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Ultra-fast detection of cancerous volatile organic compounds (VOCs) by carbon nanotube aerogel (CNT aerogel)-graphene oxide (GO) hybrid network has been studied in this paper. VOCs, especially non-polar compounds are difficult to detect due to their low electronegativity. A homogenous GO solution was drop cast on CNT aerogel film, both developed in-house, to obtain the CNT aerogel-GO composite. The CNT aerogel contains multi-directional porous CNT webs providing a stable and compact platform for GO adsorption. The loading concentration of GO and O/C ratios were optimized to obtain a highly sensitive CNT aerogel-GO hybrid sensor. The hybrid sensor could detect a range of non-polar VOCs like benzene, hexane, toluene, cyclohexane, and chlorobenzene with a limit of detection around 70 ppb. The optimized CNT aerogel-GO hybrid sensor showed 3 times better sensing performance than the bare CNT aerogel sensor. The principal component analysis (PCA) plot showed discrimination in all the VOCs as they all were distinct and spread over all four quadrants, indicating highly selective behavior of the sensor. Chemical and structural analysis by X-ray photoelectron spectroscopy and Raman spectrum showed that the oxygen loading could change the sp2 structure, making it ideal for sensing applications. The electron micrography images confirm the uniformity of the GO layer on the CNT aerogel. It is concluded that the concomitant formation of the CNT-GO junction can achieve better interaction and charge transfer during hybrid sensor fabrication. Subsequently, a sensitive, fast and durable CNT aerogel-GO hybrid sensor can be obtained for detection and continuous monitoring of cancerous VOCs.

Carbon nanotube fiber (CNT fiber) synthesized through floating catalyst chemical vapor deposition (FC-CVD) is one of the strongest man-made fibers ever synthesized. The poor carbon conversion in the FC-CVD process is one of the major hurdles in its commercial deployment. In this work, we have employed a novel method of bi-directional catalyst injection where catalysts were injected from both inlet and outlet sides of the reactor. The injection of the catalyst from the outlet into the reactor reaction zone was possible by a backflow caused by the convection vortex as predicted by the computational fluid dynamics (CFD) analysis. Bi-directional catalyst injection was able to enhance the carbon conversion by 56% compared to conventional unidirectional injection. CNT fibers obtained in bi-directional catalyst injection are a mixture of multi-walled (MW) and single-walled (SW) CNTs whereas unidirectional catalyst injection resulted in MWCNTs only. The average CNT bundle diameter dimensions were similar in both unidirectional and bi-directional catalyst injection. The amorphous carbon content was lower for bi-directional catalyst injection. A mechanism for the improvement of carbon conversion in bi-direction catalyst injection has been proposed.

Floating-catalyst chemical vapour deposition (FCCVD) is a promising method for large-scale synthesis of single-walled carbon nanotube (SWCNT). The current work focuses on the comprehensive optimization studies with the objective of maximizing the yield and minimizing the diameter of SWCNTs considering the complex dependency and interaction effects between the process parameters. Data-analytics driven process parameter selection criterion was utilized for heat map generation of the eight process parameters. Orthogonal design of experiments encompassing Taguchi L-18 array and subsequent analysis of variance reveals strong interaction effects between the process parameters and demonstrates conflicting nature between the two objectives, yield and diameter of SWCNTs. Pareto optimization was used to capture the conflicting behaviour of the dual objectives in true sense. Artificial neural network (ANN) coupled with Taguchi analysis brings out the interaction effects of process parameters that could predict the output with more than 90% accuracy. The rigorous analysis concludes that the furnace temperature mostly affects the diameter, whereas, methane flow-rate determines the SWCNT yield. The optimum condition for higher SWCNT yield with minimum diameter was obtained at a lower methane and hydrogen flow while keeping furnace temperature and argon flow at the highest level and thiophene at the lowest level.