Synthesis and Characterization of Low Dimensionality

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SYNTHESIS AND CHARACTERIZATION OF LOW DIMENSIONALITY

CARBON NANOSTRUCTURES

Dissertation

Submitted to

The School of Engineering of the

UNIVERSITY OF DAYTON

In Partial Fulfillment of the Requirements for

The Degree

Doctor of Philosophy in Materials Engineering

Michael Hamilton Check

UNIVERSITY OF DAYTON

Dayton, Ohio

December, 2013

SYNTHESIS AND CHARACTERIZATION OF LOW DIMENSIONALITY

CARBON NANOSTRUCTURES

Name: Check, Michael Hamilton

APPROVED BY:

______

Andrey A. Voevodin, Ph.D. Douglas S. Dudis, Ph.D. Advisory Committee Chairman Advisory Committee Member Professor Professor Materials Engineering Department Materials Engineering Department

______

Paul T. Murray, Ph.D. Scott A. Gold, Ph.D. Advisory Committee Chairman Advisory Committee Member Professor Professor Materials Engineering Department Chemical Engineering Department

______

John G. Weber, Ph.D. Tony E. Saliba, Ph.D. Associate Dean Dean, School of Engineering School of Engineering & Wilke Distinguished Professor

Michael Hamilton Check

2013

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ABSTRACT

SYNTHESIS AND CHARACTERIZATION OF LOW DIMENSIONALITY

CARBON NANOSTRUCTURES

Name: Check, Michael Hamilton University of Dayton

Advisor: Dr. Andrey A. Voevodin

Synthesizing nanostructures represents a critical technology in the field of materials science. The ability to actively control the structure and composition of matter have allowed some of the greatest scientific achievements in the last decade. This document explores the synthesis and characterization of various carbon nanostructures (e.g. DNA and doped fullerene materials).

Furthermore, this document addresses how these materials can be processed into low dimensional solids while maintaining compositional integrity. Processing methods include Matrix Assisted

Pulsed Laser Deposition (MAPLE), thermal evaporation, and Chemical Vapor Deposition

(CVD). The synthesized bulk structures were analyzed using physical and structural measurements. Project conclusions provided insight into the unique structure-property relationships in these materials.

Dedicated to my parents

ACKNOWLEDGEMENTS

I would like to acknowledge my Ph.D. advisory committee members for guidance and assistance with preparing my dissertation: Dr. Andrey Voevodin (advisor), Dr.

Douglas Dudis (advisor TE work), Dr. Terry Murray, and Dr. Scott Gold. In addition, I would like to thank the following people from AFRL/RX (Materials and Manufacturing

Directorate) for technical assistance and discussion: Scott Apt, John Bultman, Steve

Fairchild, Jianjun Hu, Michael Jespersen, Chris Muratore, Jose Nainaparampil, Steve

Patton, Art Safriet, Adam Waite, Willem Wennekes, and Bob Wheeler.

TABLE OF CONTENTS

ABSTRACT………………………………………………………………………...... iv

DEDICATION……………………………………………………………………………v

ACKNOWLEDGEMENTS……………………………………………………………...vi

LIST OF ILLUSTRATIONS……………………………………………………………xi

LIST OF TABLES…………………………………………………………………….xviii

LIST OF EQUATIONS………………………………………………………………..xix

LIST OF ABBREVIATIONS AND NOTATIONS…………………………………..xxi

CHAPTER I: INTRODUCTION………………………………………………………….1

CHAPTER II: BACKGROUND………………………………………………………….3

2.1 Physical Properties of Carbon Nanostructured Materials…….……………….3 2.1.1 Introduction………………….………………………………………3 2.1.2 Material Properties of Carbon Nanostructured Materials……….…..4 2.1.3 Concluding Remarks……………………………………………….22 2.2 Generalized Model for Thermal and Electrical Transport in Nanostructures..22 2.2.1 Introduction……………………………………………...…………22 2.2.2 Thermal Transport Phenomena…………………………………….23

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2.2.3 Electrical Transport Phenomena…………...………………………31 2.2.4 Concluding Remarks……………………………………………….38 2.3 Physical and Chemical Processing of Nanostructures……………………….38 2.3.1 Introduction………………………………………………………...38 2.3.2 Physical Vapor Deposition Methods………………………………39 2.3.3 Chemical Vapor Deposition (CVD) Methods……………………...47 2.3.4 Wet Chemical Based Methods……………………………………..52 2.3.5 Concluding Remarks……………………………………………….56 2.4 Thin Film Processes………………………………………………………….56 2.4.1 Growth Modes with Thermodynamic and Kinetic Considerations..56 2.4.2 Theory of Nucleation and Growth…………………………………58 2.4.3 Types of Growth…………………………………………………...60 2.4.4 Literature Examples of Carbon Nanostructured Growth…………..62 2.5 Characterization of Nanostructured Materials……………………………….64 2.5.1 X-Ray Photoelectron Spectroscopy (XPS)………………………...65 2.5.2 X-Ray Diffraction (XRD)………………………………………….66 2.5.3 Raman Spectroscopy……………………………………………….67 2.5.4 Electron Microscopy……………………………………………….68

CHAPTER III: RESEARCH OBJECTIVES…………………………………………….71

3.1 Investigate the Structure, Chemistry, Morphology and Formation Mechanism of Carbon Nanomaterials (DNA, and C60)…………..………….71 3.1.1 Motivation for the use of DNA-CTMA………………………...….71 3.1.2 Motivation for the use of Fullerides………………………………..72 3.1.3 Motivation for Deposition Techniques…………………………….75 3.2 Correlate the structure, chemistry, morphology of carbon nanomaterials with their physical properties………………………………………………...76 3.2.1 Thermal Properties…………………………………………………76

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3.2.2 Electrical Properties………………………………………………..76 3.2.3 Electron-Phonon Coupling…………………………………………76 3.3 Establish a Fundamental Relationship Between the Transport Mechanism and the Structure in DNA, and C60 Based Materials………….……….…….77

CHAPTER IV: EXPERIMENTAL METHODS…………………………...……………78

4.1 Nanostructure Deposition/Formations Methods……………………………..78 4.1.1 Formation of the DNA-CTMA Complex………………………….78 4.1.2 MAPLE of DNA…………………………………………………...80

4.1.3 Thermal Evaporation of C60……………………….….……………81

4.1.4 CVD of C60 and Zinc………………………………………………82 4.2 Thermal Properties…………………………………………………………...84 4.2.1 Thermal Conductivity……………………………………………...84 4.2.2 Heat Capacity by Means of Differential Scanning Calorimetry (DSC)………………………………………………………………90 4.3 Electrical Properties………………………………………………………….91 4.3.1 Four Point Probe…………………………………………………...91 4.3.2 PPMS………………………………………………………………93 4.3.3 Potential Seebeck Microprobe (PSM)……………………………..93

CHAPTER V: RESULTS AND DISCUSSION………………………………………...96

5.1 Process Development and Nanostructure Formation Mechanisms for DNA and C60……………………………………………………………..………...96 5.1.1 MAPLE process development……………………………………..96 5.1.2 Inducing Marangoni Flow for the Reduction of Coffee Ring Evaporation………………………………...……………………..109 5.1.3 Growth of Fulleride Thin Films…………………………………..115 5.1.4 Growth of Fulleride Nanowires…………………………………..127

5.2 Thermal Characterization of DNA and C60 Compounds…………………...134 5.2.1 Thermal Characterization of DNA-CTMA Films………………...134

5.2.2 Thermal Characterization of Zinc C60 Thin Films…………….….136

5.2.3 Thermal Characterization of the Zinc C60 Nanowires………...….138 5.3 Electrical Characterization of Fullerides…………………………………...139

5.3.1 Electrical conductivity of ZnxC60 Thin Films and ZnxC60 Nanowires………………………………………………………...139

5.3.2 Seebeck Coefficient of ZnxC60 Thin Films and ZnxC60 Nanowires………………………………………………………...141

5.3.3 Electron-Phonon Coupling in ZnxC60 Nanowires…………….….144

CHAPTER VI: CONCLUSIONS………………………………………………………150

6.1 Future Work………………………………………………………………...152

BIBLIOGRAPHY…………………………………………………………………...... 154

APPENDIX…………………………………………………………………………….172

LIST OF ILLUSTRATIONS

1.Figure 2.1.1:Relative space filling models displaying the different types of nanostructures from zero dimensional to three dimensional.4 ...... 4

2. Figure 2.1.2: A) Hall – Petch plot for different nanocrystalline materials of various sizes.5 B) Schematic of Grain size dependence vs. various mechanism for deformation behavior.7 ...... 6

3. Figure 2.1.3: Hardness of a nanocrystalline diamond film vs. grain size.9 ...... 7

4. Figure 2.1.4: Elastic modulus vs. the amount of disorder in a carbon nanotube.16 ...... 9

5. Figure 2.1.5: A) the solution of a potential well in a atom B) the time dependent Schrodinger equation C) The variation in potential wells for multiple atoms.18 ...... 11

6. Figure 2.1.6: A) Potential well with the addition of multiple atoms with various atomic spacing B) Schematic displaying the collective picture of atomic band structure.18 ...... 12

7. Figure 2.1.7: A) Illustration representing the density of states for various 0D, 1D, 2D, and 3D structures.19 B) This equation describes the relative density per energy state for a 3D system. C) The density per energy state is simply the derivative of the number of state divided by their energy...... 13

8. Figure 2.1.8: A) The normalized C K-edge absorption spectra of micron to nano sized particles of diamond. B) the calculated energy values for the conduction band edge and gap widening (insert) in small crystallites of diamond.22 ...... 14

9. Figure 2.1.9: (TOP) the theoretical DOS for a metallic nanotube and a semiconducting nanotube. (BOTTOM) the measured differential conductance vs. applied voltage on a scanning tunneling microscope.23 ...... 15

10. Figure 2.1.10: A) Graphene π and π* electronic bands. Linear dispersion relations close to the K (white dots) and K’ (black dots) points of the first 2D Brillouin zone are illustrated using the Dirac cone. B) Hall conductivity σxy (solid) and longitudinal resistivity ρxx (dashed) as a function of carrier density at B = 14T. Here, σxy is calculated as σxy = ρxy/(ρ2xx + ρ2xy) and is observed to be quantized as 2 28 σxy = 4(n + 1/2)e /h...... 16

11. Figure 2.1.11: Thermal properties of carbon allotropes and derivatives. Diagram is based on average values reported in the literature. The figure displays a generalized trend of how bonding type and number of interfaces effect thermal conductivity.32 ...... 19

12. Figure 2.1.12: The thermal conductivity of 2D and quasi 2D materials showing the intrinsic vs. extrinsic effects.37 ...... 21

13. Figure 2.2.1: Schematic of transverse waves propagating through a crystal lattice.41 ...... 24

14. Figure 2.2.2: (A) and (B) are two processes known as A Normal process is when one phonon scatters into two phonons. (C) Umklapp process where two phonons combine to create a third. Due to the discrete nature of the atomic lattice there is a minimum phonon wavelength, which corresponds to a maximum allowable wavevector. If two phonons combine to create a third phonon which has a wavevector greater than this maximum, the direction of the phonon will be reversed or flipped over with a reciprocal lattice vector G, such that its wavevector is allowed.47 ...... 27

15. Figure 2.2.3: (Left) Blackbody emission intensity as a function of wavelength and temperature. Figure displays Wien’s displacement of dominant wavelength as a function of temperature.51 (Right) The change in the dominant wavelength of propagation as a function of temperature for various wave transport processes.52 ...... 29

16. Figure 2.2.4: Temperature effects on the thermal conductivity of classical materials.47 ...... 30

17. Figure 2.2.5: (Left) A) Schematic of diffusive electronic transport (*) represent scattering events (l) is the mean free path, (L) is the length of the sample, and (W) is the width B)schematic of quasi-ballistic transport where only a few scattering events take place C) schematic of ballistic transport where no scattering takes place.64 (Right) Difference between diffusive and ballistic transport and the characteristic lengths involved.65 ...... 34

18. Figure 2.3.1: A) Partial pressure of a material with respect to Gibbs free energy of evaporation, R is the ideal gas constant, T is the temperature., l is the mean free path, kB is the Boltzman constant, p is pressure in pascal, d is the diameter of the gas particles, m is the molecular weight, Г is the particle flux B) an example of the Maxwell velocity distribution of nitrogen gas molecules at room temp. 73 ...... 41

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19. Figure 2.3.2: A) (Top Right) the Clausius – Clapeyron equation for pressure of gas, (Bottom Right) the cosine emission law for a point source as seen in “B)” Jv is emitting flux from surface, Q is the total evaporation rate from area A, K is the geometry factor, and r is the distance from the source. B) Diagram and geometry layout of a quasi-equilibrium cell. C) (Left) quasi-equilibrium cell (Right) nonequilibrium cell. D) Deposition thickness as a function of angle from the source.74 ...... 42

20. Figure 2.3.3: STM images of the hillock structure created by ion irradiation before (A) and after C60 deposition (B). An enlarged image of an area in between the hillocks (C) shows some trimers in the second fullerene layer. The orientation of the lattice is indicated by the solid lines. The table displays the types of defects observed in the film.79 ...... 43

21. Figure 2.3.4: Schematic representation of the plasma confinement observed in conventional and unbalanced magnetrons.83...... 45

22. Figure 2.3.5: Schematic illustrations of A) pulsed laser deposition and B) MAPLE. 47

23. Figure 2.3.6: A) Schematic for thermal activated CVD92 B) Schematic for plasma enhanced CVD 95 ...... 48

24. Figure 2.3.7: A) Atomic force microscopy of a nanocrystalline diamond thin film 99 B) Scanning electron microscope image of single walled carbon nanotubes100 C) Optical microscopy image of graphene layer on glass96 ...... 50

25. Figure 2.3.8: Electronic microscope images of submicrometer rods (A-D) and tubes (E-G) of C60. (Right) Schematic illustration of the formation process of C60 1D submicrometer structures. The black solid arrows and red dashed arrows on the crystal seed represent different growth rates.110 ...... 53

26. Figure 2.3.9: (Left) SEM image of SWNT cages after 3 cycles. Some cages were crashed and deformed as water evaporated during the sample preparation. The bar is 15 mm in length.111 ...... 54

27. Figure 2.3.10: (Top) Scanning electron microscope images of free standing self- assembled network of graphene oxide. (Bottom) Proposed formation mechanism.114 .... 55

28. Figure 2.4.1: Schematic displaying how film nucleation can be dominated by kinetics or thermodynamics. 117 ...... 58

29. Figure 2.4.2: (Left) Examples of the typical forces encountered when investing the mechanism involved in thin film formation.123 (Right) Characteristic time for thin film nucleation and growth processes.124...... 59

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30. Figure 2.4.3: Schematic representation of the three crystal growth modes: (A) island or Volmer-Weber, (B) Krastanov layer or Frank-van der Merwe mode, (C) layer plus island or Stranski-. θ represents the coverage in monolayers (ML).121 ..... 61

31. Figure 2.4.4: A) Island growth of C60 on graphite at room temperature, B) Layer 130 by layer growth of C60 observed at 100⁰C...... 63

32.Figure 2.4.5: A) Scanning tunneling microscope image of C60 nanowires formed on misorientated Si (111)-Ag substrates (200nm x 200nm), B) A model for the 131 growth of the C60 nanowires...... 64

33. Figure 2.5.1: Schematic for a typical XPS process.136 ...... 66

34. Figure 2.5.2: (Left) Schematic of diffraction of an X-ray in a crystal structure where there is constructive interference, (Right) Example of deconstructive interference and equation for Bragg’s law.137 ...... 67

35. Figure 2.5.3: (Left) Schematic of Sir C.V. Raman first observing inelastic scattering in a chloroform sample,140 (Right) Energy diagram of various scattering and absorption techniques.141 ...... 68

36. Figure 2.5.4: A) Schematic of a transmission electron microscope,146 B) Schematic of a scanning electron microscope.147 ...... 70

37. Figure 4.1.1: Ion Exchange Reaction of DNA with CTMA to form DNA-CTMA complex...... 79

38. Figure 4.1.2: Schematic illustrations of A) pulsed laser deposition and B) MAPLE . 80

39. Figure 4.1.3: (Left) Schematic of the vacuum system used of thermal evaporation. (Right) Telescoping thermal evaporator...... 82

40. Figure 4.1.4: Schematic layout of the custom build CVD chamber. Cartoon represent process flow and the picture are what the equipment physically looks like. .... 83

41. Figure 4.2.1: Schematic layout and components used to perform the TDTR measurements...... 86

42. Figure 4.2.2: A) Schematic of TDTR collinear detector line; B) Image of TDTR collinear detector line ...... 88

43. Figure 4.2.3: Thermal and electrical connections and circuit for the PPMS ...... 89

44. Figure 4.3.1: Diagram of the PSM assembly, with the specified temperature junctions T1 and T0, and the specified voltage junctions U1 and U2...... 95

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45. Figure 5.1.1: Effect of various solvents on the deposition of DNA-CTMA...... 98

46. Figure 5.1.2: (Top) Schematic of the proposed mechanism for low repetition rates (Bottom) Schematic of the proposed mechanism for high repetition rates...... 100

47. Figure 5.1.3: (Top) Optical micrographs of films produced with varying laser energy (Bottom) purposed mechanism to explain the observed phenomenon...... 101

48. Figure 5.1.4: Energy vs. Repetition rate for the deposition of DNA-CTMA complex...... 102

49. Figure 5.1.5: Optical micrographs of DNA-CTMA deposited at various substrate temperatures and laser energies...... 104

50. Figure 5.1.6: TEM images of the DNA-CTMA deposited at 900mJ, 2 Hz, for 45 min. (Left) the scale bar in the bottom left represent 0.2 um (Right) the scale bar in the bottom left represents 50 nm...... 105

51. Figure 5.1.7: (Top) Optical micrographs of the deposited C60 films at various volume concentrations of Toluene and DCB (Bottom Left) AFM images of the deposited film in 20% Toluene 80% DCB (by volume) (Bottom Right) TEM image of the deposited film in 20% Toluene 80% DCB...... 106

52. Figure 5.1.8: XPS spectra of the deposited film in 20% Toluene 80% DCB (by volume) (Insert) TEM image displaying the amorphous nature of the deposited material...... 108

53. Figure 5.1.9: Proposed reaction scheme involving the degradation of solvent and C60 molecules...... 108

54. Figure 5.1.10: Simulation of coffee ring evaporation. The dark blue lines represent the suspended phase in the droplet. (A-E) represent different time steps from the evaporation process.199 ...... 110

55. Figure 5.1.11: Marangoni flow patterns of fluorescent polystyrene beads suspended in various solvent mixtures.198 ...... 110

56. Figure 5.1.12: (Top)Optical Microscopy and (Bottom) white light optical profilometer data of DNA-CTMA of various (V:V) (Toluene:DMSO) solvent mixtures...... 113

57. Figure 5.1.13: (Top) AFM images of MAPLE deposited DNA-CTMA of various concentrations solutions (Bottom) RMS roughness of the AFM images above ...... 114

58. Figure 5.1.14: FTIR spectra of 70:30 Toluene:DMSO MAPLE deposited DNA- CTMA ...... 115

59. Figure 5.1.15: (Left) Raman spectra of deposited C60 film (red line) and database signature file for C60 (blue line), (Right) Scanning tunneling microscope image of the deposited C60 film...... 116

60. Figure 5.1.16: This schematic displays how the fulleride films were created. Briefly, layers of Zn (~10 nm) and C60 (~10 nm) were deposited on top of each other. The whole substrate and layer assembly was then placed in a furnace to allow for reactions between the Zn and C60...... 118

61. Figure 5.1.17: A) Differential scanning calorimetry of pure Zn and B) 75 layers of Zn/C60...... 120

62. Figure 5.1.18: Raman spectra of pure C60 (a) and Raman spectra of 75 layer sample of Zn C60 after heat treatment (b)...... 122

63. Figure 5.1.19: TEM image of deposited ZnxC60 (A) 13K magnification the dark region on the left is the Pt protection layer (B) 620K magnification (C) 620K Electron diffraction pattern...... 123

64. Figure 5.1.20: XPS surface scan of ZnxC60...... 125

65. Figure 5.1.21: Selective sputtering of carbon in C60 and the hiding effect observed in ZnxC60...... 125

66. Figure 5.1.22: Depth Profile of ZnxC60 for carbon 1s peak (A) and zinc 2p 3/2 peak (B). Each scan represents sputtering for increments of 25 seconds from the surface scan...... 126

67. Figure 5.1.23: (Left) Optical image of gradient sample (Right) Zn at % spatially resolved across the sample...... 127

68. Figure 5.1.24: Scanning electron micrograph of the as grown Zinc Fulleride nanowires. The insert shows an EDAX of the as produced wires, displaying homogeneity of the structure over a large region...... 129

69. Figure 5.1.25: Raman spectra of the Zinc Fulleride nanowires. In the inserts are enlarged regions of Hg(1) and Ag(2) modes with Lorentzian peak fits...... 130

70. Figure 5.1.26: A) D) SEM images (various magnifications) of the material produced in zone 2 B) C) E) F) TEM images (various magnifications) of the material produced in zone 2...... 131

71. Figure 5.1.27: XRD spectra of the material produced in zone 2. F(x,x,x) represents the fullerene phase, ZO(x,x,x) represents the zinc oxide phase, Z(x,x,x) represents the zinc phase...... 132

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72. Figure 5.1.28: A) TEM image of material collected from zone 2 B) EDAX map Zn peak C) EDAX map of the Oxygen d) EDAX map of the Carbon ...... 133

73. Figure 5.1.29: Proposed mechanism for the formation of zinc oxide nanotubes. .... 134

74. Figure 5.2.1: TDTR scan of a drop cast film of the pure DNA material...... 135

75. Figure 5.2.2: TDTR scan of the MAPLE deposited film of the DNA-CTMA complex...... 136

76. Figure 5.2.3: Example scans of TDTR data and models for the thermoelectric samples studied. A scan from amorphous SiO2 (a calibration standard) and model is also shown for comparison...... 137

77. Figure 5.2.4: Thermal conductivity of each spot in Zn-C60 gradient composition sample ...... 138

78. Figure 5.2.5: Thermal conductivity of the fullerides nanowires as a function of temperature...... 139

79. Figure 5.3.1: Electrical conductivity measurement of the zinc fullerides nanowires...... 141

80. Figure 5.3.2: Room Temperature Seebeck measurement ...... 142

81. Figure 5.3.3: PSM map of the Seebeck coefficient of the gradient ZnxC60 sample. . 143

82. Figure 5.3.4: Seebeck coefficient of the pressed zinc C60 nanowire sample (zone 2)...... 144

83. Figure 5.3.5: Deviation from WF of the pressed pellet of zinc C60 nanowires...... 145

84. Figure 5.3.6: Plot of the line width (FWHM) of the fitted Hg(1) modes versus the frequency shift. Insert shows the fitting of the Hg(1) modes...... 148

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LIST OF TABLES

1. Table 2.2.1: Various methods for calculation the scattering rate of phonons.48 ...... 28

2. Table 5.1.1: Marangoni number for various mole fraction percentages of Toluene and DMSO...... 111

3. Table 5.1.2: Processing conditions to find the optimal growth parameters...... 128

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LIST OF EQUATIONS

1. Equation 2.2.1: Matthiessen rule which inversely adds all scattering contribution where τi,j’s are the contributions of the various scattering mechanisms based on i, the modes of polarizations of the phonons, and j, the different types of scattering rates caused by impurities and mechanical lattice imperfections.43 ...... 28

2. Equation 2.2.2: The Fermi wavelength of a material, where n represents the electron density...... 32

3. Equation 2.2.3: The phase relaxation length as a function of the velocity of an electron at the Fermi surface vF, and the phase relaxation time (τφ) (i.e. the time taken for the phase fluctuations to reach unity) ...... 33

4. Equation 2.2.4: Landauer formula describing quantum conductance in terms of universal conductance units...... 37

5. Equation 4.2.1: Here m is an integer denoting summation over pump pulses,  is the time between unmodulated laser pulses (12.5 ns), f is the modulation frequency (9.8 MHz), and t is the time delay between pump and probe pulses. The function T is calculated with the Feldman matrix algorithm as explained in Ref. 181 ...... 85

6. Equation 4.2.2: Where m is the sample mass, H is enthalpy and ∆P is the absolute value of the heat flow to the sample, i.e. of the DSC signal. This is derived using the equilibrium-thermodynamics definition of heat capacity...... 91

7. Equation 4.3.1: The resistivity of a semi-infinite volume ( ) for given material where V is the voltage, s is the pin spacing, and I is the current passed between the outer probe...... 92

8. Equation 4.3.2: The resistivity of a finite sized material where all variables are the same as in equation 4.3.1. except for the included correction factor (a) ...... 92

9. Equation 4.3.3: The resistivity and sheet resistance in a finite solid. Where t is the sample thickness and Rs is the sheet resistance...... 92

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10. Equation 4.3.4: The mathematical procedure for solving for the Seebeck coefficient at the sample surface (Ss), where U0 and U1 are the voltages at the specified junctions, SCu is the Seebeck coefficient of the probe shell, and SCuNi is the Seebeck coefficient of the probe wire...... 95

11. Equation 5.1.1: Equation for the Marangoni number (Mg) where is the surface tension, is the surface tension of species 1, is the surface tension of species 2, L is the characteristic length, T is the temperature, is the dynamic viscosity, is the thermal diffusivity, and is the diffusion coefficient of species 1 into species 2. . 111

12. Equation 5.3.1: Equation for the electron phonon coupling constant Where is the degeneracy of the mode (5 for Hg modes), is the difference between the th FWHM of the mode of the measured material and that of pure C60 , 𝜔i is the phonon frequency, and N(0) is electronic density of state per spin at the Fermi level. ...... 147

13. Equation 5.3.2: kB is the Boltzmann constant, ħ is Planck’s constant, x as the normalized frequency, v is the speed of sound, θ is the Debye temperature, τN is the relaxation time due to normal scattering, and τC is the combined relaxation time using Matthiessen’s rule given as follows...... 148

14. Equation 5.3.3: τB is the boundary scattering, τU is the Umklapp related scattering, τN is normal scattering, τA is related to defect or alloy scattering, τeph is electron-phonon scattering, τD is due to fullerene domains...... 149

15. Equation 5.3.4: Equation for approximating the electron-phonon scattering in materials...... 149

LIST OF ABBREVIATIONS AND NOTATIONS

 Yield strength

H Hardness of the material

K Constants representing the grain boundary as an obstacle to the propagation of deformation d Grain diameter

V (x) The potential function

DOS Density of states

σxy Hall conductivity

ρxx Longitudinal resistivity

D Grain size

K Thermal conductivity

Cp Heat capacity

υ Group velocity

λF Fermi wavelength

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Electron mean free path Ɩe

Phase relaxation length Ɩφ

kF Fermi wavevector n Electron density

vF Velocity of an electron at the Fermi surface

τφ Phase relaxation time l The mean free path

L Length of the sample

W The width of the sample

σ Electrical conductivity

E The constant electric field e The elementary charge

ne The electron concentration m* Mass of the carrier

τ Relaxation time

εj Energy of the j band

ħ Planck’s constant

Tij Transmission probability

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G0 Universal conductance unit

γ The inverse phonon lifetime

Jv Emitting flux from surface

Q Total evaporation rate

K Geometry factor r The distance from the source

F The rate of condensation

Ts Temperature of the surface

Ea Surface re-evaporation energy

Ed Surface diffusion energy

Ei Binding and nucleation energy

θ Represents the coverage in monolayers

ML Monolayer

TE Thermoelectric

S Seebeck coefficient or thermopower

T Absolute temperature

e Thermal conductivity contribution from free electrons

l Thermal conductivity from lattice contributions

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ZT Dimensionless figure-of-merit

TDTR Time domain thermal reflectance

EOM Electro-optic modulator

 Time between unmodulated laser pulses f Modulation frequency t Time delay between pump and probe pulses

PPMS Physical properties measurement system s Interprobe spacing

Resistivity of a semi-infinite volume

V Voltage a Correction factor

Rs Sheet resistance

U0 Thermocouple voltage

U1 Thermocouple voltage

SCu Seebeck coefficient of the probe shell

SCuNi Seebeck coefficient of the probe wire

DCB Dichlorobenzene

Mg Marangoni number

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Surface tension

Surface tension of species 1

Surface tension of species 2

L Characteristic length

T Temperature

Dynamic viscosity

Thermal diffusivity

Diffusion coefficient of species 1 into species 2 AFM Atomic force microscope

STM Scanning tunneling microscopy

DSC Differential scanning calorimetry

XPS X-Ray Photoelectron Spectroscopy

XRD X-Ray Diffraction

MAPLE Matrix assisted pulsed laser deposition

CVD Chemical vapor deposition

TEM Transmission electron microscopy

WF Wiedman-Franz

 Electron-phonon coupling constant

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Degeneracy of the mode

Difference between the FWHM of the th mode

𝜔i Phonon frequency

kB Boltzmann constant

N(0) Electronic density of state per spin at the Fermi level x Normalized frequency v Speed of sound

θ Debye temperature

τN Relaxation time due to normal scattering

τC Combined relaxation time

τeph Electron-phonon scattering time

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CHAPTER I

INTRODUCTION

1 Thesis Introduction

The inherent properties of materials and our human interactions with them has driven and changed all aspects of humanity. Understanding why materials have their properties and figuring ways to fundamentally exploit their properties have been critical for the development of almost every science and engineering field. The application of these properties represents some of the greatest accomplishment of the past century.

Whether it was the ability of the Wright brothers to make their first flight (i.e. they were the first group to cast an engine out of aluminum, making it light enough to sustain flight) or the discovery of materials with semiconducting properties (i.e. allowing the production of digital logic elements fundamental for the computer I am typing on right now), materials developments have been critical for technological advancement. It is these intrinsic properties and their subsequent application that drive the modern day economy.

Thus, critical understanding and development of new knowledge on materials can truly change the world.

Since the world of materials is so broad (e.g. there are 118 elements and almost an unlimited way of combining them) this review will focus on carbon based materials and more specifically DNA and C60. The capability to manipulate atomic structures at sizes

1 relatively close to the atoms themselves (e.g. approximately 1-100nm) has led to the discovery of several new structure property relationships.1-3 The topics covered here will address how these materials can be deposited into thin films, how the electrical properties of C60 can be changed by metallic doping, and how to grow doped fullerene nanowires.

Furthermore, we will explore several types of deposition methods to create these unique nanostructures, and investigate their unique structure property relationships.

CHAPTER II

BACKGROUND

2 Thesis Background

2.1 Physical Properties of Carbon Nanostructured Materials

2.1.1 Introduction

The topics covered here will address how nanostructuring (e.g. 0D, 1D, 2D,3D) affects the mechanical, electron transport, phonon transport, optical and nonlinear optical, and field emission properties of the material (see Figure 2.1.1). Nanostructuring specifically relates to the dimensionality of the created material (i.e. the size of the distinguishable units in the material). Specific materials have been selected to emphasize these structure property relationships and include graphite, graphene, diamond, polymers, and nanotubes.

Figure 2.1.1:Relative space filling models displaying the different types of nanostructures from zero dimensional to three dimensional.4

2.1.2 Material Properties of Carbon Nanostructured Materials

2.1.2.1 Mechanical Properties of (0D, 1D, and 2D) Structures

Nanostructured materials display mechanical properties which can be, in some circumstances, quite different from those of their bulk counterparts. These differences are largely the result of the nature of bonding in the nanostructures. When one investigates the physical structure in 1D, 2D, and 3D materials, it becomes apparent that relative number of surface atoms compared to interior atoms is quite large. Furthermore, the coordination number and type of bonding that takes place at these surfaces is often substantially different from that of the bulk material. These changes result in creating materials that have mechanical properties which behave more like a composite, where the stiffness and elasticity are driven by the molecular interaction between the surface and bulk atoms. Additionally, nanomaterials often times have much lower defect densities

4 which can further enhance their elasticity. The net result is materials with properties much different from their bulk counterparts, and a plethora of opportunities for discovering and characterizing the driving mechanisms. Moreover, the objective of this section is to present the current models for nanomaterial mechanics and give current experimental results for some carbon based 1D, 2D, and 3D structures.

Bulk nanocrystalline materials (e.g. a 3D structure compromised of crystalline grains from 1-100 nm) have been studied amply in the past.5,6 Grain refinement is commonly known to improve the hardness and strength of conventional-grained materials

(grain diameter, d > 1 mm).5 The empirical Hall- Petch equation has been found to express this grain-size dependence of strength or hardness very well. In terms of yield

–1/2 –1/2 strength and hardness, the expressions are = 0 + Kd and H = H0 + Kd , respectively, where and H refer to the yield strength and hardness of the material, and the subscript 0 relating to the material of infinite grain size; K and K are constants representing the grain boundary as an obstacle to the propagation of deformation; and d is the grain diameter.5,6 While this model holds well for bulk and micrograined materials it fails when grain sizes are smaller than <20 nm (see Figure 2.1.2). Furthermore, making the situation even more complicated, different materials are displaying different effects at this size (e.g. materials display positive, negative, and flat slopes).

Figure 2.1.2: A) Hall – Petch plot for different nanocrystalline materials of various sizes.5 B) Schematic of Grain size dependence vs. various mechanism for deformation behavior.7

The deviations from the normal H-P behavior are commonly referred to as the inverse Hall-Petch effect, where the hardness decreases with size at the nanoscale, for sizes below 15-100 nm. This can be understood by a model presented by Guisbiers et al.8

This model states that for sizes below 15 nm, both intrinsic stress and hardness increase with the size before some other process such as voids, microcracks, creep, or other material flaws dominate. Furthermore, the model explains the origin of the intrinsic stress as a result of the strain that appear during solidification due to the change in density between the liquid and the solid phases. With these models in mind, the behavior observed by Wiora et al. of nanocrystalline diamond films can be well understood.9 They showed that as the grain size was decreased in their films there was a reduction in hardness thus following the behavior for the inverse H-P effect (see Figure 2.1.3). The authors attributed this result to the increasing number of atoms associated with grain boundaries and their subsequently different bonding (e.g. sp2 vs. sp3 hybridization). The nature of the change in this type of bonding can be accounted for using Guisbiers model,

6 and further demonstrates the importance of nanostructural characterization on mechanical properties.

Figure 2.1.3: Hardness of a nanocrystalline diamond film vs. grain size.9 Two dimensional carbon materials, such as graphene, also behave differently than its three dimensional counterpart graphite. Graphene, which consists of a two- dimensional sheet of covalently bonded carbon atoms, comprises the basic units of graphite and carbon nanotubes ( CNTs). The differences being that graphite is a stacked sheet of graphene, and CNTs are a rolled tube of graphene. Its intrinsic strength, has been predicted to exceed that of any other material10 and if realized a new class of ultralight weight and strong composite could be made (e.g. it is estimated that a one square meter graphene hammock, the equivalent weight of a cat whisker, could support a 4 kg cat).11

Recently Lee et al. measured the strength of this material by suspending it over a nanoscopic hole on a substrate and found that it had an intrinsic strength of 130 GPa, and a Young’s modulus of 1.0 TPa .12 These measurements establish graphene as the strongest material ever measured and represent huge milestone towards the future of

7 mechanical nanostructural materials. The very large strength measured for this material was attributed to the lack of defects and grain boundaries. Moreover, this gives yet another example of how controlling structures at nanoscales greatly contributes to enhancing our material world.

Carbon materials arranged into one dimension, such as CNTs, also display interesting mechanical properties. Several reviews have covered this topic in depth, and the overarching conclusion is that manipulating nanoscopic structures is a very challenging task.13-17 In order to get accurate measurement on physical samples one must be able to mount and apply a mechanical stress to objects that are typically several orders of magnitude smaller than the measuring equipment. However, work has continued to progress steadily, with both theory and experiments demonstrating that the Young’s modulus of CNTs is at least as high as graphite and can be even higher for small single walled nanotubes.13,17 Moreover, other groups have shown that the Young’s moduli for

MWNTs are dependent upon the degree of order within the tube walls.16 Figure 2.1.4 shows a schematic representation of these findings, where the Young’s modulus decreases as the disorder increases. While this chart helps to quantify qualitatively the expected result, it was noted that disorder is difficult to experimentally measure and thus represents an arbitrary scale.

Figure 2.1.4: Elastic modulus vs. the amount of disorder in a carbon nanotube.16 The mechanical properties of carbon nanomaterials present an interesting perspective on the fundamental mechanism involved in strength and hardness. This outlines the importance of understanding individual atomic bonding and its relation to dislocation, diffusional, grain boundary, and two phased events that dominate the mechanical properties observed in nanomaterials. Moreover, further study and development in this field are critical for the future of structural nanomaterials.

2.1.2.2 Electrical Transport Properties of (0D, 1D, and 2D) Structures

By observing the effects that downscaling had on the mechanical properties, it should come as no surprise that when materials are nanostructured, there are dramatic changes in their electrical behavior as well. Most of the unusual behavior observed can be explained by the exciting physics that takes place when materials become very small. At these length scales, transport becomes dominated by quantum mechanical effects. In this

9 section we will look into some examples of nanostructured carbon materials that display these surprising traits.

When the time-independent Schrodinger equation is applied to an individual atom, the potential function V (x) contains the Coulomb interactions between negative electrons and the central nucleus as well as the interaction between the electrons with each other. Qualitatively this leads to the solution set of a potential well (see Figure

2.1.5). This implies that each electron is confined to a probalistic space at a discrete energy level. Furthermore, the addition of extra electrons into the system requires additional discrete quantum levels. It is from this basis that one can understand some of the basic properties observed from atoms such as X-ray emission and absorption at discrete energy levels. When one adds other atoms to the picture the total representation of the potential well changes, as can be seen in Figure 2.1.5C. If we were to continue on this trend we would find that the columbic potentials are only valid at the edges of the material. Thus in bulk materials where the number of atoms is sufficiently large one could ignore the boundaries and just consider it an infinite periodic array represented by the bottom line in Figure 2.1.5C.

Figure 2.1.5: A) the solution of a potential well in a atom B) the time dependent Schrodinger equation C) The variation in potential wells for multiple atoms.18

This view of the atom is the fundamental basis for the electronic structure in solid state physics, and provides a through explanation of why materials have their characteristic electronic behavior. This can be summarized qualitatively using five key points (see Figure 2.1.6). First, the presence of other atoms broadens the energy levels from the atomic ones. Second, the bottom electrons are the least affected. Third, the upper level electrons begin to overlap creating energy bands. Fourth, depending on how many electrons the solid contains there can be both filled and empty bands, potentially with gaps between them. Fifth, the nature of how filled the bands are vs. the size of the band gap presence determines whether the material is an insulator, conductor or semiconductor.

Figure 2.1.6: A) Potential well with the addition of multiple atoms with various atomic spacing B) Schematic displaying the collective picture of atomic band structure.18

The last example displayed properties of materials ranging from discrete atoms to the bulk collection of atoms. One can observe that as structure goes from a single atom

(i.e. discrete energy levels in the electronic structure) to bulk materials (i.e. continuous bands of energy levels) the electronic properties can vary quite drastically. Thus the question remains as to what are the electronic properties of materials that are in between those of bulk and individual atoms. To investigate this idea more thoroughly one must look at a materials density of states (DOS). The DOS of a material can be thought of as the number of states that a quantized wave (i.e. electrons and phonons) could occupy at a given energy level. This notion is largely a result of the Sommerfeld model of conduction states, which implies that almost all of the electrons in solids have less energy than the

Fermi energy and that the corresponding wavenumbers are limited to Fermi wavenumbers. Simply, this means that when electrons are confined into a fixed volume there are also a fixed number of allowed possible electron states. This is represented in

Figure 2.1.7A where the DOS for various nanostructured materials is plotted. One observes that as materials go from 3D to 0D the DOS changes from a continuous plot to

12 one that becomes dominated by discrete energy transitions. Moreover, this means that as materials are confined to smaller and smaller spaces, one might also expect larger variations in their electronic behavior. The next section will examine some recent experimental results displaying these properties.

A B ) ) g(E)

C ) g(E)

Figure 2.1.7: A) Illustration representing the density of states for various 0D, 1D, 2D, and 3D structures.19 B) This equation describes the relative density per energy state for a 3D system. C) The density per energy state is simply the derivative of the number of state divided by their energy. The effect of quantum confinement (i.e. a widening of the bandgap due to size restriction) has been predicted by several groups, and observations of these electronic quantum actions have recently been demonstrated.20,21 In 0D structures of diamond nanocrystals, Chang et al. observed quantum confinement effects using x-ray absorption.22 More specifically they were able to use carbon K-edge x-ray absorption near edge structure spectra of nanodiamonds to show that the exciton state and conduction band edge shift to higher energies with the decrease of the crystallite size (see

Figure 2.1.8). This finding suggests a widening of the energy gap caused by the quantum confinement effect. Furthermore, they were also able to display that the crystallite size strongly influences the exciton binding energies.

A B

Figure 2.1.8: A) The normalized C K-edge absorption spectra of micron to nano sized particles of diamond. B) the calculated energy values for the conduction band edge and gap widening (insert) in small crystallites of diamond.22

Observations of quantum effects have also been seen in 1D carbon nanostructures such as carbon nanotubes. In CNTs the electronic properties are dominated by the characteristics of graphene, the size dependent properties imposed by the tubes diameter, and the chirality of the tube. The electron wavelength confined around the circumference of the tubes imposes quantized periodic boundary conditions, thus restricting the number of allowed modes.23 Although the modes are not restricted down the tubes axis, modeling and experimentation have shown that instead of having one wide electronic energy band the material splits into one dimensional subbands (see Figure 2.1.9). The one dimensional nature of this material is illustrated in the observed Van Hove singularities in the STM spectra in Figure 2.1.9.

Figure 2.1.9: (TOP) the theoretical DOS for a metallic nanotube and a semiconducting nanotube. (BOTTOM) the measured differential conductance vs. applied voltage on a scanning tunneling microscope.23 In 2D carbon nanostructure, such as graphene, quantum electronic effects are also observed. The simple building blocks that compose graphene, two atoms per unit cell, have allowed it to be extensively investigated in theory for the past 60 years.24 The electronic properties of graphene can thus be described by an effective massless Dirac fermion model in the vicinity of the charge neutrality point, with linear dispersion and electron-hole symmetry. These “Dirac cones” of carriers (holes and electrons) appear in the corners of the 2D Brillouin zone whose points touch at the Fermi energy, as illustrated in Figure 2.1.10A.25 Furthermore, this mean that in a magnetic field perpendicular to the graphene plane, the linear excitation spectrum of Dirac fermions

15 should evolve into discrete Landau levels, thus giving rise to the quantum hall effect.

Recently, this effect was observed by Novoselov et al. (see Figure 2.1.10B).26 The underlying mechanisms of these quantum Hall states are the focus of many recent theoretical discussions, where a variety of interaction- driven ground states and novel charge and spin excitations have been predicted by combining quantum Hall physics with graphene’s unique linear excitation spectrum and four-fold degeneracy.27,28

A B ) )

Figure 2.1.10: A) Graphene π and π* electronic bands. Linear dispersion relations close to the K (white dots) and K’ (black dots) points of the first 2D Brillouin zone are illustrated using the Dirac cone. B) Hall conductivity σxy (solid) and longitudinal resistivity ρxx (dashed) as a function of carrier density at B = 14T. Here, σxy is calculated as σxy = ρxy/(ρ2xx + ρ2xy) and is observed to be quantized as σxy = 4(n + 1/2)e2/h.28

The world of electron transport in nanomaterials presents an exciting picture where fundamental quantum effects dominate. Understanding these unique mechanisms and characterizing their behavior will push the development of new technologies from fields as broad as semiconducting manufacturing to biosensing. Along with these incremental technological improvements come advances in entire new fields such as quantum computing. Furthermore, we have seen that as material shrink in size different

16 mechanisms start to dominate. It is with these elementarily discoveries, and application thereof, that one can truly advance society; and thus their importance cannot be understated.

2.1.2.3 Phonon Transport Properties of (0D, 1D, and 2D) Structures

Classical size effects on the transport of quantized lattice waves (e.g. phonons) have been investigated amply in the past.29-31 Unsurprisingly, the transport properties of heat can dramatically change depending on the size scale of the underlying structure.

Furthermore, since phonon waves tend to be much larger than electron waves (e.g. 1-10 nm for electrons, compared to 10-1000 nm for phonons) the interaction between the material and wave can be much more dramatic. It is the objective of this section to explain the underlying phenomena for heat transport in 0D, 1D, and 2D carbon nanostructures.

The principles that drive phonon transport, much like electrons, can be thought about in terms of the phonon density of states (i.e. the number of allowed waves in a confined space). This not much different from what was seen in the electron density of states seen in Figure 2.1.6. This implies that as the dimensionality of a material is shrunk there can be fewer allowed states, and thus in 0D materials the DOS is reduced to individual modes. The major difference outlined between electrons and phonons, is largely a result of the interfacial scattering that takes place with phonons. Since the characteristic length of phonon is much larger than electrons, phonons tend to be scattered much more at interfaces than electrons. Therefore the basic picture presented in nanoscale heat transfer is that shrinking the size of crystalline materials results in lower

17 thermal conductivity because of increased phonon scattering at boundaries. While this is true in most instances there are special circumstances where this is violated.

Let us first discuss the thermal properties of materials where the thermal conductivity is limited by disorder or grain boundaries rather than by the intrinsic lattice dynamics (see Figure 2.1.11). Most studies have shown that the thermal conductivity of diamond materials strongly depends on the grain size D and cover the range from ~1-10

W/mK in ultra nanocrystalline diamond to ~550 W/mK in microcrystalline diamond.32

The grain size D dependence can be estimated from K = (1/3)CpυD, where K is the thermal conductivity, Cp is the heat capacity, and υ is the group velocity. Furthermore, this assumes that inside the grain, phonon propagation is the same as in bulk crystal.

Some studies suggested that heat conduction can be different in very small nanocrystalline diamond (e.g. D~3-5 nm), where thermal transport is controlled by the intrinsic properties of the grain boundaries.33 It has also been noted that the grain boundaries contain sp2-phase as opposed to the sp3-phase carbon inside the grains which can lead to addition scattering.34 Moreover, the picture that emerges from this is that both the nature of the bonding and the number of interfaces can have a very large effects on the materials overall thermal conductivity.

Figure 2.1.11: Thermal properties of carbon allotropes and derivatives. Diagram is based on average values reported in the literature. The figure displays a generalized trend of how bonding type and number of interfaces effect thermal conductivity.32

Although size reduction generally leads to lower thermal conductivity, some nanostructures such as carbon nanotubes and polymer chains can display properties which contradict this generalized trend.35 At a first glance this seems counterintuitive to the original idea that smaller sizes mean more interfaces and fewer allowed phonon modes. However, when a material is truly a 1D structure this severely limits the number of scattering sites that would occur at boundaries (since there are none). This means that in order to satisfy energy and momentum conservations the phonon mean free path down the axis of the tube or the polymer chain must become longer, thus leading to higher thermal conductivities.35 This idea is best exemplified by a molecular dynamic simulation comparing the thermal conductivities of diamond nanowires and carbon nanotubes.

Using this type of simulation Moreland et al. predicted that the thermal conductivity of diamond nanowires is much smaller than that of carbon nanotubes of comparable diameter.36 The major reasoning being that nanowires of diamond were not truly a 1D material and the additional scattering at the boundaries of the wire significantly decreased the overall thermal conductivity.

When examining the thermal transport in materials that span from 2D to 3D (i.e. the transition from graphene to graphite) several interesting trends arise. The changes in the thermal conductance of these materials can largely be attributed to the mechanisms that dominate at the various length scales. In the case of a singular layer of graphene, thermal transport is limited by the intrinsic properties of the lattice (e.g. crystal anharmonicity).32 Whereas the case when additional layers are added, the thermal transport becomes dominated by extrinsic effects (e.g. phonon scattering). Ghosh et al. described this decrease in thermal conductivity by considering the evolution of phonon

Umklapp scattering.37 They conjectured that as more layers were added the phonon dispersion changes such that more phase-space becomes available for phonon scattering.

This is displayed in Figure 2.1.12 where one can see that as the number of atomic planes is increased the thermal conductivity starts to approach that of bulk graphite.

Figure 2.1.12: The thermal conductivity of 2D and quasi 2D materials showing the intrinsic vs. extrinsic effects.37

Understanding and controlling the energy transport in nanostructured materials is critical for the development of next generation devices. Whether it is from removing more heat from processors to making a more efficient engine, thermal transport has become the rate limiting step in many applications. Moreover, we have seen that by nanostructuring carbon materials very interesting, and sometimes counterintuitive, results can be achieved. From the very large thermal conductivities observed in graphene and

CNTs to the very low thermal conductivities in the interface dominated nanocrystalline diamond. Furthermore, given that over half of the world’s energy is wasted as heat (~

1013W), thorough investigation and exploitation of new transport mechanisms could lead to new breakthroughs.

2.1.3 Concluding Remarks

In conclusion, studying and applying the fundamental knowledge of nanostructed materials and their properties, stand to significantly advance all science and engineering fields. Looking at core examples in nanostructured carbon materials we find that there are several unique structure property relationships that can be developed for 0D, 1D,2D, and

3D materials. Noteworthy changes in the mechanical, electrical, and thermal properties were demonstrated, with an emphasis on how bonding and size effect create these differences. It is with open optimism that I look forward to the advancement that nanomaterials will bring.

2.2 Generalized Model for Thermal and Electrical Transport in Nanostructures

2.2.1 Introduction

Understanding how electrons and phonons move is crucial to describing the behavior of materials. These fundamental phenomena dominate the properties that we observe and offer clues on how to make materials behave the way we want them to. The objective of this section is to describe the elementary forces at work in thermal and electrical transport. More specifically the thermal transport topics will cover phonon transport in bulk materials, phonon scattering, temperature effects, and length scale dependence. The electrical transport topics will cover the characteristic lengths, diffusive transport, ballistic transport, and electron phonon coupling. From these generalized discussions we should develop a solid understanding of classical transport, and have a primary idea of how a materials characteristic dimension can change these properties.

2.2.2 Thermal Transport Phenomena

2.2.2.1 Phonon Movement in Bulk Materials

There are two transport mechanism of heat in a solid, lattice/atomic vibrations

(e.g. phonons), and by charge carriers (e.g. electrons and holes). The relation between lattice thermal conductivity and charge carrier contribution (e.g. electrical conductivity) typically follows the Wiedemann-Franz law.38-40 Furthermore, this relation can be used to explain why good conductors (e.g. metals) typically have a high thermal conductivity. In semiconductors and electrical insulators heat transport is dominated by lattice vibrations.

Thus to review all of the pertinent transport issues this review will be broken into two sections, one primarily dealing with lattice dynamics, and the other focused on electron transport.

In a solid material, the atoms are held together by chemical bonds (e.g. covalent and ionic) and Van der Walls forces. If the bonds form long range order the material is said to be crystalline, if not the material is called amorphous. Additionally, the atoms are not held rigidly in place, but act more like a physical mass – spring system. This means that as one of the atoms starts to vibrate the kinetic energy of this motion can travel through the lattice as a wave. These lattice vibrations are quantized and are known as phonons. Phonons are respectively referred to as transverse or longitudinal depending if the atoms are displaced perpendicular or parallel to the direction of travel. Additionally, if the neighboring atom move in the same direction the wave is called acoustic, if they move in opposite direction they are called optical (see Figure 2.2.1).

Figure 2.2.1: Schematic of transverse waves propagating through a crystal lattice.41 By solving the equations of motion for these waves, one can determine the angular frequency (ω) of the waves as a function of their wavelength (λMFP) or their

42,43 wavenumber (also called wavevector, k), where k = 2π/ λMFP. Using this information one can plot ω vs. k to establish the generalized dispersion relation. Another useful parameter that can be defined by the dispersion relation is the group velocity (vg), or the speed of sound, of the phonons. This is defined as vg =∂ω/∂k which is simply the slope of the branch on the dispersion relation. When investigating the typical dispersion relation, one finds two distinct phonon branches. These represent the acoustic and optical vibrations previously discussed. Furthermore, two generalized trends can be observed for these branches 1) the acoustic branches typically have much higher group velocities, and thus make a much larger contribution to the thermal conductivity, and 2) the frequency range of vibrations for the optical branches is significantly higher than the acoustic branches and overlaps into the infrared regime.44 Additionally, the optical phonons are responsible for the interaction of a material with infrared electromagnetic radiation.45

2.2.2.2 Phonon Scattering

When phonons traverse through a lattice, often times the wave is disrupted by imperfection in the material. These interactions are referred to as scattering events, and can greatly affect the overall thermal conductivity of a material. Phonons can be scattered by dislocations, crystal boundaries, substitutional or interstitial defects, or by interactions with other phonons. These scattering mechanisms can be grouped into two categories, 1) elastic scattering (normal scattering) where the direction of the phonon changes but frequency does not or 2) inelastic scattering (Umklapp scattering) where both the frequency and direction change. Characteristic in determining scattering mechanisms are the average distance a phonon travels before a collision or scattering event, known as the phonon mean-free path (λMFP). The mean free path is defined as λMFP = ντ where ν is the phonon velocity and τ is the average time between scattering events. The mean free path in materials has been investigated amply in the past and may simply be estimated using kinetic theory.43,45

The size of a defect will determine the type of wave that will be most scattered, and for that reason high frequency phonons are typically scattered much more than low frequency phonons. Furthermore, when performing the typical mass – spring analysis it is assumed that the spring constant is independent of the spring deformation. However, when investigating the properties of strained chemical bonds we find that chemical bond strengths are a function of deformation. This has the implications then when a phonon collides with another lattice wave the continuous propagation of the new lattice wave may not have the same amount of energy. This type of event is called inelastic scattering and is responsible for direct resistance to heat flow.

Further investigation of scattering reveals that it is the discrete nature of atomic arrangements that dictate a minimum wavelength for phonon transmission. This wavelength is determined by the atomic spacing (a) and has a value of 2a. Since k = 2π/

λMFP, the maximum wave vector size would be k = 2π/2a = π/a, thus setting the upper limit for phonon propagation. Logically, this raises the question of what happens when two wave vectors are combined to form a third phonon that is larger than the upper limit

(i.e. K3 = K1+K2 > π/a). To solve this problem we must introduce a new term called the reciprocal lattice vector.43,46 This allows us to transform the disallowed phonon into a new phonon of a lower frequency in the opposite direction (e.g. the Umklapp process, see

Figure 2.2.2). The name for this scattering is derived from the German word umklappen meaning to turn over, and roughly presents the notion of non-conserved momentum by a change in direction.

Figure 2.2.2: (A) and (B) are two processes known as A Normal process is when one phonon scatters into two phonons. (C) Umklapp process where two phonons combine to create a third. Due to the discrete nature of the atomic lattice there is a minimum phonon wavelength, which corresponds to a maximum allowable wavevector. If two phonons combine to create a third phonon which has a wavevector greater than this maximum, the direction of the phonon will be reversed or flipped over with a reciprocal lattice vector G, such that its wavevector is allowed.47

Moreover, accurately quantifying and qualifying all the collisions and scattering mechanisms which contribute to the resistance of heat transfer remain one of the most demanding and difficult tasks in solving the thermal properties of solids. Traditionally, this task is numerically accounted for using the Matthiessen's rule. This states that the total relaxation rate in a solid is simply the sum of the individual constituents (see

Equation 2.2.1). However, it should be noted that the equations which govern the rate of each scattering mechanism depends heavily on heuristics, and thus fundamental challenges still remain in experimental determination of these quantities. Some of the tradition models used for calculating these rates are given in Table 2.2.1.

Equation 2.2.1: Matthiessen rule which inversely adds all scattering contribution where τi,j’s are the contributions of the various scattering mechanisms based on i, the modes of polarizations of the phonons, and j, the different types of scattering rates caused by impurities and mechanical lattice imperfections.43

Table 2.2.1: Various methods for calculation the scattering rate of phonons.48

2.2.2.3 Temperature Dependence of Phonon Scattering

The previous section described how the scatting time in a material will change due to the scattering mechanism. To further our understanding of these mechanisms it is necessary to describe how these events may change with respect to temperature. Wein et al. first described the elementary rules of waves with respect to temperature (see Figure

2.2.3).49,50 In this framework he introduces the concept of the dominant wavelength (i.e. the notion that the distribution of transmitted quantized waves will shift centered around a dominant wavelength). Wien’s displacement for phonons is defined as λdom = ħυg/3kBT, where ħ is Planck’s constant, kB is the Boltzmann constant, λdom is the dominant phonon wavelength. A plot comparing the dominant wavelength of various physical processes can be seen in Figure 2.2.3.

Figure 2.2.3: (Left) Blackbody emission intensity as a function of wavelength and temperature. Figure displays Wien’s displacement of dominant wavelength as a function of temperature.51 (Right)The change in the dominant wavelength of propagation as a function of temperature for various wave transport processes.52

The generalized overview presented using Wien’s theory is that at low temperature longer wavelengths phonons are the dominate heat carriers. This has several

29 implication, 1) the wavelengths are two long to be effectively scatter by defects, 2) phonon-phonon scattering is effectively frozen out since the wave vectors are so small, and 3) boundary scattering becomes the primary form of phonon resistance. This idea is schematically represented in Figure 2.2.4 where thermal conductivity is plotted against the normalized Debye temperature (θD) (i.e. θD = ħωd/kB, or the highest temperature possible due to a single normal vibration, where ωd is the Debye frequency).

Furthermore, when we increase the temperature we find that defect scattering starts to have a more predominate effect. This follows the logical argument that as the dominant phonons mean free path approaches the size of the defect it’s interacting with, scattering will increase. One could think of this idea as being similar to but opposite of the concept of resonance in harmonic oscillators. Continuing to increase the temperature still further we find that phonon-phonon scattering (e.g. normal and Umklapp) start to dominate the heat transport.

Figure 2.2.4: Temperature effects on the thermal conductivity of classical materials.47

2.2.2.4 Length Scale Effects

By understanding how the scattering in a material affects the thermal conductivity, it should come as no surprise that nanostructuring could severely impact thermal transport.

Nanomaterials from OD to 3D have a high ratio of surface to bulk atoms. This means that the transport that dominated in normal materials might be different in their nanostructured counterpart (e.g. the decrease in thermal conductivity of nanocrystalline diamond). Furthermore, when processing nanomaterials defects are often introduced.

These defects (whether they are surface, interstitial, or substitutional) increase the scattering rate and reduce thermal transport. However, this is not always the case and a more detailed investigation of this topic will be cover in subsequent sections.

2.2.3 Electrical Transport Phenomena

2.2.3.1 Characteristic Lengths for Electrical Transport

The movements of carriers in a material are dictated by the material composition, structure, and temperature. Critical to fully understanding how these parameters affect the transport of electrons, one must have a generalized perception of the characteristic lengths at which electrons move. Furthermore, since it is these characteristic lengths that determine the behavior of the systems, it seems logical to suspect that as we constrain a material to sizes smaller than these critical lengths the electrical transport will change.

One example of this is observed transition, from classical to quantum, in the transmission behavior of an electron through nanosized conductors.53-55 Moreover, this section will explore some of these characteristic lengths and how they are fundamentally important to

31 transport properties. They include the Fermi wavelength (λF), the electron mean free path

(Ɩe), and the phase relaxation length (Ɩφ)

The phenomenon of conductance quantization occurs when the constraining size of a material (e.g. diameter of a nanoparticle, or nanowire) is comparable to the electron

Fermi wavelength. The concept of an electron Fermi wavelength arises from the wave- particle duality (i.e. a mass particle can fundamentally behave like waves). This idea was first presented by Louis de Broglie in 1923, where he suggested that any mass has an associated vibrational wavelength. Using this knowledge, and the fact that most of the properties of solids are described by the dynamics of electrons near the Fermi level, the

Fermi wavelength is simply the de Broglie wavelength of electrons near the Fermi energy

1/d (see Equation 2.2.2). In general the Fermi wavevector (kF) is proportional to (n) , where d represents the dimensionality of the system, and n is the electron density. For most metals the value of the Fermi wavelength is between 0.1 nm and 1 nm.56 For semimetals such as Bismuth, the free electron densities are much lower and thus much longer Fermi wavelength have been observed (~26 nm).57,58

Equation 2.2.2: The Fermi wavelength of a material, where n represents the electron density.

The mean free path of a carrier (Ɩe)(either an electron or hole) is the average distance travelled before scattering (i.e. the mean free scattering length). There are several things that can scatter an electron traveling through a lattice. These include interaction with other electrons, emission and absorption events with acoustic phonons, emission and absorption events with optical phonons, interactions with impurity atoms,

32 interactions with lattice defects, and interactions with lattice boundaries. As seen with phonons the total amount of scattering can be evaluated using the Matthiessen expression

to sum the individual effects (i.e. Ɩe=τ vF)(see Equation 2.2.1). In pure metals, with relatively few defects, one finds that the electron movement without scattering can extend up to several microns at low temperature.59,60 In semiconductors and insulators the mean distance traveled is significantly reduced due and is typically between 1 and 100 nm.61,62

The last characteristic length that we will discuss here is the phase relaxation

length (Ɩφ). This is a quantum mechanical relaxation length which has no counterpart in classical physics. The phase relaxation length describes how far an electron can travel before losing its initial coherent state. This happens when electrons wave functions interfere with themselves to form standing waves. Interference inherently implies that the initial electron wave functions have phase coherence. Thus the distance traveled before an electron losses its phase coherence describes the relaxation length (see Equation

2.2.3). Furthermore, this has the consequence that observations of quantum interference cannot be made over distances larger than the phase relaxation length. The physical mechanism by which electrons lose phase coherence involves inelastic scattering. These include scattering by phonons, electron-electron collisions, and spin-flip processes.

Equation 2.2.3: The phase relaxation length as a function of the velocity of an electron at the Fermi surface vF, and the phase relaxation time (τφ) (i.e. the time taken for the phase fluctuations to reach unity)

Electrical transport in all materials is dictated by the characteristic lengths described above. The fundamental question to ask is what happens when a material is

33 confined to spaces smaller than these elementary lengths? Historically, electronic transport phenomena in low-dimensional systems are divided into two categories: ballistic transport and diffusive transport.63-65 Ballistic transport phenomena occur when carriers are observed to traverse a medium without any scattering. In this case, the conduction is not dominated by the intrinsic properties of the material and instead determined by the contacts to the external measuring circuit. Opposite of this effect, diffusive electronic transport is defined where scattering events dictate the observed electronic conduction. A comparison of theses transport mechanism can be seen in Figure

2.2.5, and subsequent section will review these topics in more depth.

Figure 2.2.5: (Left) a) Schematic of diffusive electronic transport (*) represent scattering events (l) is the mean free path, (L) is the length of the sample, and (W) is the width b)schematic of quasi-ballistic transport where only a few scattering events take place c) schematic of ballistic transport where no scattering takes place.64 (Right) Difference between diffusive and ballistic transport and the characteristic lengths involved.65

2.2.3.2 Diffusive Electrical Transport

When carriers traverse distances much larger than the carrier mean free path, they encounter multiple scattering events. In this regime, the scattering dictates the observed

34 electronic transport. The scattering mechanisms that dominate this type of transport include phonon, boundary, lattice, and impurity scattering. This type of transport is considered classical in nature, and electrical current density can be defined as j = σE

2 where σ is the electrical conductivity (σ = (e neτ/m*), E is the constant electric field, e is the elementary charge, ne is the electron concentration, m* is the mass of the carrier, and the relaxation time (τ)).65 When material become constrained in one dimension to sizes

less than the carrier mean free path (Ɩe), ( i.e., d ≈ Ɩe or d < Ɩe), but still much larger than

the Fermi wavelength of the electrons (d >> λF ), the transport falls into the classical finite size regime. This simply means that while the band structure of the material is similar to that of bulk, electronic transport may become dominated by boundary scattering instead of other scattering mechanisms.

In most current technological applications (e.g. semiconductor fabrication) the critical system dimension falls into the classical finite size regime (i.e. the diameter of features ~ 10 nm-100 nm). However, progress is steadily moving towards devices with smaller features and quantum effects might soon become very relevant. Additionally, it is possible to observe quantum effects in diffusive transport when electron interference significantly contributes to the resistance (i.e. localization effects or conductance fluctuations).66-68 This happens when the phase relaxation length is much greater than the normal scattering lengths. In conclusion, the diffusive transport of charge carriers represents a significant contribution to quantifying the observed carrier movement in real systems, and offers a solid framework for fundamental analysis.

2.2.3.3 Ballistic Electrical Transport

Ballistic transport implies that electrons can travel across a material without undergoing any scattering. Traditionally this transport regime is divided into two subsets, classical and quantum. Classical ballistic transfer occurs when the constraining dimension on a material is smaller than the phase relaxation length, and the electron mean free path; but larger than the Fermi wavelength. Experimentally this has been observed in pure metal nanowires, where the voltage drop across a nanowire can be attributed solely to the contacts.58 This is the regime of classical Ballistic transport.

Ballistic transport can also be quantum in nature. This occurs when the constraining size of material is close to or smaller than the Fermi wavelength. When materials become smaller than the electron waves traveling through them, the energy level of the electrons are forced into discrete quantum states. This happens due to the dramatic change in the electronic density of states, and the formation of quantum subbands. An additional requirement of quantum ballistic transport necessitates that a materials thermal energy (kBT) remains less the energy difference between conducting subbands (i.e. kBT < εj − εj−1 where εj is the energy of the j band, and εj−1 is the energy of the j-1 band). This quantum behavior can be modeled using the Lanauer formula seen in

Equation 2.2.4; where e is the electronic charge, ħ is the Planck’s constant, and Tij is the transmission probability from ith channel at one end of the conductor to the jth mode at the other end. This simply states that the total conductance is the sum of the value of all channels having a non-zero value of the transmission probability. If one assumes that no backscattering takes place at the contacts, Tij =1 for i=j and zero otherwise. That is G =

NG0, where N is the number of channels available for conduction. In this scenario the

36 conductance will be quantized into an integral number of universal conductance units

69,70 G0. The value of N depends on the constraining diameter of a material (e.g. for 1D systems N~ d/λF). Moreover, since ballistic conductance is dictated by the contacts and the characteristic lengths of a material, one observes discrete variation in conductance as a function of dimensionality.

;

Equation 2.2.4: Landauer formula describing quantum conductance in terms of universal conductance units.

2.2.3.4 Electron-Phonon Coupling and the Effect on Transport

Electron–phonon coupling (EPC) is of central important to the properties of solids. Ballistic transport, superconductivity, excited-state dynamics, Raman spectra, colossal magnetoresistance, and phonon dispersions all fundamentally depend on it.45

However, the non-local nature of the interactions of lattice waves and electrons present a formidable scientific challenge for prediction and measurement. Fundamentally, EPC can be described as the interaction of phonon induced charge density fluctuations with an electron gas. This is to say that as a lattice vibration distorts the distance between atoms there is a change in the electronic field around those atoms. Furthermore, this phonon induced field can cause changes to the electron gas which surrounds it, thus the potential created by the phonon is directly proportional to the EPC.

In crystalline materials, the linewidth observed for individual Raman active vibrations can be directly related to the inverse phonon lifetime (γ). This lifetime is determined by the anharmonic terms in the interatomic potential and the EPC (i.e., γ = γan

+ γEPC). If γan is negligible or otherwise known, measuring the linewidth proves to be an effective way to determine the contribution from EPC. This is the case in graphene,

17,25,28 graphite and metallic carbon nanotubes, where γan is much smaller than γEPC.

2.2.4 Concluding Remarks

Electron and thermal transport phenomena are critical to understanding how and why materials behave the way they do. Furthermore, one gains critical insights into how to manipulate these properties by evaluating the characteristic equations. Moreover, these transport properties are all governed by characteristic lengths; not only of the waves traveling through a materials but also of the boundaries placed by the material itself (e.g.

OD, 1D, and 2D systems). Therefore, controlled synthesis of nanostructured materials represents a critical tool towards the production of quantum devices, and offers an exciting means towards the quantum future.

2.3 Physical and Chemical Processing of Nanostructures

2.3.1 Introduction

Synthesizing nanostructures represents a critical technology in the field of materials science. The ability to actively control the structure and composition of matter has allowed some of the greatest scientific achievements in the last decade. In his historic

1960 speech Richard Feynman proclaimed that there is “plenty of room at the bottom”.71

Since this time society has benefited greatly by the explosive growth in nanotechnology.

This is best exemplified by the cheap, small, powerful processors that surround us every day. However, it is not only computer industry that has profited; every field from biology

38 to physics has been impacted, and it is with this core understanding that the importance of nanotechnology can be appreciated.

The objective of this review is to survey some of the fundamental technologies used for the creation of nanostructures. With an emphasis on carbon nanomaterials, physical vapor deposition (PVD) methods, chemical vapour deposition (CVD) methods, and wet chemical based methods are considered. The discussion on CVD and wet chemical methods will focus on the fundamentals of the techniques. Furthermore, the topics investigated for PVD techniques will cover thermal evaporation, sputtering, and matrix assisted pulsed laser methods. Throughout all the topics covered specific literature examples will be cited to establish their relevance in creating carbon nanostructures.

2.3.2 Physical Vapor Deposition Methods

Physical vapor deposition is a materials processing technique in which an atom or clusters of atoms are transported from a source to a desired substrate. It is a subset of the broader category of vacuum deposition. The standard physical vapor deposition involves three steps 1) the physical evaporation of the source material either into to gas or plasma phase and 2) the transport and 3) the renucleation of the source material at the substrate.

This type of processing has found broad acceptance in industry and is used to manufacture a plethora of different products from thin films on snack bags and cutting tools, to semiconductor device manufacturing.72 This section will explore three of the more standard types of physical vapor deposition and their use in creating nanostructures.

2.3.2.1 Thermal Evaporation Deposition Methods

Thermal evaporation of materials has been used for the past 200 years and still proves to be a robust and accommodating deposition technique.72 This simple technique involves the vaporization of material using a thermal source (e.g. a heated ceramic boat, or material placed in a refractory metal filament). The thermodynamics that determine the vapor pressure of the material is described by the Gibbs free energy of formation of vapor

(see Figure 2.3.1). Using this equation one can calculate what the expected partial pressure of a material will be given the temperature and pressure. Once the partial pressure of the vapor is known, the next main question involves how far each atom might travel before interacting with another atom at a given pressure and temperature (see

Figure 2.3.1A). Using the basis of kinetic gas theory one can derive the mean free path of an atom with respect to temperature, pressure and diameter. Combining these principles and assuming a Maxwell velocity distribution one can estimate what the flux of atom might be a given surface, thus allowing us to estimate the expected deposition rate (see

Figure 2.3.1B).

A B ) )

Figure 2.3.1: A) Partial pressure of a material with respect to Gibbs free energy of evaporation, R is the ideal gas constant, T is the temperature., l is the mean free path, kB is the Boltzman constant, p is pressure in pascal, d is the diameter of the gas particles, m is the molecular weight, Г is the particle flux B) an example of the Maxwell velocity distribution of nitrogen gas molecules at room temp. 73 Evaporation sources are typically classified as quasi-equilibrium or nonequilibrium. The major distinction between the two is illustrated in Figure 2.3.2C, where one can see that in the quasi- equilibrium case the orifice for gas molecule expulsion is typically much smaller than the gas mean free path. Furthermore, in the case of quasi- equilibrium one can assume that the amount of gas recondensing is equal to that in the vapor phase. This allows us to use the Clausius – Clapeyron equation (Figure 2.3.2A top right) to estimate the pressure of the escaping gas. It should be noted that for nonequilibrium sources (e.g. open boats), liquid – vapor equilibrium is never fully established and thus deposition rates are not stable and exhibit nonlinear behavior with time. Moreover, when investigating the thickness of the deposited film with respect to angle from the source, the kinetic gas theory outlines that the distribution must be the same as it is on the wall of the evaporator. This distribution follows the well-known

41 cosine law of emission as seen in Figure 2.3.2A and Figure 2.3.2B. When investigating the resulting distribution of thicknesses on a substrate, one can see that the variation is different for point sources and surface sources (see Figure 2.3.2D).

B A ) )

C D ) )

Figure 2.3.2: A) (Top Right) the Clausius – Clapeyron equation for pressure of gas, (Bottom Right) the cosine emission law for a point source as seen in “B)” Jv is emitting flux from surface, Q is the total evaporation rate from area A, K is the geometry factor, and r is the distance from the source. B) Diagram and geometry layout of a quasi-equilibrium cell. C) (Left) quasi-equilibrium cell (Right) nonequilibrium cell. D) Deposition thickness as a function of angle from the source.74 The deposition of fullerenes by means of thermal evaporation has been investigated several times.75-78 Some recent work from Buttner et al. investigated how fullerene molecules would stack and order deposited on defect-rich graphite.79 To induce the damage, and thus create nucleation sites for growth, highly ordered pyrolytic graphite was bombarded using a focused ion beam. When the thermal evaporation was complete they found that the films created had a suite of novel features comprised of enlarged

42 fullerenes, trimer, and hexamer nanostructures (see Figure 2.3.3). Furthermore, they linked the appearance of these features to the presence of graphite surface defects. This work exemplifies some of the unique nanostructures that can be created by means of simple thermal evaporation.

Figure 2.3.3: STM images of the hillock structure created by ion irradiation before (a) and after C60 deposition (b). An enlarged image of an area in between the hillocks (c) shows some trimers in the second fullerene layer. The orientation of the lattice is indicated by the solid lines. The table displays the types of defects observed in the film.79

2.3.2.2 Sputtering Deposition Methods

The basic sputtering process has been investigated amply and many materials have been successfully deposited using this technique.80,81 In the basic sputtering process, a target material (e.g. the cathode) is bombarded by energetic ions created in a glow discharge plasma. When ions from the plasma barrage the surface of the target, they have sufficient energy to expel surface atoms (i.e. sputtering). These surface expulsions take place as a collection of charged ions as well as neutral species, with the distribution of

43 each depending heavily on the type of sputtering. As the expelled atoms travel thru the plasma they lose energy and condense on a substrate as a thin film. Furthermore, as a result of the impact that caused the primary atom ejection, secondary electrons are also emitted from the target surface, which play an important role in maintaining the plasma.82

Moreover, several different types of sputtering have been used to allow control of the crucial deposition parameters (e.g. deposition rate, ionization energy, and charging issues).83 This section will briefly review both balanced and unbalanced magnetron sputtering.

Magnetron sputtering takes advantage of the fundamental Lorenz force (i.e. the curl motion of electrons in magnetic fields). To accomplish this, magnets are placed parallel to a sputtering target surface which subsequently confines the secondary electrons emitted to a smaller region of space near the target. Trapping the electrons in this way substantially increases the probability of an ionizing electron-atom collision occurring, thus creating a denser plasma.83 Furthermore, since there are an increased number of ionized atoms, the event likelihood of ion bombardment at the target also increases, thus giving higher sputtering rates. These higher efficiencies allow magnetrons to be operated at lower pressures (e.g. ~10-3 mbar compared to 10-2 mbar) and lower voltages (e.g. ~500 V compared to 2-3 kV) than traditional sputtering.81,83

The distinction between a conventional magnetron and an unbalanced magnetron are minor. However, the difference in performance can be quite drastic. In a conventional magnetron the plasma is strongly confined to the target region (see Figure 2.3.4).

Substrates placed inside this region will be strongly subjected to concurrent ion bombardment, which can greatly affect the structure and properties of the deposited

44 films.81,83 Furthermore, substrates placed outside of this region will not be subjected to this dense plasma and thus film growth is these regions may not contain the structural properties of those produced in the highly energetic regions. The energy of the bombarding ions can be increased by increasing the negative bias applied to the substrate.

However, this can lead to defects in the film and increased film stress, and therefore, be detrimental to the overall film properties.81-83 Moreover, to increase the area that contains the plasma one may use an unbalanced magnetron. In this arrangement one of the magnetic poles is larger than the other. This causes the magnetic field line to extend more towards the substrate, thus giving a larger processing window for concurrent ion bombardment (see Figure 2.3.4).

Figure 2.3.4: Schematic representation of the plasma confinement observed in conventional and unbalanced magnetrons.83

Several different types of carbon nanostructures have been synthesized using sputtering. Kundu et al. showed that nanocrystalline diamond films could be deposited at room temperature by high pressure (>45 mTorr) dc magnetron sputtering of vitreous carbon target in an argon + hydrogen (0-10 vol%) plasma.84 Furthermore, they illustrated

45 that the nanocrystallites of diamond were embedded in an amorphous carbon matrix where the ratio of sp3 and sp2 bonds in the film was dependent on the deposition conditions.84 Other carbon nanostructures, such as carbon nanotubes (CNTs), have also been created using sputtering. Yamamoto et al. reported the formation of carbon nanotubes by the argon ion beam irradiation of amorphous carbon under high vacuum conditions (~4 x 10-5 Torr).85 They noted that the CNTs were produced outside the sputtering region on the target surface. Moreover, while this is not the typical sputtering deposition, it does show the versatility of technique for the useful synthesis of carbon nanomaterials.

2.3.2.3 Matrix Assisted Pulsed Laser Evaporation (MAPLE) Deposition

MAPLE is a technique in which a presynthsized material (e.g. polymers or other organic material) is deposited on a substrate surface in a vacuum chamber. Typically one uses a laser to evaporate a frozen target which consists of the presynthesized material either dissolved of suspended in the volatile solvent matrix. The laser pulses vaporize the solvent and heat the solute material, causing them to enter the gas phase. A coating from the evaporated solute material is formed on the substrate surface, while the volatile solvent molecules are evacuated by the vacuum pump in the deposition chamber86. The process is similar to pulsed laser deposition, in which material is ablated from the target surface in the form of small molecules, ions, and atoms and settles onto the substrate to form crystalline bonds. In MAPLE, the energy from laser pulses are absorbed primarily by the frozen solvent matrix, and thus allows film deposition to occur with little or no

46 damage to the transported solute material86-89. These processes are illustrated schematically in Figure 2.3.5.

Figure 2.3.5: Schematic illustrations of a) pulsed laser deposition and b) MAPLE.

Recently MAPLE has been used to deposit carbon nanostructures. Because of its ability to volatilize molecules while keeping the molecular structure and properties of solute material intact, MAPLE is a promising technique for depositing ex situ created carbon nanostructures. Notably, Hunter et al. were able to demonstrate the successful deposition of carbon nanopearls on silicon substrates.90 Furthermore, they found that the morphology of the carbon nanopearl films was influenced by multiple factors, including composition of the matrix solvent, laser energy and repetition rate, background pressure, and substrate temperature. With this knowledge they were able to process advanced nanocomposite materials with advantageous tribological, mechanical, and physical properties.91 Moreover, this work epitomized how MAPLE could be used to create carbon nanostructured materials.

2.3.3 Chemical Vapor Deposition (CVD) Methods

Chemical Vapor Deposition (CVD) involves the dissociation and/or chemical reactions of gaseous reactants in an activated (heat, light, plasma) environment, followed by the formation of a stable solid product.92,93 The typical deposition involves a

47 homogeneous gas phase reaction, and/or a heterogeneous reaction on/near the vicinity of a surface leading to the formation of solids. The most common CVD method, uses thermal energy to activate the chemical reactions (e.g. thermally activated CVD).

However, the activated species can also be initiated using different energy sources. Such variant methods include plasma enhanced CVD (PECVD) and photo-assisted

CVD(PACVD) which use plasma and light, respectively, to activate the chemical reactions (see Figure 2.3.6).92,94 Furthermore, CVD techniques can be used to create

‘monatomic layer’ where the growth is controlled by the sequential saturation of surface reactions (e.g. atomic layer epitaxy). Using such CVD variants one can exquisitely control the fabrication of tailored molecular structures. Moreover, CVD is one of the most versatile deposition techniques and finds many uses in the formation of nanostructures. This section will explore some of the recent results on the production of

2D, 1D, and 0D carbon nanostructures.

Figure 2.3.6: A) Schematic for thermal activated CVD92 B) Schematic for plasma enhanced CVD 95

Two dimensional carbon materials covering a relatively large area (i.e. the length and width covered compared to the film thickness is several orders of magnitude apart) were recently presented by Reina et al. and others (see Figure 2.3.7C).96,97 In this work they used ambient pressure CVD to fabricate large area (~cm2) films of single- to few- layer graphene. They suggested that during the exposure of the Ni surface by the H2 /

CH4 gas mixture, a solid solution was formed. Since the solubility of carbon in Ni is temperature-dependent, carbon atoms precipitate as a graphene layer on the Ni surface upon cooling of the sample.96,98 Furthermore, they observed that as the sample was put through additional thermal cycling the Ni layer would become discontinuous due to the formation of grain boundaries, thus allowing easy removal of the graphene films. Further investigation revealed that the films consisted of regions of 1 to 12 graphene layers with single- or bilayer regions covering up to 20 μm in lateral size, with continuous coverage over the entire area.96 Moreover, this paper demonstrated the successful formation of graphene on a large scale with an easy transfer method, suggesting possible near term use in electronics and opto-electronic applications.96

A C ) )

B )

Figure 2.3.7: A) Atomic force microscopy of a nanocrystalline diamond thin film 99 B) Scanning electron microscope image of single walled carbon nanotubes100 C) Optical microscopy image of graphene layer on glass96

CVD techniques have also been used in the synthesis of bulk quantities of high quality one dimensional single-walled carbon nanotubes (SWNTs).101-104 In most cases,

SWNTs are synthesized by optimizing the chemical compositions and textural properties of the catalyst materials used in reactors. However, the other crucial component for the synthesis relies on controlled delivery of the carbon source. Cassell et al. performed a systematic study of various catalysts and substrate systems and worked to optimize the ratio of Fe/Mo bimetallic species supported on a novel silica-alumina multicomponent material.100 After thorough investigation they found a system where one could achieve a high SWNT yield (see figure 7B). Furthermore, the nanotube material created consisted of individual and bundled SWNTs that were free of defects and amorphous carbon

50 coating. This work represents a step forward toward obtaining kilogram scale perfect

SWNT materials via simple CVD routes.100

One dimensional carbon nanomaterials have also been created using CVD processes (see figure 1). A review by Butler et al. laid out the current state of the growth and characteristics of nanocrystalline diamond thin films.99 When investigating both, ultra nanocrystalline diamond (UNCD), and nanocrystalline diamond (NCD) several factors were found to control their growth. Furthermore, within this class of materials there is a continuous range of composition, characteristics, and properties which depend on the nucleation and growth conditions.99 UNCD is usually grown in argon-rich, hydrogen-poor CVD environments and may contain up to 95–98% sp3-bonded carbon.

NCD is generally grown in carbon-lean and hydrogen-rich environments. Moreover, the major findings of this review concluded that both the processing conditions (e.g. gas ratios and plasma biasing) along with the nucleation strategies (e.g. seeding techniques) greatly affected the final structure of the films.99

CVD is a broad and versatile technique used to create a plethora of different carbon nanostructures. By understanding the growth mechanism and finely controlling the processing parameters, exquisite control of the final structures is possible.

Furthermore, CVD techniques represent a scalable process for the means to create manufacturable quantities of nanomaterials. Future investigations for various CVD techniques should lead to substantial societal gains in the world of materials.

2.3.4 Wet Chemical Based Methods

Wet chemical techniques are the oldest methods for the formation of nanometer and sub-nanometer materials. Advanced understanding of chemistry has allowed the development of extraordinarily sophisticated procedures for the assembly of molecules.

Furthermore, these principles can be used to finely control the structural formation of desired materials. Typically, the synthesis of large molecules and their assemblies is broken into four categories: 1) controlled formation of covalent bonds, 2) covalent polymerization, 3) self-organization, and 4) molecular self-assembly.105,106 The following will provide a brief overview of these assembly methods with subsequent text discussing the use of these methods for the formation of carbon nanostructures.

Sequential covalent synthesis can be used to generate arrays of covalently linked atoms with well-defined composition, connectivity and shape.106 However, extending the synthesis to nanostructures remains a difficult task. Polymerization (e.g. the synthesis of long chains and cross-linked networks) provides a direct route towards stable nanostructures.107-109 Nevertheless, lack in fine control over the noncovalent interaction still remains a challenge for the production of bulk nanomaterials. The third synthetic strategy takes the opposite approach, and seeks fine control over the noncovalent interaction (e.g. ionic bonds, hydrogen bonds, and van der Waals interactions).105 Some examples of this include molecular crystals, colloids, and micelles. Finally, the fourth strategy makes used of the same approach seen in self-organization, however, it is applied at the molecular level instead of the atomic level. Critical understating of self- assembly involves the notion that the ions, atom, or molecules spontaneously assemble by trying to reach a thermodynamic minimum.106

Using the basis of molecular self-assembly Ji et al. demonstrated the growth of

110 single-crystalline C60 nanorods. The formations of these structures were attributed to the intrinsic properties of the C60 –CTAB complex and the concentration profile of the

C60 at the seed crystal. They speculated that since the C60 –CTAB complex was highly anisotropic, and crystallization of the solid was constrained to grow in only the [001] direction, thus forming the basis for a one dimensional material (see Figure 2.3.8).110

Furthermore, they found that as the crystal was growing free C60 molecules in solution preferential nucleated at the edge site of the wire (i.e. the corner sites have a higher free energy). They also established that by varying the concentration of C60 in solution they could affect the length and the length to width ratios. Overall, this work demonstrated a facile solvent induced self-assembly mechanism for the formation of nanorods and tubes, which might allow for single pot processing of bulk nanostructures in the future.

Figure 2.3.8: Electronic microscope images of submicrometer rods (a-d) and tubes (e-g) of C60. (Right) Schematic illustration of the formation process of C60 1D submicrometer structures. The black solid arrows and red dashed arrows on the crystal seed represent different growth rates.110

Other types of self-assembled nanostructures have also recently been demonstrated. Sano et al. verified the growth of hollow spherical cages made of nested single-walled carbon nanotubes.111 This task was accomplished by adsorbing SWNTs onto an amine terminated silica gel in solution (see Figure 2.3.9). Once a monolayer of nanotubes was attached, the solution was centrifuged and the supernatant was collected and dried. This process was then repeated many times to build the structure layer by layer. They further speculated that it was the absorption of the first layer that ultimately determined the network structure and that van der Waals attraction from tube to tube built the network.111 This type of self-assembly on a pre-fabricated template represents an interesting approach to synthesizing carbon nanostructures, and could lead to promising returns in the future.

Figure 2.3.9: (Left) SEM image of SWNT cages after 3 cycles. Some cages were crashed and deformed as water evaporated during the sample preparation. The bar is 15 mm in length.111

Recent work has successfully demonstrated the self-assembly of graphene sheets into high-performance thin films via multiple-step processes.112,113 Extending the usefulness of these chemical techniques, Xu et al. demonstrated the formation of three

54 dimensional self-assembled graphene macrostructures.114 This was accomplished via a one-step hydrothermal method (see Figure 2.3.10), where graphene oxide was first suspended in a solution, and then thermal evaporated, leaving behind a 3D network.

Furthermore, they were able to demonstrate that when the graphene oxide sheets were hydrothermally reduced they became regionally hydrophobic (i.e. the loss of the oxygen).

This further causes the sheets to restore their conjugated domains. Furthermore, the combination of hydrophobic and hydrophilic interactions caused a 3D random stacking between flexible graphene sheets. They also found that by controlling the concentration of the starting sheets various pore sizes could be created (see Figure 2.3.10).

Figure 2.3.10: (Top) Scanning electron microscope images of free standing self- assembled network of graphene oxide. (Bottom) Proposed formation mechanism.114

Overall, wet chemical techniques represent an exciting addition to the materials scientists’ toolbox for the construction of nanomaterials. It was demonstrated that several different types of structures could be synthesized using these techniques, and that weak chemical interaction typically dominated the self-assembly. By further studying and controlling these interactions great advances in bulk synthetic nano-manufacturing might be possible.

2.3.5 Concluding Remarks

In this section we investigated some of the fundamental technologies used for the creation of nanostructures. More specifically, the fundamental topics and applications of physical vapor deposition (PVD) methods, chemical vapor deposition (CVD) methods, and wet chemical based methods were reviewed. In highlighting these techniques, we saw how a broad range of carbon nanostructures could be synthesized. Moreover, these techniques represent a broad range of useful tools for materials scientist, and I look forward to their application.

2.4 Thin Film Processes

2.4.1 Growth Modes with Thermodynamic and Kinetic Considerations

The growth of nanostructures represents some of the greatest technological achievements of the 21st century. It has been from this fundamentally important work that society has seen the advent of entirely new fields such as semiconductor processing, biological sensing, and wireless communications. Thus comprehending the core mechanism by which these materials can be created has inherent value. Furthermore, this

56 review seeks to explain some of the fundamental mechanisms by which nanostructures are currently produced. We will start with the basic concepts involved in the nucleation and growth of thin films. Using these basic principles, we will derive the mechanisms involved in the growth of other nanostructures (e.g. nanowires, and nanosheets).

When investigating the primary mechanism involved in the growth of surface nanostructures, one must be cognizant of the fundamental forces controlling the atoms movement. Some of the original ideas on how thin films grow extend from the basis that adsorbed species (e.g. adatoms) are transported across a surface by a random hopping process.115,116 This type of movement is commonly referred to as diffusion (D) and is thermally activated (i.e. the movement of atoms requires energy to surmount the forces that hold them in their stable (or metastable) states). As is for most thermally controlled processes, surface diffusion follows the typical Arrhenius rate expression. However, surface diffusion is not the only force to consider when dealing with growth. Let’s consider a growth experiment where atoms are constantly bombarding a surface a rate F

(see Figure 2.4.1). If the rate of F is substantially smaller than the diffusion rate D, growth would be considered close to equilibrium (i.e. all atoms had enough time to explore the surface to find a local energy minimum). However, if F is much larger than

D, then atoms do not have time to discover the entire surface, and often metastable structures are created. This outlines one of the key growth parameters as the ratio of D/F

(i.e. the average distance an atom must travel before finding another adsorbate).

Furthermore, determining what happens when the adatoms meet (e.g. nucleation of a new aggregate or continued growth of a previously adsorbed aggregate) is critical in understanding the final morphology.

Figure 2.4.1: Schematic displaying how film nucleation can be dominated by kinetics or thermodynamics. 117

2.4.2 Theory of Nucleation and Growth

Detailed examination of the major processes involved in thin film growth has been performed amply in the past.118-120 This section will briefly explore some of the major concepts beyond the kinetic and thermodynamic arguments for film nucleation and growth. Outlined in Venables et al. comprehensive work are the fundamental atomistic processes that dominate thin film growth.121 These processes include re-evaporation or re-solution, nucleation of 2D or 3D clusters, capture by existing clusters, possibly dissolution into the substrate, and capture at special (defect) sites such as steps (see

Figure 2.4.2).121-123 It was further noted that each of these processes will be governed by characteristic times (see Figure 2.4.2). Often, these characteristic times are driven thermally, and the rate follows an Arrhenius type relation.

Figure 2.4.2: (Left) Examples of the typical forces encountered when investing the mechanism involved in thin film formation.123 (Right) Characteristic time for thin film nucleation and growth processes.124

So far, Figure 2.4.2 has indicated that we are concerned primarily with two independent experimental variables (e.g. F, the rate of condensation, and Ts, the temperature of the surface for thermally activated processes). With these variables one can obtain a basic picture of the fundamental processes, however, to fully characterize all the surfaces processes we also need three independent material parameters (Ea, surface re-evaporation energy, Ed, surface diffusion energy, and Ei, binding and nucleation energy). Furthermore, it should be noted that this only describes the behaviors of an atom on an idealized surface and real surfaces may contain a number of defects (e.g. dislocations, ledges, kinks, and point defects).122,124 When considering these realized surfaces these defects can have a substantial effect on the binding, diffusion, and nucleation energies. The best example of this is the preferential growth at ledges, where ones finds a substantially lower barrier to growth since there is virtually no nucleation energy to overcome for continued growth.

The last topic that is illustrated in Figure 2.4.2, presents the generalized idea of surface re-arrangement processes. This is the notion that once clusters form, they may or may not be in their most stable state, and thus rearrangements might take place. Several processes make this possible and include mixing of species (alloying), shape changes

59 caused by (surface) diffusion and/or coalescence, annealing of defects, etc.123 This further signifies the importance of diffusion processes in thin film formation, and suggests that they occur at all scales from the formation of small clusters to the rearrangement of large islands.

2.4.3 Types of Growth

2.4.3.1 Island Growth Systems

It is generally accepted that there are three possible modes of crystal growth

(outlined originally by Bauer et al.) on surfaces, these are schematically illustrated in

Figure 2.4.3.122,125 In the first type of growth (e.g. island or Volmer Weber growth), one observes small clusters that condense on the substrate into an island like formation. The generalized theory surrounding this formation speculates that the atoms or molecules have a stronger affinity (e.g. bonding) for each other than they do for the surface of the substrate. Traditionally this type of growth has been observed when metals are grown on insulating substrates.123,124

Figure 2.4.3: Schematic representation of the three crystal growth modes: (a) island or Volmer-Weber, (b) Krastanov layer or Frank-van der Merwe mode, (c) layer plus island or Stranski-. θ represents the coverage in monolayers (ML).121

2.4.3.2 Layered Growth

Opposite the island growth mode is layered, or Frank-van der Merwe mode (see

Figure 2.4.3B). In this growth scenario atoms are more strongly bound to the substrate than they are to each other. This causes the atoms to condense in a complete monolayer of coverage on the surface. Subsequent layers are less tightly bound but continue to grow as stacks of coherent monolayer, with energy of the film heading towards that of the bulk single crystal. Typically this type of growth is observed in the case of adsorbed gases, such as rare gases on graphite and on several metals, in some metal-metal systems, and in semiconductor growth on semiconductors.122

2.4.3.3 Stranski – Krastanov Growth

The last type of thin film growth that is typical observed is a hybrid between island and layered growth, typically referred to as the layer plus island, or Stranski-

Krastanov, growth mode (see Figure 2.4.3C). In this type of growth one observes that after forming the first monolayer (ML), or a few ML, subsequent layer growth is unfavorable. Instead of continuing the monolayer growth one finds islands formed on top of this ‘intermediate’ layer. This effect can be caused by several different factors, however, they typically involve a decrease in the monatomic binding energy. Some examples of this include a change in lattice parameter, or molecular orientation in the intermediate layer. Such a change would cause a large free energy in this layer, thus forcing more island like growth after the first ML.122 Furthermore, this type of growth has been observed in metal-metal, metal-semiconductor, gas-metal and gas-layer compound systems.123,124

2.4.4 Literature Examples of Carbon Nanostructured Growth

The ability to control the spatial or temporal transition in materials allows the formation of different types of nanostructures. This approach is very powerful, especially if one considers the size effects that take place when materials become nanostructured

(i.e. the band structure both electronically and phonically can be significantly impacted).

Moreover, observation of controlled thin film growth in carbon nanostructures has been recently demonstrated.126-129 This section will summarize some of the recent results on these materials.

Kenney et al. presented a scanning tunneling microscopy study of C60 thin films evaporated onto the basal plane of highly orientated pyrolytic graphite under ultrahigh

130 vacuum conditions. They demonstrated that when C60 was deposited at room temperature with low deposition rates, the C60 films would grow with island like formation (see Figure 2.4.4). Furthermore, they found that island growth for C60 was

62 nucleated at edge site on the surface, with the size of the defect directly correlating to the size of the island. They also noted that continued growth beyond a monolayer would lead to the production of stable bilayer islands (indicating that there might be some stable 3D growth). These results were juxtaposed by the depositions that they performed at higher temperatures where layer by layer growth dominated. The argument for why these structures formed was ultimately reduced to kinetics vs. thermodynamics, where the room growth displayed fundamentally kinetically limited processes.

Figure 2.4.4: A) Island growth of C60 on graphite at room temperature, B) Layer by 130 layer growth of C60 observed at 100⁰C.

Furthering the concepts of thin film deposition of carbon nanostructures,

131 Nakayama et al. produced C60 nanowires on Si substrates. To fabricate these structures the intrinsic selective adsorption of C60 molecules along step defects was exploited.

Basically the idea addresses the fundamental issue of C60 nucleation, proposing that C60 is

63 much more strongly bound at edge dislocation then other surface sites. Furthermore, by selectively controlling the temperature of the deposition they were able to preferentially remove non-edge bound C60 aggregates, thus forming nanowires along the edge defects

(see Figure 2.4.5B). This type of structuring further shows the power in understanding nucleation and growth, and represents a powerful method for the creation of fullerene nanostructures.

(b)

Figure 2.4.5: A) Scanning tunneling microscope image of C60 nanowires formed on misorientated Si (111)-Ag substrates (200nm x 200nm), B) A model for the growth 131 of the C60 nanowires. 2.5 Characterization of Nanostructured Materials

Nanostructured materials are increasingly subjected to nearly every type of analysis possible. There sizes dictate their unique properties, and thus characterization techniques that focus on high spatial resolution have become common place.

Furthermore, because nanomaterials have a very high surface to bulk atom ratio, techniques which rely upon surfaces analysis have become fundamentally important.

Regardless of the approach, the investigation of nanostructured materials presents a

64 variety of challenges to adequately understand their unique structure property relationships. This review will cover some of the elementary techniques used for the analysis of nanomaterials. These include electron microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy, and X-ray diffraction.

2.5.1 X-Ray Photoelectron Spectroscopy (XPS)

XPS is a spectroscopic technique in which one can gain understanding of the chemical composition present in the first few monolayers of a material or film.132-135 The basis for XPS involves the photoelectron effect, in which an electron can be ejected from an atom if it is irradiated by an electromagnetic wave of sufficient energy (see Figure

2.5.1). In XPS the source of electromagnetic energy is an X-ray beam, typically generated from metals irradiated by energetic electrons. Once the X-rays reach the analysis materials, electrons are ejected from various orbitals of the host atom. To resolve the amount of energy the ejected electrons have, they are typically fed through a concentric hemispherical analyzer. This device selective screens the energy of the emitted electron by passing it between a fixed electric field created by two concentric metal hemispheres. The electric field strength is then varied throughout time to selectively separate the relative intestines of the incoming electrons. Moreover, XPS gives selective information on the chemical composition of a desired material, and can also suggest the nature and/or strength of bonding.

136 Figure 2.5.1: Schematic for a typical XPS process.

2.5.2 X-Ray Diffraction (XRD)

In the basic principles of XRD an X-ray beam is exposed incident to an array of atoms. This interaction between the incident electromagnetic wave (e.g. the X-ray) and the electron clouds within the atom force a scattering event. Typically the scattered X- rays are redirected without a change in energy (i.e. the incoming and outgoing X-rays have the same frequency), this type of scattering is referred to as elastic or Rayleigh scattering. When considering the case where atoms are systematically distributed (e.g. a crystal lattice) and exposed to a monochromatic source of X-rays one could envision several scattering events taking place simultaneously. Furthermore, depending on the angle and spacing between the events, the scattered X-rays could interact in both a constructive or deconstructive fashion (see Figure 2.5.2). One other possibility is that the scattered waves themselves become scattered, however, the probability of this in

66 crystalline materials is small and thus assumed negligible. Moreover, if one were to analyze the intensity of the reflected waves vs. the incident angle the expected result would be a unique diffraction pattern. Additionally, besides giving a distinctive fingerprint, the spacing and intensities given in the spectrographic pattern will relay specific crystallographic information about the analyzed material. This analysis is called

Bragg diffraction and can be used to determine atomic spacing.

Figure 2.5.2: (Left) Schematic of diffraction of an X-ray in a crystal structure where there is constructive interference, (Right) Example of deconstructive interference and equation for Bragg’s law.137

2.5.3 Raman Spectroscopy

Raman spectroscopy is a technique used to investigate various vibrational, rotational, torsional, and other low-frequency modes in a material.41,138,139 Opposite of traditional absorption or reflection spectroscopy, this technique makes use of the relatively small amount of light that is inelastic scattering. Commonly this type of scattering is referred to as Raman scattering. First observed by Sir C.V. Raman by use of focused monochromatic sunlight on a chloroform sample, the technique requires the use 67 of a high intensity monochromatic light (due to the small cross section for inelastic scattering) (see Figure 2.5.3). Thus in modern day the procedure often uses laser light to probe the inelastic electromagnetic interaction with molecular vibrations, phonons or other excitations in a system. The traditional model for the spontaneous Raman effect, depicts a photon exciting a molecule from its ground state to a higher virtual energy state

(see Figure 2.5.3). When the light is reemitted the molecule relaxes back to a different rotational or vibrational state. The net result is a shift in the observed frequency of light

(both up and down, known as stokes and antistokes shifts) (see Figure 2.5.3). This effect should not be confused with fluorescence where the system is excited to a discrete energy level. This technique is useful for both “fingerprint” identification, and in determining how structural changes can affect the vibrational modes in a given system.

Figure 2.5.3: (Left) Schematic of Sir C.V. Raman first observing inelastic scattering in a chloroform sample,140 (Right) Energy diagram of various scattering and absorption techniques.141

2.5.4 Electron Microscopy

Various microscopy techniques have existed for the last four hundred years, with the basic principle consisting of some type of electromagnetic wave interacting with a

68 sample to generate an image.142,143 One important concept is that the resolution of an image (i.e. the maximum magnification) will be limited by the wavelength of the probing beam. Thus, the use of sources that have much smaller wavelengths such as electron beams (~100,000 times shorter than visible light) become necessary to create images of vary high magnifications. This concept is best exemplified by the fact that current electron microscopes can produce images of around 50 pm resolution and magnifications of up to about 10,000,000x compared to non-confocal light microscopes which are diffraction limited to ~200 nm resolution or 2000x magnification.

The technology that make the electron microscope possible, fundamentally involve the same principles as optical microscopes, except that instead of using diffraction lenses to focus the source beam, electrostatic and electromagnetic "lenses" are used to confine and control the source electromagnetic wave.144 Furthermore, there are two main types of electron microscopes commonly referred to as either transmission electron microscopes (TEM) or scanning electron microscopes (SEM).

In the operation of TEM an electron beam is focused to a small spot size and transmitted through a sample (see Figure 2.5.4A). During the transmission some of the electrons lose energy by interacting with the material, and others are elastically scattered.

Thus when the electron beam is magnified after the transmission, information as to the structure of material has been transferred to the electrons. This spatial variation is typically portrayed as an image of the source material. Moreover, one downside to this technique is that in order for electrons to pass through the material, they must be very thin (<100 nm).144 Unlike TEM, where the electron beam carries all of the image information at the same time, SEM involves the use of a rastered electron beam across a

69 sample surface (see Figure 2.5.4B). When the beam interacts with the surface the electrons typically lose energy. This can happen through a variety of mechanisms, such as creation of heat, emission of low energy secondary electrons, light or X-ray emission, or emission of high energy backscattered electrons.145 Furthermore, since the beam is rastered these emitted signal and their relative intensities can be mapped over an area, thus producing an image. However, it should be noted that since an SEM relies on surface processes, image resolution is typically an order of magnitude lower than that of a

TEM.

A) B)

Scanning Electron Microscope

Figure 2.5.4: A) Schematic of a transmission electron microscope,146 B) Schematic of a scanning electron microscope.147

CHAPTER III

RESEARCH OBJECTIVES

3 Research Objectives

3.1 Investigate the structure, chemistry, morphology and formation mechanism of carbon nanomaterials (DNA, and C60)

The formation of nanostructures of various carbon materials is of high interest to many researchers. It is the objective of this study to investigate the structure (i.e. the chemistry, and morphology) of low dimensional carbon materials. This will be accomplished using several different techniques and carbon materials. The techniques of primary interest for low dimensional formation include MAPLE, thermal evaporation,

CVD, and wet chemical synthesis. These techniques were selected as they offer a diverse mechanism for deposition and synthesis of carbon nanomaterials.

3.1.1 Motivation for the use of DNA-CTMA

Deoxyribonucleic acid, complexed with cationic surfactant cetyltrimethylammonium chloride (DNA-CTMA), has recently been displayed as a promising material for bio-electronic and photonic applications 148-151. For these types of applications thin film processing becomes an essential part of successful device formation. Traditionally, DNA-CTMA has been deposited using spin coating and

71 molecular beam deposition 152,153. In this paper we explore the use of matrix assisted pulsed laser evaporation (MAPLE) for deposition of thin films of various molecular weight DNA-CTMA. MAPLE has previously been shown to be an effective technique for thin film deposition of bio-materials 154,155. MAPLE further offers the advantage of multi-component processing (i.e. MAPLE and magnetron sputtering) without having to expose the deposited material to atmospheric conditions. Multi-component processing becomes especially important when considering the use of this material in organic light emitting diodes 150.

3.1.2 Motivation for the use of Fullerides

Thermoelectric (TE) devices are distinctive in that these solid state devices can be used for efficient electric heating and heat pumping, cooling and refrigeration, power generation as well as energy scavenging, and sensing. The efficiency of TEs as measured by specific power (W/kg of system) is often better than competing technologies for small scale applications (< 100 W), though for most applications TE efficiencies do not compare favorably with alternative technologies. Generally TEs are utilized in applications for which cost and efficiency are not as important as reliability, quiet operations, independence of orientation, or convenience. The Voyager and Cassini deep space missions have demonstrated the long term reliability of TEs for primary power generation in an environment in which reliability and predictability are at a premium, while more recently the use of TE elements in portable food coolers and automobile seat coolers are penetrating the commercial sector. The much broader societal impacts of

72 highly efficient TEs for power and thermal applications have been recently re-assessed and give strong impetus for discovering and developing new TE materials.156,157

The relative efficiencies of TE materials and TE devices are usually compared

2 based on ZT, the dimensionless figure-of-merit defined as ZT = S T/(el) where is the electrical conductivity, S is the Seebeck coefficient or thermopower, T is the absolute temperature, e is the thermal conductivity contribution from free electrons, and l is the thermal conductivity from lattice contributions. While effective in describing the efficiencies of TE materials, ZT does not account for thermal losses experienced when the material is incorporated into a device. Several recent papers have described device level modeling and it is estimated that 10-30% of the device efficiency can be loss due to heat sinks and thermal interfaces.158-162 These device level losses can be largely explained by surface defects which can cause large temperature discontinuities at the interfaces.

Furthermore, since most thermal electric materials are brittle the majority of device level geometries have been limited to planar orientations. Use of flexible TEs would allow both increases in ease of device manufacturing, and improvements in device efficiencies.

Furthermore, the TE material presented here is nontoxic, cheap to produce, and not limited by physical resources. These types of improvements could lead to a paradigm shift in the use of TE devices. Some examples of this would be large increases in the cycling times in portable polymerase chain reaction devices, wide deployment of autonomous sensing nodes, wearable TEs for energy harvesting, and direct temperature regulation for biological samples (e.g. blood / organ transportation).163-166

Recent research has suggested that by using nanotechnology (i.e. nanostructuring

/ nanoengineering) large advances can be gained in controlling interfaces to hinder

73 thermal transport while allowing electrical movement. Thin film structuring of thermoelectric materials potentially offers several advantages over bulk thermoelectric materials. It has been suggested that by making thermoelectric materials very small, one can achieve an enhanced ZT (the thermoelectric figure of merit) due to quantum confinement effects.167-170 It has also been shown that one can enhance ZT by creating superlattice architectures.171-174 The superlattice structure lowers the effective thermal conductivity in two main ways: 1) it allows for a potentially large acoustic mismatch between layers, and 2) it offers more locations for diffuse interface scattering. Thus, the creation of thin films of thermoelectric materials becomes an important aspect in the design and creation of high efficiency thermoelectric devices.

A new class of promising TE materials are fullerides built from metals and fullerenes such as C60, C70, C80, C120 etc. Metal fullerides prepared from alkali and alkaline earth metals were studied in the 1990s because a number of them showed promising and novel superconductive properties.175-177 These were prepared by direct reaction of the metal with C60 in sealed tubes at elevated temperatures according to the general reaction xM + C60 = MxC60. One remarkable feature of C60 is its facile ability to reversibly accommodate six electrons and hence a variety of stoichiometries are possible

178 and fulleride salts with charges from -1 to -6 on the C60 have been prepared. In this context the fulleride moieties can be considered superatoms, as many of their important properties originate from the cluster unit acting as a cluster, rather than properties of the individual constituent atoms. While superconductive materials are not of interest for TE applications since thermopower of a superconductor is identically zero, non- superconducting metal fullerides are of interest for at least two reasons. First, metal

74 fullerides can be highly electrically conductive tending to favor a high ZT. Second, the neutral fullerenes have exceptionally low thermal conductivities which if this persists in the metal fullerides, will also tend to favor a ZT.

The preparative routes to metal fullerides are rather limited beyond sealed tube reactions involving low melting alkali and alkaline earth metals. Reacting elemental zinc with C60 under such conditions results in destruction of the fullerene cage, and metals with proclivities to form stable metal carbides do not form fullerides. Zinc metal will reduce C60 in the presence of proton donors, but no zinc fulleride has been reported.

3.1.3 Motivation for Deposition Techniques

MAPLE will be used to investigate the thin film formation mechanism of DNA-

CTMA and C60 thin films. MAPLE is a versatile technique, and through the manipulation of the process parameters (i.e. repetition rate, fluence, and pressure), correlations as to the film formation mechanism should arise.

Thermal evaporation is one of the oldest techniques used for thin film deposition and while simple, does offer a fine amount of control for deposited films. Processing conditions investigated using this technique include material thermal stability, and interaction of a vapor plume while magnetron sputtering.

Chemical vapor deposition offers one of the most diverse processing techniques for combined carbon material formation and nanostructuring. The other techniques require that the deposited materials be pre-synthesized, whereas, CVD allows both synthesis and formation to take place simultaneously. Moreover, CVD will be investigated as an alternative formation mechanism of nanostructured carbon materials.

3.2 Correlate the structure, chemistry, morphology of carbon nanomaterials with their physical properties

3.2.1 Thermal Properties

The thermal properties of a material are dictated by the lattice and electron dynamics. Furthermore, since structure, chemistry, and morphology all impart their own change to the lattice and the movement of electrons; it should come as no surprise that they play a critical role in determining the thermal transport properties of a material. This work is directed at characterizing how these changes impact the phonon movement in nanostructured carbon materials.

3.2.2 Electrical Properties

The electrical properties of a material are dictated by many of the same constraints given for the thermal properties, however, since the fundamental mean free path of electrons in much different than phonons new correlations arise. The objective here is to establish fundamental relationships between the structure and chemistry of the various carbon materials discussed and their electrical transport properties.

3.2.3 Electron-Phonon Coupling

The previous two objectives asked the question how the transport properties of phonon and electrons are affected by structure and chemistry. This section will explore how electron and phonon can interact with each other, and how morphology and chemistry can impact this.

3.3 Establish a fundamental relationship between the transport mechanism and the structure in DNA, and C60 based materials.

The overarching goal of this work is to outline a framework for the controlled synthesis of carbon nanostructures. Once growth conditions are established, the relationships between these nanostructural formation and their primary transport properties will be investigated.

CHAPTER IV

EXPERIMENTAL METHODS

4 Experimental Methods

4.1 Nanostructure Deposition/Formations Methods

4.1.1 Formation of the DNA-CTMA Complex

DNA-CTMA complexes for solution spinning were prepared according to the reported procedure.179 Briefly, 4 g of the pristine DNA sample (Mw ~ 8000 kDa) provided by the Chitose Institute for Science and Technology (CIST) was dissolved in 1

L of 14 MΩ· cm distilled/deionized water at room temperature. The DNA solution was then sonicated at 0 °C with 10 and 20 s durations for each of the sonication wave pulses and between the pulses, respectively, to reduce the molecular weight of DNA to ~100 kDa. This was followed by filtration through a nylon filter with a 0.45 µm pore size to remove any particles created during sonication. The filtered DNA solution was then added dropwise to an equal amount of CTMA solution (4 g/L in 14 MΩ · cm distilled/deionized water) with a burette. White DNA-CTMA precipitates formed as the

DNA was added to the aqueous solution of CTMA (see Figure 4.1.1). After having mixed the solution for an additional 4 h at room temperature, the precipitate was removed by filtering the solution under a vacuum using a nylon filter with a pore size of 20 µm.

During the filtering process, an additional 3.4 L of 14 MΩ · cm distilled/deionized water was poured through the filter to rinse the precipitate and to ensure that any CTMA that did not bind to the DNA was thoroughly rinsed away. The precipitate was then collected, placed in a Teflon beaker, and dried in a vacuum oven overnight at 40 °C. The resultant

DNA-CTMA complexes were found to be soluble in alcohol but not in water or other common organic solvents for solution-spinning into thin films.

CTMA

Negatively charged DNA-CTMA DNA precipitate

Figure 4.1.1: Ion Exchange Reaction of DNA with CTMA to form DNA-CTMA complex.

4.1.2 MAPLE of DNA

MAPLE is a technique in which a polymer or other organic material is deposited on a substrate surface in a vacuum chamber using an excimer laser to evaporate a frozen target consisting of polymer or other organic compound dissolved in a volatile solvent matrix. When the laser pulse hits the surface of the MAPLE target the energy of the light get absorbed by the solvent and causes it to vaporize. This simultaneously causes the material trapped in the solvent matrix to be transported with this vapor towards the substrate. As the vapor and solute plume travel towards the substrate a coating from the solute material is formed on the substrate surface, while the volatile solvent molecules are evacuated by the vacuum pump in the deposition chamber 86. The process is similar to pulsed laser deposition, in which material is ablated from the (usually organic) target surface in the form of small molecules, ions, and atoms and settles onto the substrate to form crystalline bonds. In MAPLE, the energy from laser pulses is absorbed primarily by the frozen solvent matrix, and thus allows film deposition to occur with little or no damage to the transported solute material 86-89. These processes are illustrated schematically in Figure 4.1.2.

Figure 4.1.2: Schematic illustrations of a) pulsed laser deposition and b) MAPLE A wide range of solvents have been studied using MAPLE, including distilled water, dichlormethane, DMSO/PBS (Dimethyl sulfoxide/ phosphate buffered solution), chloroform, ethyl-acetate, DMSO, dimethylformamide, benzene, toluene, acetone, and

80 phys. serum180. Typically, solvents having a high absorption at the applicable laser energy are selected, though low wavelength absorbing solvents can be also used due to the laser energy trapping on inhomogeneities and cracks of the frozen target surfaces 180.

Solvent selection is a critical component for the successful homogenous deposition of a selected material. Some of the key parameters include: solubility and surface wettability of the desired solute material, laser absorption coefficient of the solvent material, solution vapor pressure, laser penetration depth, solution freezing temperature, and heat capacity.

Since the extent to which each of these effects has on the final film is largely unknown, it is important to look a large group of solvents before optimization of deposited films continues.

4.1.3 Thermal Evaporation of C60

The C60 depositions were performed through the implementation of a thermal evaporation system located in a load lock attached to the main chamber. The load lock was differential pumped to a base pressure of <5 × 10-7 Torr via a miniturbomolecular pump. The thermal evaporation crucible was maintained at a temperature of 400 °C and was filled with C60 powder (99.98% pure MER Corp.). During the deposition of each C60 layer the main chamber was separated from the load lock by a closed gate valve.

Furthermore, other samples were deposited using the same layering procedure as mentioned above; however, their deposition was operated using a hand fabricated telescoping vertical thermal evaporator controlled by a custom written Labview VI (see

Figure 4.1.3).

Automated thermal evaporator

Figure 4.1.3: (Left) Schematic of the vacuum system used of thermal evaporation. (Right) Telescoping thermal evaporator.

4.1.4 CVD of C60 and Zinc

In an attempt to obtain high-quality products with low content of oxygen and measure their thermal and electrical properties, we successfully fabricated large-scale Zn fullerides nanowires with high purity employing chemical vapor deposition. The fabrication process was carried out in a quartz tube filled with argon gas. The details were as follows. 0.50 g of 99.98% pure C60 (MER Corp.) and 0.50g of granular Zinc were loaded into the center of an alumina boat, which was placed inside a high-temperature tube furnace. Before heating, the quartz tube was pumped to 1*10-2 Torr and then filled with argon. Then the furnace was heated at a rate of 40°C min−1 to 900°C and maintained for 10 h. Simultaneously, the pressure in the quartz tube was attempted to be controlled at

3.75 Torr. However, it was noted that over the course of the run the pressure controller could not keep up with the evaporation of the Zn/C60, and the ultimate pressure in the

82 reaction vessel equalized at 129 Torr. The furnace was then allowed to cool to room temperature naturally. The fabrication of the Zinc fullerides nanowires was carried out in custom built chemical vapor deposition system fitted with a quartz tube as can be seen in

Figure 4.1.4. Granular zinc powder (Aldrich Chemicals) and microcrystalline C60 powder

(MER Corp.) were placed in an aluminum oxide crucible in the center of the evaporation zone. The pressure and flow rate flow rate in the chamber were actively controlled using a MRS pressure controller and a MRS mass flow controller respectively. The pressure for the deposition was fixed at 3.7 Torr and the gas flow rate of Argon was fixed at 25

SCCMs. The temperature in the evaporation zone was ramped up to 950°C at 20°C per minute. Simultaneously, the growth zone region was ramped to 350°C at 20°C per minute. The temperature in both zones were held for 15 hours and then allowed to cool to room temperature naturally.

Figure 4.1.4: Schematic layout of the custom build CVD chamber. Cartoon represent process flow and the picture are what the equipment physically looks like.

4.2 Thermal Properties

4.2.1 Thermal Conductivity

4.2.1.1 Time Domain Thermal Reflectance (TDTR)

The thermal conductivity was measured using the TDTR technique. All samples studied were coated with a thin film ( 90 nm) of aluminum (Al) to facilitate the TDTR experiments. A schematic of the TDTR lab arrangement is shown in Figure 4.2.1 . The output of a mode-locked Ti:sapphire laser (pumped by a frequency doubled Nd:YVO4 laser) is split into a “pump” and a “probe” beam. The pump beam is sent through an electro-optic modulator (EOM), which imposes a square-wave pulse train with a frequency of 9.8 MHz. The probe beam is aligned along a variable-delay stage to alter the timing between the pump and probe pulses. The polarization of the probe beam is rotated to be orthogonal to that of the pump beam. Both beams are then focused to a spot size of

50 μm diameter at a 45 deg angle to the samples. Overlapping of the pump and probe beam spots was facilitated by the use of a precision-cut pinhole and a CCD camera with an imaging lens. The initial timing of the pump and probe pulses was determined with cross-correlation second-harmonic generation through a thin -B2O4 crystal. The incident laser powers at the sample position were 100 mW for the pump beam and 20 mW for the probe beam. The pump beam heats the thin Al film coated on the surface, thereby changing the imaginary component of the surface refractive index (i.e. absorption coefficient); the probe beam responds to this change and, hence, has its reflectivity altered. In this manner, the 9.8 MHz amplitude modulation from the pump beam is

84 transferred to the probe beam. The reflected pump beam is blocked. The reflected probe beam is then recollimated and sent through a Glan laser polarizer to block any additionally scattered pump beam. Finally, the probe beam is passed through a neutral- density filter (optical density = 1.0) and focused onto a Si photodiode detector. The detector has built-in bandwidth filtering that is set to accept the 9.8 MHz modulation frequency while rejecting all higher odd harmonics. The output of the detector is sent to the input of a dual-phase RF lock-in amplifier, which has its reference channel connected to the same electronic signal that drives the EOM. The phase of the lock-in amplifier was set such that the quadrature component of the signal was unchanged as the probe pulse crossed the t = 0 delay position. The scans and data acquisition were computer-controlled by means of a homemade LabVIEW program.

TDTR data analysis for the extraction of thermal conductivity was accomplished with a frequency-domain model 181 in which the ratio of the in-phase and out-of-phase lock-in amplifier signals is calculated as a function of time:

m Tm /  f  Tm/  f expi2mt /  V   in  m V m out iTm /  f  Tm/  f expi2mt /  m Equation 4.2.1: Here m is an integer denoting summation over pump pulses,  is the time between unmodulated laser pulses (12.5 ns), f is the modulation frequency (9.8 MHz), and t is the time delay between pump and probe pulses. The function T is calculated with the Feldman matrix algorithm as explained in Ref. 181 All data for probe delay times earlier than t = 100 ps was overlooked since electron-phonon coupling has not equilibrated, which allows the Al film coating to reach a uniform temperature. Picosecond acoustics also perturb this regime (which facilitates direct measurements of the Al thickness). A four-layer system was used with a single

85 interfacial conductance. This four-layer system was found sufficient since the sample coatings were 500 nm thick, thereby causing the model to be insensitive to the substrates.

From the TDTR scans of each sample, the thickness of the Al film was determined from observable acoustic echoes in the TDTR spectra, and this thickness was fixed in the TDTR model.

Figure 4.2.1: Schematic layout and components used to perform the TDTR measurements. The automation of the data collection was achieved by redesigning and upgrading a large amount of optical and electronic hardware on the experiment’s detector line. The redesign of the detector line from a perpendicular set up to the collinear design (Figure

4.2.2) allowed for accurate sample indexing which was required in order to perform sample alignment and simplify signal detection. Switching to the collinear design required the addition of a secondary modulation by an optical chopper and two acoustic frequency lock-in amplifiers for enhanced noise filtering due to the increase in scattered

86 pump beam light that reached the detector. The addition of the computer controlled 3- axis substrate stage was the final hardware addition and software upgrade to allow for automated data collection. Control of the X- and Y-axes was required for accurate sample indexing while the Z-axis control was required to optimize the spot focus for each sampling location. In addition random point selection by the control software, the user can define specific sample points or set up line scans from a start and end point to facilitate analysis of gradient composition thin films.

Because current methods for modeling TDTR data involved a tedious guess and check method of simulating data and evaluating the fit with the raw data, simplified fit statistics were integrated into the data modeling system to allow for accurate modeling but still assist in minimizing processing time. Batch processing and data fitting was accomplished by integrating an in-house developed Fortran executable program using

Cahill’s frequency domain solution into the custom built LabView user interface.181

Using preset parameters from the user, an iterative, error minimization scheme was developed utilizing segmented R2 values, scaled sum squares of the error, and a scaled

‘next guess’ system for the unknown interface conductances and thermal conductivities.

Figure 4.2.2: a) Schematic of TDTR collinear detector line; b) Image of TDTR collinear detector line

4.2.1.2 Physical Properties Measurement System (PPMS)

The PPPS system measures thermal conductivity κ by applying heat from the heater shoe in order to create a temperature differential across the sample of interest. Heat is applied to sample in a dynamic way (i.e. a low frequency square wave heat pulse) to expedite the data acquisition. Using thermal models established by Maldonado et al. the software can then calculate thermal conductivity directly from the applied heater power, resulting ΔT, and sample geometry.182,183

The PPMS system also determines the Seebeck coefficient α by creating a specified temperature drop between the two thermometer shoes just as it does to measure thermal conductivity. However, for Seebeck coefficient the voltage drop created between the thermometer shoes is also monitored. The additional voltage-sense leads on these thermometer shoes are connected to the ultra-low-noise preamplifier of the electronics board.

The PPMS system measures electrical resistivity ρ by using a precision digital current source and phase-sensitive voltage detection. In typical resistivity measurements,

4 electrical leads are attached to a rectangular sample along a straight line (see Figure

4.2.3). A current is fed from contact A to contact B, and the voltage is measured across contacts C and D, which must be far away from the current contacts in order for the lines of current flow to be uniform and parallel between C and D. The resistivity of the sample can be derived from the voltage drop across contacts C and D, the applied current, and the geometry of the sample (this is the standard Van der Paw or 4-point probe method that will be described in more detail later).

Figure 4.2.3: Thermal and electrical connections and circuit for the PPMS In continuous measurement mode, the software uses adaptive algorithms to optimize measurement parameters such as heater current, heat pulse period, and resistivity excitation amplitude and frequency. These details are further outline in the

PPMS manual which goes into great depth on the nonlinear least squares fitting routines used.183

4.2.1.3 Hot Disk Method

The hot disk method makes use of a flat sensor with a continuous double-spiral of electrically-conducting Nickel (Ni) metal thin foil sandwiched between two layers of

Kapton. The purpose of the Kapton is to act as both a support structure for the probe and an electrically insulative barrier to the sample. The sensor is placed between the surfaces of two pieces of the sample to be measured. A variety of probe sizes are available to accommodate samples of different geometries.

The measurement begins when a current is passed through the Nickel spiral and creates an increase in temperature due to Joule heating in the foil. The heat generated in the probe then dissipates through the sample on either side at a rate dependent on the thermal transport characteristics of the material. By monitoring the temperature versus time response in the sensor, these characteristics can accurately be calculated. This type of measurement is known as a transient plane source technique and several bodies of work have documented its experimental accuracy.184,185 More specifically further details of the technique can be found in the literature of Gustavsoon et al. and Suileman et al.184-

186

4.2.2 Heat Capacity by Means of Differential Scanning Calorimetry (DSC)

DSC is a thermoanalytical technique, where the difference in heat flow to a sample and reference is monitored against time or temperature. The technique is typically performed while incrementally increasing the temperature of the sample and the

90 reference. It enables the determination of a number of parameters connected with the physical or chemical processes in condensed phase. These include but are not limited to the temperature of 1st and 2nd order phase transitions, enthalpies of phase transitions, heat capacities, polymorphism in food and pharmaceuticals, liquid crystalline transitions, phase diagrams, thermoplastic polymer phase changes, glass temperatures, purity measurements and kinetic studies.187

The physical measurement of the heat capacity can be derived using the classical thermodynamic model seen in Equation 2.2.1. From this it is clear to see that by recording the absolute value of the heat flow to the sample, one can directly calculate the heat capacity. The heat capacity plots generated later in this work were carried out using a Q1000 DSC in the temperature range 0 - 500 °C with a ramping rate of 10 °C/min.

Equation 4.2.2: Where m is the sample mass, H is enthalpy and ∆P is the absolute value of the heat flow to the sample, i.e. of the DSC signal. This is derived using the equilibrium-thermodynamics definition of heat capacity.

4.3 Electrical Properties

4.3.1 Four Point Probe

The four point probe is an apparatus used to determine bulk resistivity of a material. As discussed in previous sections the mobility of the carriers depends upon temperature, crystal defect density, and any impurities present in the material. The four point probe contains four thin collinearly placed wires probes which are made to contact the sample under test. To begin the measurement current (I) is passed between the outer

91 probes, and voltage (V) is measured between the two inner probes, ideally without drawing any current. If the sample is of semi-infinite volume and if the interprobe spacing’s are s1= s2 = s3 = s4 = s, then it can be shown that the resistivity of the semi- infinite volume is given by:

Equation 4.3.1: The resistivity of a semi-infinite volume ( ) for given material where V is the voltage, s is the pin spacing, and I is the current passed between the outer probe. The preceding equation makes the broad assumption that the sample is of semi- infinite size. Realistically, samples have a finite size and thus Equation 4.3.1 is not accurate. However, correction factors for six different boundary configurations have been derived by Valdes et al.188 These results conclude that if the distance of any of the probes to the edge of the sample is greater than five times the pin spacing (s) then no correction factors is needed. This applies in any direction (i.e. when samples are much thinner than

5s correction factors must be used). Equation 4.3.2 represents the modified equation with the included correction factor (a).

Equation 4.3.2: The resistivity of a finite sized material where all variables are the same as in equation 4.3.1. except for the included correction factor (a) Using the correction factors tabulated by Valdes et al. we find that in all of our measurement situations a = 0.72 t/s.188,189 When substituted into the basic equation we get

Equation 4.3.3:

( )

Equation 4.3.3: The resistivity and sheet resistance in a finite solid. Where t is the sample thickness and Rs is the sheet resistance.

Equation 4.3.3 introduces the term sheet resistance (Rs) which is simple the resistivity divided by the thickness. Note that Rs is independent of any geometrical dimension and is therefore a function of the material alone. Typically, this type of measurement is represented as Ohms/sq but the sq is there as a reminder of the geometrical significance of sheet resistance.

4.3.2 PPMS

The PPMS makes use of the same technique described above for the four point probe measurement. Fundamentally the techniques are the same, with exception that the

PPMS probe head can be varied as a function of temperature.

4.3.3 Potential Seebeck Microprobe (PSM)

The potential Seebeck microprobe is instrument that can provide data on the spatial resolution of the Seebeck coefficient and the electrical conductivity of a sample.

The Seebeck-coefficient (Se) is a measure of the electrically active constituents in a material for a given temperature differential. Since the tip of the microprobe is small, and mounted to an x-y translation stage the Se coefficient at various locations (micron size resolution) can be acquired. This is particularly useful when investigating functionally graded materials (e.g. combinatorial samples). The usefulness of many materials depend on the homogeneity, thus spatial mapping of the material properties greatly helps in accessing the quality of the material. The PSM makes use of a low frequency AC current measurement with a fast Fourier analysis to access the electrical conductivity. This ensures that contributions from the Seebeck effect are minimal on the electrical conductivity measurement.

The operation of the PSM is as follows. A heated probe tip is positioned onto the surface of a sample (see Figure 2.1.1). The probe is connected with a thermocouple (in this case type T, Cu-CuNi) measuring the temperature T1. The sample is in good electrical and thermal contact with a heat sink and also connected with a thermocouple measuring T0. The probe tip heats the sample in the vicinity of the tip leading to a temperature gradient. Combining the Cu-Cu and the CuNi-CuNi wires of the thermocouples the voltages U0 and U1 are measured yielding in the Seebeck coefficient S

(see Equation 4.3.4). Mounting the pointed probe to a three dimensional micro- positioning system allows the determination of the individual thermopower of each single sample position for a certain temperature. The result is a two dimensional image of the

Seebeck coefficient of the sample surface. Using a special sample holder where an electrical current can be applied to the sample, the potential between one end and the probe tip can be measured, that is related to the electrical conductivity at the samples position. Thus in the same run a spatially resolved imaging of the Seebeck coefficient as well as the electrical conductivity can be performed. The specific resistivity can be calculated for each single measurement point according to Ohm´s law.

Figure 4.3.1: Diagram of the PSM assembly, with the specified temperature junctions T1 and T0, and the specified voltage junctions U1 and U2.

U0 = (Ss-SCu) * (T1 –T2)

U1 = (Ss-SCuNi)*(T1-T0)

Ss = U0/(U1-U0) *(SCu – SCuNi) + SCu

Equation 4.3.4: The mathematical procedure for solving for the Seebeck coefficient at the sample surface (Ss), where U0 and U1 are the voltages at the specified junctions, SCu is the Seebeck coefficient of the probe shell, and SCuNi is the Seebeck coefficient of the probe wire.

CHAPTER V

RESULTS AND DISCUSSION

5 Results and Discussion

5.1 Process Development and Nanostructure Formation Mechanisms for DNA and C60

5.1.1 MAPLE process development

This section will explore the processing parameters of MAPLE for the creation of

DNA-CTMA and C60 thin films. The major parameters of interest include the type of solvent, laser fluence, laser repletion rate, and substrate temperature. Each of these processing parameters has a significant effect on the formation of thin films, and mechanisms will be proposed to identify the underlying cause.

5.1.1.1 MAPLE processing of DNA-CTMA

Development of MAPLE to deposit DNA-CTMA films requires study of the effect of processing parameters on the morphology of the films as assessed by optical microscopy and image analysis. These processing parameters include deposition rate, laser fluence, substrate temperature and type of solvent.

The first processing parameter investigated was the solvent used to make the target material. Solvents were selected for evaluation in this study based on the following criteria: vapor pressure, melting temperature, absorbance at 248 nm, compatibility with vacuum systems, and toxicity. Target solutions containing 5 mg/ml of DNA-CTMA material were made using DMSO, water, acetone, toluene, and methanol. Thin films were deposited onto silicon wafers using the MAPLE process with the following deposition parameters: 1 Hz laser repetition rate, 700 mJ laser energy, 45 minutes deposition time, ambient laboratory temperature (20ºC), and unregulated vacuum pressure. DNA-CTMA was deposited on the surface of all of the silicon wafer samples with varying surface coverage and morphology depending on the target solvent (see

Figure 5.1.1). The samples deposited using the methanol and acetone had the densest surface coverage of all the solvents. However, circular features were observed in all samples which were indicative of liquid droplets striking the surface and drying. This phenomenon of droplet drying has been observed several times before and has been commonly referred to as the “coffee ring effect”.190-192 The characteristics of these droplet created films include distinct ring patterns with raised edges. Further insight into the formation mechanisms, and how they can be avoided, will presented in future sections.

DMSO

H20

Acetone

Toluene

Figure 5.1.1: Effect of various solvents on the deposition of DNA-CTMA.

The effect of laser repetition rate on MAPLE sample surface morphology was evaluated by comparing films produced at 1, 2, and 3 Hz laser repetition rates. For these experiments, 5 mg/ml of DNA-CTMA in methanol, 700 mJ laser energy, 45 minutes deposition time, ambient laboratory temperature (20ºC), and vacuum pressure (~10-7

Torr). The optical micrographs displayed in Figure 5.1.2 emphasize that the area densities of the deposited films are similar, however the morphology is different. Laser

98 pulses striking the target cause a layer of solvent on the outer surface to melt, and some of the liquid at the surface is vaporized. DNA-CTMA material is carried to the substrate surface by solvent vapor and by liquid droplets ablated from the target surface. One observation that is apparent in these films involves the larger clusters of material observed in the 3 Hz deposition. This is largely attributed to the transport mechanism of the DNA-CTMA to the substrate. In the case where the deposition rate is low (1 Hz), we hypothesize that most of the material is transported as very small droplets or completed evaporated solvent (see Figure 5.1.2). Furthermore, since the repetition rate is low the frozen MAPLE target has time in-between laser pulses to completely refreeze. This means that each addition pulse is exposed to a purely frozen target. Whereas in the case of high deposition rates (i.e. 3 Hz), the target material does not have time to refreeze between pulses and the observed film contains more large spots. This is largely a result of the laser striking a surface that is partially liquid, thus causing the ejection of more liquid droplets.

700mJ, 1Hz

This figure shows the case where there is a low repetition rate

700mJ, 3Hz

This figure shows the condition of higher repetition rate. Figure 5.1.2: (Top) Schematic of the proposed mechanism for low repetition rates (Bottom) Schematic of the proposed mechanism for high repetition rates.

The effect of laser energy on MAPLE sample surface morphology was evaluated by comparing films produced at 500, 700, and 900 mJ laser pulse energy. For these experiments, 1 Hz laser repetition rate, 5mg/ml carbon nanopearls in methanol, 45 minutes deposition time, ambient laboratory temperature (20º C), and vacuum pressure

(~10-7 Torr) were used. It was observed that the area fraction increased with increasing laser energy. Additionally, the mean agglomerate size was smaller at higher laser fluences as observed in Figure 5.1.3.

100

When films are deposited at higher laser energies, more of the frozen target is converted to vapor per pulse, while at lower laser energies below a certain threshold, more liquid is produced at the target surface. This means that when depositing at lower laser fluence one would expect more of the film to be produced by liquid droplets.

However, there is balance between achieving the highest amount of vapor produced per pulse and potential damage that high laser fluences may induce on the produced films.

This result is in agreement with Sellenger et al., who showed that increasing laser fluence may increase the number density and decrease the size of surface features of deposited material193.

900mJ, 1Hz 700mJ, 1Hz 500mJ, 1Hz

900mJ

700mJ

Figure 5.1.3: (Top) Optical micrographs of films produced with varying laser energy (Bottom) purposed mechanism to explain the observed phenomenon.

101

Now that mechanisms have been established for how laser fluence and repetition rate have been established, it is important to investigate if there are any confounding factors between these effects. To examine this, a matrix of samples with various deposition conditions was prepared (see Figure 5.1.4). The optical images observed from these depositions display properties similar to those observed in previous films, however, in the films deposited with higher laser energy and higher rep rates more droplets were present. It is hypothesized that this is a result of the target not refreezing between pulses and lack of complete conversion to vapor per pulse. The optimal deposition condition for

DNA-CTMA was determined to be around 900 mJ and 2 Hz because of the higher deposition rate and greater dispersion.

1Hz 2Hz

5 mg/ml 100k DNA in MtOH 900mJ

3Hz

700mJ

500mJ

Figure 5.1.4: Energy vs. Repetition rate for the deposition of DNA-CTMA complex.

102

The effect of substrate temperature on MAPLE sample surface morphology was evaluated by comparing films produced at ambient temperature ( ~20ºC ), 100ºC and

200ºC. For these experiments films were deposited at 2 Hz laser repetition rate, 900 mJ laser energy, 5 mg/ml in methanol, 45 minutes deposition time, and unregulated vacuum pressure (~10-7 Torr). Optical micrographs of the deposited films are shown in Figure

5.1.5. The largest area fraction of material was observed in the films deposited at ambient temperature and decreases as the temperature increases. Furthermore, the material deposited by droplets was observed to increase with increasing temperature, with the mean droplet size becoming smaller at the highest temperature. Thus, the optimal temperature for MAPLE deposition at ~10-7 Torr was the ambient condition.

103

Ambient 100°C 200°C

700mJ

900mJ

FigureAmbient 5.1 condition.5: Optical micrographs of DNA-CTMA deposited at various substrate temperatures• Drops hit the andsurface laser and energies. merge and then evaporate to create more uniform films Hot Condition •DropsTo do furthernot have characte time to rizespread the out DNA on -theCTMA surface thin and film quickly TEM evaporates was performed. where For this they hit. experiment a film was deposited at 2 Hz laser repetition rate, 900 mJ laser energy, 5 mg/ml in methanol, 45 minutes deposition time, and unregulated vacuum pressure (~10-

7 Torr) on a TEM grid mounted to the substrate stage. Figure 5.1.6 displays the images that were captured. One of the prominent features observed in these films is the droplets discussed earlier. The droplets range in size from several microns down to only a few nanometers. Since this is not ideal for the formation of uniform thin films, other mechanism to thwart this “coffee ring evaporation” were investigated (see Section 5.1.2).

104

Figure 5.1.6: TEM images of the DNA-CTMA deposited at 900mJ, 2 Hz, for 45 min. (Left) the scale bar in the bottom left represent 0.2 um (Right) the scale bar in the bottom left represents 50 nm.

5.1.1.2 MAPLE processing of C60

Using the knowledge gained from the MAPLE depositions of the DNA-CTMA, a similar study was performed using fullerenes. Since C60 has vastly different properties than DNA-CTMA, it was not surprising that a new solvent system would have to be developed for the formation of C60 thin films using MAPLE. These solvents followed the same criteria as before with the inclusion that the solvent chosen should allow for a high solubility of fullerenes. Working through the matrix of solvent choices, toluene and dichlorobenzene (DCB) were selected as potential candidates.

Section 5.1.2 gives an overview of how Marangoni flow could be used to help stop the coffee ring formation in liquid droplets. Since it is the objective of this work to create uniform thin films, solvent blends were explored as a mechanism to eliminate coffee ring formation. For this study solutions ranging from 100% toluene by volume to

105

100% DCB by volume at a concentration of 2.8 mg/ml of C60 were prepared. These solutions were then frozen and deposited using MAPLE at 700mJ, 2 Hz, 45 min, at vacuum pressure (~10-7 Torr). The results of this study can be seen in Figure 5.1.7. These results display similar characteristics (agglomerate and droplet formation mechanisms) to those seen in the DNA-CTMA study, however, it was noted that during the depositions a plasma was formed. This was concerning for two reasons 1) plasma formation is indicative of ion formation (i.e. instead of depositing whole molecules of C60, the carbon was being ionized) and 2) plasma formation would allow for the formation of other chemical reactions.

MAPLE Deposition of C60 :

10um

AFM: TEM:

Figure 5.1.7: (Top) Optical micrographs of the deposited C60 films at various volume concentrations of Toluene and DCB (Bottom Left) AFM images of the deposited film in 20% Toluene 80% DCB (by volume) (Bottom Right) TEM image of the deposited film in 20% Toluene 80% DCB.

106

Before the study continued any further, answers surrounding the efficacy of the use of MAPLE for C60 thin film formation were sought. To examine the effect of plasma formation during MAPLE, we looked at the XPS spectra of the deposited film. These results can be seen in Figure 5.1.8. Unfortunately, the spectra confirmed the suspension that the plasma was creating reactive species (i.e. chlorine) and subsequently combining with materials deposited on the substrate. This result was further confirmed by EDAX and TEM results of the deposited film (see insert in Figure 5.1.8). The observed structure displays characteristics of an amorphous carbon material (i.e. branched carbon chains with no sense of long range order). Further investigation of the literature revealed that C60 with its relatively large bandgap (~1.9eV) can generate electron hole pairs (under UV stimulation) strong enough to dissociate the solvents.194,195 A proposed reaction scheme for the process taking place during the MAPLE deposition can be seen in Figure 5.1.9.

Since, there was not a foreseeable workaround for the interaction between the laser and the C60 molecules; MAPLE was abandoned as a potential deposition technique for C60

107

thin films.

1 2 x 10 Cl LMM C KLL O KL L O 1s 14 C 1s Cl 2s Cl 2p1/2 O 2s O 2p1/ 2 Cl 2p3/2 Cl 3s O 2p3/ 2 Cl 2p O 2p C 2p1/2 C 2p3/2 C 2p Cl 3p1/2 Cl 3p3/2 Variable Name Pos. FWHM Area At% Cl 3p 12 0 C 1s 284.763 2.56177 18.5 90.44 Cl 2p 3/2 199.833 2.95904 3.0454 9.557

10 C 1s C

8 CPS

2 Cl 2p 3/2 2p Cl

350 300 250 200 150 100 50 Bi ndi ng E nergy (eV)

Figure 5.1.8: XPS spectra of the deposited film in 20% Toluene 80% DCB (by volume) (Insert) TEM image displaying the amorphous nature of the deposited material. :

Cl hV 600-900 mJ / Amorphous + pulse chlorinated 248 nm from KrF carbon Laser

Figure 5.1.9: Proposed reaction scheme involving the degradation of solvent and C60 molecules.

108

5.1.2 Inducing Marangoni Flow for the Reduction of Coffee Ring evaporation

When the initial films of DNA-CTMA were investigated a “coffee-ring” evaporation effect was observed (see Figure 5.1.6). The “coffee-ring” evaporation effect is a phenomenon that was first described Deegan et. al 190. In this work Deegan et al. outlined that capillary flow, induced by the evaporation of a droplet at a fixed contact line, can cause coffee ring phenomenon (see Figure 5.1.10 ). Furthermore, this type of film formation has been observed for DNA-CTMA when depositing using inkjet techniques 196. Deegan’s model was further extended by the work of Fischer et al., Hu and Larson.191,192,197 Collectively, using lubrication theory and numerical methods, these authors were able to precisely describe the physics of induced capillary flow in an evaporating droplet. Since this type of non-uniform deposition is not desirable for thin- film applications, methods to circumvent the problem were investigated. One of the primary techniques explained in the literature to thwart “coffee-ring” formation is to use solvents that have a high Marangoni flow 198. The Marangoni flow patterns of fluorescent polystyrene beads suspended in various solvent mixtures was observed by Hu et al., and displayed promising results for fighting coffee ring formation (see Figure 5.1.11).

Moreover, to obtain solvent systems that were compatible with MAPLE processing and had relatively high Marangoni flow, mixtures of toluene and DMSO were investigated.

109

Figure 5.1.10: Simulation of coffee ring evaporation. The dark blue lines represent the suspended phase in the droplet. (a-e) represent different time steps from the evaporation process.199

Figure 5.1.11: Marangoni flow patterns of fluorescent polystyrene beads suspended in various solvent mixtures.198

The Marangoni number (Mg) is a dimensionless number that describes the ratio of surface tension forces in a solution to the viscous forces. The equation for the Mg number

110 can be described in Equation 5.1.1: Equation for the Marangoni number (Mg) where is the surface tension, is the surface tension of species 1, is the surface tension of species 2, L is the characteristic length, T is the temperature, is the dynamic viscosity,

is the thermal diffusivity, and is the diffusion coefficient of species 1 into species 2..

To investigate the effect that Marangoni flow may have on the reduction of coffee ring formation, I first calculated the Mg number for various mixtures of toluene and DMSO

(the results can be seen tabulated in Table 5.1.1)

( )

Equation 5.1.1: Equation for the Marangoni number (Mg) where is the surface tension, is the surface tension of species 1, is the surface tension of species 2, L is the characteristic length, T is the temperature, is the dynamic viscosity, is the thermal diffusivity, and is the diffusion coefficient of species 1 into species 2.

Mole fraction Toluene Viscosity (mPa s) Marangoni Number 0 0.58 1.85E+06 0.1004 0.631 1.70E+06 0.2027 0.7 1.53E+06 0.3047 0.782 1.37E+06 0.4044 0.877 1.22E+06 0.5057 0.99 1.08E+06 0.6045 1.116 9.61E+05 0.705 1.269 8.45E+05 0.803 1.45 7.40E+05 0.9011 1.68 6.39E+05 Table 5.1.1: Marangoni number for various mole fraction percentages of Toluene and DMSO. According to experimental data, a turbulent regime arises for considerably larger values of the Marangoni number (i.e. Mg > 22000).200 Additionally, studies that were performed with polymer solutions demonstrate that the use of a binary mixture of solvents can eliminate the formation of ring stains if one of the solvents has a much higher boiling point than the other.201,202 Moreover, the expected Marangoni number for

111 solutions of toluene and DMSO, and the difference in boiling points for toluene (~ 111

ºC) and DMSO (189 ºC), suggest that they would be a good candidate for suppressing coffee ring evaporation.

Various solutions, ranging from 30:70 (v:v toluene:DMSO) of 5 mg/ml DNA-

CTMA were prepared. Thin films were deposited onto silicon wafers using the MAPLE process with the following deposition parameters: 2 Hz laser repetition rate, 700 mJ laser energy, 45 minutes deposition time, ambient laboratory temperature (20ºC), and vacuum pressure (~10-7 Torr). The films were then examined using optical microscopy and white light optical profilometery (see Figure 5.1.12). These films clearly display a lack of the droplets that dominated the film formation profile of the previously made films. There are two aspects for the suppression of these coffee stains 1) the solvent composition at the contact line is constantly shifting to an increasing percentage of the higher boiling point solvent, which causes a decrease in the rate of evaporation and establishes a surface tension gradient and 2) Marangoni flow is induced from regions in the droplet with low surface tension to regions with high surface tension. These results were found to be comparable with Schubert et al. work who found large Marangoni numbers (~106) for solutions of ethyl acetate and acteophenone and witnessed large Marangoni flow.202,203

112

Various Solutions of Toluene:DMSO (V:V)

30:70 40:60 50:50 60:40 70:30

Figure 5.1.12: (Top)Optical Microscopy and (Bottom) white light optical profilometer data of DNA-CTMA of various (V:V) (Toluene:DMSO) solvent mixtures

Tapping Mode Scanning Probe Microscopy was done on the Digital NanoScope

Atomic Force Microscope (AFM). A single crystal silicon tip was utilized during the method. Samples were placed into the microscope and parameters were set to capture images. To obtain accurate images and tip frequency (~300 kHz), the laser is centered onto the tip and the deflection voltage, photodetector output signal and SUM signal were zeroed. The drive amplitude, scan rate and amplitude set point for each section of the sample tested, were kept in relative values and ranges. Tapping Mode-AFM Images showed that DNA-CTMA thin-film morphology and surface roughness varied with toluene: DMSO solvent blend concentration (Figure 5.1.13 ). Furthermore, the root mean squared roughness was calculated for all of the various blends and found to have minimum roughness at the 50:50 concentration solutions (Figure 5.1.13).

113

30:70 40:60 50:50 60:40 70:30

5 x 5 m images Z = 100 nm

50 50

40 40

30 30

20 20

10 10 Mean RMS Roughness (nm) 0 0 0 20 30 40 50 60 70 80 1 0 0 % T o lu e n e

Figure 5.1.13: (Top) AFM images of MAPLE deposited DNA-CTMA of various concentrations solutions (Bottom) RMS roughness of the AFM images above To confirm that the DNA-CTMA complex was not damaged during the deposition, FTIR was performed on the 70:30 (toluene:DMSO, v:v) sample. The spectra seen in Figure 5.1.14 displays the drop cast DNA-CTMA complex as well as the MAPLE deposited film. Ideally, the spectrum of the drop cast films would identically match the

MAPLE deposited sample. While several of the peaks match the location seen in the drop cast films the ratio and intensity of others are slightly shifted or display asymmetric features. This suggests the two materials are not identically, however, since many of the stretching modes are similar, we can say with a fair amount of confidence that the samples are very similar. Furthermore, since the material involves a biological compound that has a molecular weight of several hundred kiloDalton, exact identification of the modifications made to the compound would be very challenging.

114

Drop Cast 0.2 Room temp drop cast 70/30

0.0 Abs

-0.2

* MA PLE 70/30 0.20 MAPLE 0.15

0.10 Abs 0.05

0.00

-0.05 0.20 Subtraction R esult:* MA PLE 70/30 Subtracted 0.15

Abs 0.10

0.05

3500 3000 2500 2000 1500 1000 Wavenumbers (cm-1) Figure 5.1.14: FTIR spectra of 70:30 Toluene:DMSO MAPLE deposited DNA- CTMA

5.1.3 Growth of Fulleride Thin Films

The growth of fulleride thin films has not been reported in the literature, and thus we began this work from a basic study on the growth of pure C60 thin films. To accomplish this, a thermal evaporator was constructed and attached to the vacuum deposition system (see Figure 4.1.3). The heating assembly was calibrated with a Type K thermocouple which allowed control of the evaporation temperature ± 2.5 ºC. Films of

C60 were then deposited on silicon substrates. During this deposition the chamber was held at vacuum pressure (<10-7 Torr), the evaporator crucible was held at 400ºC, and the substrate was at ambient lab temperature. The deposition time was 20min. The film was then analyzed using Raman spectroscopy and scanning tunneling microscopy (STM) (see

Figure 5.1.15). Clearly visible in the STM image are the C60 spheres. This along with the matching fingerprint Raman spectra confirm the successful deposition of C60. The

115 deposition rate (~0.8 nm per min) was calculated using contact profilometer on a masked portion of the deposited film

Figure 5.1.15: (Left) Raman spectra of deposited C60 film (red line) and database signature file for C60 (blue line), (Right) Scanning tunneling microscope image of the deposited C60 film.

The procedure to produce fulleride films was as follows. Zn/C60 films were deposited in a vacuum chamber via magnetron sputtering and thermal evaporation processing. One inch substrates of sapphire were ultrasonically washed in acetone and loaded onto a rotating fixture within the processing chamber. A turbomolecular pump was used to evacuate the chamber to a base pressure of <5 × 10-7 Torr. The film growth consisted of alternating depositions of Zn and C60 layers of 10 nm each in thickness.

Samples were prepared with alternating layers of Zn and C60 (~10nm each) for a total of

150 layers (75 zinc, 75 C60). The Zn depositions were achieved by a dc glow discharge from a magnetron plasma source with a 32 mm, 99.99% pure Zn cathode in an argon (Ar) environment. The power density on the Zn cathode was 15 W cm -2. The pressure of the

116 system during deposition was 15 mTorr, which was achieved through the introduction of

50 sccm of Ar into the chamber. This pressure was maintained through an automated throttle valve adjustment located between the chamber and the turbomolecular pump.

The thermal evaporation crucible was maintained at a temperature of 400 °C and was filled with C60 powder (99.98% pure MER Corp.). During the deposition of each C60 layer the main chamber was separated from the load lock by a closed gate valve.

Following the deposition, the sample was heated in a tube furnace under dynamic flow of 99.98% pure Ar for 12 hrs at a temperature of 400 °C. This annealing step was done to facilitate Zn atom diffusion and intercalation into the C60 layers, as will be discussed later (see Figure 5.1.16).

117

Repeat Metal Fullerene (C60) layer Unit Metal

Anneal Substrate

Metal rattler C60

Figure 5.1.16: This schematic displays how the fulleride films were created. Briefly, layers of Zn (~10 nm) and C60 (~10 nm) were deposited on top of each other. The whole substrate and layer assembly was then placed in a furnace to allow for reactions between the Zn and C60.

To study microstructural changes from the surface to the interface between film and substrate, cross-sectional transmission electron microscopy (TEM) specimens were prepared by liftout in a FIB microscope, FEI-DB235. It was operated at 5 keV of electron beams and 30 keV of Ga+ ion beams. To protect surfaces, a 2 nm-thick Pt cap was deposited on the top of the sample by using a gas injection system, which first gently deposited with electron beams and then with ion beams. Microstructures were observed at high-resolution using a Philips CM200- FEG TEM operated at 200 keV. The probe size of incident electron beams was adjustable from 25 nm down to 1 nm for chemical 118 microanalyses using a NORAN X-ray energy dispersive spectrometer (EDS) installed on the TEM.

Compositional analyses were made with an X-ray photoelectron spectroscopy system outfitted with an SSI channel detector operated at a pressure of 5 × 10 -9 Torr.

Binding energy positions were calibrated using the C 1s peak at 284.5 eV, and the Zn

2p3/2 peak at 1021.8 eV. Relative peak areas for C 1s, O 1s, Zn 2p3/2 peaks were used for composition analysis with Gaussian-Lorentzian line shape fitting. Electron escape depth variation was neglected for the analysis. Depth profiling with Ar ion sputtering was done to study the composition as a function of depth and to ensure removal of surface oxide and carbon formed during handling and transfer. Operating conditions during sputtering included 6.7 mTorr Ar partial pressure, 10 mA ion current, 25 s sputter time per cycle, and 2000 V accelerating voltage. The Ar ion gun axis was at an angle approximately 45 degrees normal to the sample surface.

For the first part of the analysis, DSC was used to see if there were any noticeable endotherms or exotherms being generated when the Zn was diffusing / reacting with the

C60 layer. To accomplish this, samples of pure Zn metal and 75 layers of alternating Zn /

C60 were deposited in DSC pans. The derivative of the heat DSC results can be seen in

Figure 5.1.17. The layered sample in Figure 5.1.17b shows an additional endotherm at

357° C. This peak is attributed as showing where the majority of the Zn is diffusing / reacting with the C60. To confirm this hypothesis, Raman spectroscopy was used to probe the structure of the post heat treated material.

119

Figure 5.1.17: a) Differential scanning calorimetry of pure Zn and b) 75 layers of Zn/C60.

204 Raman spectroscopy of pure C60 has previously been performed. The Raman spectroscopy seen in Figure 5.1.18 shows peaks that can be attributed to pure C60, shifts

205,206 in normal C60 modes, and new vibrational modes induced by metal C60 interactions.

These shifts, along with the additional peaks, are indicative of the creation of transition metal fullerides.205,206 It has also been noted by other authors that as the metal content in the fullerides becomes large the presence of the pure C60 modes disappear leaving just the

206 fulleride modes. Moreover, the main difference between pure C60 and C60 in fullerides is the charge transfer that takes place upon metal intercalation. This causes a slight distortion in the C60 molecules and further softens the C60 – C60 vibrational modes in the material.207 One of the most suggestive peaks is the one at 152cm-1 which has been linked to vibrational modes between metal atoms and fullerenes.206,207

In comparing this compound to known transition metal fullerides other studies

-1 -1 have shown that for each 6 cm shift in the peak at around 1468 cm , the C60 in ionic

120 compounds is holding an additional electron.205,208 This compound shows a shift of

-1 approximately 30 cm which would suggest that the C60 molecule is holding between 4 and 5 electrons advocating x = 2- 3 for ZnxC60.The nature of this particular shift is linked to the bonding mode between the metal and the fullerene. If the bonding is strictly ionic one would expect a very large dependence between peak position and formal charge on

C60; however, if the nature of the bonding is more covalent this dependence might not be as straightforward. Nevertheless, since most fullerides are unstable in air, the observation that this sample was air-stable was unexpected. Furthermore, in the case of full charge transfer fullerides (i.e. alkali fullerides) one would expect a broadening / softening of the

-1 -1 205 Hg(7) (~1425 cm ) and Hg(8)(~1570 cm ) modes, which are not present here. These observations connote that for this metal to C60 ratio both the charge transfer and covalent bonding should be evaluated as possible explanations for the Raman spectra observed. To further investigate the composition of this sample XPS was performed.

121

Figure 5.1.18: Raman spectra of pure C60 (a) and Raman spectra of 75 layer sample of Zn C60 after heat treatment (b).

122

TEM was used to investigate the microstructure of the annealed film. Figure

5.1.19 is a TEM image of the film; the low resolution results (Figure 5.1.19a) show that the film is relatively homogenous with small crystallites. At higher resolution the film shows no distinct evidence of the existence of Zn crystallites in film neither in atomic images nor in electron diffraction patterns. Although a limited solid solution may be formed at the boundaries, it is unlikely for Zn to form a bulk compound with C60 due to its high cohesive energy. The most possible explanation for the absence of Zn diffraction patterns is that atoms or small clusters of Zn were dispersed uniformly into the C60 matrix, so the electron diffraction signals are too weak to be visible. This result suggests that Zn clusters or small grains are still well dispersed without agglomerating into larger crystallites. Furthermore, the electron diffraction pattern seen in Figure 5.1.19c displays intense peaks at periodic spaces, however, these peaks do not match the expected peaks for pure C60 or pure Zinc. We speculate that these peaks arise from the superposition of the ZnxC60 phase along with zinc and C60 phases.

a) b) c)

Figure 5.1.19: TEM image of deposited ZnxC60 (a) 13K magnification the dark region on the left is the Pt protection layer (b) 620K magnification (c) 620K Electron diffraction pattern.

123

The XPS results conjectured several things about the relative composition of this material. Surface scans were performed along with depth profiling. The surface scans gave a relative composition of 71 at% carbon, 24 at% oxygen, and 5 at% zinc (See Figure

5.1.20). However, it should be noted that these numbers represent a significant amount of surface absorbed carbon and oxygen. To probe the films uniformity and to achieve a clearer representation of the actual composition, through thickness Ar sputtering was used. When performing the depth profiling analysis it was observed that the concentration of the zinc relative to the concentration of the carbon was rapidly increasing even after the first few seconds normally sufficient to remove hydrocarbons absorbed due to sample exposure from handling in air. After 225 s of sputtering the composition of the material had changed to 70 at% zinc, 23 at% carbon, and 7 at% oxygen. Such dramatic change of the measured chemical concentration was indicative of selective sputtering of carbon. A possible schematic of the preferential sputtering of the fullerene cages and the zinc-hiding effect from the incident Ar bombardment is shown in

Figure 5.1.21, which takes into account the high surface area of the exposed C60. The hiding effect is enhanced by the shadowing of Zn atoms from incoming Ar ions due to the oblique incident angle.

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Figure 5.1.20: XPS surface scan of ZnxC60.

Figure 5.1.21: Selective sputtering of carbon in C60 and the hiding effect observed in ZnxC60.

The depth profile XPS scans for both zinc and carbon can be seen in Figure

5.1.22. Interestingly, the spectra showed that after the sample was sputtered for 25 s there was a downshift of about 0.5 eV in the carbon 1s peak. This shift is indicative of a net negative charge on the carbon in the sample-- the expected result for fulleride formation.206 Furthermore, the zinc showed an upshift of about 0.5 eV after 25 s of

125 sputtering which is more in line with what would be expected for pure zinc metal.

Although the XPS was not able to pinpoint the exact composition it was suggestive of the creation of a ZnxC60 fulleride with x in the range of 3-4 with additional Zn coming out as another phase.

Figure 5.1.22: Depth Profile of ZnxC60 for carbon 1s peak (a) and zinc 2p 3/2 peak (b). Each scan represents sputtering for increments of 25 seconds from the surface scan.

A gradient composition Zn-C60 sample was also prepared using the synthesis described above, however, the substrate stage was not rotated during deposition of the zinc films. This meant that the expected sample should have a variable thickness of zinc.

126

To confirm this, a compositional line scan was performed using the Kratos XPS. Analysis of the Zinc 2p 3/2 peak revealed the composition from the start of the scan to the end with increase in the Zn concentration from 6.7% to 11.5% (Figure 5.1.23).

Figure 5.1.23: (Left) Optical image of gradient sample (Right) Zn at % spatially resolved across the sample.

5.1.4 Growth of Fulleride Nanowires

The fabrication of the Zinc fullerides nanowires was carried out in custom built chemical vapor deposition system fitted with a quartz tube as can be seen in Figure 4.1.4.

Granular zinc powder (Aldrich Chemicals) and microcrystalline C60 powder (MER

Corp.) were placed in an aluminum oxide crucible in the center of the evaporation zone.

The pressure and flow rate flow rate in the chamber were actively controlled using a

MKS pressure controller and a MKS mass flow controller respectively. The temperature ramp rate on both furnaces was set to 20ºC. The temperature in both zones were held for

15 hours and then allowed to cool naturally. To gain perspective on the ideal growth conditions a matrix of various samples were prepared (see Table 5.1.2)

127

CVD Runs for optimizing Growth

Temp Side 1 (°C) Time (h) Temp Side 2 (°C) Time (h) Flow (SCCM) Press (Torr) 1000 15 200 15 10 3.7 1000 15 250 15 10 3.7 1000 15 300 15 10 3.7 950 15 350 15 10 3.7 950 15 350 15 40 3 950 15 325 15 15 5 950 15 325 15 10 5 900 15 300 15 10 5 950 15 325 15 40 4

Table 5.1.2: Processing conditions to find the optimal growth parameters.

After analyzing all of the samples listed in Table 5.1.2 the optimum growth conditions were found (i.e. Temp Side 1 = 950 ºC, Temp Side 2 = 350 ºC, Flow Rate =

10 SCCM, and a Pressure = 3.7 Torr). These conditions yielded approximately 85%.

After a run had completed, two distinct regions coating the inside wall of the entire growth zone appeared. The growth region closest to the hot zone (i.e. zone 1) was a light gray color material, while the zone further from the hot zone (i.e. zone 2) was dark gray wool like material. The material that was collected furthest from the hot zone (i.e. the dark gray wool like material) was analyzed first.

The SEM micrographs shown in Figure 5.1.24 displayed that the material produced in zone 2 has a rod like geometry consisting of wires with diameters in the range of 50-200 nm and several microns in length. Furthermore, the structures do not consist of straight geometries, and tend to follow a tortuous path where several kinks and serpentine configurations can be observed. This is advantageous for two reasons 1) the

128 kinks and bends in the tube are most likely caused by dislocations and defects in the crystal structure which should act as phonon scattering sites and 2) free electrons in the materials should be allowed to tunnel between wires whereas the phonons will be forced to scatter. The EDAX analysis of this material suggested that the composition was 25 at%

Zn, 64 at% Carbon, and 11 at% oxygen.

Figure 5.1.24: Scanning electron micrograph of the as grown Zinc Fulleride nanowires. The insert shows an EDAX of the as produced wires, displaying homogeneity of the structure over a large region.

204 Raman spectroscopy of pure C60 has previously been performed. The Raman spectroscopy seen in Figure 5.1.25 shows peaks that can be attributed to pure C60, shifts

205,206 in normal C60 modes, and new vibrational modes induced by metal C60 interactions.

These shifts, along with the additional peaks, are indicative of the creation of transition

129 metal fullerides.205,206 In comparing this compound to known transition metal fullerides

-1 other studies have shown that for each 6 cm shift in Ag(2) mode, the C60 in ionic compounds is holding an additional electron.205,208 This compound shows a shift of

-1 approximately 10 cm which would suggest that the C60 molecule is holding between 1 and 2 electrons. The nature of this particular shift is linked to the bonding mode between the metal and the fullerene. If the bonding is strictly ionic one would expect a very large dependence between peak position and formal charge on C60; however, if the nature of the bonding is more covalent this dependence might not be as straightforward.

Hg(1) Ag(2)

Figure 5.1.25: Raman spectra of the Zinc Fulleride nanowires. In the inserts are enlarged regions of Hg(1) and Ag(2) modes with Lorentzian peak fits.

The SEM micrographs shown in Figure 5.1.26 displays the material produced in zone 2, which had a serpentine tube like geometry with diameters in the range of 50-

200nm and several microns in length. Furthermore, the structures appeared in the back scattered detector to be somewhat electron transparent, suggesting that that the walls were very thin. X-ray diffraction measurement showed that the tubes had three phases, composed of Zinc (DB Card# 03-065-3358), Zinc Oxide (DB Card# 01-079-0207), and buckminster fullerene (DB Card# 00-044-0558) see Figure 5.1.27. The peaks for each of

130 these three phases was identified in Figure 5.1.27 and labeled according to crystal orientation. These phases were further investigated using high resolution transmission electron microscopy (TEM). The structures do not consist of straight geometries, and tend to follow a tortuous path where several kinks and serpentine configurations can be observed.

a) b) c)

100u d) m e) f)

30u m Figure 5.1.26: a) d) SEM images (various magnifications) of the material produced in zone 2 b) c) e) f) TEM images (various magnifications) of the material produced in zone 2.

131

Figure 5.1.27: XRD spectra of the material produced in zone 2. F(x,x,x) represents the fullerene phase, ZO(x,x,x) represents the zinc oxide phase, Z(x,x,x) represents the zinc phase.

The XRD measurements clearly represented three distinct phases in this material.

To gain further insight into the morphology of this material, TEM EDAX mapping was performed. The images seen in Figure 5.1.28 show that the material consisted of zinc oxide hollow tubes, with zinc wires dispersed inside the zinc oxide tubes. The carbon

EDAX images present the case for a small amount of dispersed carbon phase in the zinc oxide and zinc, with the remainder as agglomerates attached to the surface of the zinc oxide tubes and zinc wires. Furthermore, these images were suggestive as to the formation mechanism of the zinc oxide tubes.

132 a) b)

c) d)

Figure 5.1.28: a) TEM image of material collected from zone 2 b) EDAX map Zn peak c) EDAX map of the Oxygen d) EDAX map of the Carbon

Figure 5.1.29 displays the proposed mechanism for the formation of zinc oxide nanotubes. This model describes a self templated growth mechanism, in which the zinc nanowires are grown first and act as the nucleation site for oxide formation. As the oxide continues to grow, zinc from the core nanowire continues to diffuse outward until the zinc is depleted. Furthermore, since there is a small presence of C60 vapor around while this material is nucleating, we believe that it becomes incorporated into the lattice.

133

Figure 5.1.29: Proposed mechanism for the formation of zinc oxide nanotubes.

5.2 Thermal Characterization of DNA and C60 Compounds

5.2.1 Thermal Characterization of DNA-CTMA films

The TDTR technique was chosen to measure the thermal properties of the thin- film material. This method, first introduced by Eesley, is an all-optical, noncontact, and nondestructive measurement that uses ultrashort laser pulses.209 Compared to other thermal conductivity experiments such as laser flash and 3, TDTR provides advantages such as 1) nanometer-scale depth resolution, and 2) differentiation between the thermal conductivity of a thin film and the thermal conductance of its interfaces.210

TDTR measurement were performed on a drop cast sample of the pure DNA, along with a MAPLE deposited film 70:30 (toluene:DMSO, v:v) DNA-CTMA sample.

The results seen in Figure 5.2.1 and Figure 5.2.2 display the experimental data (black line) along with the model fit (red line). The pure DNA drop cast films gave a thermal

134 conductivity reading ( 0.82 W/mK) that was larger than the DNA-CTMA complex (0.62

W/mK). One possible explanation for this was that the CTMA layer coating the DNA complex acts as an additional thermal barrier hindering the phonon movement between

DNA strands. Furthermore, since the CTMA molecule is only ionic bond one would expect a non-coherent interface. This lead to situations where there should be a great deal more scattering, thus lower thermal conductivity.

Figure 5.2.1: TDTR scan of a drop cast film of the pure DNA material.

135

Figure 5.2.2: TDTR scan of the MAPLE deposited film of the DNA-CTMA complex.

5.2.2 Thermal Characterization of Zinc C60 Thin Films

The heat capacity of the fulleride sample was held fixed to the value for pure C60 (

1.2 x 106 J m-3 K-1) .211 Therefore, in the TDTR model, only the thermal conductivity of the thin film and the thermal conductance of the Al/film interface were varied. The measured thermal conductivity was 0.13 ± 0.01 W m-1 K-1(see Figure 5.2.3). Due to such a low thermal conductivity value, the TDTR model was insensitive to the Al/film interfacial conductance. An example plot with representative data and models is shown in

Figure 8. Also shown in Figure 5.2.3 is a scan for amorphous SiO2, and the figure illustrates that the fulleride film is about an order of magnitude lower in thermal conductivity.

136

Figure 5.2.3: Example scans of TDTR data and models for the thermoelectric samples studied. A scan from amorphous SiO2 (a calibration standard) and model is also shown for comparison.

Interestingly, this value for the ZnxC60 film is lower than a similarly-deposited

-1 -1 pure C60 thin film, the latter having a thermal conductivity of 0.15 ± 0.01 W m K .

Furthermore, this material demonstrated a 11x improvement in thermal conductivity over other known fullerides.212 The low thermal conductivity of the metal/fullerene films is very promising, especially when compared with those of some standard TE materials.

A gradient composition Zn-C60 sample was analyzed for composition in the

Kratos XPS and a line scan was performed with the automated TDTR system to measure thermal conductivity. The composition from the start of the scan to the end showed an increase in the Zn concentration from 6.7% to 11.5% (Figure 5.1.23). The TDTR line scan showed a decrease in thermal conductivity from about 0.05 W/m*K to about 0.03

137

W/m*K (Figure 5.2.4) corresponding with the increase in Zn content. While there is a downward trend in thermal conductivity, there are outliers at several points in the scan.

This can be attributed to variability in the sample surface as the sample had visible surface roughness appearing as fine horizontal lines as seen in Figure 5.1.23. The lines are a result of surface damage from previous scanning micro-Seebeck measurements.

Another issue with the sample surface was due to the unevenness, locating an acoustic echo to accurately determine the aluminum sensor layer thickness was very difficult. The thickness of the aluminum layer is a sensitive parameter in the data modeling, which would lead to more uncertainty in the measured value. Due to the surface damage issue and noisier than expected data, a second, undamaged sample will be analyzed to verify the results.

Figure 5.2.4: Thermal conductivity of each spot in Zn-C60 gradient composition sample

5.2.3 Thermal Characterization of the Zinc C60 Nanowires

A portion of the loose powder collected from zone 2 of the CVD furnace was isostatically cold pressed into a 10 mm circular die at 10 MPa (two samples were

138 produced). Using these samples the thermal conductivity was measured by the hot disk method. This gave values ranging from 4.90 W/mK to 5.99 W/mK from -20 ºC to 100 ºC

(see Figure 5.2.5). This represents a significant decrease compared to that of pure Zinc metal (typically > 30 W/mK). There are several reasons that this samples thermal conductivity might be lower. One of the most obvious possibilities is that the fullerene / fulleride inclusion in the wire are acting as scattering sites for phonon. Another possibility involves the scattering of phonon at the wire to wire interfaces. Additionally, since the sample is very zinc rich, it could be that the fullerides phase is acting as a diffusive interface which can severally limit thermal transport.

Figure 5.2.5: Thermal conductivity of the fullerides nanowires as a function of temperature.

5.3 Electrical Characterization of Fullerides

5.3.1 Electrical conductivity of ZnxC60 Thin Films and ZnxC60 Nanowires

Electrical conductivity of the ZnxC60 thin films was performed using the 4-point probe method mentioned above. Using this method the ZnxC60 thin films had an electrical conductivity of 4.8 S/cm. When comparing this value to those of other reported in the

139

-8 -14 literature for single crystals of the pure C60 (~10 S/cm), and thin films of C60 (~10 ) this value is exceeding large. Also, this result represents the very unusual situation where the doping of a material simultaneously increasing the electrical conductivity several orders of magnitude while decreasing it thermal conductivity. To investigate how the electrical conductivity of these films was affected by the zinc concentration conductivity mapping using the PSM was attempted. The results achieved for this measurement were inconclusive and a detailed write up can be seen in the appendix.

The electrical conductivity of the pressed pellet of the zinc nanowires produced in zone 2 was measured using the PPMS instrument described above. This instrument makes use of a 4-point probe technique; however, it has a variable temperature stage.

This allows for the electrical measurements of the sample at several different temperatures. The results can be seen in Figure 5.3.1. While these numbers are an order of magnitude lower than that of pure zinc (~1.6x107 S/m) they remain very large, especially when comparing them to other thermoelectric materials. The other curiosity surrounding this measurement pertains to how the sample can remain this conductive while having a modest thermal conductivity. Furthermore, since the behavior of this material is that of a metal, it would be expected that the overwhelming majority of the heat carriers are free electrons. If this is the case it would be expected that the

Wiedemann-Franz (WF) law would hold and the thermal and electrical conductivity ratio would remain a relative constant. That is not the case here and further discussion of this issue will be presented in the electron-phonon coupling section.

140

Figure 5.3.1: Electrical conductivity measurement of the zinc fullerides nanowires.

5.3.2 Seebeck Coefficient of ZnxC60 Thin Films and ZnxC60 Nanowires

A plot showing the measurement of the open circuit voltage V as a function of the temperature gradient across the film is shown in Figure 5.3.2. The plot shows the expected linear relationship (i.e. constant change in Voltage with respect to change in temperature), allowing the Seebeck coefficient to be obtained via: S = dV/dT. After subtracting the contact potential the Seebeck coefficient for our material at room temperature was 5 µV/K. The sign of the thermopower was positive indicating that holes are the majority carriers.

141

0.0004

0.0003

0.0002

0.0001

0 Voltage (V)

-0.0001

-0.0002

-0.0003

-0.0004 -15 -10 -5 0 5 10 15 20 Temp Difference (K) Figure 5.3.2: Room Temperature Seebeck measurement

The gradient ZnxC60 sample was characterized using the PSM, to access how the concentration of zinc was affecting the Seebeck coefficient of the material. The results can be seen in Figure 5.3.3. The left corner of this image represents the highest concentration of zinc, and the bottom left corner of the sample represent the lowest concentration of zinc, as analyzed by the XPS line scan. This data reveals that as the concentration of zinc is increased in the sample there is a clear trend to lower Seebeck coefficients. The erratic nature of the scan profile can be attributed mostly to inaccuracy in this measurement. We noted that as the scan was progressing micro- indentations were visible on the surface. This suggested that the contact pressure and was enough to damage / deform the thin film. While not detrimental, this type of damage could result in material contamination.

142

Figure 5.3.3: PSM map of the Seebeck coefficient of the gradient ZnxC60 sample.

The Seebeck coefficient of the pressed zinc C60 nanowire sample (zone 2) was analyzed using the PPMS. The results can be seen in Figure 5.3.4. The value for the

Seebeck coefficient is seen to change from ~5uV/K to ~7uV/K at high temperature.

These numbers represent a very low thermal power which is typical of metal.

Furthermore, these result correlate well with the ZnxC60 thin film samples. They also are indicative of holes being the majority carrier.

143

Figure 5.3.4: Seebeck coefficient of the pressed zinc C60 nanowire sample (zone 2).

5.3.3 Electron-Phonon Coupling in ZnxC60 Nanowires

The Wiedemann-Franz (WF) law states that at a given temperature the ratio of a materials electronic thermal conductivity e to electrical conductivity  is equal to a constant called the Lorenz number Lo, such that Lo = e /The WF law especially pertains to materials best approximating a Fermi gas where the thermal and electrical currents are carried by the same fermionic quasiparticles, and instances of significant deviations from WF are of current interest.213 Since the thermal conductivity and the electrical conductivity are both proportional to the number of charge carriers, WF works as long as the heat capacity of the electrons and the mobility of the electrons are gaseous.

Deviations from WF are known when, for example, electron-electron interactions and electron-phonon interactions come into play.213-215 In the present case, the exceptionally large electrical conductivity and modest thermal conductivity suggest values for the

Lorenz number that are an order of magnitude lower. In this paper we will report the

144 synthesis and characterization of zinc fullerides nanowires and suggest a possible mechanism for the large deviation observed.

The following presents a case for the possible explanation of this result.

Generally, the electrons are thought the dominant carriers of charge and heat in metallic samples, and therefore, a decrease of electron mobility due to scattering should reduce thermal conductivity and electrical conductivity by the same factor, and consequently their ratio should be equal to the bulk Lorenz number. In analysis of the pressed zinc C60 nanowires we find that there is actually quite a large variation from WF (see Figure 5.3.5)

Figure 5.3.5: Deviation from WF of the pressed pellet of zinc C60 nanowires.

Research on single electron transistors have shown large violations in WF law can occur, however, these violations have led to situations where L/Lo >> 1, unfortunately providing materials with much lower ZTs.216 Recent theoretical work has suggested that

145 by increasing the electron-phonon coupling constant, , one can increase the number of resonance peaks and enable multi-phonon-assisted tunneling.217 This can have a very large effect on the values of ZT and Ren et al. predicted that if materials can be made with large strong violations in the WF law are possible and ZT of greater than 10 are possible. To investigate  in our material we performed analysis on the Raman spectra observed. In metallic fullerides, others have characterized the broadness of the Hg derived intermolecular vibrations as a result of coupling of the degenerate t1u electronic states. Since orientational disorder leads to a violation of momentum conservation, the observed scattering in the Raman spectra gives a measure of the decay of a phonon into an electron hole pair, allowing estimation of 

The electron-phonon coupling constant can be expressed mathematically as seen in Equation 5.3.1. Where is the degeneracy of the mode (5 for Hg modes), is the difference between the FWHM of the th mode of the measured material and that of pure

C60 , 𝜔i is the phonon frequency, and N(0) is electronic density of state per spin at the

Fermi level. All of these values can be directly calculated from the fitted Raman spectra except for N(0). However, using the framework of Allen’s theory to obtain the linear relationship between linewidth and density of states this value can be estimated as seen in equation 2. Where is the FWHM of the fitted th mode, and is the bare phonon frequency of the Hg(1) mode of pure C60. This assumes that the Hg(1) mode has five fold degeneracy and loses this when splitting into individual components. These individual components can then be fit and compared with the Hg(1) mode of pure C60. This type of heuristic has been used in the past and has given reasonably good correlation to predicted values of N(0) for metallic fullerides.

146

Equation 5.3.1: Equation for the electron phonon coupling constant Where is the degeneracy of the mode (5 for Hg modes), is the difference between the th FWHM of the mode of the measured material and that of pure C60 , 𝜔i is the phonon frequency, and N(0) is electronic density of state per spin at the Fermi level.

The Lorentzian fitting and application of Allen’s formula for the Hg(1) modes can be seen in Figure 5.3.6. To most accurately estimate the electron phonon coupling constant, one needs to sum up the contributions from all of the Hg and Ag modes.

However, since  is inversely proportion to the square of the phonon frequency it can be assumed that modes higher than Hg(2) do not contribute significantly to the overall value.

This further helps analysis since fitting the higher modes introduces a significant amount of error. The tabulated values for the Hg(1) and Hg(2) modes were Hg(1)=0.17 ,

Hg(2)=0.02 and total 



147

Hg(1)

Figure 5.3.6: Plot of the line width (FWHM) of the fitted Hg(1) modes versus the frequency shift. Insert shows the fitting of the Hg(1) modes.

To understand the role of the fullerides phase in reducing the thermal conductivity below the alloy limit, the thermal conductivity could be predicted using Callaway’s model (see Equation 5.3.2). However, in our case the phonon dispersion curves are not known, thus we can only speculate on the real outcome.

Equation 5.3.2: kB is the Boltzmann constant, ħ is Planck’s constant, x as the normalized frequency, v is the speed of sound, θ is the Debye temperature, τN is the relaxation time due to normal scattering, and τC is the combined relaxation time using Matthiessen’s rule given as follows.

148

Equation 5.3.3: τB is the boundary scattering, τU is the Umklapp related scattering, τN is normal scattering, τA is related to defect or alloy scattering, τeph is electron- phonon scattering, τD is due to fullerene domains.

( 𝜔 ( 𝜔 )

( )

Equation 5.3.4: Equation for approximating the electron-phonon scattering in materials. Here it can be seen that the combined relation time depends on the sum of its parts using the Matthiessen’s rule. Furthermore, it is shown that the relaxation time for phonon electron coupling depends on the square of the electron phonon coupling constant This means that small changes in can cause much larger changes in the overall phonon relaxation time. We speculate that these larger relaxation times, in addition to Jahn-

Teller distortions, are contributing to the large variation in the WF law.

149

CHAPTER VI

CONCLUSIONS AND FUTURE WORK

6 Conclusions

The overarching goal of this work was to outline a framework for the controlled synthesis of carbon nanostructures (e.g. DNA and fullerenes). Once growth conditions were established the relationships between these nanostructural formations and their primary transport properties were investigated. The techniques to deposit these low dimensional formation included MAPLE, thermal evaporation, and CVD. These techniques were selected as they offered a diverse mechanism for deposition and synthesis of carbon nanomaterials.

In studying the thin film formation of DNA-CTMA, we saw that solvent choice was critical for the formation of flat uniform thin films. The root cause for this was identified as Marangoni flow in the droplets that nucleated on the substrates. This concept was further developed through careful experimentation, and continuous films were created. Furthermore, the structure property relationships for these films were investigated using thermal characterization techniques, and a possible mechanism explaining the conductivity was discussed. Overall, this work presented the first successful MAPLE thin film deposition of DNA-CTMA with a mechanism to thwart coffee ring evaporation.

150

The deposition of thin films of fullerides presented its own unique challenges.

When investigating the use of MAPLE for fullerene thin films, we found a distinct interaction between the photo-excited fullerene and the solvent used to deposit it. For this reason MAPLE was abandoned as a possible deposition technique, and a vertical thermal evaporator was constructed. This equipment was then used to create a thin film layered structure of metal and fullerenes. Subsequently, these films were thermally processed and fulleride structures were created. Once the formation mechanism of the fulleride structure was established several samples were created and the physical properties of the thin films were investigated.

Though neutral fullerenes have very poor electrical conductivity, fullerides have been measured to have electrical characteristics from insulating to conducting, depending upon their reduction state. With a carefully-tuned metal/fullerene stoichiometry, it is believed that the ratio of electrical to thermal conductivity can be maximized for use as a

TE material. Moreover, thin films of ZnxC60 were found to have an exceeding low thermal conductivity of 0.13 Wm-1K-1 and modest electrical conductivity of 4.8 S/cm.

XPS, DSC, and Raman Spectroscopy were used to investigate the synthesis and structural properties of the material. Analysis indicated that both covalent and ionic bonding between the zinc atoms and the fullerenes is needed to explain the spectra observed.

Furthermore, analysis of the gradient produced sample suggested that metal content in the

ZnxC60 films could be manipulated to optimize the Seebeck coefficient.

To further extend the knowledge base for the growth of carbon nanostructures, chemical vapor deposition was used to create fulleride nanowires. The growth conditions for these structures were examined, and mechanisms for the formation of these nanowires

151 were identified. Furthermore, the physical properties of these nanowires were explored and a violation of the WF law was observed. Using Raman spectroscopy and the framework established by Allen et al., an estimate of the electron phonon coupling constant was acquired. Subsequently, this was used to establish a possible means to explain the observed violation in the WF law.

Overall this dissertation has presented several deposition and growth methods for carbon nanostructures. Furthermore, a plethora of new mechanisms have been established to control the structure of these materials. Additionally, the structure property relationships have given new insight into the exciting world of nanostructured materials.

It is with great anticipation that I welcome the exciting future of nanotechnology.

6.1 Future Work

The work presented here has established several new mechanisms for controlled nanostructure growth. That being said, several avenues could be explored to further enhance the understanding of this field.

To further advance the study of the nucleation and growth of DNA-CTMA thin films by MAPLE deposition one could use electrostatic quadrupole mass spectroscopy to study the vapor composition. This would give insight into the molecular species present during the deposition, and might suggest how they were interacting. Furthermore, investigation of other solvent systems might lead to new nucleation mechanism allowing for the deposition of a broader range of materials.

152

Additionally, investigating other metals for the formation of fulleride nanostructures would greatly enhance the search for new TE materials. While the results presented here are promising, these results represent a small fraction of what might be possible for the use of fullerides in TE materials. To further this we work we intend to characterize the thin film fullerides and nanowires at low temperatures. This should allow us insight into the fundamental physics, and hopefully allow us to better understand the violation in the WF law.

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APPENDIX

8 Appendix

From the beginning of examining data files exported by the Potential Seebeck

Microprobe (PSM), it was readily noticed that results provided did not seem accurate. For example, the electrical conductivity never rose above 1 S/cm for samples. See Figure 1 below illustrating this point of interest.

Figure 1. Cu substrate with film deposition of C60 and Zn in a graded orientation across surface

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To ensure that PSM was running correctly, bismuth telluride (BiTe) p-type and n- type were obtained. In early tests, it was observed that different values for Seebeck and electrical conductivity were recorded depending on whether the tests were performed together or separate. Thereby, all subsequent tests were run separately to ensure similar testing parameters. Also early in testing it was noticed while cleaning the probe tip that a wire was not connected to the PSM near the probe tip. With assistance, the wire was reattached and testing continued to determine if this could have resulted in erroneous data. Unfortunately, there appeared to be no change in the exported files for the electrical conductivity. It was not determined if the Seebeck coefficient was invalid prior to the wire’s reattachment; nevertheless, the values exported from the PSM for the Seebeck coefficient for BiTe correspond with literature (210-200 μV/K) and can be seen in Table

Table 1. BiTe Seebeck Coefficient from PSM Seebeck Coefficient Material [μV/K]

BiTe n- -200 type

BiTe p- 246 type

Area Correction Factor:

A means of manipulating the electrical conductivity data was then proposed. The data collected from the PSM regarding the electrical conductivity was assumed to be correct, but somewhere in the programming the variables were assumed to have incorrectly related. After detailed analysis, the variables for the simple equation relating

173 electrical conductivity, resistance, characteristic length, and area were identified and their significance is shown in Table 2.

Table 2. Relationship of Variables to PSM Variable Physical Significance of Variable

Probe tip location from side wall during Length (L) measurement

Area (A) Contact area of probe tip

Resistance (R) Resistance of material from side wall to probe tip

Electrical Conductivity Ease of electron travel through material (σ)

Utilizing the BiTe sample which has a well characterized electrical conductivity from literature, it was believe the area value, which is internal and never displayed, could be the culprit for the erroneous data. Using an assumed value of 1000 S/cm, the required area was determined for the p-type and n-type BiTe. Values of 0.001826 cm2 and

0.003277 cm2 were found for the p-type and n-type respectively for what the area should be.

The next question that need to be address was could these values be used for materials other than BiTe. Consequently, a Cu square was tested in the PSM and analyzed using an average of the two area correction factors. The electrical conductivity was determined to be 28300 S/cm using this method. Literature values for copper were given as ~59000 S/cm, however, these were believed to be for thin wire tests and bulk copper would have a lower electrical conductivity. Also, while not visually present, there

174 could have been a thin film of copper oxide as the sample after slight polishing was not kept in an inert atmosphere.

Other sample’s data files were investigated including the Zn fulleride pressed pellet, Zn fulleride 50% doped pressed pellet, Zn fulleride 50% doped and annealed pressed pellet, and Cu substrate with C60 and Zn (shown back in Figure 1). The new electrical conductivity values are below in Table 3.

Table 3. Electrical Conductivity as Determined by the Area Correction Factor Electrical Material Conductivity [S/cm]

Zinc Fulleride 1330

Zinc Fulleride 50% doped with Zn 109

Zinc Fulleride 50% doped and annealed with 2720 Zn

Cu substrate with C60 and Zn thin film 2690000

Examining the trend in the zinc fulleride series, the electrical conductivity follows what would be expected for the material. The zinc fulleride drops in electrical conductivity when doped with zinc nanopowder. This is apparently common due to the ball-milling procedure used. The ball-milling, while dispersing the zinc, does not put the zinc in the interstitial sites like anneal does. This has the potential then to create more resistance due to the additional barriers of a non-homogenized material. The annealed pellet then increases in electrical conductivity due to the zinc settling in interstitial sites and assisting the fulleride in electron transfer as to be expected. The Cu substrate with

C60 and Zn thin film conductivity has an extremely high electrical conductivity and needs to be re-evaluated. The data used was from one of the first runs and could have

175 been either recorded when the wire was not attached at the probe tip, or when the

Seebeck and electrical conductivity were run together.

Modifying the Area Correction Factor:

Up to this point, the area correction factor seems to be generating acceptable values for electrical conductivity. It was then noticed once a surface plot was generated, that there could be issues still with this correction factor. As seen below in Figure 2, the zinc fulleride which should be a homogenous material is anything but homogenous if the area correction factor is true.

Figure 2. Zinc Fulleride Electrical Conductivity across Pellet Using Area Correction

Factor

The average of the electrical conductivity is the 1330 S/cm, however, that is not representative of what should be a uniform sample. This plot prompted a re-examination

176 of the area correction factor. After examining the data file, it concluded that the 1/L factor strongly correlated with the slope seen in Figure 2. A means of normalizing the data is now the issue to be determined. There have been two methods used to approach this problem. The first is to adjust the data at the end, thereby leveling out the rows of electrical conductivity into a corrected electrical conductivity. The second is to eliminate the 1/L issue when it starts, thereby generating a R/L modified value that is used in analysis. The question lies in which of these methods to use and if this data can be verified on another instrument. The results of both correction methods are illustrated below.

177

Figure 3a & 3b. Type 1 Correction Adjustment. Fitting electrical conductivity to power regression in (a) and the resulting normalization is shown in (b). The average electrical conductivity changed from 1330 S/cm to 1640 S/cm.

178

Figure 4a & 4b. Type 2 Correction Adjustment. Fitting R/L to power regression in (a) and the resulting normalization is shown in (b). The average electrical conductivity changed from 1330 S/cm to 1300 S/cm.

This modeling was preformed simultaneous to two other files. ‘High Res with

AFC’ and ‘Double Check’ files were generated at approximately the same time. ‘High

Res with ACF’ file is of n-type BiTe where the electrical conductivity was allowed to be gathered overnight on the PSM in order to generate a data file with considerably more

179 data points. Here too it was noticed that area correction factor was not allowing a homogenous sample to have uniform characteristics.

Figure 5. High Resolution of n-type BiTe after Area Correction Factor has been used

It was assumed that the same equations could be used to adjust the electrical conductivity and normalize it. This was found to be a poor assumption. The same methods can be used; however, the equation used to adjust the electrical conductivity changes each time due to the change in stepping distance and number of points in the x direction. New equations where generated and the average electrical conductivity was re- determined. This process can be better illustrated in Table 4.

180

Table 4. Evolution of Electrical Conductivity Determination for ‘High Res with AFC’ file on n-type BiTe Average Electrical Method Conductivity [S/cm]

Area Correction Factor 5460

Modified Area Correction Factor using Equation from ‘Zinc 85077 Fulleride with AFC’ file

Modified Electrical Conductivity using R/L modifier 890

Modified Electrical Conductivity using Sigma modifier 1014

As can be seen, the latter two methods for determining electrical conductivity appear to be more accurate even on other data files. If you have examined the files, you will notice that the R/L modified equation has a constant at the end that may seem random. This constant was found using Solver in Excel and its origin is in the file ‘Double Check.’

This is the final excel file that has been worked on. It compares the two methods of analysis on several samples including: n-type BiTe, p-type BiTe, a new test file for n- type, copper square, zinc fulleride, zinc fulleride 50% doped, and zinc fulleride 50% doped and annealed. The results of modifying the files with area correction factor and then using either the R/L modifier or Sigma modifier are in Table 5. It was this point that manipulation with electrical conductivity stopped until any data could be validated on another system (i.e. PPSM).

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Table 5. Electrical Conductivity after Area Correction Factor and Normalizing Equation Average Average Electrical Electrical Conductivity using Material Conductivity Sigma Modifier using R/L [S/cm] Modifier [S/cm] n-type BiTe, High Resolution 1014 890 p-type BiTe 4800 4213 n-type BiTe 1238 732

Copper Square 3379 2966

Zinc Fulleride Pressed Pellet 1641 1440

Zinc Fulleride 50% Doped Pressed Pellet 3774 3313

Zinc Fulleride 50% Doped and Annealed 15469 12263 Pressed Pellet

From Table 5, one observation about the methods being used is that one just needs to be chosen. They R/L and the sigma modifier generate the same number given the uncertainty of the PSM instrument. Another observation is that while, the n-type BiTe values are close to the literature values (1000 S/cm), the p-type BiTe is off by a factor of

4. Refining the data file to exclude points far from the average electrical conductivity

(approximately 6% of data points) drops the electrical conductivity to 2156 S/cm; thereby achieving a more reasonable, yet off, value for the p-type. The copper square is low from its literature value, but like explained earlier, this is possibly due to copper oxide formation. Next, the series of zinc fulleride pressed pellets seem reasonable for the trend.

It can be debated as to whether the only doped pellet should be above or below the plain pellet. Lastly and most important, the validity of the all values in Table 5, hinges upon

182 the PSM being accurate in its data collection and reporting. The testing samples need to be examined on another instrument to compare results and confirm or deny our interpretations to the electrical conductivity.

183