1. Characterizing the Nanoscale Layers of Tomorrow’s Electronics : An Application of Fourier Analysis Chris Payne In Collaboration With: Apurva Mehta & Matt Bibee

2. A Relevant Challenge Moore’s Law demands smaller devices Economically smart Compatible with current fabrication facilities The electronics industry is increasingly focusing on thin film applications … …but they need a way to characterize the layer structure of these devices on the nanometer scale Bearing in mind a single page is about 100,000 nanometers thick ~200nm

3. Defining the Challenge -Number of Layers -Layer Order -Individual Layer Thickness -Individual Layer Density -Chemistry -Individual Layer Roughness Glass Substrate Zinc Oxide(3) Silicon(2) Zinc Oxide(1) Cross sectional SEM look at a solar cell X-Ray Reflectivity Can Help Provide A Comprehensive Answer to All these Questions

4. Our Tool : XRR Reflectivity Detector Substrate Thin Top Layer X-Ray Source Θ z λ The path length difference causes interference patterns to arise at the detector according to: Reflectivity Detector X-Ray Source

5. The path length distance, a function of Θ and Z, is embedding information in the interference pattern seen by the detector, But what does this interference look like? How this Interference appears in the Data Θ z λ The varying interference appears as oscillations that span over 8 Orders of Magnitude! The oscillations carry the information we want!

6. 1. We first convert Θ to S which importantly gives the X – axis units of m -1 2. The intensity can now be approximated (assuming no roughness) as I Extracting Oscillations Mathematically Layer 2 SubstrateLayer 1 Z Derivate of Density Depth Along Z Θ Z

7. Extracting Oscillations Mathematically 3. Lastly, lets cut out the Falloff term and free the thickness information from the FT, by taking the inverse FT 2N Algorithm (Because the falloff isn’t as simple as s 4 ) Inverse Fourier Transform

8. Applying the Math to Simulated Data Substrate Layer 1 Layer 2 2 nm 20 nm Using a simulation program, I generate raw intensity data for two layers on a substrate

9. Applying the Math to Simulated Data Then I convert to s:

10. Applying the Math to Simulated Data Calculate local average point by point using 2N Method S [ Gm -1 ]

11. Applying the Math to Simulated Data Remove the falloff: S [Gm -1 ]

12. Applying the Math to Simulated Data Take the FT inverse, to ‘unlock’ FT: Substrate Layer 1 Layer 2 Important Note: At this time, this technique does not indicate the order of the layers! Nanometers

13. Applying this Process to Real Data Original Sample Cleaned Sample ??? Silicon Oxide SiC Substrate ??? Silicon Oxide SiC Substrate

14. Thank You For Your Time Especially Apurva Mehta & Matt Bibee