Abstract
Ga-doped zinc oxide (ZnO:Ga) thin films were prepared on glass substrate by magnetron sputtering at room temperature (RT) and thermally annealed in hydrogen atmosphere for 1 h. The effects of film thickness and annealing temperature on sheet resistance, transmittance and figure of merit of ZnO:Ga thin films were analyzed and modeled using the artificial neural networks (NNets). The NNet models presented the good prediction on sheet resistance, transmittance and figure of merit of ZnO:Ga thin films and it was found that the electrical and optical properties of ZnO:Ga thin films were enhanced by thermal annealing. After NNet models were verified, genetic algorithm (GA) was used to search the optimized recipe for the desired figure of merit of ZnO:Ga thin films. The methodology allows us to estimate the optimal process condition with a small number of experiments.
Sign-in/Register to access full text options 
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 callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
