Modelling and Measurement of Magnetically Soft Nanowire Arrays for Sensor Applications

Abstract

Soft magnetic wires and microwires are currently used for the cores of magnetic sensors. Due to their low demagnetization, they contribute to the high sensitivity and the high spatial resolution of fluxgates, Giant Magnetoimpedance (GMI), and inductive sensors. The arrays of nanowires can be prepared by electrodeposition into predefined pores of a nanoporous polycarbonate membrane. While high coercivity arrays with square loops are convenient for information storage and for bistable sensors such as proximity switches, low coercivity cores are needed for linear sensors. We show that coercivity can be controlled by the geometry of the array: increasing the diameter of nanowires (20 µm in length) from 30 nm to 200 nm reduced the coercivity by a factor of 10, while the corresponding decrease in the apparent permeability was only 5-fold. Finite element simulation of nanowire arrays is important for sensor development, but it is computationally demanding. While an array of 2000 wires can be still modelled in 3D, this is impossible for real arrays containing millions of wires. We have developed an equivalent 2D model, which allows us to solve these large arrays with acceptable accuracy. Using this tool, we have shown that as a core of magnetic sensors, nanowires are efficiently employed only together with microcoils with diameter comparable to the nanowire length.

A parallel ring-ring capacitive proximity sensor for detection of approaching conductor

“…According to the working principle, the proximity sensor can be categorized into capacitive sensor, ultrasonic sensor, optical sensor, infrared sensor, electromagnetic induction sensor and microwave sensor (Lu et al , 2018; Min et al , 2010; Kim and Joo, 2016; Chen et al , 2011; Ripka et al , 2021; Huang et al , 2022; Matheoud et al , 2019; Fericean et al , 2009). As one kind of proximity sensors, capacitive sensor has the advantages of high sensitivity, high compatibility, low power consumption and simple structure (Ponce Wong et al , 2012).…”