A Sers Characterization of the Stability of Thiosulfate and Related Electrolytes at the Gold-Electrolyte Interface
Bibliographic record
Abstract
Recent studies of the Au leaching process have employed thiosulfate as the alternative complexing ligand to cyanide for gold extraction from ores containing carbonaceous components which preferentially absorbs gold and gold-cyanide complexes ( the so called preg-robbing). Thiosulfate, in the presence of an appropriate oxidant such as dissolved oxygen, is well known to complex Au(I) ions and form a soluble [Au(S2O3)2]3- complex. However, the kinetics of this process are inhibited by the formation of a passivating layer of species on the Au surface that block the lixiviant reagents from reaching the underlying Au atoms, thereby preventing full recovery of Au from the ore. To determine the composition of this passive layer, the interfacial behaviour of tetrathionate, trithionate, the [Au(S2O3)2]3- complex and thiosulfate upon immersion of a Au nanorods electrode into each of the electrolyte solutions was investigated using surface enhanced Raman spectroscopy (SERS). Raman bands indicative of adsorbed tetrathionate, trithionate, and [Au(S2O3)2]3- were identified at early immersion times. However, bands assigned to decomposition products such as elemental sulfur, were observed in all SERS spectra at longer immersion times. The SERS spectra for tetrathionate, trithionate, the [Au(S2O3)2]3- complex were compared to SERS spectra collected in a thiosulfate electrolyte in an attempt to better identify the passivating species that accumulate on the Au surface in typical gold leaching conditions. In thiosulfate solution, Au surface passivation by elemental sulfur did not occur to the same extent relative as in the three other electrolytes in the time period studied. This behavior indicates that complexation of the oxidized Au atoms by thiosulfate and its subsequent mass transportation into the bulk electrolyte is the predominantly favoured pathway at early immersion times. However, the disappearance of the Raman bands characteristic of the [Au(S2O3)2]3- complex and the appearance of bands indicative of elemental sulfur on the Au surface at longer immersion times confirms the growth of a passivating film of elemental sulfur on the gold surface in the thiosulfate electrolyte, albeit at much longer immersion times.
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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 | 0.001 |
| 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".