详细信息
化学气相沉积法制备纳米炭纤维块体 ( SCI-EXPANDED收录 EI收录)
Synthesis of carbon nanofiber monoliths by chemical vapor deposition
文献类型:期刊文献
中文题名:化学气相沉积法制备纳米炭纤维块体
英文题名:Synthesis of carbon nanofiber monoliths by chemical vapor deposition
作者:葛翔[1];吴晓龙[1];王际童[1];龙东辉[1];乔文明[1,2];凌立成[1]
机构:[1]华东理工大学,化学工程联合国家重点实验室,上海200237;[2]超细粉末国家工程研究中心,上海200231
年份:2015
卷号:30
期号:1
起止页码:54
中文期刊名:新型炭材料
外文期刊名:New Carbon Materials
收录:CSTPCD;;EI(收录号:20151900817762);Scopus;WOS:【SCI-EXPANDED(收录号:WOS:000350616000007)】;北大核心:【北大核心2014】;CSCD:【CSCD2015_2016】;
基金:Foundation item: National Natural Science Foundation of China (20977028, 51172071, 51272077); National Key Basic Research Program of China (2014CB239702); Fundamental Research Founds for the Central University; Program of Shanghai Subject Chief Scientist (B type, 13XD1424900)
语种:中文
中文关键词:纳米炭纤维;Cu-Ni催化剂;化学气相沉积;机械性能
外文关键词:Carbon nanofiber; Copper-nickel catalyst; CVD; Mechanical properties
摘要:以乙烯为碳源、无负载型铜镍(Cu-Ni)合金为催化剂,采用催化化学气相沉积法(CVD),制备出性能优异的纳米炭纤维(CNF)块体,并考察制备条件对CNF块体的形貌、机械性能及比表面积的影响。结果表明,CNF块体的成形主要依赖于催化剂Cu-Ni的组成、生长温度及生长时间等因素。当Cu-Ni质量比为2∶8、生长温度为580℃时,经3 h制备的CNF块体,其密度、压缩弹性模量、比表面积分别达到0.28g/cm3、1.7KPa和117m2/g。CNF生长初始阶段的形貌观察表明,章鱼状粗纤维和细纤维交织成的三维网络结构是块体成形的主要原因。
Carbon nanofiber(CNF) monoliths with excellent properties were prepared by catalytic chemical vapor deposition,using ethylene(C2H4) and a non-supported Cu-Ni alloy as carbon source and catalyst,respectively.The structure,mechanical properties,and specific surface area of the CNF monoliths were characterized for various preparation conditions.The formation of CNF monoliths mainly depended on the Cu/Ni ratio,growth temperature and time.A CNF monolith synthesized at 580℃ for 3 h from a Cu-Ni catalyst with a Cu/Ni mass ratio of 0.25 exhibited a bulk density of 0.28 g/cm^3,a compressive elastic modulus of1.7 kPa,and a specific surface area of 117 m^2/g.SEM images of the CNF monoliths in the initial growth stage further indicated that they were composed of thick octopus-like nanofibers and thin nanofibers that were interwoven with each other to form a three dimensional CNF network and finally the CNF monolith.
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