Convolutional neural networks for temperature robust medium chemical concentration detection with micro-ring resonators

Thomas J/G. Mikhail; Sarah Shafaay; Mohamed A. Swillam

doi:10.1117/12.3002426

8 March 2024 Convolutional neural networks for temperature robust medium chemical concentration detection with micro-ring resonators

Thomas J/G. Mikhail, Sarah Shafaay, Mohamed A. Swillam

Author Affiliations +

Proceedings Volume 12890, Smart Photonic and Optoelectronic Integrated Circuits 2024; 1289004 (2024) https://doi.org/10.1117/12.3002426
Event: SPIE OPTO, 2024, San Francisco, California, United States

Abstract

An approach to measuring chemical concentrations using a micro-ring resonator (MRR) is proposed which is robust to thermo-optic noise and spectral shifts caused by temperature changes. The method uses a modified ResNet50 with varied kernel size and achieved a mean-square error (MSE) of 4.548E-4, and performance is compared to other machine learning methods including VGG20 and XGBoost. The model was trained to read the transmission spectra of a slotted MRR etched into heavily doped silicon and output the concentrations of chemicals in the surrounding analyte. The chemicals tested on were water, ethanol, methanol, and propanol, with concentrations ranging from 0-100%, with a dataset containing . This occurs over the mid-infrared wavelengths and within the temperature range of 290-310 K. Transfer learning was also utilized to retrain the models on several other datasets, consisting of 528 transmissions each. These datasets operated over different temperature ranges (310-320), and the other with a different set of chemicals, (water, ethanol, methanol and butanol). Similar results were achieved, with both networks achieving similar MSE. We then perform the same process on another design with the same chemicals, also operating over the infrared range, demonstrating the robustness of the method. All datasets used in the study were obtained through simulation, although we hope to test on real data.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Thomas J/G. Mikhail, Sarah Shafaay, and Mohamed A. Swillam "Convolutional neural networks for temperature robust medium chemical concentration detection with micro-ring resonators", Proc. SPIE 12890, Smart Photonic and Optoelectronic Integrated Circuits 2024, 1289004 (8 March 2024); https://doi.org/10.1117/12.3002426

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