A noninvasive, remote and precise method for temperature and concentration estimation using magnetic nanoparticles.

This study describes an approach for remote measuring of on-site temperature and particle concentration using magnetic nanoparticles (MNPs) via simulation and also experimentally. The sensor model indicates that under different applied magnetic fields, the magnetization equation of the MNPs can be discretized to give a higher-order nonlinear equation in two variables that consequently separates information regarding temperature and particle concentration. As a result, on-site tissue temperature or nanoparticle concentration can be determined using remote detection of the magnetization. In order to address key issues in the higher-order equation we propose a new solution method of the first-order model from the perspective of the generalized inverse matrix. Simulations for solving the equation, as well as to optimize the solution of higher equations, were carried out. In the final section we describe a prototype experiment used to investigate the measurement of the temperature in which we used a superconducting magnetometer and commercial MNPs. The overall error after nine repeated measurements was found to be less than 0.57 K within 310-350 K, with a corresponding root mean square of less than 0.55 K. A linear relationship was also found between the estimated concentration of MNPs and the sample's mass.