QUALITATIVE ORGANIC ELECTROANALYSIS USING COMPUTERIZED PATTERN RECOGNITION

This thesis describes how structural information can be obtained from organic electrochemical data using computerized pattern recognition. The pattern recognition technique was also used to search for a relationship between the electrochemical and herbicidal activity of nitrodiphenylethers. The introduction discusses the principles of pattern recognition and also explains some of the problems associated with qualitative electrochemical analysis. The methods of analysis and the results obtained in this study are placed in perspective with earlier work. Part one describes the instrumentation and experimental methods which were used to generate an electrochemical data base suitable for pattern recognition. Part two discusses the pattern recognition process and improvements which were made in the process to facilitate structural elucidation. Part three reports the pattern recognition analysis of nitrodiphenylethers, nitroaromatics and azo compounds. The compounds studied could be identified according to structural class with a classification accuracy of over 90% using features derived from either capacitive or Faradaic electrochemical responses.