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Automated mineralogy particle dataset: apatite flotation

Hoang, D. H.; Pereira, L.; Kupka, N.; Tolosana Delgado, R.; Frenzel, M.; Rudolph, M.; Gutzmer, J.

This particle dataset was used for demonstrating the particle-tracking method presented in the paper "Computing single-particle flotation kinetics using automated mineralogy data and machine learning", submitted to Minerals Engineering in 08/10/2020, by Lucas Pereira, Max Frenzel, Duong Huu Hoang, Raimon Tolosana-Delgado, Martin Rudolph, Jens Gutzmer from the Helmholtz Institute Freiberg for Resource Technology.

This data belongs to the flotation tests performed by Duong Huu Hoang, and presented in:

Hoang, D.H., Kupka, N., Peuker, U.A., Rudolph, M., 2018. Flotation study of fine grained carbonaceous sedimentary apatite ore – Challenges in process mineralogy and impact of hydrodynamics. Miner. Eng. 121, 196–204.

For this study, phosphate rock samples from the Lao Cai province, Vietnam, were provided by the Vietnam Apatite Limited Company. The objective of the flotation experiments was to determine the best way to efficiently separate fluorapatite from dolomite, calcite and silicates. After grinding for 8 minutes in a laboratory ball mill to assure a d90 of 67 µm, batch flotation tests were performed in a flotation cell built at the TU Bergakademie Freiberg. Corn starch ((C6H10O5)n) gelatinized with sodium hydroxide (NaOH) was used in combination with sodium silicate (Na2SiO3) to depress gangue minerals. The latter also acts as a fine particle dispersant. Solution pH was kept at 10 using the modifier sodium carbonate (Na2CO3), which can also be regarded as a depressant. Berol 2015 was used as the collector. Four concentrate fractions were collected after 0.75 min (CA), 1.50 min (CB), 3.00 min (CC), and 6.00 min (CD). In addition, a final tailings sample was collected (TD). Five replicates of the test were done to ensure reproducibility and produce enough sample mass for detailed characterization. All samples, including the feed, were wet sieved into four size fractions (-20 µm, +20 to -32 µm, +32 to -50 µm, and +50 µm) before characterization by MLA at the Helmholtz Institute Freiberg for Resource Technology. Samples were analyzed on a FEI Quanta 650F scanning electron microscope equipped with two Bruker Quantax X-Flash 5030 EDX detectors. The SEM was operated at 25 kV overall electron beam accelerating voltage and Extended BSE Liberation Analysis measurement mode. MLA results were validated with ICP-OES chemical assays. Particles from the flotation product samples (concentrate and tailings) are in the Traindata.csv file, while particles from the feed sample are in the FeedData.csv file. The weight distribution of each sample is given below:

Sample | wt.%

CA -20µm | 6.7

CA 20-32µm | 5.8

CA 32-50µm | 4.6

CA +50µm | 2.2

CB -20µm | 6.4

CB 20-32µm | 5.4

CB 32-50µm | 3.9

CB +50µm | 2.8

CC -20µm | 5.8

CC 20-32µm | 4.3

CC 32-50µm | 3.5

CC +50µm | 2.0

CD -20µm | 4.7

CD 20-32µm | 2.8

CD 32-50µm | 2.3

CD +50µm | 1.1

TD -20µm | 11.3

TD 20-32µm | 7.0

TD 32-50µm | 6.7

TD +50µm | 10.7

Feed -20µm | 36.60

Feed 20-32µm | 23.88

Feed 32-50µm | 21.75

Feed +50µm | 17.78

Variable names:

  • Mineral composition: Actinolite, Albite, Almandine, Apatite, Barite, Biotite, Calcite, Chalcopyrite, Clinochlore, Diopside, Dolomite, Fluorite, Hematite, Muscovite, Orthoclase, Plagioclase, Phlogopite, Pyrite, Pyrrhotite, Quartz, Rutile, Sanidine, Sphalerite_Fe, Titanite, Zircon.
  • Surface composition:,,,,,,,,,,,,,,,,,,,,,,,,
  • Size and shape: AspectRatio, Solidity, ECD
  • Sample identifier: Class - In this case, particles identified with "CA20", for example, are the particles from the <20µm size fraction of the first concentrate sample, while "TD50" are the particles from the >50µm size fraction of the final tailings sample.

Keywords: Apatite; Froth flotation; Automated mineralogy; Geometallurgy; Particle-tracking

  • Reseach data in the HZDR data repository RODARE
    Publication date: 2020-10-08
    DOI: 10.14278/rodare.542
    License: CC-BY-4.0


Publ.-Id: 31592