Multiple Solution Solving in Plasmon Sensing by Deep Learning: Determination of Layer Refractive Index and Thickness in One Experiment

2021 ◽  
Author(s):  
Qian Du ◽  
Quan Zhang ◽  
Guohua Liu
Keyword(s):  
Refractive Index ◽  
Deep Learning ◽  
Multiple Solution

scholarly journals Optical Characterization of Ultra-Thin Films of Azo-Dye-Doped Polymers Using Ellipsometry and Surface Plasmon Resonance Spectroscopy

Photonics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 41
Author(s):  
Najat Andam ◽  
Siham Refki ◽  
Hidekazu Ishitobi ◽  
Yasushi Inouye ◽  
Zouheir Sekkat
Keyword(s):  
Refractive Index ◽  
Optical Properties ◽  
Surface Plasmon Resonance ◽  
Surface Plasmon ◽  
Spectroscopic Ellipsometry ◽  
Plasmon Resonance ◽  
Complex Refractive Index ◽  
Resonance Spectroscopy ◽  
Doped Polymers

The determination of optical constants (i.e., real and imaginary parts of the complex refractive index (nc) and thickness (d)) of ultrathin films is often required in photonics. It may be done by using, for example, surface plasmon resonance (SPR) spectroscopy combined with either profilometry or atomic force microscopy (AFM). SPR yields the optical thickness (i.e., the product of nc and d) of the film, while profilometry and AFM yield its thickness, thereby allowing for the separate determination of nc and d. In this paper, we use SPR and profilometry to determine the complex refractive index of very thin (i.e., 58 nm) films of dye-doped polymers at different dye/polymer concentrations (a feature which constitutes the originality of this work), and we compare the SPR results with those obtained by using spectroscopic ellipsometry measurements performed on the same samples. To determine the optical properties of our film samples by ellipsometry, we used, for the theoretical fits to experimental data, Bruggeman’s effective medium model for the dye/polymer, assumed as a composite material, and the Lorentz model for dye absorption. We found an excellent agreement between the results obtained by SPR and ellipsometry, confirming that SPR is appropriate for measuring the optical properties of very thin coatings at a single light frequency, given that it is simpler in operation and data analysis than spectroscopic ellipsometry.

Determination of pseudo-refractive index in self-assembled ligand layers from spectral shift of surface plasmon resonances in colloidal silver nanoplates

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Pavel Malakhovsky ◽  
Dmitry Murausky ◽  
Dmitry Guzatov ◽  
Sergey Gaponenko ◽  
Mikhail Artemyev
Keyword(s):  
Refractive Index ◽  
Surface Plasmon ◽  
Mie Theory ◽  
Spectral Shift ◽  
Localized Surface Plasmon ◽  
Clear Trend ◽  
Silver Nanoplates ◽  
Assembled Monolayers ◽  
Self Assembled

Abstract We examined systematically how self-assembled monolayers (SAMs) of different mercaptoacids affect the spectral shift of the localized surface plasmon resonance in silver nanoplates and nanospheres. We observed a clear trend in the magnitude of a redshift with a molecular length or the SAM thickness within a homologous series of aliphatic mercaptoacids: the thicker shell the stronger the red shift. Using classic Mie theory for plasmonic core-dielectric shell spheres and oblate spheroids we developed the method for determination of a pseudo-refractive index in SAM of different molecules and obtained a good correlation with the reference refractive indices for bulk long-chain aliphatic acids, but only in case of silver nanoplates. Calculations for silver core–shell nanospheres gave overestimated values of refractive index perhaps due to restrictions of Mie theory on the minimum particle size.

Radiology “forensics”: determination of age and sex from chest radiographs using deep learning

2021 ◽  
Author(s):  
Paul H. Yi ◽  
Jinchi Wei ◽  
Tae Kyung Kim ◽  
Jiwon Shin ◽  
Haris I. Sair ◽  
...  
Keyword(s):  
Deep Learning ◽  
Chest Radiographs ◽  
Age And Sex

scholarly journals Deep Learning Based HPV Status Prediction for Oropharyngeal Cancer Patients

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 786
Author(s):  
Daniel M. Lang ◽  
Jan C. Peeken ◽  
Stephanie E. Combs ◽  
Jan J. Wilkens ◽  
Stefan Bartzsch
Keyword(s):  
Deep Learning ◽  
Cancer Patients ◽  
Oropharyngeal Cancer ◽  
Characteristic Curve ◽  
Learning Models ◽  
Convolutional Network ◽  
Hpv Status ◽  
3D Information ◽  
External Test

Infection with the human papillomavirus (HPV) has been identified as a major risk factor for oropharyngeal cancer (OPC). HPV-related OPCs have been shown to be more radiosensitive and to have a reduced risk for cancer related death. Hence, the histological determination of HPV status of cancer patients depicts an essential diagnostic factor. We investigated the ability of deep learning models for imaging based HPV status detection. To overcome the problem of small medical datasets, we used a transfer learning approach. A 3D convolutional network pre-trained on sports video clips was fine-tuned, such that full 3D information in the CT images could be exploited. The video pre-trained model was able to differentiate HPV-positive from HPV-negative cases, with an area under the receiver operating characteristic curve (AUC) of 0.81 for an external test set. In comparison to a 3D convolutional neural network (CNN) trained from scratch and a 2D architecture pre-trained on ImageNet, the video pre-trained model performed best. Deep learning models are capable of CT image-based HPV status determination. Video based pre-training has the ability to improve training for 3D medical data, but further studies are needed for verification.

scholarly journals Determination of non-linear refractive index of laser crystals and ceramics via different optical techniques

2020 ◽  
Vol 8 ◽  
pp. 100065
Author(s):  
Laurent Lamaignère ◽  
Guido Toci ◽  
Barbara Patrizi ◽  
Matteo Vannini ◽  
Angela Pirri ◽  
...  
Keyword(s):  
Refractive Index ◽  
Optical Techniques ◽  
Linear Refractive Index ◽  
Non Linear ◽  
Laser Crystals
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