1. A Numerical Model of Template based Chemical Vapor
Deposition Process for Carbon Nanotube Manufacturing 1 Thesis
Proposal Thursday, July 31th, 2014 Yashar Seyed Vahedein Thesis
Committee Members: Michael G. Schrlau, PhD; Mechanical Engineering
(Advisor) Robert Parody, PhD; Statistician Steven Day; PhD;
Mechanical Engineering Patricia Taboada-Serrano, PhD; Chemical and
Biomedical Engineering Agamemnon Crassidis, PhD; Mechanical
Engineering
2. Nano-Bio Convergence Molecular Switch DNA barcode Molecular
Imaging Biochip / Biosensor Nano-therapy / Delivery
Bio-TechnologyNano-Technology Bionano-machine / Nano-Robot
Bio-inspired device and system Development of tools and methods
More sensitive More specific Multiplexed More efficient and
economic Implementation: Diagnosis and treatment of diseases Rapid
and sensitive detection (Biomarkers, Imaging) Targeted delivery of
therapeutics Drug development Understanding of life science
3. Analytical tools : Atomic force microscopy(AFM), Electron
microscopy (EM) Nano-sized materials Magnetic nanoparticles
(Ferromagnetic, super paramagnetic) Gold or Carbon nanotubes
Quantum dots (Semiconductor nanocrystals) Carbon nanotubes:
Properties: High Thermal conductivity(3500 > diamond),
strength(>100 Gpa), durability relative to their small size, one
dimensional transport. Applications in nanobiotechnology:
Intracellular electrochemistry, drug delivery and fluid injection
(single cell analysis) and etc. Ideal for single cell analysis.
Useful in many different fields, e.g electronics, optics and etc.
Example of Tools in Nano-biotechnology
4. Carbon Nano Tubes (CNTs) Development Research groups What
they did Impact (L. V.Radushkevich, V. M. Lukyanovich 1952)
Multiwall nano tubes First to find imperfect CNTs (Iijima 1991)
Highly perfect multiwall carbon nano tubes, used arc discharge And
(Thess et al. 1996) used Laser ablation to manufacture CNTs (Iijima
and Ichihashi 1993) Single Wall CNTs Dragged attention of
Researchers (Zhang and Li 2009) Review of some other types Bent,
waved, helically coiled, branched and beaded CNTs (Choy 2003)
Review on those Used Chemical Vapor Deposition Introduced as most
efficient way of making CNTs (Kyotani, Tsai, and Tomita 1995),
(Martin 1994), (Schrlau et al. 2008) Template Based-CVD (TB-CVD)
Can produce perfectly aligned amorphous CNTs (Sarno et al. 2012)
(Ciambelli et al. 2011) Structural analysis of CNTs made by TB-CVD
Effect of deposition time, temperature, gas mixture on CNT
synthesis 4(M. Golshadi, J. Maita, D. Lanza, M. Zeiger, V. Presser,
M. G. Schrlau) 2.5 m Study effect of gas flow rate, temperature of
furnace and time of process on CNT synthesis using TB-CVD
5. Schematics of the TB-CVD Setup in NBIL1 1. NBIL: Nano Bio
Interface Laboratory 5 Exhaust Heated region - causing deposition
Heater Heater Flow meter Precursorgas Carriergas Temperature knobs
Position of the templates Carbon deposited in a template
6. Template based manufacturing CVD Experiment CVD Simulation
fabricating CNTs Need for template based manufacturing of CNTs
Output of the processNBIL Single cell analysis Electrical,Bio
,nano, Mechanical app. High conductivity & strength Inlet
Gasses AAO Template Furnace Dimensions Temperature and Flow rate
NBIL 6 Motivations: Control the process and the effect of the
parameters on deposition. save time and resources by simulating the
process Create a universal method to be used by others for TB-CVD
(not currently available in literature) Diagram of the Driving
Needs, Process and Outcome of TB-CVD
7. Research Questions and Plan 7 How can temperature profile
and flow characteristics near the templates be identified? Is it
possible to simulate the deposition due to CVD process for a single
(>50nm) nano-pore in a template and to predict the deposition
rate of carbon for different flow rates and temperatures? Is it
possible to create a more flexible and comprehensive model that can
predict deposition in different flow, temperature and furnace
conditions? Schematics of the CVD 2 2. Model by Spear 1982
8. 8 Research groups What they did Impact (Oberlin, Endo, and
Koyama 1976b),(Tibbetts, Devour, and Rodda 1987), (T. Kato, K.
Haruta 1992) & etc. Understanding reactor operation and product
morphology Illustrated importance of CFD on vapor grown carbon
fibers (VGCFs) (Endo et al. 2004a), (Kazunori Kuwana and Saito
2005), (Kazunori Kuwana, Li, and Saito 2006) Predicted Carbon
deposition rate for catalytic decomposition of xylene Modeled
catalytic CVD process including reactions using CFD (He, Li, and
Bai 2011)- with 3 stage heating tube furnace Investigated
non-uniform nanotube growth in horizontal CVD reactor and suggested
changes for experimental setup accordingly 2D model and Experiment
on space dependent growth rate, temperature and flow structure
coupled with pyrolysis kinetics for samples (Mishra and Verma 2012)
2D, CFD simulation on the vertical furnace Made modifications on
the CFD code to raise the accuracy of the model (Ibrahim and
Paolucci 2011b), (Zhou and Wolden 2003), (Cheng, Li, and Huang
2008) & etc. Information on mass, momentum, concentration and
energy conservation in porous media Provided information on how to
model reactions in porous media Use of Computational Fluid
Dynamics(CFD) on CVD Simulation
9. The Gap in Simulations Conducted so Far and Significance of
This Work CNT synthesis using TB-CVD is controlled by parameters
such as: Temperature of the furnace, Flow rate and Time of the
process. No simulations have been found on TB-CVD processes without
catalyst and using only temperature as the reaction activator (Raji
and Sobhan 2013). Numerical models provided useful information
about similar experimental setups. Therefore a CFD simulation is
suggested to provide insight on the fundamentals of the TB-CVD
process being run in NBIL and to predict the carbon deposition
rate. 9
10. 10 Schematics of The Problem Pore size bigger than 50nm =
continuum regime Inlet flow rates=20 to 300 sccm
11. Heated Walls 1 = 668.160 Mass Flow Inlet = 3.93 07 to 5.9
06 Static pressure = 0 D=3.88 mm and 4.88 mm above the bottom wall
1 = 688.160 1 = 668.160 = 0 5 304.8 = 0 = 0 No slip condition on
tube wall: = 0 Boundary Conditions of the Furnace 11
12. Velocity and temperature profiles or Deposition rate as
Output 3D Steady state and/or transient Simulation of the Processes
Iterating continuity, momentum, energy and species conservation eq.
Defining Species Transport Model With Reactions for gas
decomposition and deposition of substances Initial Velocity,
Species Concentration Creating the Meshed Model UDF 3 Development
Creating a Numerical Model for Reactions and/or velocity in the
model to be able to code them Defining Boundary Conditions
Velocity, Temperature, Concentration Field and Reaction Rates 3.
UDF: User Defined Function for implementing in FLUENT code
Repeating the process for different conditions of the furnace and
parameters Simulation Steps 12
13. Trend of the Model Development 13 v1 v2 v3 v4 v5 v6 v7 v8
v9 v10 v11 v12 2D 3D Coarse mesh Fine mesh Adapted Mesh Residuals
10e-3 Residuals 10e-4 Residuals 10e-6 SIMPLE Solver SIMPLEC Solver
PISO Solver COUPLED Solver COUPLED Solver - Psuedo Transient
Laminar Turbulent - standard k-epsilon Constant Fluid Properties
Energy equation on Ideal gas-temp dep Cp Temp dep Visc, Thermal
cond. Shell Conduction Tube Furnace Just 60 SCCM 20, 40, 60, 80,
100, 150, 300 SCCM Flow Rate 20, 40, 60, 80, 100, 200, 300 Flow
Rate axisymmetric scaling fixed Temp fixed based on exp data fixed
inlet Diameter Sample Boat 2D Boat 3D VERSION SPECS talkabout
whythis semi-transientsolver has beenusedand whyit isnot needed in
2D meshstudy, meshadaption Solversettings ResidualStudy Odd V# Even
V# Tried parameters Semi- transient solver is needed for 3D but not
in 2D Mesh study, mesh adaption dimensionality Mesh quality and
adaption Residual study Solver study for best convergence Flow
regime Properties, Equations, boundary conditions Different Flow
rates Modification on model Sample and boat model
14. Expected Flow Conditions Inside the Tube 14 (Fotiadis and
Jensen 1990) - Smoke-test - Interference holography(Giling 1982) =
= 3968.4063 (In 60 sccm 4000>Reynolds at inlet>2300,
therefore Laminar ) Re inside tube = = 220 States Laminar flow
inside the tube = 3 2 = 1.212980888 8, = 0.00113, = . = 4.75 106
> 3 105 Turbulent (Chiu et al. 2000) What we would expect to see
in simulation Cross Flows Recirculation
15. 2D Vs. 3D 15 Boltzmann number =16.875 so Radiation is
neglected 2D does not capture the uniform Temperature region
correctly 3D model is able to capture the cross flows in YZ
plane
16. Comparing Mesh and Geometry of Two Modelled Cases w and
w/out Boat (Holder) 16 Mesh Report - CASE 2 : BOAT AND TEMPLATES
Mesh Information Domain Nodes Elements gas 1711039 1367244 Mesh
Report - CASE 1 : ONLY TEMPLATES Mesh Information Domain Nodes
Elements gas 516040 498575 Boat Two solid circles as templates
0.003 0.004 0.005 0.006 0.007 0.008 0.009 0 500000 1000000 1500000
2000000 Velocitymagnitude(m/s) Number of mesh elements Finding Mesh
Independent Solution Boundary layer meshing
17. 17 Temperature Data from Simulation showing the same trend
with Experimental Results 645 650 655 660 665 670 675 680 685 690
695 2 2.25 2.5 2.75 3 Temperature(C) Length (ft) Temperature vs
Length (Flow Rate = 500 sccm experiment and simulation) Radial
Position = 0 (inch) Data from simulation 500 SCCM near wall Radial
Position = 1 (inch) Data from simulation 500 SCCM 1 Inch Radial
Position = 1.5 (inch) Data from simulation 500 SCCM 1.5 inch Boat
0.47582 ft Potential reasons for data disagreement piece-wise
linear temperature dependent properties. Tube considered to be
isolated from outside(in simulation). Thermal resistivity of the
tube has been neglected and temperature considered to be uniform on
each zone. Accuracy of the sensors may create mistakes. Shape of
the sensor which will affect the flow has not been considered in
the CFD model
18. Properties on cross-section along longitude:20 and 300sccm
Recirculation is the main cause for having a curve shaped
temperature distribution along the tube. Recirculation regions
Recirculation regions
19. Temperature Contours on Mid Cross-Section of the Tube
Furnace 0.025m scale 20 sccm 40 sccm 60 sccm 80 sccm 300 sccm200
sccm100 sccm =0.025 Nearly symmetric distribution Sample & Boat
TurbulentLaminar = 13228.021 = 733.33 =4.75 106 = 6614 = 366.66 =
4.75 106
20. Temperature distribution on middle-cross section
961.550961.547961.544961.541961.538961.535961.532 Median Mean
961.54300961.54275961.54250961.54225961.54200961.54175961.54150 1st
Q uartile 961.54 Median 961.54 3rd Q uartile 961.55 Maximum 961.55
961.54 961.54 961.54 961.54 0.01 0.01 A -Squared 36.97 P-V alue
< 0.005 Mean 961.54 StDev 0.01 V ariance 0.00 Skewness -0.32227
Kurtosis -1.06591 N 2327 Minimum 961.53 A nderson-Darling Normality
Test 95% C onfidence Interv al for Mean 95% C onfidence Interv al
for Median 95% C onfidence Interv al for StDev 95% Confidence
Intervals Summary for Temperature [K]-80sccm
21. Temperature distribution on middle-cross section Linear
increase in temperature range in Laminar phase. Temperature range
change is (0.025 K) and can be considered constant for CVD By
getting to turbulent phase, Temperature range becomes narrower in
200 sccm
22. Contours of Velocity Components (u[x],v[y],w[z]) 20 sccm
300 sccm200 sccm100 sccm =0.0089/ TurbulentLaminar =0.0356/
velocity>00 velocity =0.0247/ 0.025m scale Highest velocity
value between 3 components but not near the Templates
23. U-velocity distribution on middle-cross section Linear
increase in range and mean velocity with increasing flow rate. Does
not depend on change from Laminar to turbulent. Compared to v and w
component, u velocity has the highest change by increasing flow
rate ( = 0.001156 /)
24. V-velocity distribution on middle-cross section Change in
mean value is in scale of 0.000001 m/s in Laminar phase. Outliers
in box plot and std of .004854 are the outcome of cross flows due
to natural convection & buoyancy effects (sudden changes in
density) =.000615 m/s between laminar and turbulent This drop is
due to having more disturbed flow
25. W-velocity distribution on middle-cross section Very small
decrease in mean velocity by changing from Laminar phase to
turbulent. = .000004 m/s Outliers in the boxplot, demonstrate the
disturbance which exist here duo to buoyancy driven flow. By
contour plots and statistical data, flow conditions around sample
can be extracted
26. Conclusions from preliminary work Buoyancy and flow regime
v and w vel. Threshold of change to turbulent 200 sccm and the
deposition change observed in experiments can be caused by this.
Symmetric and nearly constant temperature. Tube furnace model with
boat and template as final model. Using Peclet number, effect of
small changes in velocity components on diffusion and reaction can
be tested. A statistical method for relating the data in different
cross sections, flow conditions and furnace temperatures is
required. 26 Diffusion Characteristic length Characteristic
velocity
27. Research Questions and Plan 27 How can temperature profile
and flow characteristics near the templates be identified? Is it
possible to simulate the deposition due to CVD process for a single
(>50nm) nano-pore in a template and to predict the deposition
rate of carbon for different flow rates and temperatures? Study
reaction kinetics and reaction-diffusion systems Study how to
simulate species transport, reaction and porous media Develop the
user defined functions (UDF) for reactions Create model for carbon
deposition in one pore Compare carbon deposition rate with
experiment to modify the model Is it possible to create a more
flexible and comprehensive model that can predict deposition in
different flow, temperature and furnace conditions? Check
requirements to achieve a general model applicable to different
furnaces Modify the numerical model to match requirements
28. Introducing diffusion-reaction system to FLUENT 28
Generalized Source term (constant and linear) Generalized diffusion
coefficient Generalized transport variable By taking divergence of
these two, they can be transformed into volume integrals. + . = . +
Rate of increase of mole of the species Net rate of additions of
mole of the species per unit volume by convection Molar-averaged
velocity Net rate of mole of the species per unit volume by
diffusion in a binary system of components, otherwise xa is
replaced by The molar rate of production of species by chemical
reaction. = = =1 If the number of chemical reactions taking place
in the system is , the mass production rate is: stoichiometric
coefficient Difference between the forward and backward
reactions
29. Diffusion AAO Membrane Deposited carbon Outlet boundary
condition from macro-scale model and gas spectrometry Reaction zone
Diffusion of remaining gas and by- products of reactions Control
Volume for model Schematics of the Micro-Scale Model 29 Inlet
boundary condition from Macro-scale model Dehydrogenization or
Coking? By trying both and comparing the results with experimental
data for carbon deposition We anticipate the results to be
presented 1. Concentration [vol ppm] plot for each substance versus
position along axis of Tube 2. Carbon deposition rate[mgc m-2h-1]
plot for different flow rates versus position[X] After conducting
gas chromatography, the substances that exist here will be
revealed
30. Timetable for Work Plan 30
31. Required Facilities 31 High-end computer with these specs
is required for decreasing the simulation time: Processor: Intel(R)
Xeon(R) CPU E5-2620 v2 @ 2.10GHz (2 processors) Enabled Processor
Count: 12 Total Memory: 16 GB Local Storage: 931.51 GB (1 drives)
Graphics Card & Driver: FirePro W7000 3 stage ZTF CARBOLITE
furnace. - Already Exist. AAO membranes (Whatman Anodisc 13,
nominal pore diameter: 200 nm, nominal thickness: 60 m),
Ethylene-helium gas mixture and Argon, in already set CVD setup. -
Already Exist. Gas chromatography - Cooperating with chemical
engineering department of RIT High performance research computing
Cooperating with research computing Section of RIT
32. Acknowledgments I would like to thank my advisor, Professor
Michael G. Schrlau and PHD candidate Masoud Golshadi,, Dr.
Taboada-Serrano, Dr. Robert Parody Dr. Steven Day and Dr. Agamemnon
Crassidis for their valued advice and support of this work at
Rochester Institute of Technology. Furthermore, I would like to
thank Ms. Brenda Mastrangelo and Mr. Thomas Allston for their helps
on conducting gas chromatography and Mr. William Finch for his kind
cooperation in the process of buying the required hardware. Ayomipo
Ayowosola, Ryan Dunn Karen De Souza Martins and all the other lab
members who helped and supported my work. 32
33. Thanks for listening to my presentation, Questions? 33