Artificial neural network for predictive synthesis of single-walled carbon nanotubes by aerosol CVD method

被引：41
|
作者：
Iakovlev, Vsevolod Ya [1 ]
Krasnikov, Dmitry V. [1 ]
Khabushev, Eldar M. [1 ]
Kolodiazhnaia, Julia V. [1 ]
Nasibulin, Albert G. [1 ]
机构：
[1] Skolkovo Inst Sci & Technol, Nobel Str 3, Moscow 121205, Russia
来源：
CARBON | 2019年 / 153卷
基金：
俄罗斯科学基金会;
关键词：
GROWTH;
D O I：
10.1016/j.carbon.2019.07.013
中图分类号：
O64 [物理化学（理论化学）、化学物理学];
学科分类号：
070304 ; 081704 ;
摘要：
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. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码：100 / 103
页数：4
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