Design of a digital twin for an impedance-based microplastic sensor using a flow-through method

Detecting microplastic in the field is the first step to solve the microplastic challenge. To achieve this, innovative sensors must be developed. One alternative to standard laboratory methods is a sensor comprising a flow-through cell with electrodes the frequency-dependent impedance of which depends on the presence and type of particle in the cell. This has already been described in the literature. To speed up the development of such sensors and identify the influence of design details, it is advantageous to have a digital twin of the sensor. So, this work focuses on the design of a digital finite-element (FE) twin for this microplastic sensor, with the aim of predicting the output signal of the sensor derived from changes in the impedance spectrum (magnitude and phase) when a particle passes through the sensor. Ideally, it even suffices to work with features of the spectrum (such as the impedance at 2 MHz) rather than the entire spectrum; such features have to be identified first, and this represents another use of our digital twin. In our investigations, the material parameters from the standard database of the FE tool used (Ansys Electronics) were chosen to incorporate the influence of the electrical conductivity of water into the simulation. It was found that the simulation results corresponded to the measurement results during sensor characterization, i.e., when recording the impedance of the sensor with pure water filling over a frequency range from 20 Hz to 2 MHz. The signals of the sensor obtained from measurements due to a particle in the sensor were confirmed by the simulation. The simulated impedance magnitude described the measured signals both qualitatively and quantitatively. For the impedance phase, this was true only qualitatively. It was found that the particle position and size have a decisive influence on the impedance of the sensor. Effects observed in the measurements (e.g., a negative change in the magnitude of the impedance, when a particle enters the sensor) could be attributed to the particle position or size based on the simulation results. In the future, the digital twin that has been created will allow the effects of changes to the sensor geometry to be analysed digitally first (e.g., a higher sensitivity and/or selectivity on a certain polymer), before the sensor is physically built and measured. While searching the optimal sensor geometry the digital twin reduces the measurement effort and speeds up the development process.