York University

Published purpose

The Project aims to develop rapid and accurate point-of-need (PoN) tools for real-time, on-site mineral sample analysis to enhance mineral processing efficiency and AI-guided process control. Current methods like Inductively Coupled Plasma mass spectrometry and optical emission spectroscopy are time-consuming or inaccurate. The Project first will extract and concentrate target minerals using ion-imprinted polymers and porous membrane filters to selectively capture and concentrate metal ions. This involves optimizing these materials with real hydro- or solvo-metallurgical samples. Secondly, the Project will develop portable optofluidic and bench-top electrochemical sensors for PoN detection and quantification of ions. These sensors will be integrated with sample preparation devices to create a comprehensive field-deployable system that will be tested against existing methods. The outcomes will support real-time monitoring of mineral processing reactors for efficient metal ion extraction and recycling, contributing to sustainable metal recovery and improved process parameter optimization through AI tools.