An Algorithm to Simulate Two- Dimensional Scattering Patterns of - - PowerPoint PPT Presentation

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An Algorithm to Simulate Two- Dimensional Scattering Patterns of - - PowerPoint PPT Presentation

An Algorithm to Simulate Two- Dimensional Scattering Patterns of Particles for Use in Holography Claudia Morello, Embry-Riddle Aeronautical University Matt Berg, Osku Kemppinen, Kansas State University Overview Holography is Relatively


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An Algorithm to Simulate Two- Dimensional Scattering Patterns of Particles for Use in Holography

Claudia Morello, Embry-Riddle Aeronautical University Matt Berg, Osku Kemppinen, Kansas State University

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Overview

 Holography is

 Relatively new  Lots of effort  Perfect to use for tiny things that move

 Will be used with a drone for agricultural research

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My Project

 To create an algorithm that will make the scattering

pattern for any particle

 Basically to make a library to match a scattering pattern

to a particle

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Process

 Learn python/ theory  Figure out algorithm by comparing the experimental

and simulated pattern using trial and error

 Test and refine the algorithm  Simulate the patterns of every particle I can

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Theory

 Rayleigh Scattering  Interference  Symmetry

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Algorithm

 Designed by starting with a silhouette of a particle and

an experimental scattering pattern to see how similar I could get

 Now only need a silhouette

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Testing

 Airy Curve

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From Huygens-Fresnel and Babinet Principles

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Two Spherical Particles Pecan Pollen Glass Sphere

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Conclusion

 No one really knew how well this project would work  Worked a lot better than anticipated  Can now simulate 2-D scattering patterns of nearly any

particle

 Future work will probably consist of making a library to

match the scattering pattern to the particle

 Or 3D patterns

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References

  • 1. M. J. Berg, S. Holler (2016). Simultaneous holographic

imaging and light-scattering pattern measurement of individual microparticles (pdf). Optics Letters, 41, 3363

  • 3366.
  • 2. “Open-CV Python Tutorial." Open-CV. Open Source

Computer Vision, n.d. Web. 28 Jul. 2017.