Electrochemical and SERS Studies of the Interfacial Behaviour of Thiosulfate and Polythionate Solutions with Gold Electrodes and Oxide Ores
Bibliographic record
Abstract
This thesis presents electrochemical and SERS studies of the interfacial interactions of thiosulfate and some related electrolytes with pure gold electrodes and oxide ores. In the first study, development of a nanoparticle modified gold electrode is presented with the first recorded SERS characterization of a hydrophilic self-assembled monolayer (SAM) of 1-thio-β-D-glucose (TG) adsorbed to a gold surface using electrochemical surface enhanced Raman spectroscopy (EC-SERS). Gold nanoparticles were deposited on the gold electrode surface and then subjected to electrochemical desorption to remove all contaminants. The TG SAM was observed as partially oxidized in the -0.60 to -0.20 V vs. SCE region with a large retention of water near the gold surface. In the second study, SERS spectra of gold nanorods (AuNRs) exposed to electrolyte solutions of tetrathionate, trithionate, sulfide, the [Au(S2O3)2]3- complex, and thiosulfate are discussed. The band positions of each species are compared to those recorded with the thiosulfate electrolyte over an extended period of time. Initially, in a thiosulfate electrolyte the interfacial region consisted of thiosulfate and the gold thiosulfate complex. At longer exposure it was concluded the layer that inhibits gold dissolution is predominantly sulfides, cyclo-S8, and polysulfide chains. Using shell-isolated nanoparticles (SHINs), the interaction of thiosulfate with bulk gold electrodes or oxides ore samples was studied with SERS. A novel analytical procedure to correct for fluctuations in surface enhancement is presented. The relative change in the quantity of the [Au(S2O3)2]3- complex, and elemental sulfur bands related to the passive layer, were found to coincide well with the electrochemically determined gold leaching rate. Furthermore, the first reported interaction and subsequent removal of several passive layer constituents from the gold surface by copper and ammonia is presented. Finally, differences in passive layer growth were observed between untreated and pressure-oxidation (POX) treated oxide ore samples exposed to the thiosulfate electrolytes. The passive layer observed of the untreated oxide ore-SHINs-electrolyte interface was found to contain metal-sulfides and polysulfide chains (Sn/Sn2-) after longer exposure. In comparison, the passive layer observed with the POX treated sample was found to be predominantly metal-sulfides with only a small quantity of polysulfide chains. The pretreatment process was concluded to destroy or sufficiently inactivate minerals present in the ore that catalyze thiosulfate decomposition.
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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".