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  4. Tunable Low Crystallinity Carbon Nanotubes/Silicon Schottky Junction Arrays And Their Potential Application For Gas Sensing
 
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Tunable Low Crystallinity Carbon Nanotubes/Silicon Schottky Junction Arrays And Their Potential Application For Gas Sensing

Journal
Nanomaterials
Date Issued
2021-11-12
Author(s)
Alvaro R. Adrian
Daniel Cerda
Leunam Fernández-Izquierdo
Segura, Rodrigo  
Facultad de Ciencias  
José Antonio García-Merino
Samuel A. Hevia
DOI
10.3390/nano11113040
WoS ID
WOS:000727702500001
Abstract
Highly ordered nanostructure arrays have attracted wide attention due to their wide range of applicability, particularly in fabricating devices containing scalable and controllable junctions. In this work, highly ordered carbon nanotube (CNT) arrays grown directly on Si substrates were fabricated, and their electronic transport properties as a function of wall thickness were explored. The CNTs were synthesized by chemical vapor deposition inside porous alumina membranes, previously fabricated on n-type Si substrates. The morphology of the CNTs, controlled by the synthesis parameters, was characterized by electron microscopies and Raman spectroscopy, revealing that CNTs exhibit low crystallinity (LC). A study of conductance as a function of temperature indicated that the dominant electric transport mechanism is the 3D variable range hopping. The electrical transport explored by I–V curves was approached by an equivalent circuit based on a Schottky diode and resistances related to the morphology of the nanotubes. These junction arrays can be applied in several fields, particularly in this work we explored their performance in gas sensing mode and found a fast and reliable resistive response at room temperature in devices containing LC-CNTs with wall thickness between 0.4 nm and 1.1 nm.
Subjects

Chemistry, Multidisci...

Chemical Engineering

Materials Science, Mu...

Materials Science

Nanoscience And Nanot...

Physics, Applied

OCDE Subjects

Engineering And Techn...

Quartile (Date Issued)
SQ
License
acceso abierto
Open Science Path
https://creativecommons.org/licenses/by/4.0/

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