ELECTRICAL PROPERTIES AND STRUCTURE OF POLYMER COMPOSITES WITH CONDUCTIVE FILLERS. Ye. P. Mamunya

Transcription

1 ELECTRICAL PROPERTIES AND STRUCTURE OF POLYMER COMPOSITES WITH CONDUCTIVE FILLERS I. Influence of filler geometry and spatial distribution Ye. P. Mamunya Institute of Macromolecular Chemistry National Academy of Sciences of Ukraine Kiev, Ukraine

2 National Academy of Sciences of Ukraine Institute of Macromolecular Chemistry Director of the Institute academician, professor E. Lebedev A d m i n i s t r a t i o n of the I n s t i t u t e Associate directors on science Professor Yu. Kercha DSc Yu. Savelyev Academic secretary PhD V. Myshak Chief engineer V. Krulitskiy Accountant-general M. Kolchenko 1. Chemistry of heterochain polymers and interpenetraiting networks Synthesis, mechanisms of forming and methods of creation in water and organic medium, investigation of interpenetrating polymer networks and composites on their base (personnel - 30) DSc Yu. Savelyev 2. Physical chemistry of polymers Physical chemistry of multi-component polymer systems, polymer blends and melts, structure of multicomponent systems (personnel - 28) DSc T. Todosiychuk S c i e n t i f i c d e p a r t m e n t s 3. Polymer modification Structural, chemical and physical modification of heterogeneous polymers and related systems (personnel - 22) DSc, professor Yu. Kercha 4. Polymers for medical purposes Elaboration of biocompatible polymer materials for medical applications and medical-biological testing of polymer materials (personnel - 25) DSc N. Galatenko 5. Polymer composites Structure and properties of polymer composites based on conventional polymers and organic-inorganic systems (personnel - 33) Academician, professor E. Lebedev 6. Chemistry of oligomers and cross-linked polymers Synthesis reactive oligomers and creation of polymer systems based on synthesized oligomers. Development of functional polymers (personnel - 17) DSc, professor V. Shevchenko 7. Physics of polymers Physics of polymer systems and nanocomposites. Characterization of microheterogeneous state of polymer systems and composites (personnel - 10) DSc V. Klepko General information G e n e r a l d e p a r t m e n t s Scientific-technical information, patent-license and publishing activities (personnel - 7) A. Dyakova Standards and metrology (personnel - 6) V. Krulitskiy Personnel management (personnel - 2) E. Kazina Ancillary technical department (personnel - 37) V. Krulitskiy General numbers of personnel Scientific personnel - 92 including: DSc - 17 PhD - 75 PhD students - 23

3 Scope of the Institute for the application of new polymer materials and technologies 3 Produced materials Adhesives Pilot plant (personnel - 23) N. Gladyreva Mastics Lacquers Paints Polymer composites Materials and technologies Protective dampproofing of concrete constructions based on elaborated materials: Technical laboratory MONOLITH (personnel - 9) PhD V.Kolyada - water protection in the metro tubes and stations - breakdown elimination of the concrete pipelines - moisture protection of the concrete bridges - protection and insulating of the nuclear station constructions - soil solidification - flooding floors in the special factory sections

4 4 New polymer materials elaborated in the Institute New lacquer and paint compositions New protective composite materials and technologies of their use New film materials

5 5 The topics proposed: structure of conductive polymer composites influence of shape of conductive particles on electrical properties influence of spatial distribution of filler on electrical characteristics methods of conductivity measurements influence of polymer-filler interaction on structure and electrical properties filled conductive polymer blends: structure and properties phase inversion in filled polymer blends conductive composites with carbon nanotubes: technology, structure, conductivity, dielectric properties

6 Electrical characteristics of materials 6 Conductors Semi-conductors Insulators σ, S/cm Metals Carbon materials Polymers with intrinsic conductivity Organic conductors, ionic conductors Antistatic materials Polymer materials

7 7 Types of conductive and insulating materials Conductive Metals Carbon materials: carbon black, carbon fibers and tissue, carbon nanotubes Conductive ceramic Polymers with intrinsic conductivity (polyaniline, polypyrol, polythiophen and others) high conductivity Disadvantages metals high density, high weight carbon low mechanical characteristics rest impossibility of processing by highly productive industrial methods high cost Advantages Nonconductive Polymer materials Advantages low density, low weight high mechanical characteristics procesability by highly productive industrial methods low cost Disadvantages no conductivity impossible to use at high temperatures

8 8 Conductive polymer composites Two-phase system polymer-insulator + conductive filler Advantages presence of conductivity low density, low weight high mechanical characteristics possible to process by highly productive industrial methods low cost

9 9 Types of conductive fillers Conductive composite is two-phase system with insulating phase (polymer matrix) and conductive phase (filler). Several kinds of materials can be used as conductive fillers: dispersed metals; carbon black; metallized mineral particles; carbon and metallic fibers; carbon nanotubes; conductive ceramic; polymers with instrinsic conductivity

10 10 Why such materials are attractive for research and application? They combine the properties of polymer and metals or carbon. Electrical properties can be close to metals while the processing is typical for the polymers. It is relatively easy to adjust the electrical and dielectric properties in the wide range. Conductive polymer composites can be extended for application in various fields : heaters with distributed heat-emission and self-regulated heaters; shieldings for electromagnetic protection; contact buttons in computers and media technics; current-limiting devices; conductive adhesives; and many others.

11 Correlation of structure with conductive properties of composite 11 Conductivity, log σ nonconductive Region 1 ϕ c conductive Region 2 percolation threshold Filler volume fraction, ϕ Region 3 Conductivity of composite is a function of the filler content and reflects the structure of composite. Region 1 the composite is nonconductive, the matrix includes the separate particles of conductive filler. Region 2 the region of percolation, the conductive cluster is created, the conductivity sharply increases at ϕ > ϕ c. Region 3 the conductivity slowly increases because of growth of conductive cluster.

12 Methods of definition of the percolation threshold methods of definition of the percolation threshold Conductivity, log σ Start of creation of the conductive cluster and sharp growth of conductivity of the composite. 2. When conductive cluster is completed and the composite is conductive. ϕ c Filler volume fraction, ϕ 3. At maximum of the derivative function d(log σ)/dϕ, it is close to method 1. 5 log σ 4. At value of conductivity σ c = σ σ p f log (ϕ-ϕ c ) 5. By fitting of equation σ ( ϕ ) t ϕ c

13 13 Main factors that define the conductive properties of polymer composites with conductive fillers value of conductivity of the filler; content of filler in the polymer matrix; shape of the filler particles; spatial distribution of filler in the polymer matrix; polymer-filler interaction;

14 Influence of shape of conductive particles and their distribution on the percolation threshold 14 log σ log σ log σ ϕ c = 0.16 ϕ c << 0.16 ϕ c < 0.16 ϕ ϕ ϕ Statistical distribution of the sperical particles, theoretical value of percolation threshold, ϕ c = 0.16 Statistical distribution of the anisotropic particles with l/d > 1, low value of percolation threshold, ϕ c < 0.16 or ϕ c << 0.16 Ordered distribution of the particles, creation of the regular skeleton structure, low value of percolation threshold, ϕ c < 0.16 The shape and spatial distribution of the filler particles are very important for the value of percolation threshold.

15 15 What parameter can take into accout the shape and spatial distribution of the filler particles? It is the packing-factor F.

16 What is the packing-factor of filler? 16 The packing-factor of filler F is one of the most important characteristics of the fillers and filled polymer composites. The F parameter means a limit of system filling and is equal to the highest possible filler volume content: F = V f V f + V p V f volume occupied by the filler particles; V p volume occupied by the polymer (space among filler particles). For statistically packed monodispersed spherical particles of any size, F s = 0.64 The value of F depends on: monodispersed particles particles shape, l/d > 1 fraction composition formation of the skeleton structure opal in epoxy resin V f V p F s = 0.64 F < F s F > F s F < F s F = 0.60

17 Experimental measurements of the value of packing-factor Vibrational compression method Ye.P.Mamunya, V.V.Davydenko, P.Pissis, E.V.Lebedev. Europ. Polym. J., 38 (2002) Ye.P.Mamunya, V.F.Shumskii, E.V.Lebedev. Polym. Sci., 36B (1994) Rheological method 17 F P = ρ V η η p 1.25 ϕ = 1 + F ϕ 2 f For the portion of powder: P weight V volume ρ density η is viscosity of composite η p is viscosity of polymer ϕ is volume fraction of filler F is value of packing-factor For monodispersed spherical particles F = In any system the volume occupated by filler can not 0 be higher than 64 %. 0,00 0,05 0,10 0,15 0,20 η/η p η c /η p PP+CB, F= PE+CB, F=0.28 ϕ Filler content, ϕ 1 2

18 Influence of aspect ration l/d on the value of packing-factor F D.M.Bigg. Advanc. Polym. Sci., 119 (1995) Ye.P.Mamunya, V.D.Myshak, E.V.Lebedev. Compos. Polym. Mater., 20/1 (1998) F l / d Computer simulation gives the graphical form of relationship between ratio l/d and value of packing-factor F for the anisotropic filler. This relation can be presented in analytical form by empiric equation: F 5 = l / d + l / d In turn, the value of F is joined with value of percolation threshold ϕ c

19 Correlation between values of packing factor F and percolation thrshold ϕ c 19 log lg ϕ c c * -0,5-1,0-1,5-2,0-2,5 ϕ c = X c F ϕ c X c F theoretical value 6-7 dispersed metals 8-9 carbon black ,0-2,0-1,5-1,0-0,5 0,0 log lg F carbon fibers with l / d = 20 for for for for for for 15 Ye.P.Mamunya, V.V.Davydenko, E.V.Lebedev. Doklady AN USSR., 5B (1991) Ye.P.Mamunya, V.V.Davydenko, P.Pissis, E.V.Lebedev. Europ. Polym. J., 38 (2002) If to measure or to calculate the value of F, possible to predict the value of ϕ c of composite with any shape of particles because the value of ϕ c is defined by values of F. Critical parameter Xc is constant in the case of lack of interaction between conductive and nonconductive phases in the polymer composite. Packing-factor F is key parameter of filled composites

20 Relationship between packing-factor F and parameters of conductive lattices 20 A.L.Efros. Physics and geometry of disorder. Moscow: Nauka, This relation exists for all types of lattices conductivity nonconductive conductive percolation threshold, ϕ c ϕ c =0.16 conductive volume, ϕ ϕ c = X c F For any type of lattice the values X c and F are changed such a way that the value ϕ c is constant and equal ϕ c = 0.16 : ϕ X c c F Type of lattice: cubic centered cubic diamond

21 Influence of the packing-factor F values on physical-mechanical properties of PWC 21 Model system: composite of polymer/wood = 60/40 Ye.Mamunya, M.Zanoaga, V.Myshak, F.Tanasa, E.Lebedev, C.Grigoras, V.Semynog. J. Appl. Polym. Sci. 101 (2006) Wood particles size, L, mm F σ t, MPa ΔW, % ΔS, % M, g m 0, particles mixture F F 0, ,2 0.2 If to use the wood filler with higher value of F (0.71 versus ), the sharp increase of the composite properties takes place. What is a reason of characteristics improvement? 0, L, L, mm F 1 > F 2 R F = L 3 1 ϕ R is a distance between particles; L is a size of particles; ϕ is volume filler content in composite ϕ 1 = ϕ 2 The increase of F value determines the increase of R value, i.e. the polymer layers between wood particles become thicker, which is equivalent to the decrease of wood content.

22 How to take into account the packing-factor F and other parameters of composites? 22 Well-know equation joins the values of conductivity σ, volume fraction of filler ϕ and value of percolation threshold ϕ c : σ = σ 0 (ϕ - ϕ c ) t Ye.P.Mamunya, V.V.Davydenko, E.V.Lebedev. Polym. Compos., 16 (1995) Ye.Mamunya, Yu.Musychenko, P.Pissis, E.V.Lebedev, M.Shut. Polym. Eng. Sci, 42 (2002) The generalized equation can be obtained by introducing the parameters of conductivity into eq. 1 σ 0 is parameter of conductivity; t is critical exponent, t = σ m σ σ σ m c σ c = ϕ ϕ c F ϕ c t Conductivity, log σ σ c σ p σ = σ c + ( σ σ ) m c ϕ ϕ c F ϕ c t ϕ c Filler volume fraction, ϕ F

23 Correlations between parameters l/d, F and ϕ c in the real fillers 23 Filler l /d F ϕ c Ideal spheres Dispersed metals Carbon black Carbon fibers Carbon nanotubes The lowest values of percolation threshold and packing factor exist for the carbon nanotubes because of their highest value of l/d. 50 μm 50 μm 100 μm 80 μm 70 μm 3 nm 100 nm 500 nm 45 μm

24 Spatial distribution of filler in the polymer matrix 24 It is possible to create the skeleton structure of filler in the volume of polymer matrix. The real local concentration of particles into skeleton (ϕ loc ) is much higher than the average concentration (ϕ) related to the whole volume of composite, ϕ loc >> ϕ. Skeleton structure can be arranged by technological methods in two ways: compacting of powder-powder mixtures; using the polymer blends as the composite matrix. skeleton structure of filler (segregated structure)

25 Creation of segregated structure by compacting method 25 d D polymer particle d filler particle D > d D Ye.P.Mamunya, E.G.Privalko, E.V.Lebedev, V.P.Privalko. Macrom. Sympos. 169 (2001) Ye.P.Mamunya, V.V.Davydenko, H.Zois, L.Apekis, A.A.Snarskii, K.V.Slipchenko. Polym. & Polym. Comp. 10 (2002) Evolution of the skeleton structure with filling powderpowder mixture Temperature of polymer softening hot pressing (compacting) PVC-Ni composites: D=100 μm, d=10 μm

26 26 Geometrical model of segregated structure D Ye.P.Mamunya, V.V.Davydenko, P.Pissis, E.V.Lebedev. Europ. Polym. J., 38 (2002) nd Model in a form of cubic lattice Structural coefficient ϕ = ϕ loc K s = F F s ϕ cs ϕ cc 0,20 0,16 0, For PVC-Ni composites with D/d=10 the model predicts the value of percolation threshold ϕ cs two times lower comparing with ϕ c at random distribution of filler 1 K s nd = 1 1 D Relationship between value of percolation threshold and parameters of model 3 0,08 0,04 0, D/d ϕ cs = ϕ c 1 nd D 3

27 Computer simulated model of segregated structure 27 N.Lebovka, M.Lisunova, Ye.Mamunya, N.Vygornitskii. J. Phys. D: Appl. Phys., 39 (2006) 1-8. R r n=2 A composite was simulated as the lattice containing small conductive particles distributed in the channels between large insulative particles PVC-Cu L ϕcs ( R / r, n) ϕc d = nr R PC-Cu ϕ cs Composites R r R/r n ϕ c teor ϕ c exp R/(r n) PVC-Cu PC-Cu ± ±

28 PVC/CNT and PE/CNT composites with ultralow value of percolation threshold 28 l/2r 1000 D = 100 μm Ye.P.Mamunya, N.I.Lebovka, M.O.Lisunova, E.V.Lebedev, A.Rybak, G.Boiteux. J. Nanostr. Polym. Nanocomp., in print. M.O.Lisunova, Ye.P.Mamunya, N.I.Lebovka, A.V.Melezhyk. Europ. Polym. J. 43 (2007) nm 100 μm MWCNT: l =10-20 μm, 2r = nm, l/2r =1000. log (, S/cm) PVC/CNT 0,000 0,002 0,004 0,006 0,008 Volume fraction, ϕ log (, S/cm) PE/CNT -12 ϕ c = ϕ c = ,001 0,002 0,003 0,004 0,005 Volume fraction, ϕ The model equation ϕ cs 3n = l D 2r d predicts the value of ϕ cs = The real value of ϕ cs is sufficiently higher because of non-ideal distribution of filler

29 What advantages have the composites with anisotropic filler and ordered spatial distribution of particles? 29 Fillers with high aspect ratio l/d (for example, carbon nanotubes with l/d ~1000) enable to reach very low percolation threshold in the composites, hence the composites can be conductive at very low filler content. The change of spatial filler distribution from the random to the ordered distribution, can essentially reduce the percolation threshold for isotropic fillers. It allows to obtain the conductive material with low content of filler and with mechanical and rheological properties close to the pure polymer.

30 Experimental methods of the conductivity measurements on DC D 30 h R v h R v R s d l ρ v = V I πd 4h 2 V I ρ v = V I d l h D 2 D 1 R c ρ < R v R v R c V I ρ = v V I πd 4h 2 2 R s V/I R ρ = s V I π ( D1 + D2 ) ( D D ) 1 2 R c h h

31 C o n c l u s i o n s 31 Combination of conductive filler and non-conductive polymer gives the two-phase system which can be in two states: conductive and non-conductive. Transition between two states takes place at percolation threshold ϕ = ϕ c. Geometric characteristics of filler are very important and enables to regulate the value of percolation threshold and physicalmechanical properties of composites. Change of the spatial distribution of filler is effective method to obtain the conductive composites with low value of percolation threshold. Combination of strongly anisotropic filler and its segregated spatial distribution for composites polymer/mwcnt enables to obtain ultralow percolation threshold.