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We report on optimizing the catalytic chemical vapor deposition synthesis of multiwall carbon nanotubes (MWCNTs) from ethene over supported transition metal SiO 2 nanocomposite aerogels using the statistical design of experiments (DOE) approach. DOE allowed us to test 19 different catalysts in a total of 49 reactions instead of testing 27 catalysts in 729 runs as required by a three-level full factorial design. Both catalyst-related and process-related variables were optimized; in particular varied parameters were Fe þ Co loading, Fe/Co ratio, Ni loading, C 2 H 4 flow rate, temperature, and duration of the reaction. The results of the optimization indicate that a good catalyst should contain a high overall loading (10 wt %) of iron and cobalt in similar amount, should be free of nickel and should be operated at a relatively low temperature (650-700 °C) at high carbon source space velocity for optimum performance. The uniqueness of this work is that we demonstrated that catalyst-related and process-related variables can be optimized simultaneously in the DOE of MWCNT synthesis.

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