Prediction of the functional properties of ceramic materials from composition using artificial neural networks

• Published in: Journal of the European Ceramic Society Vol. 27; no. 16; pp. 4425 - 4435
• Main Authors: Scott, D.J., Coveney, P.V., Kilner, J.A., Rossiny, J.C.H., Alford, N.Mc N.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 2007; Elsevier
• Subjects: Applied sciences; Building materials. Ceramics. Glasses; Ceramic industries; Chemical industry and chemicals; Dielectric properties; Electrotechnical and electronic ceramics; Exact sciences and technology; Functional applications; General studies; Ionic conductivity; Neural networks; Perovskites; Technical ceramics; Perovskites; Neural networks; Dielectric properties; Functional applications; Ionic conductivity; Perovskite type compound; Electrical properties; Prediction; Theoretical study; Neural network; Technical ceramics; Advanced technology; Electroceramics

We describe the development of artificial neural networks (ANN) for the prediction of the properties of ceramic materials. The ceramics studied here include polycrystalline, inorganic, non-metallic materials and are investigated on the basis of their dielectric and ionic properties. Dielectric mater...