Avalon Reports Positive Ore Sorting Results in Kemptville

Avalon Advanced Materials (TSX:AVL,OTCQX:AVLNF), has received positive results from an ore-sorting testwork program conducted on samples of tin mineralization from its East Kemptville tin project.

Canadian mineral development company, Avalon, specializes in niche market metals and minerals with growing demand in new technology. The company’s ongoing tin project is located in East Kemptville, near Yarmouth, Nova Scotia.

As quoted from the press release:

Sensor-based ore-sorting  is an emerging technology seeing increasing application in the mining industry. It involves the scanning of individual rock particles on a conveyor using various types of available sensor technologies. Depending on the chemical, mineralogical or physical characteristics, the particles of value are individually identified and separated from the “rejects” by applying either a mechanical, hydraulic or, in the case of East Kemptville, a pneumatic process.

The successful application of an ore-sorting process offers a number of potential benefits through the rejection of low or non-mineralized waste rock before it is fed into the processing plant. This can lead to a significant reduction in the size of the plant, along with attendant reductions in both capital and operating costs. It may also allow for the economic processing of low grade feed materials that would otherwise be un-economic to treat.

The recent work was conducted by Cronimet Mining Processing, who are providing technical and metallurgical services to Avalon in relation to the East Kemptville Project. CMPSA has also expressed interest in partnering with Avalon on the development of the project.

Drill core samples from the in-ground resources at East Kemptville were delivered in July 2018 to a test facility in Kentucky, USA in order to determine the amenability of East Kemptville tin mineralization for beneficiation utilizing sorting technology. Samples varying from relatively high-grade to low-grade tin concentrations were scanned using a multisensory sorter platform. Based on these scans an algorithm was developed to allow for the separation of the material during the test campaign.

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