浮动催化剂化学气相沉积无氢流的碳纳米管纤维的开放气氛纺丝:对机理的洞察

IF 5.5 3区 材料科学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Rajath Alexander, Amit Kaushal, Jaspreet Singh, Kinshuk Dasgupta
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引用次数: 0

摘要

本研究介绍了一种在开放气氛下不需要氢气作为载气的情况下,利用浮式催化剂化学气相沉积(FC-CVD)合成碳纳米管(CNT)纤维的新方法。传统的FC-CVD技术依赖于氢气,并且需要一个带有惰性气体净化的收获箱,这限制了可扩展性。我们的方法利用氮气作为唯一的载体,允许碳纳米管纤维生产没有收获箱。为了了解在开放气氛下的旋转过程机理,我们进行了热力学和计算流体动力学(CFD)分析。根据热力学计算选择甲醇作为碳源,结果表明,在高温下,甲醇生成CO和H2作为热力学稳定的物质,而不是碳(C),从而防止了烟灰的形成。此外,甲醇只在催化剂存在的情况下进行催化裂化,进一步防止了烟灰的形成。这种方法允许在高分压下运行,甚至高于爆炸上限(UEL),有效防止燃烧。反应器内设置了一个600毫米的冷却区,将出口气体温度降低到甲醇的自燃点以下,降低了燃烧风险。采用CFD计算确定所需的冷却区长度。此外,我们利用XGBoost机器学习方法开发了预测模型,有效地映射了碳纳米管纤维纺丝的参数空间,准确率达到95.24%。所得碳纳米管纤维具有高导电性(240±24 S/cm)和低ID/IG比,表明结晶度高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Open-atmosphere spinning of carbon nanotube fibers sans hydrogen flow by floating catalyst chemical vapor deposition: an insight into the mechanism

This study introduces a novel method for synthesizing carbon nanotube (CNT) fibers using floating catalyst chemical vapor deposition (FC-CVD) in an open-atmosphere without the need for hydrogen as a carrier gas. Traditional FC-CVD techniques depend on hydrogen gas and require a harvest box with inert gas purging, which restricts scalability. Our approach utilizes nitrogen gas as the sole carrier, allowing for CNT fiber production without a harvest box. To understand the spinning process mechanism in an open-atmosphere, we conducted thermodynamic and computational fluid dynamics (CFD) analyses. Methanol was selected as the carbon source based on thermodynamic calculations, which revealed that at high temperatures, methanol forms CO and H2 as thermodynamically stable species instead of carbon (C), thereby preventing soot formation. Moreover, methanol undergoes catalytic cracking exclusively in the presence of catalysts, further preventing soot formation. This approach allows operation at high partial pressure, even above the upper explosive limit (UEL), effectively preventing combustion. A 600 mm cooling zone was incorporated into the reactor to lower the outlet gas temperature below methanol's auto-ignition point, mitigating combustion risks. CFD calculations were employed to determine the necessary cooling zone length. Additionally, we developed a predictive model using the XGBoost machine learning method to efficiently map the parameter space for CNT fiber spinning, achieving an accuracy of 95.24%. The resulting CNT fibers demonstrate high electrical conductivity (240 ± 24 S/cm) and a low ID/IG ratio, indicating a high degree of crystallinity.

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来源期刊
Carbon Letters
Carbon Letters CHEMISTRY, MULTIDISCIPLINARY-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
7.30
自引率
20.00%
发文量
118
期刊介绍: Carbon Letters aims to be a comprehensive journal with complete coverage of carbon materials and carbon-rich molecules. These materials range from, but are not limited to, diamond and graphite through chars, semicokes, mesophase substances, carbon fibers, carbon nanotubes, graphenes, carbon blacks, activated carbons, pyrolytic carbons, glass-like carbons, etc. Papers on the secondary production of new carbon and composite materials from the above mentioned various carbons are within the scope of the journal. Papers on organic substances, including coals, will be considered only if the research has close relation to the resulting carbon materials. Carbon Letters also seeks to keep abreast of new developments in their specialist fields and to unite in finding alternative energy solutions to current issues such as the greenhouse effect and the depletion of the ozone layer. The renewable energy basics, energy storage and conversion, solar energy, wind energy, water energy, nuclear energy, biomass energy, hydrogen production technology, and other clean energy technologies are also within the scope of the journal. Carbon Letters invites original reports of fundamental research in all branches of the theory and practice of carbon science and technology.
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