Open AccessНейросетевой метод прогнозирования образования дефектов на поверхности тонких пленок ITO при механических нагрузках
Author(s) -
Д.А. Кириенко,
О.Я. Березина
Publication year - 2018
Publication title -
pisʹma v žurnal tehničeskoj fiziki
Language(s) - English
Resource type - Journals
eISSN - 1726-7471
pISSN - 0320-0116
DOI - 10.21883/pjtf.2018.09.46069.17207
Subject(s) - materials science , ultimate tensile strength , substrate (aquarium) , bending , composite material , radius , coating , artificial neural network , stress (linguistics) , computer science , artificial intelligence , linguistics , oceanography , philosophy , computer security , geology
A method for determining the number of defects arising under compressive and tensile stress in bended thin transparent conducting coatings on polymer substrates is proposed. This algorithm is based on the use of mathematical methods of artificial neural networks. The network is trained for calculating the average defect density per unit length at the input parameters corresponding to film and substrate sizes, surface resistance of the conducting coating, and bending radius. The application of this method allows one to determine the average defect density with high accuracy.