Abstract
Mossbauer spectroscopy is a useful technique for characterizing the valencies, electronic and magnetic states, coordination symmetries and site occupancies of the cation. The Mossbauer parameters of isomer shift and quadrupole splitting are useful to distinguish paramagnetic ferrous and ferric iron in several substances, while the internal magnetic field provides information on the crystallinity. In recent years artificial neural networks have shown to be a powerful technique to solve problems of pattern recognition of a mineral from its Mossbauer spectrum, Mossbauer parameters data bank, crystalline structure and magnetic phases of soil from Mossbauer parameters. A computer software named Mossbauer Effect Assistant has been developed. It uses learning vector quantization neural network linked to a Mossbauer data bank that contains Mossbauer parameters of isomer shift, quadrupole spliting, internal magnetic field and the references of the substances. The program identifies the substance under study and/or its crystalline structure when fed with experimental Mossbauer parameters. It can also list the references from the literature by feeding the name of the substance or the author of the publication. Typical application of Mossbauer Effect Assistant in iron-bearing materials Mossbauer spectroscopy is present in user friendly Microsoft Windows environment.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call