Machine learning-integrated multi-wavelength SPR sensor based on aluminum-doped zinc oxide and 2D amorphous silicon for high-precision salinity measurement
Abstract
This study proposes a highly sensitive SPR sensor for the rapid and accurate determination of water salinity in the range of 1%-30%. The sensor is based on an aluminum-doped zinc oxide and 2D amorphous silicon material, an MgF 2 prism, and a five-wavelength light source. Four machine learning models, namely RBFNN, ANN, ANFIS, and LSTM, are used for the accurate determination of salinity in water. The proposed SPR sensor has high sensitivity, 472.1 (deg./RIU), 0.71 (deg./%cons.), a high quality factor 116.17 (1/RIU), and a high figure of merit 115.75, low reflectance (
Fields of Study & Subjects
Analytical Chemistry and Sensors
Advanced Fiber Optic Sensors
Gas Sensing Nanomaterials and Sensors
Publication details
- Journal / source
- Biomedical Optics Express
- Publisher
- Optica Publishing Group
- Volume
- 17
- Issue
- 6
- Pages
- 3275–3275
- Publication date
- 22 May 2026
- Language
- EN