Real time sensors are crucial in industrial processing applications. The quantitative determination of minerals in slurries is a key issue but existing technologies either cannot achieve the required measurement accuracy or be implemented outside of the laboratory. Zero-Field Nuclear Magnetic Resonance is an excellent candidate for the measurement of chalcopyrite (CuFeS2), the most abundant copper mineral, due to its intrinsic hyperfine magnetic field in the antiferromagnetic crystal lattice which negates the requirement for a DC applied field. Our research presents the development of an autonomous, quantitative NMR (qNMR) sensor for chalcopyrite in slurry that then remotely operated in a mineral processing plant for 6 months.
The sensor, called the Magnetic Resonance Slurry Analyser (MRSA), featured a novel automatic tune-and-match (ATaM) circuit which successfully counteracted rapid changes in the slurry’s permittivity and conductivity caused by natural variations in the ore geology and concentrations of chemical reagents. Further, a custom FPGA-based pulser board with an integrated ARM processor was developed that autonomously controlled the NMR measurement. Real-time feedback control systems were implemented in the ARM processor that dynamically adjusted the input RF pulse power and frequency to account for shifts in the chalcopyrite Larmor frequency, which varied with slurry temperature.
To the author’s knowledge, the MRSA represents the first time NMR has been used to quantify mineral concentrations in a processing plant, where it successfully operated for 6 months in harsh operating conditions. The MRSA provided the plant with variations of the chalcopyrite grade rapidly enough for the potential for real-time adjustment of process reagents to optimise copper yield. The MRSA demonstrated that NMR is a viable tool for real-time mineral analysis in the mining industry, an area that NMR has struggled to historically gain traction in.