Open AccessMODELING THE PROPERTIES OF GAS SENSOR MATERIALS BASED ON ORGANIC SEMICONDUCTORS
Author(s) -
С. П. Коноваленко
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.30987/conferencearticle_61c997efbaca58.21140409
Subject(s) - annealing (glass) , semiconductor , materials science , organic semiconductor , nonlinear system , artificial neural network , mass fraction , simulated annealing , semiconductor device modeling , nonlinear regression , biological system , electronic engineering , process engineering , nanotechnology , optoelectronics , regression analysis , computer science , composite material , cmos , engineering , algorithm , artificial intelligence , machine learning , physics , quantum mechanics , biology
An approach has been developed for modeling the gas-sensitive and physicochemical properties of materials based on organic semiconductors. The approach is based on the use of various modeling methods: linear, nonlinear regression analysis and neural networks. The parameters of the technological process of the formation of materials were selected as external signals for modeling: the mass fraction of metal in the film-forming solution, the temperature and time of the first and second stages of annealing.