Nanoassemblies of sulfonated polyaniline multilayers - ARPAL

Table 1. Electrochemical parameters of PDDA/SPANI films.
Diffusion
Oxidation Reduction coefficients D 0
Acidic media potential (mV) potential (mV) Slope in cm 2 s −1
HCl 664.2, 455.3, 179.3 664.2, 455.3, 179.3 5.53 1.2 × 10 −8
H 2 SO 4 630, 228.1 563.6, 89.3 5.125 0.92 × 10 −8
CH 3 COOH 381.9, 124 328.6, 15.45, 2.7 4.061 0.75 × 10 −9
Nanoassemblies of sulfonated polyaniline multilayers
Table 2. CV of 15 bilayers of PDDA/SPANI films.
After number of cycles Oxidation potential (mV) Reduction potential (mV)
2nd 689.7, 161.3 588.3, 8.33
2 × 10 2 677.9, 494.9, 186.9 565.1, 17.66
10 3 438.5, 315 359.2, 162.5
10 4 369.9, 28.09 334.5, 133.5
10 5 414.0 87.8, −37.24
10 6 246.4 −32.67
polymer were monitored by UV–visible spectroscopy. The
linear variation in the PDDA/SPANI revealed a uniform
deposition process, whereas the SPANI used as polyanion and
polycation did not give a uniform film because the dipping
solution was found to change the structure of polyanion
or polycation SPANI. The nucleation and growth of the
deposited films were investigated by AFM, showing a surface
topology of PDDA/SPANI bilayers films covering particle
size varying from 30 to 62.5 nm in diameter. The distribution
of the grain size decreases with increase in the number
of bilayers which is contrary to the results of Langmuir–
Blodgett or LBL films of PANI. The redox processes in
CH 3 COOH medium are slower than in H 2 SO 4 or HCl media.
The weak acid takes longer diffusion time in the SPANI
films. The diffusion coefficient (D 0 ) was calculated to
be 1.2 × 10 −8 cm 2 s −1 . Typical multilayer films reveal
a conductivity range from 10 −3 to 0.75 × 10 −9 Scm −1 .
This investigation allowed us to fabricate thin films of
SPANI in a controlled way and we look forward to use
such a structure in photovoltaic and light-emitting diode
devices. We are also investigating the structural properties of
bilayer PDDA/SPANI LBL films to address the technological
application of conjugated polymers.
Acknowledgments
We are grateful to M Panza for his help in carrying out the experiments.
Financial support from Fondazione Elba (Chapter
2102 of Ministry of Universities and Research of Italy) and a
Murst-PST contract on Neural Net Work with Polo Nazionale
Bioelettronica is gratefully acknowledged. This paper was
presented as a poster in the Elba Foresight Conference on
Nanotechnology in Rome on April 14–17, 1999.
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