Affinity of dual energy X-ray transmission sensors on minerals bearing heavy rare earth elements

被引:19
作者
Veras, Moacir Medeiros [1 ]
Young, Aaron Samuel [2 ]
Born, Cristiano Rocha [3 ]
Szewczuk, Artur [4 ]
Bastos Neto, Artur Cezar [3 ]
Petter, Carlos Otavio [5 ]
Sampaio, Carlos Hoffmann [6 ]
机构
[1] Fed Inst Amapa IFAP, Min, Macapa, Brazil
[2] Univ Utah, Min Engn, Salt Lake City, UT 84112 USA
[3] Univ Fed Rio Grande do Sul, Geosci Inst, Porto Alegre, RS, Brazil
[4] COMEX AS, Innovat Ind Technol, Wroclaw, Poland
[5] Univ Fed Rio Grande do Sul, Postgrad Program Min Engn Met & Mat, Porto Alegre, RS, Brazil
[6] Univ Politecn Cataluna, Dept Engn Minera Ind & TIC, Barcelona Tech, Barcelona, Spain
关键词
DE-XRT; Rare earth elements; Attenuated energy X-ray; Sensor-based sorting equipment; ALBITE-ENRICHED GRANITE; AMAZONIA; PITINGA; IMPACT;
D O I
10.1016/j.mineng.2019.106151
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This work demonstrates the effective use of automatic sensor-based sorting technology as a viable separation method for rare earth element (REE) rich ores composed primarily of xenotime minerals with gagarinite-(Y) and fluocerite-(Ce, La) inclusions. A dual energy X-ray transmission (DE-XRT) sensor affinity was used to evaluate forty-two heavy rare earth element (HREE) ore grab samples from the Madeira deposit. These samples and separated products were scanned by the sensor under many operating parameters. Subsequent analyses, including petrographic and multi-element chemical analyses were performed on the grab samples. Specific mass tests were also compared with energy attenuation curves from the sensor, which correlated strongly with every concentration stage the highest achieved density being 3.01 g/cm(3). The best estimated HREE recovery from laboratory-scale sorting of the samples identified by the sensor was effectively 100%, however this occurred in conjunction with a mass recovery equal to 97% of the feed. Such results are expected knowing that the sample method was not entirely representative. Ongoing research into automatic sorting technology for the upgrading of Brazilian ores is being performed by the Federal University of Rio Grande do Sul (UFRGS), Brazil.
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页数:10
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