Adsorption of dextrin onto sulphide minerals and its effect on the differential flotation of the Inco matte
Bibliographic record
Abstract
The major constituents of the Inco matte, chalcocite (Cu2S) and heazlewoodite (Ni3S2), are separated by differential flotation with diphenylguanidine as collector. To select an effective organic depressant, many dextrins were tested and tapioca dextrin 12 was found to have an exceptional affinity towards heazlewoodite surface at a particular pH of the mineral suspension. A new reagent system, involving the use of this dextrin as a modifying agent which provides better selectivity, has been studied. Adsorption tests revealed that while dextrin exhibits high affinity towards heazlewoodite, especially in alkaline solutions, the adsorption isotherm shape for dextrin on chalcocite showed weak affinity. The adsorption density of dextrin on Ni3S2was found to vary with pH, with the maximum adsorption occurring around pH 11.7, which was established to be the i.e.p. of nickel hydroxide. For Cu2S, the adsorption was much lower and did not exhibit any pH dependence. Electrokinetic and co-precipitation measurements confirm such observations. While the zeta potential-pH curves for Ni3S2 and freshly precipitated Ni(OH)2 were practically identical in alkaline solutions and revealed the presence of a nickel hydroxide layer on Ni3S2, such a correlation was absent for the Cu2S and Cu(OH)2 curves. The zeta potential-pH curves forNi3S2 and Ni(OH)2, and for Cu2S and Cu(OH)2 in the presence of dextrin, exhibited quite different trends. While the results indicate strong interactions and flat orientation of dextrin macromolecules onto nickel hydroxide and heazlewoodite, weak interactions between dextrin and chalcocite (and copper hydroxide) seem to result in an extended adsorption layer that drives the shear plane further away from the interface. Conductometric and ATR-FTIR tests confirm that dextrin interacts strongly with Ni3S2 most likely through chemical bonding, while its interaction with chalcocite is physical in nature. This is a brand name for the tapioca dextrin sample obtained from Staley Mfg. Co. Based on the adsorption studies, batch differential flotation tests of Inco matte using diphenyl guanidine (DPG) and potassium amyl xanthate (KAX) as collectors and tapioca dextrin as a depressant were carried out. A single stage cleaner flotation using DPG collector in the presence of tapioca dextrin yielded a high grade copper concentrate. As compared to the cleaner flotation in the absence of tapioca dextrin, this resulted in about 70% reduction in the Ni content in the concentrate. Although amyl xanthate exhibited poor selectivity, the presence of tapiocadextrin dramatically improved its performance in the selective separation of the chalcocite fromthe heazlewoodite. This makes amyl xanthate a very attractive alternative to the currently utilized DPG collector. On the basis of this research, it has been possible to provide a rational interpretation of all data pertaining to chalcocite-heazlewoodite differential flotation and to improve the selectivity of such separation with the use of dextrin as Ni3S2 depressant in the alkaline pH range. A significant link has been established between the results of fundamental analyses and industrially related observations. In particular, it was shown how electrokinetic measurements can be utilized along with FTIR and adsorption measurements to study the interactions of macromolecular modifiers with sulphide minerals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".