Drag Detection and Identification by Whispering Gallery Mode Optical Resonance Based Sensor

摘要

Experimental data on optical resonance spectra of whispering gallery modes of dielectric microspheres in antibiotic solutions under varied in wide range concentration are represented. Optical resonance was demonstrated could be detected at a laser power of less than 1 microwatt. Several antibiotics of different generations: Amoxicillin, Azithromycin, Cephazolin, Chloramphenicol, Levofloxacin, Lincomicin Benzylpenicillin, Riphampicon both in de-ionized water and physiological solution had been used for measurements. Both spectral shift and the structure of resonance spectra were of specific interest in this investigation. Drag identification has been performed by developed multilayer perceptron network. The network topology was designed included: a number of the hidden layers of multilayered perceptron, a number of neurons in each of layers, a method of training of a neural network, activation functions of layers, type and size of a deviation of the received values from required values. For a network training the method of the back propagation error in various modifications has been used. Input vectors correspond to 6 classes of biological substances under investigation. The result of classification was considered as positive when each of the region, representing a certain substance in a space: relative spectral shift of an optical resonance maxima - relative efficiency of excitation of WGM, was singly connected. It was demonstrated that the approach described in the paper can be a promising platform for the development of sensitive, lab-on-chip type sensors that can be used as an express diagnostic tools for different drugs and instrumentation for proteomics, genomics, drug discovery, and membrane studies.