TY - JOUR
T1 - Artificial neural network to estimate the refractive index of a liquid infiltrating a chiral sculptured thin film
AU - McAtee, Patrick D.
AU - Bukkapatnam, Satish T.S.
AU - Lakhtakia, Akhlesh
N1 - Funding Information:
This paper is substantially based on the conference paper58 entitled, “Artificial neural network to predict the refractive index of a liquid infiltrating a chiral sculptured thin film,” presented at the SPIE Optics and Photonics conference, Biosensing and Nanomedicine XI, held August 19 to 23, 2018, in San Diego, California, United States. The research of P. D. McAtee and A. Lakhtakia was funded by the Charles Godfrey Binder Endowment at Pennsylvania State University.
Publisher Copyright:
© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE).
PY - 2019/10/1
Y1 - 2019/10/1
N2 - We theoretically expanded the capabilities of optical sensing based on surface plasmon resonance in a prism-coupled configuration by incorporating artificial neural networks (ANNs). We used calculations modeling an index-matched substrate with a metal thin film and a porous chiral sculptured thin film (CSTF) deposited successively on it that is affixed to the base of a triangular prism. When a fluid is brought in contact with the exposed face of the CSTF, the latter is infiltrated. As a result of infiltration, the traversal of light entering one slanted face of the prism and exiting the other slanted face of the prism is affected.We trained two ANNs with differing structures using reflectance data generated from simulations to predict the refractive index of the infiltrant fluid. The best predictions were a result of training the ANN with the simpler structure. With realistic simulated-noise, the performance of this ANN is robust.
AB - We theoretically expanded the capabilities of optical sensing based on surface plasmon resonance in a prism-coupled configuration by incorporating artificial neural networks (ANNs). We used calculations modeling an index-matched substrate with a metal thin film and a porous chiral sculptured thin film (CSTF) deposited successively on it that is affixed to the base of a triangular prism. When a fluid is brought in contact with the exposed face of the CSTF, the latter is infiltrated. As a result of infiltration, the traversal of light entering one slanted face of the prism and exiting the other slanted face of the prism is affected.We trained two ANNs with differing structures using reflectance data generated from simulations to predict the refractive index of the infiltrant fluid. The best predictions were a result of training the ANN with the simpler structure. With realistic simulated-noise, the performance of this ANN is robust.
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U2 - 10.1117/1.JNP.13.046006
DO - 10.1117/1.JNP.13.046006
M3 - Article
AN - SCOPUS:85074639714
VL - 13
JO - Journal of Nanophotonics
JF - Journal of Nanophotonics
SN - 1934-2608
IS - 4
M1 - 046006
ER -