Powder diffraction indexing as a pattern recognition problem: A new approach for unit cell determination based on an artificial neural network
Habershon, Scott, Cheung, E. Y., Harris, K. D. M. and Johnston, R. L.. (2004) Powder diffraction indexing as a pattern recognition problem: A new approach for unit cell determination based on an artificial neural network. The Journal of Physical Chemistry Part A: Molecules, Spectroscopy, Kinetics, Environment and General Theory, Vol. 108 (No. 5). p. 711. ISSN 1520-5215Full text not available from this repository.
Official URL: http://dx.doi.org/10.1021/jp0310596
An artificial neural network, in combination with local optimization, is shown to be an effective approach for determining unit cell parameters directly from powder diffraction data. The viability of this new approach is initially demonstrated using simulated powder diffraction data. Subsequently, the successful application of the method to determine unit cell parameters is illustrated for two materials using experimental powder X-ray diffraction data recorded on a standard laboratory diffractometer.
|Item Type:||Journal Article|
|Divisions:||Faculty of Science > Chemistry|
|Journal or Publication Title:||The Journal of Physical Chemistry Part A: Molecules, Spectroscopy, Kinetics, Environment and General Theory|
|Publisher:||American Chemical Society|
|Page Range:||p. 711|
|Access rights to Published version:||Restricted or Subscription Access|
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