journal article·2023-02-09

Statistical analysis of the synthesis of carbon nanotubes using wet-impregnated catalysts for improved robustness

Hyeongyun Song, Dong Hwan Kim, Cheol Woo Park, Jungho Jae, Seungki Hong, Jaegeun Lee

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Abstract

Mass production of high-quality carbon nanotubes (CNTs) remains a challenge, requiring the development of new wet-impregnated catalyst suitable for the catalytic chemical vapor deposition (CCVD) of CNTs in a fluidized bed reactor. For the successful development of a new catalyst, a highly robust system to synthesize CNTs must be established. Here, we systematically investigated the robustness of CNT synthesis by CCVD using a wet-impregnated catalyst. We statistically tested four factors that could potentially affect the robustness of CNT synthesis system, focusing on carbon yield and IG/ID. First, we tested the effect of vacuum baking before CNT growth. F test and CV equality test concluded that vacuum baking recipe did not significantly reduce the variability of the CNT synthesis. Second, we tested the batch-to-batch variation of catalysts. The results of t test and one-way analysis of variance indicate that there is significant difference in carbon yield and IG/ID among catalysts from different batches. Third, we confirmed that there is spatial non-uniformity of wet-impregnated catalysts within a batch when they are produced in large scale. Finally, we developed a multi-step heating recipe to mitigate the temperature overshooting during the CNT synthesis. The multi-step recipe increased the mean of carbon yield, but did not influence the variability of CNT synthesis. We believe that our research can contribute to the establishment of a robust CNT synthesis system and development of new wet-impregnated catalysts.
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Research context

OpenAlex topics: Carbon Nanotubes in Composites · Graphene research and applications · Advancements in Battery Materials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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