Abstract
The distributions of atomic and molecular ions of 12 different masses were measured by imaging SIMS at low mass resolution. Due to mass interferences, visual interpretation of the chemical phases represented in the different distributions is not possible. These single phases were extracted by classification using a Kohonen network. To demonstrate this technique, the behavior of the Kohonen map is compared with manual classification. For determination of the optimal dimension of the network (the number of nodes should be equal to the number of expected classes), and to reduce the artifacts due to noise and nonlinearities, principal component analysis was performed. Alternatively, the number of necessary classes can be determined by a second classification of the nodes of a Kohonen network that is sufficiently large with the help of dendrograms.
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