Quantitative Quantitative In-situIn-situ Mechanical Characterization Mechanical Characterization of Functionalized Individual of Functionalized Individual Carbon Nanofibers (CNFs)Carbon Nanofibers (CNFs)

Jiangnan ZhangMechanical Engineering and

Materials Science

Rice University

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Introduction

Carbon Nanofiber (CNF)• cylindric nanostructures with graphene layers arranged as stacked

cones, cups or plates

• catalytic chemical vapour deposition

0.05 μm ~0.3 μm

10 μm ~ >1000

μm

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Motivation

CNFs as composite additive • CNFs reinforcements enhance properties of matrix (polymer,

ceramic and metal) due to their superior mechanical properties.

Effectiveness of reinforcement depends upon • Dispersion• Mechanical properties of filler• Nature of interfaces

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Motivation

Composite Interface Behaviour• Strong interfaces with large adhesive force between CNFs and the

matrix can results in tough composites

Challenges of reinforcements• Poor CNFs dispersion in matrix• Poor load transfer between CNFs and matrix

Crack bridging observed in CNFs/PS film Poly(phenylacetylene) (PPA) wraps perfectlyaround single-walled carbon nanotube

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Mechanical Testing of CNFs

Atomic force microscope based bending test2 In-situ testing of VGCNFs carried out using a MEMS based platform5

1. Kim G. T. et al, Applied Physics Letters, 20022. Lawrence J. G. et al, ACS Nano, 20083. Zhang H. et al, Chemical Physics Letters, 2009

4. Zussman E. et al, Carbon, 20055. Ozkan T. et al, Carbon 20106. Arshad S. N. et al, Carbon 2011 7

Microdevice and Nanoindenter

Devices were fabricated on SOI wafers

inSEM nanoindenter (Agilent Tech.) can be usedwithin FEI Quanta FEG SEM

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X

Y

Functionalized CNFs

Pristine CNFs

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Fluorinated CNFs Amino-Functionalized CNFs

Collaborated with Dr. Khabashesku from UH

CNFs Characterizations

C1F1 d=0.657 nm

C5F d=0.338 nm

d=0.340 nm

1. G and D’ peak red shift after fluorination

2. Two peaks shift back after de-fluorination

1. D spacing difference in fluorocarbon layer

2. The composition difference in fluorocarbon

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CNFs Positioning

a. Micromanipulators housed within a probe stationb. The tungsten tip that was used for CNFs manipulations

a. The ends of the sample stage shuttles were coated with a thin layer of epoxy.b. Using micromanipulators housed within a probe station, a tungsten tip was brought

into contact with an individual carbon nanofiber.c. The nanofiber, which was found to easily adhere itself to the tip, was subsequently

placed across the gap between the sample stage shuttles.d. The epoxy layer generally tends to coalesce around the nanofiber thus attaching it to

the sample stage shuttles. 12

CNFs Positioning

epoxy

CNFs

a. Deposited epoxy on edge part of the shuttle b. Aligned the CNFs on the stagec. Cured the epoxy and clamped the sample

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a

b

c

Top view Side view

Stress vs. Strain Curve Extraction

Disp. conversion coeff. vs. sample stiffness curveThe displacement conversion coefficient, CD ,the ratio of the stage shuttle displacement/sample elongation to the nanoindenter tip displacement.CD 0.975 for the devices used in this experiment

F(strain the sample)=F(deform device+specimen) – F(deform device)

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In situ Tensile Testing of CNFs

SEM Snapshots show a pristine CNFs specimen undergoing deformation and failure under a tensile test at (1) t=0, (2) t=10, (3) t=19, (4) t=30 s.

P=1.5 GPa

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(1) t=0 s (2) t=10 s

(3) t=19 s (4) t=30 s

SEM Snapshots show a Fluorinated CNFs specimen undergoing deformation and failure under a tensile test at (1) t=0, (2) t=12, (3) t=23, (4) t=34s.

P=3.0 GPa

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(1) t=0 s (2) t=12 s

(3) t=23 s (4) t=34 s

In situ Tensile Testing of CNFs

SEM Snapshots show an Amino-F CNFs specimen undergoing deformation and failure under a tensile test at (1) t=0, (2) t=10, (3) t=19, (4) t=30s.

P=1.4 GPa

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(1) t=0 s (2) t=12 s

(3) t=23 s (4) t=34 s

In situ Tensile Testing of CNFs

Statistical Analysis

Weibull cumulative probability density function

σ: the applied stress

Pf(σ): a probability of failure

Smaller m wider spectrum of flaw size

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σ0: the material stress parameter

m: the Weibull modulus

1. Ranking the failure stresses (σi) in ascending order (i=1, 2,…n)

2. Assigning probabilities of failure according to Pi=(i-0.5)/n, n is the number of broken specimens

3. Fitting the ln[-ln(1- Pi)] versus ln(σi) data points to a straight line

Fitting Curves

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Pristine CNFs Fluorinated CNFs

Amino-F CNFs

Mechanical Parameters

• The fluorinated and amino-F CNFs have relatively small Weibull modulus.

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• The characteristic strength of fluorinated CNFs is greater than the other two CNFs.

• The measured strength of three CNFS follows the same trend as the σ0.

TEM Sample Preparation

Left: Sections of the device’s inclined and support beams were etched.

Center: Using a micromanipulator probe, the device was picked up.

Right: The shuttle was placed on a TEM grid.

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1. Pristine CNFs

HRTEM Fracture Surface Examination

2. Fluorinated CNFs

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HRTEM Fracture Surface Examination

HRTEM Fracture Surface Examination

3. Amino Functionalized CNFs

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Functionalization Schemes

0.340 nm 0.657 nm 0.338 nm

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TEM images1 of carbon nano-onion Specimens: (A) pristine CNO, (B) F-NO-350, (C) F-NO-410, (D) F-NO-480; hydrazine-treated F-NO-410 (E) and F-NO-480 (F).

1. Liu Y. et al, Chemistry of materials, 2007. 26

Conclusions

• This study focused on the in situ tensile testing of CNFs with different functional groups.

• The Fluorinated CNFs was found to possess higher nominal strength but similar strain compared with the pristine and the amino-F CNFs.

• The nominal CNFs strengths followed the Weibull distribution with characteristic strength between 1.94-3.05 Gpa.

• All types of CNFs samples failed in the similar cup-cone fashion in the fracture surface.

• HRTEM of fluorinated CNFs revealed a change of the hollow core before and after fiber fracture, which was attributed to the possible effects of fluorination-induced compressive force on nanofiber surface.

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Acknowledgement

•NSF CMMI 0800896

•Welch Foundation grant C-1716

•AFRL FA8650-07-2-5061

•PipeWrap, LLC

•Dr. Jun Lou

•Rice NanoMechanics lab colleagues

•Dr. Yogee Ganesan (Intel)

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