Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

Canada is a leading mining nation and a major producer of base and precious metals (copper, nickel and gold),x000D
rare metals (rare earth elements and cesium) and industrial and gem minerals (barite, zeolite, diamond). Thex000D
Abitibi greenstone belt of central Ontario and Quebec, in particular, is a world-class mining district for basex000D
metals and gold, and has been so for over 200 years. However, mining also creates challenges, withx000D
environmental impacts a particular concern. Many ore deposits contain toxic elements that end up in wastex000D
streams during mining, processing and smelting, and these materials need to be isolated from the environment.x000D
Unlike many organic contaminants, metal toxicity does not decay over time, and long-term safe storage andx000D
isolation is therefore critical. One of the elements of particular concern is arsenic. Arsenic is a commonx000D
element in many ore deposits and has a high toxicity in the biosphere. It is present up to mass percent levels inx000D
the sulfides that host the base and precious metals in many ore deposits, including those of the Abitibi, but withx000D
little direct value it generally ends up in the waste streams of metal production and extraction. Owing to itsx000D
toxicity and the large volume of arsenic-contaminated material that exists, both from active metal productionx000D
and as a legacy from 200 years of mining, there is an urgent need to develop new methods of containing andx000D
isolating arsenic. In fact, the costs of dealing with arsenic-waste currently makes several promising ore depositsx000D
in Canada uneconomical to mine. Recently, immobilization of arsenic in synthetic glass has been proposed as ax000D
long-term safe storage solution, equivalent to the approach proposed for radionuclide wastes. The researchx000D
proposed here will develop a thermodynamic database for these glasses based on phase diagram experiments.x000D
This database will allow for predictive modelling of the glass process, thereby identifying the optimumx000D
chemical and physical conditions for the process in order to maximize arsenic immobilization whilex000D
minimizing energy consumption and furnace wear. This predictive modelling capability is crucial to transformx000D
this technology from the laboratory to a functioning and profitable industrial process.