Characterization of polygrama green photopolymer for Compact Optoelectronic Integrated Neural (COIN) coprocessor applications
Includes bibliographical references (leaves 33-34).
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2009
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| Online Access: | http://hdl.handle.net/1721.1/44461 |
| _version_ | 1826189201685610496 |
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| author | Harton, Renee M |
| author2 | Cardinal Warde. |
| author_facet | Cardinal Warde. Harton, Renee M |
| author_sort | Harton, Renee M |
| collection | MIT |
| description | Includes bibliographical references (leaves 33-34). |
| first_indexed | 2024-09-23T08:11:25Z |
| format | Thesis |
| id | mit-1721.1/44461 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T08:11:25Z |
| publishDate | 2009 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/444612019-04-09T17:12:51Z Characterization of polygrama green photopolymer for Compact Optoelectronic Integrated Neural (COIN) coprocessor applications Harton, Renee M Cardinal Warde. Massachusetts Institute of Technology. Dept. of Physics. Massachusetts Institute of Technology. Dept. of Physics. Physics. Includes bibliographical references (leaves 33-34). Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Physics, 2008. The research described in this thesis is a portion of a larger project within the Photonic Systems Group at MIT to design Compact Optoelectronic Integrated Neural (COIN) co processor [13]. The choice of photopolymers is critical in determining the performance of COIN processors as we look at ways to increase the diffraction efficiency. The focus of this research was to optically characterize Polygrama Green, a photopolymer that is sensitive to green light (514 nm). We were able to plot diffraction efficiency versus the exposure energy density for a series of gratings. We found the maximum diffraction efficiency to be that of the 678 mJ/cm2 grating with a value of 29.5%. We were able to fit the data to a sin2(x) curve with a X2- value of 20.79. We concluded that this somewhat high X2-value is due to our low number of data points. However, using Kogelnik's equation and the measured diffraction efficiency of each grating, we were also able to calculate the An, of each grating. This analysis shows that Polygrama Green seems to be a promising candidate for the photopolymer used in subsequent optoelectronic neural network applications. by Renee M. Harton. S.B. 2009-01-30T16:49:16Z 2009-01-30T16:49:16Z 2008 2008 Thesis http://hdl.handle.net/1721.1/44461 297175872 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 34 leaves: application/pdf Massachusetts Institute of Technology |
| spellingShingle | Physics. Harton, Renee M Characterization of polygrama green photopolymer for Compact Optoelectronic Integrated Neural (COIN) coprocessor applications |
| title | Characterization of polygrama green photopolymer for Compact Optoelectronic Integrated Neural (COIN) coprocessor applications |
| title_full | Characterization of polygrama green photopolymer for Compact Optoelectronic Integrated Neural (COIN) coprocessor applications |
| title_fullStr | Characterization of polygrama green photopolymer for Compact Optoelectronic Integrated Neural (COIN) coprocessor applications |
| title_full_unstemmed | Characterization of polygrama green photopolymer for Compact Optoelectronic Integrated Neural (COIN) coprocessor applications |
| title_short | Characterization of polygrama green photopolymer for Compact Optoelectronic Integrated Neural (COIN) coprocessor applications |
| title_sort | characterization of polygrama green photopolymer for compact optoelectronic integrated neural coin coprocessor applications |
| topic | Physics. |
| url | http://hdl.handle.net/1721.1/44461 |
| work_keys_str_mv | AT hartonreneem characterizationofpolygramagreenphotopolymerforcompactoptoelectronicintegratedneuralcoincoprocessorapplications |