Back close

Development of High-Performance Polyamides from Renewable Natural Source

Start Date: Friday, Oct 01,2004

School: School of Engineering, Coimbatore

Project Incharge:Dr. Bhagawan S. S.
Project Incharge:Dr. S.S. Bhagawan Dr. K. Ajitha
Funded by:GoI
Development of High-Performance Polyamides from Renewable Natural Source

The  project  envisages  development  of  novel  polymers  based  on cardanol,  a  constituent  of  a  natural  product,  viz.cashewnut  shell liquid.  Polyamides  using  diamine  have  been  synthesized  and characterized.   The   various   steps   included   preparation   of nitrocompound  NDMT  [2-nitro-dimethyl  terephthalate]  followed  by coupling  reaction  with  potassium  salt  of  cardanol  leading  to  2-(3- pentadecyl)  phenoxy  dimethyl  terephthalate  /  2-(3-pentadecyl) phenoxy  1,4  dimethylbenzene;  Hydrolysis  of  this  compound  by ethanolic  KOH  to  produce  2-(3-pentadecyl)  phenoxy  benzene  1,  4  – dicarboxylic  acid.      The  polyamide  was  finally  obtained  by  solution polymerization  technique  using  m-phenylene  diamine  [MPDA]  and 2-(3-pentadecyl)  phenoxy  benzene  1,  4  dicarboxylic  acid.    The intermediate  products  and  polyamide  were  characterized.

Related Projects

Measurement of Burning Velocities of Hydrocarbon Hydrogen Mixtures and Application to Premixed Laminar Burner Design
Measurement of Burning Velocities of Hydrocarbon Hydrogen Mixtures and Application to Premixed Laminar Burner Design
Development of Surface-Modified Carbon Steel by employing Advanced Surface Engineering Technique
Development of Surface-Modified Carbon Steel by employing Advanced Surface Engineering Technique
Study of Heat Transfer Characteristics of Nanofluids as Coolants for Automotive Application
Study of Heat Transfer Characteristics of Nanofluids as Coolants for Automotive Application
Synthesis and Characterization of Functionally Graded Copper Metal Matrix Composites
Synthesis and Characterization of Functionally Graded Copper Metal Matrix Composites
Deep Learning of Generic Features for Vision
Deep Learning of Generic Features for Vision
Admissions Apply Now