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Fiber Textures: application to thin film textures

Fiber Textures: application to thin film textures. 27-750, Spring 2008 A. D. (Tony) Rollett. Acknowledgement : the data for these examples were provided by Ali Gungor; extensive discussions with Ali and his advisor, Prof. K. Barmak are gratefully acknowledged. Lecture Objectives.

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Fiber Textures: application to thin film textures

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  1. Fiber Textures: application to thin film textures 27-750, Spring 2008 A. D. (Tony) Rollett Acknowledgement: the data for these examples were provided by Ali Gungor; extensive discussions with Ali and his advisor, Prof. K. Barmak are gratefully acknowledged.

  2. Lecture Objectives • Give examples of experimental textures of thin copper films; illustrate the OD representation for a simple case. • Explain (some aspects of) a fiber texture. • Show how to calculate volume fractions associated with each fiber component from inverse pole figures (from ODF). • Explain use of high resolution pole plots, and analysis of results. • Discuss the phenomenon of axiotaxy - orientation relationships based on plane-edge matching instead of the usual surface matching. • Give examples of the relevance and importance of textures in thin films, such as metallic interconnects, high temperature superconductors and magnetic thin films. Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  3. Summary • Thin films often exhibit a surprising degree of texture, even when deposited on an amorphous substrate. • The texture observed is, in general, the result of growth competition between different crystallographic directions. In fcc metals, e.g., the 111 direction typically grows fastest, leading to a preference for this axis to be perpendicular to the film plane. • Such a texture is known as a fiber texture because only one axis is preferentially aligned whereas the other two are uniformly distributed (“random”). • Although vapor-deposited films are the most studied, similar considerations apply to electrodeposited films also, which are important in, e.g., copper interconnects. • Especially in electrodeposition, many different fiber textures can be obtained as a function of deposition conditions (current density, chemistry of electrolyte etc., or substrate temperature, deposition rate). • Even the crystal structure can vary from the equilibrium one for the conditions. Tantalum is known is known to deposit in a tetragonal form (with a strong 001 fiber) instead of BCC, for example. • Thin film texture should be quantified with Orientation Distributions and volume fractions, not by deconvolution of peaks in pole figures, or pole plots. The latter approach may look straightforward (and similar to other types of analysis of x-ray data) but has many pitfalls.

  4. Example 1: Interconnect Lifetimes • Thin (1 µm or less) metallic lines used in microcircuitry to connect one part of a circuit with another. • Current densities (~106 A.cm-2) are very high so that electromigration produces significant mass transport. • Failure by void accumulation often associated with grain boundaries Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  5. Interconnects provide a pathway to communicate binary signals from one device or circuit to another. Issues: - Performance - Reliability A MOS transistor (Harper and Rodbell, 1997) Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  6. Reliability: Electromigration Resistance • Promote electromigration • resistance via microstructure • control: • Strong texture • Large grain size • (Vaidya and Sinha, 1981) Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  7. Top view (111) _ _ - (111) (111) e Grain Orientation and Electromigration Voids • Special transport properties on certain lattice planes cause void faceting and spreading • Voids along interconnect direction vs. fatal voids across the linewidth Slide courtesy of X. Chu and C.L. Bauer, 1999. Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  8. Aluminum Interconnect Lifetime Stronger <111> fiber texture gives longer lifetime, i.e. more electromigration resistance H.T. Jeong et al. Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  9. References • H.T. Jeong et al., “A role of texture and orientation clustering on electromigration failure of aluminum interconnects,” ICOTOM-12, Montreal, Canada, p 1369 (1999). • D.B. Knorr, D.P. Tracy and K.P. Rodbell, “Correlation of texture with electromigration behavior in Al metallization”, Appl. Phys. Lett., 59, 3241 (1991). • D.B. Knorr, K.P. Rodbell, “The role of texture in the electromigration behavior of pure Al lines,” J. Appl. Phys., 79, 2409 (1996). • A. Gungor, K. Barmak, A.D. Rollett, C. Cabral Jr. and J.M. E. Harper, “Texture and resistivity of dilute binary Cu(Al), Cu(In), Cu(Ti), Cu(Nb), Cu(Ir) and Cu(W) alloy thin films," J. Vac. Sci. Technology, B 20(6), p 2314-2319 (Nov/Dec 2002). • Barmak K, Gungor A, Rollett AD, Cabral C, Harper JME. 2003. Texture of Cu and dilute binary Cu-alloy films: impact of annealing and solute content. Materials Science In Semiconductor Processing 6:175-84. -> YBCO textures Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  10. Fiber Textures • Common definition of a fiber texture: circular symmetry about some sample axis. • Better definition: there exists an axis of infinite cyclic symmetry, C, (cylindrical symmetry) in either sample coordinates or in crystal coordinates. • Example: fiber texture in two different thin copper films: strong <111> and mixed <111> and <100>. Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  11. film substrate Research on Cu thin films by Ali Gungor, CMU See, e.g.: Gungor A, Barmak K, Rollett AD, Cabral C, Harper JME. Journal Of Vacuum Science & Technology B 2002;20:2314. C 2 copper thin films, vapor deposited:e1992: mixed <100> & <111>; e1997: strong <111> {001} PF for strong <111> fiber Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  12. Epitaxial Thin Film Texture From work by Detavernier (2003): if the unit cell of the film material is a sufficiently close match (within a few %) the two crystal structures often align.

  13. Axiotaxy - NiSi films on Si Detavernier C, Ozcan AS, Jordan-Sweet J, Stach EA, Tersoff J, et al. 2003. An off-normal fibre-like texture in thin films on single-crystal substrates. Nature426: 641 - 5. Spherical projection of {103}:

  14. Plane-edge matching  Axiotaxy C. Detavernier

  15. Possible Orientation Relationships

  16. Fiber Textures: Pole Figure Analysis:Example of Cu Thin Film: e1992 Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  17. Recalculated Pole Figures: e1992 Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  18. COD: e1992: polar plots:Note rings in each section Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  19. SOD: e1992: polar plots:note similarity of sections Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  20. Crystallite Orientation Distribution (COD):e1992 1. Lines on constant Qcorrespond to rings inpole figure 2. Maxima along top edge = <100>; <111> maxima on Q= 55° (f = 45°) Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  21. Sample Orientation Distribution (SOD): e1992 1. Self-similar sections indicate fiber texture:lack of variation withfirst angle (y). 2. Maxima along top edge -> <100>; <111> maxima on Q= 55°, f = 45° Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  22. Experimental Pole Figures: e1997 Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  23. Recalculated Pole Figures: e1997 Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  24. COD: e1997: polar plots:Note rings in 40, 50° sections Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  25. SOD: e1997: polar plots:note similarity of sections Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  26. Crystal Orientation Distribution (COD): e1997 1. Lines on constant Qcorrespond to rings inpole figure 2. <111> maximumon Q= 55° (f = 45°) Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  27. Sample Orientation Distribution (SOD): e1997 1. Self-similar sections indicate fiber texture:lack of variation withfirst angle (y). 2. Maxima on <111> on Q= 55°, f = 45°,only! Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  28. Fiber Locations in SOD [Jae-Hyung Cho, 2002] <100>fiber <110>fiber <100>,<111>and<110>fibers <111>fiber Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  29. Inverse Pole Figures: e1997 Slight in-plane anisotropy revealed by theinverse pole figures.Very small fraction of non-<111> fiber. Electromigration Weak Strong IPF VolumeFraction PolePlot Deconvolution

  30. Inverse Pole figures: e1992  <111> <11n> <001> <110> F TransverseDirectionTD NormalDirectionND RollingDirectionRD Electromigration Weak StrongIPF VolumeFraction PolePlot Deconvolution

  31. Method 1: Volume fractions from IPF • Volume fractions can be calculated from an inverse pole figure (IPF). • Step 1: obtain IPF for the sample axis parallel to the C symmetry axis. • Normalize the intensity, I, according to 1 = SI()sin() dd • Partition the IPF according to components of interest. • Integrate intensities over each component area (i.e. choose the range of  and ) and calculate volume fractions:Vi =SiI()sin() dd • Caution: many of the cells in an IPF lie on the edge of the unit triangle, which means that only a fraction of each cell should be used. A simpler approach than working with only one unit triangle is to perform the integration over a complete quadrant or hemisphere (since popLA files, at least, are available in this form). In the latter case, for example, the ranges of  and  are 0-90° and 0-360°, respectively. Electromigration Weak StrongIPF VolumeFraction PolePlot Deconvolution

  32. Volume fractions from IPF • How to measure distance from a component in an inverse pole figure?- This is simpler than for general orientations because we are only comparing directions (on the sphere).- Therefore we can use the dot (scalar) product: if we have a fiber axis, e.g. f = [211], and a general cell denoted by n, we take f•b (and, clearly use cos-1 if we want an angle). The nearer the value of the dot product is to +1, the closer are the two directions. • Symmetry: as for general orientations one must take account of symmetry. However, it is sensible to simplify by using sets of symmetrically related points in the upper hemisphere for each fiber axis, e.g. {100,-100,010,0-10,001}. Be aware that there are 24 equivalent points for a general direction (not coincident with a symmetry element).

  33. Method 2: Pole plots • If a perfect fiber exists then it is enough to scan over the tilt angle only and make a pole plot. • A “perfect fiber” means that the intensity in all pole figures is in the form of rings with uniform intensity with respect to azimuth (C, aligned with the film plane normal). • High resolution is then feasible, compared to standard 5°x5° pole figures, e.g 0.1°. • High resolution inverse PF preferable but not measurable. Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  34. {001} Pole plots Intensityalong aline fromthe centerof the {001}polefigureto theedge(any azimuth) e1992: <100> & <111> e1997: strong 111 Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  35. High Resolution {111} Pole plots e1997: pure <111>; very small fractions other? e1992: mixture of <100>and <111> ∆tilt = 0.1° Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  36. Volume fractions • Pole plots (1D variation of intensity):If regions in the plot can be identified as being uniquely associated with a particular volume fraction, then an integration can be performed to find an area under the curve. • The volume fraction is then the sum of the associated areas divided by the total area. • Else, deconvolution required, which, unfortunately, is the usual case. • In other words, this method is only reasonable to use if the only components are a single fiber texture and a random background. Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  37. {111} Pole plots for thin Cu films E1992: mixture of 100 and 111 fibers E1997: strong 111 fiber <100> <111> Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  38. Log scale for Intensity NB: Intensities not normalized Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  39. Area under the Curve • Tilt Angle equivalent to second Eulerangle, q F• Requirement: 1 = S I(q)sin(q) dq; qmeasured in radians. • Intensity as supplied not normalized. • Problem: data only available to 85°: therefore correct for finite range.• Defocusing neglected. Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  40. Extract Random Fraction Mixed <100>and <111>,e1992 Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  41. Normalized Randomcomponentnegligible~ 4% Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  42. Deconvolution • Method is based on identifying each peak in the pole plot, fitting a Gaussian to it, and then checking the sum of the individual components for agreement with the experimental data. • Areas under each peak are calculated. • Corrections must be made for multiplicities. Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  43. {111} Pole Plot <111> <100> <110> A3 A2 A1 q Ai = Si I(qsinq dq Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  44. {111} Pole Plot: Comparison of Experiment with Calculation Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  45. {100} Pole figure: pole multiplicity:6 poles for each grain <100> fiber component <111> fiber component North Pole South Pole 3 poles on each of two rings, at ~55° from NP & SP 4 poles on the equator;1 pole at NP; 1 at SP Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  46. {100} Pole figure: Pole Figure Projection (010) The number of poles present in a pole figure is proportional to the number of grains (-100) (100) (001) (001) (100) (010) (0-10) <100> oriented grain: 1 pole in the center, 4 on the equator <111> oriented grain: 3 poles on the 55° ring. Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  47. {111} Pole figure: pole multiplicity:8 poles for each grain <100> fiber component <111> fiber component 1 pole at NP; 1 at SP3 poles on each of two rings, at ~70° from NP & SP 4 poles on each of two rings, at ~55° from NP & SP Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  48. {111} Pole figure: Pole Figure Projection (-111) (111) (-111) (1-11) (001) (111) (-1-11) (1-11) (-1-11) <100> oriented grain: 4 poles on the 55° ring <111> oriented grain: 1 pole at the center, 3 poles on the 70° ring. Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  49. {111} Pole figure: Pole Plot Areas • After integrating the area under each of the peaks (see slide 35), the multiplicity of each ring must be accounted for. • Therefore, for the <111> oriented material, we have 3A1 = A3;for a volume fraction v100of <100> oriented material compared to a volume fraction v111 of <111> fiber,3A2 / 4A3 = v100 /v111and,A2 / {A1+A3} = v100 /v111 Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

  50. Intensities, densities in PFs • Volume fraction = number of grains  total grains. • Number of poles = grains * multiplicity • Multiplicity for {100} = 6; for {111} = 8. • Intensity = number of poles  area • For (unit radius) azimuth, f, and declination (from NP), q, area, dA = sinq dq df. Electromigration Weak StrongIPFVolumeFraction PolePlot Deconvolution

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