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Research Papers

Ab Initio Study of Iodine-Doped Carbon Nanotube Conductors

[+] Author and Article Information
Yangchuan Li

Department of Mechanical Engineering,
University of Texas,
Austin, TX 78712
e-mail: liyangchuan@utmail.utexas.edu

Eric Fahrenthold

Department of Mechanical Engineering,
University of Texas,
Austin, TX 78712
e-mail: epfahren@mail.utexas.edu

Contributed by the Materials Division of ASME for publication in the JOURNAL OF ENGINEERING MATERIALS AND TECHNOLOGY. Manuscript received May 8, 2017; final manuscript received December 13, 2017; published online January 19, 2018. Assoc. Editor: Peter W. Chung.

J. Eng. Mater. Technol 140(2), 021008 (Jan 19, 2018) (9 pages) Paper No: MATS-17-1132; doi: 10.1115/1.4038780 History: Received May 08, 2017; Revised December 13, 2017

The widespread use of copper in power and data cabling for aircraft, ships, and ground vehicles imposes significant mass penalties and limits cable ampacity. Experimental research has suggested that iodine-doped carbon nanotubes (CNTs) can serve as energy efficient replacements for copper in mass sensitive cabling applications. The high computational costs of ab initio modeling have limited complimentary modeling research on the development of high specific conductance materials. In recent research, the authors have applied two modeling assumptions, single zeta basis sets and approximate geometric models of the CNT junction structures, to allow an order of magnitude increase in the atom count used to model iodine-doped CNT conductors. This permits the ab initio study of dopant concentration and dopant distribution effects, and the development of a fully quantum based nanowire model which may be compared directly with the results of macroscale experiments. The accuracy of the modeling assumptions is supported by comparisons of ballistic conductance calculations with known quantum solutions and by comparison of the nanowire performance predictions with published experimental data. The validated formulation offers important insights on dopant distribution effects and conduction mechanisms not amenable to direct experimental measurement.

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Figures

Grahic Jump Location
Fig. 1

CNT(5,5) models: aligned 0.7/u.c. (left), aligned 1.0/u.c. (center), and random 2.3/u.c. (right) doping

Grahic Jump Location
Fig. 2

Conductance of the metallic CNT models

Grahic Jump Location
Fig. 3

CNTs (8,0) models: aligned 1.0/u.c. (left), aligned 1.5/u.c. (middle), and random 4.9/u.c. (right) doping

Grahic Jump Location
Fig. 4

Conductance of the semiconducting CNT models

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Fig. 5

Doped metallic CNT(5,5): 1.3/u.c. (left) and 2.0/u.c. (right)

Grahic Jump Location
Fig. 6

Conductance of the interstitially doped dual CNT(5,5) models

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Fig. 10

Conductance of a metallic CNT(5,5) junction

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Fig. 11

Doped CNT(8,0) junction: overlaps of 0.7 unit cells (left) and 4.7 unit cells (right)

Grahic Jump Location
Fig. 12

Conductance of a semiconducting CNT(8,0) junction

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Fig. 13

Transmission line model

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Fig. 7

Doped CNT(8,0): 2.0/u.c. (left), and 3.0/u.c. (right)

Grahic Jump Location
Fig. 8

Conductance of the interstitially doped dual CNT(8,0) models

Grahic Jump Location
Fig. 9

Doped CNT(5,5) junction: overlaps of 2 unit cells (left) and 10 unit cells (right)

Grahic Jump Location
Fig. 14

Performance of the polyiodide-doped CNT nanowires (MFP = 1000 nm, top, and 500 nm, bottom)

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