Development of an Oxidizing-Distillation Technology for the Extraction of Tellurium from a Tellurium-Containing Middling
Bibliographic record
Abstract
In this paper, the results of studying aimed at tellurium extraction from its compound with copper in the form of oxides by the pyrometallurgical method are presented.Technical copper telluride of Kazakhmys Corporation LLP containing crystalline phases, %: Cu 7 Te 4 -36.5;Cu 5 Te 3 -28.5;Cu 2 Te -12.9;Cu 2.5 SO 4 (OH) 3 •2H 2 O -16.2 and Cu 3 (SO 4 )(OH) 4 -6.0 was used as an object of research.As a result of the physical and chemical research and technological experiments, the fundamental possibility of processing technical copper telluride by oxidative distillation roasting with the extraction of tellurium into a separate product has been shown.Air oxygen was used as an oxidant.It has been established that a pressure decrease at the same temperature entails an increase in the degree of tellurium extraction.However, from a technological point of view, the value of the degree of tellurium extraction (93.0-98.0%) at all pressures (within 1 hour) is achieved at a temperature of 1100 °C.Increasing the exposure to 3 hours has a minor beneficial effect.The derived condensate is a free-flowing mixture of crystalline phases of tellurium dioxide and tellurium oxysulfate.This condensate is a middling product for further production of elemental tellurium.
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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 | 0.001 |
| 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".