Extraction of material parameters from a multilayer multi-harmonic thickness shear mode (MTSM) sensor data using genetic algorithm

A novel multi-resonant thickness shear mode (MTSM) sensor has been used to study multi-layer biological processes and to determine mechanical and geometrical properties of the layered structure by using a genetic algorithm for analyzing the sensor data. First, the genetic algorithm was tested theoretically. The Response of MTSM sensor loaded with a model biological system was simulated by using MTSM transmission line model (TLM) representation. Specifically, maximum amplitude and resonant frequency values at the fundamental and odd harmonics (up to 9^th harmonic) were calculated. These values then were entered into the genetic algorithm (GA) to extract the properties of the model biological systems. The algorithm was tested with single and multiple layers and was able to provide mechanical and geometrical properties of each layer (up to three layers) with an error of less than 5 percent. Next, the GA algorithm was positively tested with experimental data obtained for multi-layer layer structure of Newtonian fluids. Preliminary results showed that genetic algorithm could accurately extract the properties of real biological layered media. The obtained results demonstrate that the proposed approach, which combines a MTSM sensor and genetic algorithm, could fill the gap in quantification and interpretation of measured multi-layer interfacial processes and provide a comprehensive experimental and modeling foundation, which could lead to the development of quantitative tool for the characterization of a broad range of biological interfacial processes.