sahibi olmak için çok iyi bilinmesi gereken ince film uygulamalarını içerir.
Bu çalışmada, PPy’ün, metil metakrilatın, anilinin, ε-kaprolaktonun ve stirenin polimerleri ile diblok kopolimerleri modellenmiş ve elektronik, optik, morfolojik özellikleri çalışılmıştır. Pirole blok olarak eklenen polimerler, farklı polarlık derecesindeki ve çözünürlük davranışındaki PPy’den daha yumuşak polimerler olarak seçilmiştir. Bu kopolimerlerin kısa oligmerlerinin temel ve uyarılmış hal geometrileri DFT ve TDDFT metotlarıyla B3LYP/6-31g* seviyesinde her biri ayrı olarak optimize edilmiştir. Bant aralık değerlerindeki değişimler ve diblock kompozisyonunun fonksiyonu olarak UV soğurma spektrumu incelenmiştir. Çözünürlük değişkenlerine ve polimer zincirlerinin etkileşimlerine son derece bağlı olduğu gösterilmiş olan kopolimerlerin yapısal ve morfolojik özellikleri mikro ve mezo ölçekte MD simülasyonları ile elde edilmiştir.
1. INTRODUCTION
1.1 Conjugated Polymers
Research into the electronic, optical, and magnetic properties of conjugated polymers began in the 1970s [1], and the inorganic polysulfur nitride (SN)x which is highly conducting in 1973, was a key discovery in outlook for producing highly conducting polymers [2] First, the synthesis of polyacetylene thin films in 1974 and the subsequent success in doping was the real breakthrough for conjugated organic conducting polymers. Polyacetylene was prepared through polymerization of the hydrocarbon acetylene, had particularly interesting and unusual low-lying electronic excitations. The discovery and development of conductive polymers was recognized by the award of the Nobel prize for chemistry in 2000.[1]
A conjugated polymer is a carbon-based macromolecule through which the valence π-electrons are delocalized. Polyacetylene, illustrated in Figure 1.1, is a linear polyene, whose ground state structure is composed of alternating long and short bonds. H C C H H C C H H C C H H C C H H C C H H C C H H C C H H C CH
Figure 1.1 : Linear polyacetylene.
The charge transport of conjugated polymers has been studied for nearly two decades. Early work focused on developing conjugated polymers as plastic conductors and tried to increase the conductivity, σ, to that of the inorganic metals. This was accomplished by highly doping the polymer and stretch orienting the films. Polyacetylene, polyaniline, and polythiophene were the predominant polymers studied for conductor applications [3].
A group of organic polymers having conjugated double bonds on their backbone are known to be electroconductive [4]. The electronic conductivity of conducting polymers results from mobile charge carriers introduced into the conjugated π-
2
system through doping. To explain the electronic phenomena in these organic conducting polymers, polarons and bipolarons have been proposed by solid-state physicists. [2]
The electronic properties of any material are determined by its electronic structure. The theory that most reasonably explains electronic structure of materials is band theory. The band theory accounts for the different behaviours of metals, semiconductors, and insulators. The band gap is the energy spacing between the highest occupied energy level (valence band) and the lowest unoccupied energy level (conduction band).[5]
LUMO:
HOMO:
Figure 1.2 : The phases of the π-orbitals in the HOMO and LUMO.
Quantum mechanics stipulates that the electrons of an atom can only have specific or quantized energy levels. However, in the lattice of a crystal, the electronic energy of individual atoms is altered. When the atoms are closely spaced, the energy levels are form bands. The highest occupied electronic levels constitute the valence band and the lowest unoccupied levels, the conduction band (Figure 1.3).
Figure 1.3 : Energy band in solid.
The electrical properties of conventional materials depend on how the bands are filled. When bands are completely filled or empty no conduction is observed. If the band gap is narrow, at room temperature, thermal excitation of electrons from the valence band to the conduction band gives rise to conductivity. This is what happens in the case of classical semiconductors. When the band gap is wide, thermal energy
at room temperature is insufficient to excite electrons across the gap and the solid is an insulator. In conductors, there is no band gap since the valence band overlaps the conduction band and hence their high conductivity [2].
Metals have a zero band gap which means that they have a high electron mobility, i.e., conductivity. Semiconductors have a narrow band gap (2.5–1.5 eV), conductivity only occurs on excitation of electrons from the valence band to the conduction band (e.g., by heating). If the band gap is larger (3 eV), electron excitation is difficult; electrons are unable to cross the gap and the material is an insulator [5].
In conjugated polymers, the chemical bonding between the monomer units leads to the formation of one unpaired electron (π-electron) per carbon atom. Since the carbon orbitals are in the sp2pz configuration, in which the orbitals of successive carbon atoms along the polymer backbone overlap, leads to electron delocalization. The delocalized electrons over the length of the polymer chain form bands analogous to that of a semiconductor and the distortion of the polymer chain around the injected charge carriers leads to formation of polarons.
Conducting polymer are commonly prepared through chemical or electrochemical oxidative polymerization of the appropriate monomers. An important step is the incorporation of a counteranion (dopant) into the polymer chains during polymerization to neutralize the electrical charge, a process called ‘’doping’’. The overall reactions for the synthesis of polyaniline, polypyrrole and polythiophene are shown in Figure 1.4 respectively (A- = dopant/counteranion) [6].
Polymer-based conducting materials have received considerable attention because they can be substituted for conductors or semiconductors in a wide variety of electrical and electronic devices. The potential advantages of conductive or semiconductive polymers lie in their light weight and in the versatility with which their synthesis and fabrication can be accomplished [7].
Three classes of polymers are in the forefront of the research: 1) polyacetylene-based systems,
2) polylp-phenylene) and its derivatives 3) polyaniline and poly(heterocyc1ic)s [8].
4
Figure 1.4 : Reaction mechanism for the synthesis of PANI (a), PPy (b) and PTs (c). That conductivity, is achieved by incorporating a large amount of dopant via a redox reaction, e.g. iodine or AsF, that can also adversely affect the polymer's mechanical properties. In addition, doped polyacetylene and poly(p-phenylene) have poor stability in air [9]. However, most conducting polymers have at least one of the following undesirable characteristics: environmental instability, poor processability and poor physical properties. In the last few years, a considerable amount of investigation on conducting polyheterocyclic polymers has been carried out because of their good environmental stability [7].
Several approaches have been taken to improve the mechanical properties and processability of conducting polymers and still exploit their electrical conductivity. [10] One of the effective methods is to introduce insulating polymers. This can be achieved by composite, blending, and copolymerization [11].
Blending conducting polymers with thermoplastic polymers is one attempt to increase their processability [10], and improve the mechanical properties [12]. On the other hand, synthesis of composite films through electrochemical polymerization of the conducting component on the electrode coated with insulating polymer yields rather homogeneous products compared to blends prepared as mechanical mixtures. Copolymerization could be a desirable way because the chemical linkage between the insulating matrix and the conjugated polymer can improve the chemical stability
of polymer [11]. Copolymerization is often used to prepare a new polymer with properties different from homopolymers of the constituent monomers. Generally speaking, the physical and chemical properties of a copolymer are in the range of those of respective homopolymers but significantly distinct from those of a composite and a blend [13]. Efforts have been made to combine the advantages of conjugated and insulating polymers by copolymerization. However, the complicated synthesis methods and strict reaction conditions have limited the applications of these copolymers [14,10].
1.2 Polypyrrole
Polypyrroles are a class of conjugated polymers that have been extensively studied due to their excellent thermal and environmental stability, high conductivity, good ability to form coherent films, and ease of synthesis, low oxidation potential leading to stable conductors. Since the first report on the electrochemical preparation of conductive polypyrrole films, interest in the electronic properties of this polymer and its derivatives has increasingly grown. In early work, it was shown that flexible polymer films could be prepared with conductivities as high as 105 Scm-1 in the doped state [15,5].
1.3 Chain Structure
The pyrrole ring itself contains 4 carbon atoms and one nitrogen atom in an aromatic configuration. The two carbons located beside the nitrogen atom are in the alpha (α) position and the other two are in the beta (β) position (Figure 1.5). Similarities and differences exist between chemically formed and electrochemically formed PPy, but most studies on PPy find similar chemical structures, with being presented below.
N H
β
α
β
α
6 1.4 The Charge Transport
The charge-transport mechanism in these conducting polymers is yet to be understood from various transport measurements. The common feature of these conducting polymers is the delocalized electrons in their backbone. In particular, PPy is a polymer having nondegenerate ground states and charge transport occurs via polarons and, predominantly, bipolarons (Figure 1.6) [16].
Charge transport in PPy take place both along the polymeric backbone and between polymer chains. Intrachain transport, the movement of charge along a single polymer chain, requires only low levels of energy.
Interchain transport, the movement of charge between two seperate polymer chains, involves larger activation energies therefore reducing conductivities when it dominates charge transport. Therefore, PPy composite structures that favour intrachain charge transport are likely to possess higher conductivities than composites that favour interchain charge transport [17].
Figure 1.6 : Chemical structures for polypyrrole in its aromatic, polaron and bipolaron configurations [2].
Electron acceptor
polaron Electron acceptor
1.5 Synthesis
PPy was prepared either by the chemical oxidative polymerization method or by the electrochemical oxidative polymerization method [7]. The most widely accepted polymerization mechanism of PPy is the coupling between radical cations (Figure 1.7) [19]. In the initiation step, the oxidation of a pyrrole monomer yields a radical cation. Coupling of the two generated radical cations and deprotonation produces a bipyrrole, as confirmed by Andrieux et al [2].
Figure 1.7 : Polymerization mechanism of pyrrole through the coupling of two radical cation
8
The electrochemical polymerization of pyrrole produced free-standing conducting films, whose conductivity at room temperature was as high as 102 S cm~1.9. In electrochemical oxidation method, pyrrole and an electrolyte salt are dissolved in a suitable solvent and then the solution is subjected to oxidation, resulting in the growth of a conducting PPy film on the anodic working electrode [2]. Advantages in using electrochemical polymerization including the ease in controlling growth rate and PPy film thicknesses are exploited to produce PPy composites. However, electrochemical polymerization of pyrrole is expensive to scale up [17,18].
In contrast, the chemical polymerization method produced a finely divided, insoluble black powder, the conductivity of which extended from 10~15 Scm-1, depending on the specific preparative conditions. In the chemical oxidation method, an oxidizing agent such as lead dioxide, quinones, ferric chloride or persulfates is added to the pyrrole and a dopant dissolved in a suitable solvent, resulting in the precipitation of doped PPy powder. In general, the electrical conductivities of chemically prepared PPy are a little lower than those of PPy films prepared electrochemically. Nevertheless, the chemical oxidation method is suitable for commercial mass production of PPy and may produce processible PPy since the method has much greater feasibility to control the molecular weight and structural feature of the resulting polymer than the electrochemical oxidation method [2]. However, both the electrochemically prepared PPy and chemically prepared PP powders were difficult to handle and this restricted their potential for applications [7].
N H N H n n + (2+x)nFeCl 3 +x xCl -+ (2 -+ x) n FeCl2 + 2nHCl
Figure 1.8 : Chemical oxidative polymerization of pyrrole. 1.6 Morphology
Polypyrrole (PPy) is a widely studied polymer because of its ease of synthesis. The main difficulty in the investigation of mechanical properties of conducting polymers arises from their irregular structure. The polymeric film is usually not only brittle but also fragile. Dendritic growth of PPy chains during electrochemical polymerization causes the presence of weak points within the polymer matrix. Noteworthy errors in most characterization studies stem from ill-measured thickness, which results in
mechanical properties scattered in a rather broad range of values. The result is the same when one attempts to measure the electrical conductivity of the product.
The insolubility of PPy in most solvents and its infusibility at elevated temperatures seriously limit its characterization, processability, and fabrication. The insolubility of PPY may result from the highly rigid and flat, ribbonlike chain structure which is something like that of oligothiophene and pentacene [5].
Also the difficulty in solubility of conductive polypyrrole orginates from its delocalized p-electronic structure, which is the very same molecular characteristic that gives rise to its novel optical and electronic properties necessary for applications. The delocalized p-electronic structure leads to large electronic polarizability and large interchain p–p interaction, which favors aggregation instead of solution of polymer. It is possible to decrease this polarizability by structural modification, although in this case the polymer would lose all of its useful optical and electronic properties. Polymers are introduced to the reaction media to overcome the solubility problem of PPy. However, these polymers belong to the class of neutral polymers that only exhibit physical adsorption of PPy, which is in the colloidal form. Another way to overcome the solubility problem of PPy to obtain polymer–polymer complexes, either by interaction of opposite charges of two macromolecules or by matrix polymerization.
Advances in device performance characteristics have resulted from the introduction of novel materials either obtained by chemical modification of existing ones or by the synthesis of completely new structures, following by optimization of their morphology and structural order [20].
1.7 Modifying
The conformation and packing of conducting polymers in the amorphous glassy state are poorly understood, despite the fact that such characteristics dictate their most important physical and mechanical properties. Developing an ability to predict the structure and structure property relations of conducting polymers in the bulk will assist the design of new structures that combine processability with favourable electronic properties. A simulation strategy will be available for the reliable prediction of the structure, and physical properties of polymers with complex
10
chemical constitution and stiff backbones, including electronically conducting polymers [21].
Several approaches have been taken to improve the mechanical properties and processability of conducting polymers and still exploit their electrical conductivity [13]. The improvement of the processability of the conducting polymers, especially PPY, should depend on the enhancement of the polymer solubility by chemical modification, because the solubility is one of the most important performances deciding the feasibility of solution-processing method [22]. One of the effective methods is to introduce insulating polymers matrix into them due to the excellent processability of classical insulating polymers. This can be achieved by blending, composite and copolymerization (block and graft copolymers containing insulating) [11,13].
Blending conducting polymers with thermoplastic polymers is one attempt to increase their processability. On the other hand, synthesis of composite films through electrochemical polymerization of the conducting component on the electrode coated with insulating polymer yields rather homogeneous products compared to blends prepared as mechanical mixtures [23]. However, most of these composites and blends gradually lose their conductivity upon aging [13,24].
Table 1.1 : Polypyrrole blends with different polymer.
Polymer Blend Polymerization mechanism Ref
PCP PCP-PPy chemical 25
PEO PEO-PPy chemical 25
PMMA PMMA-PPy chemical 19, 25, 26
PVA PVA-PPy chemical and electrochemical 25, 27,28
PVAC PVAC-PPy chemical 25
PCL PCL-PPy chemical 29
EPDM EPDM-PPy chemical 30
PVMK PVMK-PPy chemical and electrochemical 30
PVC PVC-PPy photopolymerization 31, 32
PS PS-PPy blend chemical 33
In the past years, electrically conducting blend was prepared, based on PPy as the conductive polymer and PCL as an insulating polymeric matrix for investigating how the electrical conductivity is related to the morphology created during film formation [30]. The research indicated that the favorable intermolecular interactions, the hydrogen bonds between PCL and PPy, prevent the formation of isolated domains of
PPy, achieving high electrical conductivity using small amounts of conductive polymer. Also the results showed that controlling the crystallization process of the insulating polymer, modification of the morphology of the blend becomes possible. Zappi et al synthesized PPy and EPDM rubber blends by using CuCl2 in sorption process of pyrrole in an EPDM matrix. They investigated the effect of the oxidant particle size on the sorption and polymerization equilibrium, electrical conductivity, and mechanical properties of blends [29]. The dispersion of the oxidant, however was heterogeneous, and although PPy did grow at the CuCl, particles, the percolation of the PPy required for conductivity was not achieved [9] and they reported that electrical conductivity increased when oxidant particle size decreased.
Analysis of PPy/PVMK blend showed that cystallinity does not vary with PPy concentration in the PPy/PVMK (poly(vinyl methyl ketone)) blend and no significiant change in conductivity on stretching the blends over 200%. [34]
Girotto and co-workers obtained PPy/PVC blend which has low conductivity and rather poor electroactivity due to the loss of conjugation length of polypyrrole (PPy) provoked by halogenation. [31] Olivera et al. reported that the physical properties of the PPy/PVA blends are dependent on the amount of incorporated PPy as their electrical characteristics can vary from the limit of a highly insulating material to that of a very conducting polymeric film, similar in conductivity to doped electrochemically prepared PPy [27].
PPy/PSt blend prepared by Tang using different dopants and found that the conductivity changed for the concentration of the doping solution with a bell-shape profile [33].
Further, mechanical behavior can be improved by the synthesis of block or graft copolymers containing conventional and conducting sequences. This is achieved mostly by the use of polymeric initiators with functional groups within or at the end of the chain, which then is electropolymerized in the presence of the monomer of the conducting polymer [23].
Block and graft copolymers rank among the most interesting tailor-made polymer products because they combine the properties of several different homopolymers in a single molecule. Because of the presence of a covalent bond between each segment,
12
these type of copolymers lead to well-organized nanoscale morphologies both in bulk and in solution [35].
Morphological and electrical properties of PAC-g-PPy copolymers was investigated by Park et al. and was found that PAC-g-PPy copolymer showed higher electrical conconductivity than their composites. Also copolymer had homogenous structure distinctly from composite [4].
The research of Mecerreyes was about solubility in organic solvents and electrical conductivity of PCL-g-PPy copolymers. It was observed microphase separation into PPy and PCL rich domain. These domains effected the solubility and electrical conductivity of copolymers. The electrical conductivity of the copolymers increases with the amount of polypyrrole in the copolymer. Poly(e-caprolactone) rich copolymers (>85 wt.%) were partly soluble in common organic solvents, whereas polypyrrole-rich copolymers were completely insoluble. Also it was reported in the literature that PVAc-g-PPy copolymers were soluble with low PPy content but had low electric conductivity [36]. There are so much research about the graft copolymers of polypyrrole and some of them was shown in Table 1.2.
Table 1.2 : Polypyrrole graft copolymers with different polymer.
Polymer Copolymer Polymerization mech. Ref
PMMAa PMMA-graft-PPy Electro 37
PDMSa PDMS-graft-PPy Electro 37
PMMTha PMMTh-graft-PPy Electro 37
PACa PAC-graft-PPY Electro 4
PMMA-co-PEMAa (PMMA-co-PEMA)-graft-PPY Electro 37,38 PMMA-co-PMTMa (PMMA-co-PMTM)-graft-PPy Electro 37,39
PMMTa PMMT-graft-PPy Electro 40,37
PVAa PVA-graft-PPY Chem. and elect. 36
PSSAa PSSA-g-PPY Chemical 41,37
PCLa PCL-graft-PPY Chemical 42,43
a
Polymers, PSSA=poly(styrene sulfonic acid), PMMA = poly(methyl methacrylate), PPy = polypyrrole, PDMS = poly(dimethyl siloxane), PCL = polycaprolactone, PVA= poly(vinyl acetate), PMMT = Poly(3-methylthienyl methacrylate), PMMTh = poly(methacryloyloxy methylthiophene), PAC = poly(acryloyl chloride), PMMA-co-PMTM= polymethyl methacrylate-co-polymethyl thienyl methacrylate, PMMA-co-PEMA=poly[(methyl methacrylate)-co-(2-(n-pyrrolyl) ethyl methacrylate)]. Moon and co-workers [44] synthesized random copolymer of aniline and pyrrole by chemical oxidative polymerization and they investigated the solubility, electrical conductivity, thermal stability of obtained copolymers. The results showed that molecular weight and solubility increased with the molecular ratio of aniline in
copolymers (Figure 1.8), but electrical conductivity decreased with aniline ratio. Random pyrrole and aniline copolymers were black powdery and slightly soluble in polar organic solvent.
N H NH2 1 N H l H N m
1- H2O2 and Fe2+, at 30 oC in an aqueous H2SO4 solution
Figure 1.9 : Copolymerization of pyrrole and aniline.
π-conjugated polymers containing flexible aliphatic side groups more soluble than others but have lower electrical conductivity. Also in different study, random copolymers of pyrrole and ethylaniline was prepared (Figure 1.9) for improving the solubility of pyrrole with high electrical conductivity by combining two monomers’ properties [22]. It was observed that in contrast to complete insolubility of PPy, the copolymers exhibit good solubility in the solvent which had high boling point and criticize the solvents with their solubility parameter, polar index and dielectric constant. Also according to the report, ethyl groups contributed to increase the solubility of copolymers because steric hindrance lowered the interchain action and increase the interchain distance so strengthened the interaction and affinity between polymer chains and solvent molecules. Finally, they conclude that Py/EA comonomer ratio effects all of molecular weight, solubility, film forming ability, electroconductivity and thermostability.
Figure 1.10 : Copolymerization of pyrrole and ethylaniline. 1.8 Block Copolymers of Polypyrrole
The block copolymer, a kind of polymer alloy, behaves as a rubber at ambient conditions, but can be moulded at high temperatures due to the presence of the glassy domains that act as physical crosslinks. In solutions, attachment of a water soluble polymer to an insoluble polymer leads to the formation of micelles in amphilic block
14
copolymers. The presence of micelles leads to structural and flow characteristics of the polymer in solution that differ from either parent polymer [45].
Neutral polypyrroles don’t have expected properties for commercial applications (low density, flexibility, processibility, and low cost) [30] and tend to be insoluble and infusible due to the strong crosslinking, inter- or intramolecular interaction between ring-based backbones which are relatively strong compared with the van der Waals force or hydrogen bonding between saturated polymers. So block copolymerization is used as a method for solving insolubility problem.
Figure 1.11 : Block copolymers architecture.
Pyrrole and aniline have both high electrical conductivity and limited processability because of their insolubility properties. Guo and co-workers [46] investigated synthetic conditions, size of hollow spheres and effect of TX-100 miscelles as a template in bulk solution for these conducting polymers as formed poly(aniline-co-pyrrole) (PACP). For estimating whether the nanospheres were hollow or the cores filled with different templates.
They found that average hydrodynamic average value increased with concentration of comonomers and this result showed that comonomers were solubilized in spherical micelles formed by an amphiphlic molecule.
Also it was reported that increased [pyrrole]/[aniline] ratio produced decreasing in the size of cavities at center of hollow spheres. Introduction of pyrrole units changed the conjugated structure of aniline chain, and thus improved their processability.
Figure 1.12 : A) SEM and (B,C) TEM images of PACP hollow nanospheres synthesized in the presence of TX-100, synthetic conditions: [TX-100] = 1.6 mM, [aniline]=[pyrrole] = 0.05 M,
[APS]/[comonomers] = 1.0:1, 5oC [46].
Figure 1.13 : (C,D) TEM images of hollow spheres synthesized at different [pyrrole]/[aniline] molar ratios: (C) 1.2:1,(D) 1.4:1.
Block copolymers of polytetrahydrofuran and polypyrrole was synthesized in different investigation by potentiostatic anodic polymerization of pyrrole in different electrolytic media (Figure 1.13) [47] and living polymerization [48]. In both of researches, the results of characterization analysis showed that the chain length of polytetrahydrofuran segments did not effect the properties of copolymers like thermal, electrochemical behaviors, surface morphologies and conductivities significiantly. But the supporting electrolytes had greatly effect on these properties. Also, it was reported in another study to prepare block copolymer of pTHF and pyrrole (Figure 1.14) by the same conditions and electrochemical method for improving the hydrophilic charactheristic of PPy with pTHF [11].
16 (CH2)4O N N H Electrolysis N NH HN (CH2)4O n (CH2)4O N N H Electrolysis N HN HN CH4 N NH HN N (CH2)4O
Figure 1.14 : Block copolymers of polypyrrole and polytetrahydrofuran [11].
In a experimental research about the block copolymers of thiophene-capped poly(methyl methacrylate) with pyrrole (Figure 1.15), it was observed low percentage of blocking in polymer film but thermally stable and electrically conducting polymer films were obtained [49].
Figure 1.16 : Copolymer of polypyrrole and thiophene-capped PMMA. The hopping theory of conducting polymer for understanding conduction mechanism was investigated by Parlak so a block copolymer which had a conjugated polymer-polypyrrole- part and insulating part, polysiloxane, in different temperature. was synthesized (Figure 1.18).
Figure 1.17 : Copolymer of polypyrrole and polysiloxane.
It was observed that temperature range conduction was predominantly provided by the Mott variable range hopping mechanism [16]. A semiconducting pyrrole-styrene copolymer was electhrochemically synthesized by Xue and charactherization analysis showed that it was a block copolymer with better mechanical properties and processibility than pyrrole [13].
18
Electhrochemically synthesized block copolymer thiophene-ended polystyrene with pyrrole (Figure 1.17) by using several supporting electrolytes [50] showed thermally stable and electrically conducting properties.
Figure 1.18 Copolymer of polypyrrole and polystyrene [13].
Several kinds of copolymer containing pyrrole and other insulating units, such as polystyrene tetrahydrofuran, methyl methacrylate, ε-caprolactone, and acryloyl chloride have been prepared and studied. All results showed the success in improving the mechanical and physical properties of polypyrrole [11].
2. METHODOLOGY
2.1 Quantum Mechanical Methods
Generally it is accepted taht the word quantum comes from Latin and was first used in by Max Planck in 1900, to denote the constrained quantities or amounts in which energy can be emitted or absorbed. Although the term quantum mechanics was apparently first used by Born in 1924. “Mechanics” as used in physics is traditionally the study of the behavior of bodies under the action of forces like, e.g. gravity (celestial mechanics). Molecules are made of nuclei and electrons, and quantum chemistry deals, fundamentally, with the motion of electrons under the influence of the electromagnetic force exerted by nuclear charges [24].
Quantum mechanics (QM) is the correct mathematical description of the behavior of electrons and thus of chemistry [24,15]. Quantum mechanics teaches basically, that energy is quantized: absorbed and emitted in discrete packets (quanta) of magnitude hv, where h is Planck’s constant and v is the frequency associated with the energy [24].
E= h.υ (2.1) In theory, QM can predict any property of an individual atom or molecule exactly. In practice, the QM equations have only been solved exactly for one electron systems [24,15].
The fundamental methods of quantum mechanics are:
1. Semi – Emprical Methods; based on approximate solutions of the Schrödinger equation with appeal to fitting to experiment (i.e. using parameterization)
2. Ab–Initio Methods; based on approximate solutions of the Schrödinger equation without appeal to fitting to experiment.
20
3. DFT (Density Functional Theory) based on approximate solutions of the Schrödinger equation, bypassing the wavefunction that is a central feature of ab initio and semiempirical methods [24].
Ab initio and the faster DFT enable novel molecules of theoretical interest to be studied, provided they are not too big. Semiempirical methods, which are much faster than ab initio or even DFT, can be applied to fairly large molecules
2.1.1 Semi Empirical Methods
Semiempirical (SE) calculations are, like ab initio, based on the Schrödinger equation. However, more approximations are made in solving it, and the very complicated integrals that must be calculated in the ab initio method are not actually evaluated in SE calculations: instead, the program draws on a kind of library of integrals that was compiled by finding the best fit of some calculated entity like geometry or energy (heat of formation) to the experimental values. This plugging of experimental values into a mathematical procedure to get the best calculated values is called parameterization (or parametrization). It is the mixing of theory and experiment that makes the method “semiempirical”: it is based on the Schrödinger equation, but parameterized with experimental values (empirical means experimental) [51].
Many semiempirical methods have been created for modeling organic compounds. These methods correctly predict many aspects of electronic structure, such as aromaticity. Furthermore, these orbital-based methods give additional information about the compounds, such as population analysis. There are also good techniques for including solvation effects in some semiempirical calculations [52].
2.1.2 Ab – Initio Methods
The term ab initio is Latin for ``from the beginning.'' from first principles (ab initio calculations give results in terms of fundamental physical constants – Planck’s constant, the speed of light, the charge of the electron– that must be measured to obtain their actual numerical values, but a chemical theory could hardly be expected to calculate the fundamental physical parameters of our universe) [52,24] This name is given to computations that are derived directly from theoretical principles with no inclusion of experimental data [52].
Ab initio calculations are based on the Schrödinger equation. This is a one of the fundamental equations of modern physics and describes, among other things, how the electrons in a molecule behave.
HΨ=EΨ (2.2.) The ab initio method solves the Schrödinger equation for a molecule and gives us the molecule’s energy and wavefunction. The wavefunction is a mathematical function that can be used to calculate the electron distribution (and, in theory at least, anything else about the molecule). From the electron distribution we can tell things like how polar the molecule is, and which parts of it are likely to be attacked by nucleophiles or electrophiles. The Schrödinger equation cannot be solved exactly for any molecule with more than one electron. Thus approximations are used; the less serious these are, the “higher” the level of the ab initio calculation is said to be. Regardless of its level, an ab initio calculation is based only on basic physical theory (quantum mechanics) and is in this sense “from first principles” [24].
The most common type of ab initio calculation is called a Hartree-Fock calculation (abbreviated HF), in which the primary approximation is the central field approximation. This means that the Coulombic electron-electron repulsion is taken into account by integrating the repulsion term. This gives the average effect of the repulsion, but not the explicit repulsion interaction. This is a variational calculation, meaning that the approximate energies calculated are all equal to or greater than the exact energy. The energies are calculated in units called Hartrees (1 Hartree=27.2116 eV). Because of the central field approximation, the energies from HF calculations are always greater than the exact energy and tend to a limiting value called the Hartree-Fock limit as the basis set is improved.
One of the advantages of this method is that it breaks the many-electron Schrödinger equation into many simpler one-electron equations. Each one electron equation is solved to yield a single-electron wave function, called an orbital, and an energy, called an orbital energy [52].
22 2.1.3 DFT (Density Functional Theory)
Density functional theory (DFT) is a well established approach for the description of many electron systems, comprising atoms, molecules, clusters and solids [53]. Density functional calculations are, like ab initio and SE calculations, based on the Schrödinger equation. However, unlike the other two methods, DFT does not calculate a wavefunction, but rather derives the electron distribution (electron density function) directly. A functional is a mathematical entity related to a function [24,12]. This theory originated with a theorem by Hohenberg and Kohn that stated this was possible. The original theorem applied only to finding the ground-state electronic energy of a molecule. A practical application of this theory was developed by Kohn and Sham who formulated a method similar in structure to the Hartree-Fock method [52].
In this formulation, the electron density is expressed as a linear combination of basis functions similar in mathematical form to HF orbitals. A determinant is then formed from these functions, called Kohn-Sham orbitals. It is the electron density from this determinant of orbitals that is used to compute the energy. This procedure is necessary because Fermion systems can only have electron densities that arise from an antisymmetric wave function. There has been some debate over the interpretation of Kohn-Sham orbitals. It is certain that they are not mathematically equivalent to either HF orbitals or natural orbitals from correlated calculations. However, Kohn-Sham orbitals do describe the behavior of electrons in a molecule, just as the other orbitals mentioned do.
The exact density functional is not known. Therefore, there is a whole list of different functionals that may have advantages or disadvantages. Some of these functionals were developed from fundamental quantum mechanics and some were developed by parameterizing functions to best reproduce experimental results. Thus, there are in essence ab initio and semiempirical versions of DFT.
DFT tends to be classiffied either as an ab initio method or in a class by itself [52]. The correct mathematical form of the DFT functional is not known, in contrast to conventional ab initio theory where the correct mathematical form of the fundamental equation, the Schrödinger equation, is known. In conventional ab initio theory, the wavefunction can be improved systematically by going to bigger basis
sets and higher correlation levels, which takes us closer and closer to an exact solution of the Schrödinger equation, but in DFT there is so far no known way to systematically improve the functional. [24] Density functional calculations are usually faster than ab initio, but slower than semi-empirical. [24,12].
2.2 Statistical Mechanical Methods
Many of the problems that we would like to tackle in molecular modelling are unfortunately too large to be considered by quantum mechanics. Quantum mechanical methods deal with the electrons in a system, so that even if some of the electrons are ignored (as in the semi-empirical schemes) a large number of particles must still be considered, and the calculations are time-consuming. Force field methods (also known as molecular mechanics) ignore the electronic motions and calculate the energy of a system as a function of the nuclear positions only. [54] Molecular mechanics (MM) is based on a model of a molecule as a collection of balls (atoms) held together by springs (bonds). If the normal spring lengths and the angles between them is known, and how much energy it takes to stretch and bend the springs, the energy of a given collection of balls and springs, i.e. of a given molecule can ce calculated; changing the geometry until the lowest energy is found enables us to do a geometry optimization, i.e. to calculate a geometry for the molecule.[24] Molecular mechanics is used to perform calculations on systems containing significant numbers of atoms. In some cases force fields can provide answers that are as accurate as even the highest-level quantum mechanical calculations, in a fraction of the computer time. However, molecular mechanics cannot of course provide properties that depend upon the electronic distribution in a molecule.
That molecular mechanics works at all is due to the validity of several assumptions. The first of these is the Born-Oppenheimer approximation, without which it would be impossible to contemplate writing the energy as a function of the nuclear coordinates at all. Molecular mechanics is based upon a rather simple model of the interactions within a system with contributions from processes such as the stretching of bonds, the opening and closing of angles and the rotations about single bonds. Even when simple functions (e.g. Hooke's law) are used to describe these contributions the force field can perform quite acceptably. Transferability is a key
24
attribute of a force field, for it enables a set of parameters developed and tested on a relatively small number of cases to be applied to a much wider range of problems. Moreover, parameters developed from data on small molecules can be used to study much larger molecules such as polymers [54].
2.2.1 Molecular Dynamics Simulation
The most serious problem with MM as a method to predict molecular structure is convergence to a false, rather than the global minimum in the Born-Oppenheimer surface. The mathematical problem is essentially still unsolved, but several conformational searching methods for approaching the global minimum, and based on either systematic or random searches have been developed. These searches work well for small to medium-sized molecules. The most popular of these techniques that simulates excitation to surmount potential barriers, has become known as molecular dynamics [55].
Molecular dynamics calculations use the equations of classical physics to simulate the motion of a molecule under the influence of forces; the required force fields can be computed by ab initio methods or, for large systems, semiempirical methods or molecular mechanics. [24] The simplest MD procedure is to keep the total energy constant and allow the molecule to drift through various conformations as the kinetic energy (temperature) fluctuates. This routine, also known as microcanonical MD is useful for simulating internal motion in a molecule.
In quenched MD, structures are periodically extracted from the microcanonical MD progression in time and minimized. The configurations found in this set of minimized structures are analyzed for uniqueness and the low energy subset is said to represent the structure of the molecule. In annealed MD, the temperature of the system is incrementally increased and then decreased between low and high temperatures for a number of cycles with the lowest-energy structures being saved for further minimization and analysis [55].
2.2.2 Dissipative Particle Dynamics
Hohenberg and Kohn introduced a simulation technique for hydrodynamic behavior, called dissipative particle dynamics (DPD) and Español modified to its present form [56,47]. This technique is based on the simulation of soft spheres, whose motion is
governed by certain collision rules. By introducing bead-and-spring type particles, polymers can be simulated with the same method [56].
Figure 2.1 : Schematic illustration of the DPD system.
In the dissipative particle dynamics (DPD) approach, solvent particles are coarsegrained into fluid elements, thereafter called dpd-particles and each DPD bead represents a fluid package [47,57]. The evolution of the positions rij and impulses vij
of all interacting beads over time is governed by Newtonian second law of motion [58]. i i
f
dt
dt
d
=
=
=
=
=
=
=
=
v
i,
d
v
irrrr
(2.3)The equations of motion are solved using the modified velocity-Verlet algorithm presented by Groot and Warren. The total force acting on a bead is composed of three pair wise additive forces:[57]
ƒi = Σ ( FijC + FijD + FijR ) (2.4)
where FijC , FijD , FijR are the conservative, dissipative, and random forces, respectively.
DPD is differentiated from MD by the use of soft repulsive conservative interactions. This allows for time steps in DPD that are much larger than those in typical MD simulations. The three pairwise forces are given by [57].
26 ij ij C C ij
r
e
F
=
Π
0ω
(
)
(2.5a) ij ij ij ij D D ij r e p e F =−γω
( )( . ) (2.5b) ij ij R ij R ijr
e
F
=
σξ
ω
(
)
(2.5c) Beads interact only with those that are within a certain cut-off radius rc. When rc =1, then where, ξ ij is a random number drawn from a uniform distribution with zero mean, ω(rij) the weight function, γ the friction factor and σ defines the fluctuation amplitude.Groot and Warren rewieved DPD as a mesoscopic simulation method. They derived a relation between χ parameters and the repulsion parameters between unequal particles in the simulation by applying the condition that the solubility of one phase into the other should be described correctly. So mutual solubility and compressibility of liquids consisting of parts of macromolecules can be calculated using retaining all atmoistic details [46]. 3 , 75 = = = = = = = =
ρ
ρ
ρ
ρ
ρ
ρ
ρ
ρ
kBT aii (2.6)3. COMPUTATIONAL DETAILS
In order to investigate the electronic and optic properties, monomers, pentamers and diblock oligomers formed as (A)5-b-(B5) architecture were generated. Ground and excited state geometries of monomers, pentamers and the short oligomers of PPy copolymers were optimized at B3LYP/6-31g* level by DFT and TDDFT methods and using the Gaussian 2003 (G03) software package. Molecular mechanics is used to perform calculations on systems in the mesoscopic scale and to descripe large systems. In each diblock copolymer, weight percent of PPy segment was kept constant as 14 %. The number of the PPy monomer was determined as 40, so the number of PCL, PMMA, PSt and PANI monomer were calculated as 137, 156, 150 and 171. All simulation were performed by Material Studio (MS) 4.01 software. This structures were used for molecular dynamic simulations. MD simulation processes were shown basically as flowchart in Figure 3.1.
Figure 3.1 : Flow chart of the molecular dynamic simulation studies.
Morphological properties of the PPy diblock copolymers were studied by DPD simulations. By using RIS-Monte Carlo and QSPR methods, DPD input parameters were obtained. All these operations were represented by flow chart in Figure 3.2.
Generation of the diblock copolymer
chains
Minimization of chains with Smart minimizer algorithm, COMPASS forcefield for 10000 step at 298K.
Molecular dynamic simulations for 2000 ps of NVT Dynamics at 298 K Bonded and nonbonded
energy calculations and configurational
28
Calculation of DPD input parameters
Figure 3.2 : Flow chart of the DPD simulations. Generation of oligomers of (20) PY, CL, ANI, MMA and St oligomers Minimization of the chains Constructed in amorphous cells for oligomers and minimization of the cells
for 10000 steps Performing the dynamics for 2000 ps with NVT ensemble Analyzing the cohesive energy density and solubility
parameter
DPD simulations for 1000 step
Examining the miscibility of the systems Calculation of characteristic ratio, solubility parameters and other structural parameters by QSPR method.
4. RESULTS AND DISCUSSION
4.1. Electronic Properties of Diblock Copolymers
Ground and excited state geometries of monomers, pentamers and the short cooligomers of (Py)m-b-(B)n (B=CL, MMA, St, ANI) were optimized by using DFT hybrid functional of B3LYP/6-31g* level. Number of the monomer in each block (m and n) was increased one to five, so twenty five optimized stuctures and ESP charges for each copolymers were obtained. Optimized structures of oligomers were shown in the Table 4.1.
While pyrrole polymerization, pyrrole monomers links together from their α position. Polypyrrole is linear but not fully coplanar with zero torsional angle. Increasing average torsional angle of polypyrrole decreases the conjugation length so the torsional angle has the direct effect on the conductivity. Decreasing of conjugation length which is typically experienced in graft copolymers, does not have considerable effect on the diblock copolymers of polypyrrole. The torsional angle for pyrrole pentamer (in gas phase, zero Kelvin) was calculated as 23o and this angle between the pyrrole units does not change with the soft segment, meaning that the rigidity of conjugated segment is conserved.
30
Table 4.1 : Oligomers with quantum mechanically obtained atomic charges.
Cooligomer Optimized Diblok Oligomers obtained by DFT Method
(Py)5-b-(St)5 (Py)5 -b-(MMA)5 (Py)5 -b-(CL)5 (Py)5 -b-(ANI)5
Table 4.2: Monomers with quantum mechanically obtained atomic charges. Cooligomer Optimized structure of monomers with atomic charges
Pyrrole (Py)
Styrene (St)
Methyl methacrylate (MMA)
Aniline (ANI)
32
Total electronic energies, HOMO- LUMO energies and the band gap of oligomers were calculated by DFT and the plots of the band gap was given in Figure 4.1. The band gaps was obtained from the calculations of the highest occupied molecular orbital (HOMO) –lowest unoccupied molecular orbital (LUMO) energy differences of the molecules.
Figure 4.1 : The changes in the band gap of the diblock cooligomer with the conjugated chain
Figure 4.1 : The changes in the band gap of the diblock cooligomers with the conjugated chain (continued)
The changes in the band gap showed that the band gap of the diblock cooligomers decreases with conjugated chain length, so the conductivity increases for these cooligomers.
In (CL)n, (St)n, (MMA)n systems, it was observed that band gap decreases with number of the Py monomer (m), does not change with number of these soft segments (n) so the length of the non-conjugated segment seems to have a minor effect on the conductivity. This result may be misleading due to the fact that short lengths of the non-conjugated segments have no power to deviate the rigid segments from the linearity,
34
However, initial energy band gap for these molecules started with higher value than the energy band gap of Py because CL, MMA, St pentamers have larger band gap than Py and ANI. Different from the others, number of ANI monomer (n) caused to decreases in the energy band gap due to the conjugated structure. But reducing effect on the band gap looses with increased ANI monomer due to the energy band gap of ANI is higher than Py’s.
In order to investigate the optic properties of diblock copolymer of PPy, (Py)m-b-(CL)n copolymer was choosen and intensity was calculated in 200-800 nm wavelength for each (Py)m(CL)5, m was varied 1 to 5. After excited state geometries were optimized by TDDFT, UV absorption spectra as a function diblock composition was observed and given in Figure 4.2.
Figure 4.2 : The change of UV absorbtion sprectrum with m of (Py)m-(CL)5 PCL doesn’t absorb in UV region because it has any chromophore group. But PPy is a conducting polymer so it absorbs light in UV region and the red shifts (the shifts to higher wavelength or smaller energy region) of the absorption maxima with the extension of the conjugated segment are consistent with our band gap results belongs the homo→ lumo (or π-π* ) transition in the heteroaromatic ring, was calculated as 366 nm. For a fixed number of the CL monomer, upon increasing of the number of
the pyrrole monomer, the π-π* peak shifted to longer λ (red shift) as expected (Table 4.3).
Table 4.3 : The changes of m- λ and m-band gap in (Py)m-(CL)5 copolymer.
m
1 2 3 4 5λ (nm) (homo→lumo transition) 254 324 374 409 435
λ (nm) (homo→lumo+1 transition) - 221, 247 289 322 352
Band Gap (eV) 5,053 4,020 3,557 3,305 3,130
4.2. Molecular Dynamic Studies of Diblock Copolymers
Diblock copolymers of PPy in different configuration were simulated to investigate the dynamical behaviour and the structures of polymeric chains in the equilibrium by MD simulation. By using MD simulation, it is intended to study these large systems in the mesoscopic scale. All of the structures were subjected to equilibration for 2 ns of NVT dynamics at 298 K in vacuum.
(I) (II) (III) Figure 4.3 : Configuration of the studied diblock copolymer system.
In order to model the polymer chain packing and orientation, for each diblock copolymers, MD simulations were performed in three different configuration as single diblock chain (I), paralel (II) and anti-parallel diblock two chain(III) (Figure 4.3).
36
Table 4.4 : The snapshot pictures of the equilibrium structures of two PPy-b-PCL diblock copolymers.
PPy-b-PCL Equlibrium structure of PPy-b-PCL diblock copolymers
Single chain Two parallel chain Two anti-parallel chain
Table 4.5 : The snapshot pictures of the equilibrium structures of two PPy-b-PSt diblock copolymers.
PPy-b-PSt Equlibrium structure of PPy-b-PSt diblock copolymers
Single chain
Two parallel chain
Two anti-parallel chain
38
The equilibrium structures of PPy-b-PCL copolymers are shown in Table 4.4. The first snapshot belongs to the single chain of PPy-b-PCL. The linearity of the rigid PPy backbone is broken if the soft segment has a high coiling tendency in single-chain structures. Similiar to single single-chain of PPy-b-PCL copolymer, for anti-parallel configuration, PCL chains were colied by bending the linearity of the PPy chains as half-moon. But in this conformation, steric hindrance and O-O interaction of PCL caused to coil partially outside of PPy chains. Parallel configuration of copolymer showed different structure than the others. It was observed that linear structure of PPy doesn’t break down as well as the other configurations and PCL doesn’t pack in the spiral chain of PPy. PCL chains which started folding from the head line, showed packing predisposition from the each head. While PCL chains were aggregating, they formed a coil structure in the tail point of the PPy molecules. So rod(PPy)-coil(PCL) structured was formed. Also, the equilibrium structures of double chains showed that the hard segments prefer to align parallel to each other favoring the π-stacking due to the strong inter-chain interactions of the π-clouds. PPy-b-PSt parallel configuration showed that π stacking is maintained after MD simulations (Table 4.5) and PSt segment coiled together. Also conjugated PPy didn’t fall off configuration 2.
PANI segments which has conjugated backbone as PPy, didn’t prevent the π stacking of PPy chains so it behaves differently than the other (non-conjugated) segments. It does not cause bending of the PPy chain. No significiant change in the end-to–end distance of PPy segment is observed. But especially in parallel configurations, change of end to end distance of PPy backbone is lower than others.
The tendency to coiling of PMMA was observed in configuration 1 and 3. Coiled PMMA segment affected planarization and decreases conjugation of PPy. Parallel configuration and π stacking of PPy provided PMMA to be parallel.
Table 4.6 : The snapshot pictures of the equilibrium structures of two PPy-b-PMMA diblock copolymers.
PPy-b-PMMA Equlibrium structure of PPy-b-PMMA diblock copolymers
Single chain
Two parallel chain
Two anti-parallel chain
