Discrimination of Six Flotation Kinetic Models Used in the Conventional Flotation and Carrier Flotation of −74 μm Coal Fines
In this study, experimental results of conventional flotation and carrier flotation were characterized by six commonly used flotation kinetic models. Two statistical criteria (coefficient of determination, R 2 , and root mean square error, RMSE) were used for comparison of fitting performance of dif...
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Veröffentlicht in: | ACS omega 2020-06, Vol.5 (23), p.13813-13821 |
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Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In
this study, experimental results of conventional flotation and
carrier flotation were characterized by six commonly used flotation
kinetic models. Two statistical criteria (coefficient of determination,
R
2
, and root mean square error, RMSE) were used
for comparison of fitting performance of different models. All kinetic
models tested gave good levels of goodness of fit, but the second-order
model with rectangular distribution (model 6) provided the best fitting
performance for the experimental data of conventional flotation and
carrier flotation. On this basis, two parameters, that is, modified
flotation rate constant (
K
m
) and selectivity
index (SI), were used to evaluate the difference in flotation separation
selectivity between conventional flotation and carrier flotation.
Comparisons of
K
m
and SI values indicated
that carrier flotation significantly improved the flotation rate constant
of combustible materials and flotation separation selectivity of ultrafine
coal (−74 μm). In addition, measurements of average bubble
size and water recovery indicated that both the coalescence of bubbles
and the drainage of liquid in the froth were promoted when coarse
coal particles (contact angle >90°) were employed as the carrier
to assist the flotation recovery of ultrafine particles, which in
turn favored the inhibition effect of the entrainment of gangue materials
in carrier flotation compared to conventional flotation. |
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ISSN: | 2470-1343 2470-1343 |
DOI: | 10.1021/acsomega.0c01116 |