In many minerals, the magnetic permeability and/or the resistance depends on the applied magnetic field. These properties, magnetic hysteresis and magnetoresistance, could therefore be used as a way of identifying minerals to differentiate ore from waste in the mining industry. This application requires the properties to be measured without electrical contacts, operate at room temperature and in low magnetic fields. We have created a lab-based instrument that is capable of simultaneously measuring the magnetoresistance and magnetitic hysteresis of granular materials at room temperature. This instrument is designed to be scaled up for use in a mining application. The instrument consists 
of a Helmholtz coil, a radiofrequency power supply, a simple well-characterised radiofrequency circuit and custom circuitry for analogue processing of the signal before it is digitized. In this setup, a periodic time varying magnetic field is applied to the circuit using the Helmholtz coil, thereby inducing a periodic resistance and permeability change in the material. The periodic changes in the impedance of the radiofrequency circuit at the resonant frequency that are induced by the oscillating magnetic field are measured. Using Fourier analysis, the coefficient of magnetoresistance and the parameters of a magnetic hysteresis model to be determined. The magnetoresistance of bismuth and simultaneous resistance and permeability changes in an iron ore sample were successfully measured with this setup.

Dr Larissa Huston is a Research Scientist in the Magnetic Resonance Development Team in the Sensing and Sorting Program at CSIRO Minerals Resources, and in the Autonomous Sensors Future Science Platform. Her research involves developing electromagnetic sensing techniques for the detection of minerals. Larissa completed a PhD in Physics at the Australian National University. She also completed a postdoctoral appointment at Los Alamos National Laboratory prior to joining CSIRO. Dr Huston is working on the “Non-linear Electromagnetics for Real-Time Materials Detection” project under the supervision of Peter Coghill.