Quantitative Polarization‐Resolved Second‐Harmonic‐Generation Microscopy of Glycine Microneedles
Source abstract
Abstract
Abstract Second‐harmonic generation (SHG) is a nonlinear optical process that can provide disease diagnosis through characterization of biological building blocks such as amino acids, peptides, and proteins. The second‐order nonlinear susceptibility tensor χ(2) of a material characterizes its tendency to cause SHG. Here, a method for finding the χ(2) elements from polarization‐resolved SHG microscopy in transmission mode is presented. The quantitative framework and analytical approach that corrects for micrometer‐scale morphology and birefringence enable the determination and comparison of the SHG susceptibility tensors of β‐ and γ‐phase glycine microneedles. The maximum nonlinear susceptibility coefficients are d33 = 15 pm V−1 for the β and d33 = 5.9 pm V−1 for the γ phase. The results demonstrate glycine as a useful biocompatible nonlinear material. This combination of the analytical model and polarization‐resolved SHG transmission microscopy is broadly applicable for quantitative SHG material characterization and diagnostic imaging.
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Research context
OpenAlex topics: Advanced Fluorescence Microscopy Techniques · Spectroscopy Techniques in Biomedical and Chemical Research · Spectroscopy and Quantum Chemical Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Physics and Bernal Institute University of Limerick Castletroy, Co. Limerick Limerick V94 T9PX Ireland
Funding
Science Foundation Ireland · Irish Research Council · European Regional Development Fund
References (30)
Show source-provided references
1. Mutailipu M. · Acc. Chem. Res. · 2019 · 3 · 79110.1021/acs.accounts.8b00649 ↗
2. 10.1515/nanoph-2016-000310.1515/nanoph-2016-0003 ↗
3. 10.1016/j.jcrysgro.2005.03.07410.1016/j.jcrysgro.2005.03.074 ↗
4. 10.1038/nprot.2012.00910.1038/nprot.2012.009 ↗
5. 10.1021/acs.nanolett.6b0408710.1021/acs.nanolett.6b04087 ↗
6. 10.1038/lsa.2016.4010.1038/lsa.2016.40 ↗
7. 10.1021/acs.accounts.6b0020910.1021/acs.accounts.6b00209 ↗
8. 10.1038/nmat320010.1038/nmat3200 ↗
9. 10.1038/nmat504510.1038/nmat5045 ↗
10. 10.1021/ac103232510.1021/ac1032325 ↗
11. 10.1016/j.optmat.2018.04.05110.1016/j.optmat.2018.04.051 ↗
12. 10.1021/cg500747x10.1021/cg500747x ↗
13. 10.1021/acs.cgd.5b0018710.1021/acs.cgd.5b00187 ↗
14. 10.1023/A:101317970273010.1023/A:1013179702730 ↗
15. 10.1021/cg200933610.1021/cg2009336 ↗
16. 10.1021/cg500111a10.1021/cg500111a ↗
17. 10.1016/j.optmat.2017.07.00710.1016/j.optmat.2017.07.007 ↗
18. 10.1039/C5TC00226E10.1039/C5TC00226E ↗
19. 10.1364/AO.57.00591410.1364/AO.57.005914 ↗
20. 10.1117/1.277231110.1117/1.2772311 ↗
21. 10.1364/OE.18.01933910.1364/OE.18.019339 ↗
22. Jatirian‐Foltides E. · Rev. Mex. Fis. E · 2016 · 62 · 5
23. Jackson J. D. · 1975
24. 10.1016/j.optmat.2014.09.00710.1016/j.optmat.2014.09.007 ↗
25. 10.1093/oso/9780198520757.001.000110.1093/oso/9780198520757.001.0001 ↗
26. Xin Y. · J. Opt. Soc. Am. B · 2005 · 22 · 218510.1364/JOSAB.22.002185 ↗
27. 10.1016/j.optmat.2018.06.01010.1016/j.optmat.2018.06.010 ↗
28. 10.1021/acs.cgd.6b0163310.1021/acs.cgd.6b01633 ↗
29. 10.1007/s10853-018-03211-y10.1007/s10853-018-03211-y ↗
30. 10.1039/C4CE01429D10.1039/C4CE01429D ↗