Tracking of Dual Gas Concentration Using Carbon Nanotubes Based Reservoir Computing
Yan Zhuang, Wenli Zhou, Chengzhu Li, Zhoujun Sheng, Yuyao Wang, Angdi Li, Mengbo Qi, Yuyang Duan · 2024
Reservoir computing (RC) has the advantages of fast learning and low training cost, as only the readout weights need training. Furthermore, it is suitable for multi-task processing or continuous learning as there could be no interferences between tasks. In this paper, we prepared a carbon nanotubes (CNTs)/PBMA reservoir modified with phosphomolybdic acid molecules (POM). The dynamical tracking of dual gas concentration in the environment was carried out by our lab-made RC experimental platform with the CNT reservoir under atmosphere. Through grid search of several RC parameters in this implementation, we obtained the optimized minimum tracking accuracy of less than 1 ppm for NH3and NO2when they were randomly mixed under a closed measurement environment or an open environment. This demonstrates a very promising potential of the POM/CNT/PBMA reservoir to perform near/in gas sensor computing.