Classification of ecstasy tablets using trace metal analysis with the application of chemometric procedures and artificial neural network algorithms

Waddell, R.J.H. and Nic Daeid, N. and Littlejohn, D. (2004) Classification of ecstasy tablets using trace metal analysis with the application of chemometric procedures and artificial neural network algorithms. Analyst, 129. pp. 235-240. ISSN 0003-2654 (https://doi.org/10.1039/b312336g)

Abstract

This work is concerned with an investigation into the practicalities of using ICP-MS data obtained from the analysis of ecstasy tablets to provide linkage information from seizure to seizure. The generated data was analysed using different statistical techniques, namely principal component analysis, Hierarchical clustering and artificial neural networks. The relative merits of these different techniques are discussed.

ORCID iDs

Littlejohn, D. ORCID: https://orcid.org/0000-0002-1555-9427

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• Item metadata

  Item type:	Article
  ID code:	38265
  Dates:	Date Event 2004 Published
  Keywords:	ICP-MS, ecstacy, seizure, principal component analysis, Hierarchical clustering, Chemistry, Biochemistry, Spectroscopy, Environmental Chemistry, Analytical Chemistry, Electrochemistry
  Subjects:	Science > Chemistry
  Department:	Faculty of Science > Pure and Applied Chemistry
  Depositing user:	Pure Administrator
  Date deposited:	07 Mar 2012 11:47
  Last modified:	19 May 2023 01:21
  URI:	https://strathprints.strath.ac.uk/id/eprint/38265