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Adaptive Neuro-Fuzzy Modeling of Mechanical Behavior for Vertically Aligned Carbon Nanotube Turfs 被引量:1
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作者 Mohammad Al-Khedher charles pezeshki +1 位作者 Jeanne McHale Fritz Knorr 《Journal of Materials Science & Technology》 SCIE EI CAS CSCD 2011年第4期301-308,共8页
Several characterization methods have been developed to investigate the mechanical and structural properties of vertically aligned carbon nanotubes (VACNTs). Establishing analytical models at nanoscale to interpret ... Several characterization methods have been developed to investigate the mechanical and structural properties of vertically aligned carbon nanotubes (VACNTs). Establishing analytical models at nanoscale to interpret these properties is complicated due to the nonuniformity and irregularity in quality of as-grown samples. In this paper, we propose a new methodology to investigate the correlation between indentation resistance of multi-wall carbon nanotube (MWCNT) turfs, Raman spectra and the geometrical properties of the turf structure using adaptive neuro-fuzzy phenomenological modeling. This methodology yields a novel approach for modeling at the nanoscale by evaluating the effect of structural morphologies on nanomaterial properties using Raman spectroscopy. 展开更多
关键词 Adaptive neuro-fuzzy Carbon nanotubes Image analysis NANOINDENTATION Raman spectroscopy
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