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Experimental Design to evaluate a reagent system for a nickel ore flotation. Authors. Jean Louzada; Ronald Hacha ; Marisa Monte and Mônica Cassola (a) CETEM – Centre for Mineral Technology, Rio de Janeiro, Brazil (b) Clariant S.A, São Paulo, Brazil. MOTIVATION.
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Experimental Design to evaluate a reagent system for a nickel ore flotation
Authors • Jean Louzada; Ronald Hacha; Marisa Monte and Mônica Cassola • (a) CETEM – Centre for Mineral Technology, Rio de Janeiro, Brazil • (b) Clariant S.A, São Paulo, Brazil
MOTIVATION • The optimization of flotation conditions is a complex task because many process variables can affect flotation responses. • It is not uncommon for multiple interactions to occur between independent variables; • The identification of these interactions play an important role in advancing our understanding of the chemistry of such system in plant operations.
OBJECTIVES • To employ a factorial design to investigate the effect of chemical variables on the flotation performance of dithiophosphates for a nickel ore; • To optimize these variables for maximum nickel recovery and grade.
EXPERIMENTAL • REAGENTS • Ethyl secbutil sodium dithiophosphates (Hostaflot E501) and sodium dialkyldithiophosphate (Hostaflot M92) were supplied by Clariant; • Polypropylene glycol methyl ether (CH3(OC3H6)n-OH and other consisting of a mixture of aliphatic alcohols, ethers and esters. The two frothers were supplied by Clariant . • The activator and the depressant used were copper sulfate and carboxymethyl cellulose, respectively
EXPERIMENTAL • A nickel ore sample from Minas Gerais, Brasil, was completely characterized for mineralogical and chemical compositions: • Mineralogical composition, associations and liberation were measured in a FEI Quanta 400 SEM with the Mineral Liberation Analyzer (MLA) software. • Chemical analysis were carried out in a PanAnalytical Epsilon 3 X-ray Fluorescence machine.
EXPERIMENTAL • Factorial Design; • Only factors which influenced in the recovery of nickel by flotation will be presented here. • The factorial design was implemented with two levels and six factors resulting in thirty two experiments. • The Statistics software was used for the regression analysis, statistical and optimization calculations.
Table 1. Factorsandlevelsapplied in 26-1 fractionalfactorial design. Flotanol(low: 20; high: 40); Montanol (low: 20; high: 80).
Experimental • FlotationTests • The samples were ground in a rod mill, to which were added the dispersant and the activator at pH 6.0. • Immediately after grinding, the material was deslimed and, subsequently, the sample was transferred to a cell with two liters. • The pulp was kept under stirring at 1400 rpm and the pH was adjusted to 9.5 with a solution of NaOH 10% (p/v). • pH adjustment was immediately followed by depressant addition, carboxymethyl cellulose, and conditioning for 4 minutes. • Afterwards, the collector was added and conditioned for 30 seconds. • Finally, the frother was added to the system and conditioned for 1 minute. • The pH was kept at about 9.5 during the conditioning with all reagents. The flotation time was 4 min.
Experimental • Curve Fitting and Statistical Analysis • The important response variable chosen in this study was nickel recovery • The statistical significance of effects and interactions between processes and the response variable was determined using the F-test. • Probability (P) values larger than 0.05 were indicative of a measured effect being statistically significant at a confidence level 95%
RESULTS AND DISCUSSION Mineralogical characterization • These studies showed that the major minerals are talc, hornblende, ilmenite, pyrite and pyrrhotite. • The results revealed that talc is not the predominant magnesium carrier mineral • Hornblende is present and predominates over talc in all ranges of particle size.
Figure 1 Mineralogical Composition as a function of the particle size
Figure 2 Minerals associated to pentlandite in the particle size range between 210 and 38 μm.
Figure 3 - Synthesis of the results obtained for theoretical recovery and grades of pentlandite in the concentrate at different size ranges.
AnalysisofVariance These variables and their interactions presented higher probabilities: • B: Concentration of collector ; • D: Concentration of frother • BD: interactions between them • In other cases, the null hypothesis is rejected because the estimated values of p-levels (Test P) are smaller than 0.05, i.e., the effects have a probability smaller than 5% so they represent only of noise.
CONCLUSIONS • The results of these studies showed that the main factors that influence more significantly the nickel recovery are the collectors and frothers concentrations. • The differences between the collectors are the alkyl chains do not influence the recovery.