Artificial neural network for predictive synthesis of single-walled carbon nanotubes by aerosol CVD method
No Thumbnail Available
Access rights
openAccess
URL
Journal Title
Journal ISSN
Volume Title
Letter
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
Date
2019-11-01
Department
Major/Subject
Mcode
Degree programme
Language
en
Pages
4
100-103
100-103
Series
Carbon, Volume 153
Abstract
We propose to use artificial neural networks to process the experimental data and to predict the performance of the aerosol CVD synthesis of single-walled carbon nanotubes based on Boudouard reaction. We employ five key input parameters of the growth (pressures of CO, CO2 and ferrocene as well as the residence time and the growth temperature) to control the performance of produced nanotube films (yield, mean and standard deviation of the diameter distribution, and defectiveness). The prediction errors were found to be comparable with the corresponding experimental errors. We believe the proposed approach is of great interest for the synthesis of nanocarbons with tailored characteristics.Description
Keywords
Other note
Citation
Iakovlev, V Y, Krasnikov, D V, Khabushev, E M, Kolodiazhnaia, J V & Nasibulin, A G 2019, ' Artificial neural network for predictive synthesis of single-walled carbon nanotubes by aerosol CVD method ', Carbon, vol. 153, pp. 100-103 . https://doi.org/10.1016/j.carbon.2019.07.013