2013
DOI: 10.1002/pssb.201300033
|View full text |Cite
|
Sign up to set email alerts
|

Charge transport in surfactant‐free single walled carbon nanotube networks

Abstract: Conduction in thin random networks of single‐walled carbon nanotubes (SWNTs) is typically dominated by metallic SWNT segments and limited by variable‐range hopping (VRH) in disordered junction regions. However, in our surfactant‐free networks, we show that in parallel with VRH there is another mode of conduction involving both semiconducting and metallic SWNTs. This second process showing activated behavior makes a substantial contribution to conductance at higher temperatures, with similar activation energies… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

2
17
0

Year Published

2014
2014
2021
2021

Publication Types

Select...
5
2
1

Relationship

0
8

Authors

Journals

citations
Cited by 17 publications
(19 citation statements)
references
References 21 publications
2
17
0
Order By: Relevance
“…3 a). A similar phenomenon was measured in non-separated Buckypapers 45 47 , where the high-temperature factor was interpreted as a characteristic phonon scattering in 1D conductor 11 , 12 or as a result of the concentric expansion of the tubes (radial breathing), which constantly change the distance between tubes and reduce the tunneling probability 41 , 48 . This effect could be also related with the de-doping effect 26 , 37 , but in our case we excluded this by proper annealing before measurement (see Fig.…”
Section: Resultssupporting
confidence: 60%
“…3 a). A similar phenomenon was measured in non-separated Buckypapers 45 47 , where the high-temperature factor was interpreted as a characteristic phonon scattering in 1D conductor 11 , 12 or as a result of the concentric expansion of the tubes (radial breathing), which constantly change the distance between tubes and reduce the tunneling probability 41 , 48 . This effect could be also related with the de-doping effect 26 , 37 , but in our case we excluded this by proper annealing before measurement (see Fig.…”
Section: Resultssupporting
confidence: 60%
“…Among several interesting points to note, we highlight that the parameter G a has negative values. Ravi et al followed the same analysis to explain the temperature-dependent conductance variation for carbon-nanotube networks by including a thermal activation term. , Although the fitting parameters were not available, they assumed three types of parallel conducting pathways along which the dominant conducting mechanisms are VRH, quantum tunneling, and thermal activation. However, we argue that the negative values of G a imply that the medium disordered regions giving the thermal activation term in eq do not form their own separate conducting pathways but are embedded as a constituent in the VRH and/or quantum tunneling pathways.…”
Section: Resultsmentioning
confidence: 99%
“…The availability of Fermi level electronic states can be justified when the SWNT network is formed from a mixture of MT-and SC-SWNTs, only MT-SWNTs, or heavily doped SC-SWNTs, which are capable of providing a finite density of states in the vicinity of the Fermi level. [27][28][29][30]32 In the next two sections, the contributions of residual concentration of MT-SWNTs to the conductance of a predominantly SC-SWNT network and the effect of the doping of SC-SWNTs will be analyzed in order to delineate the nature of the Fermi level electronic states contributing to the weak temperature dependence of conductivity of SC-SWNT networks.…”
Section: Columns 2 and 3 Inmentioning
confidence: 99%
“…The inverse temperature plot (Figure 2d) shows that the low temperature region is associated with very low energy processes of a variable activation energy, E LT = 2−10 meV, similar in magnitude to the weak temperature dependences reported in literature for networks of mixed MT-and SC-SWNTs. [27][28][29][30]32 We tested several models that were reported to describe the electrical transport in SWNT networks. 27−32 Figure 3 presents a fitting of the experimental data using fluctuation induced tunneling (FIT) model, 33,34 2D variable range hopping model (2D-VRH), 35 and Efros and Shklovskii VRH model, denoted as ES-VRH, which takes into account Coulomb interactions.…”
Section: Temperature Dependence Of Conductivitymentioning
confidence: 99%