Electrochemical Oxidation of Ammonia-Laden Wastewater in the Mining Industry
Bibliographic record
Abstract
Ammonia is a common contaminant in municipalities where human waste causes nitrification of local water bodies. In mining, ammonia contamination occurs as a byproduct of biological water treatment, from the use of ammonium nitrate fuel oil in explosives, and from the exposure of ammonia rich soils during the excavation process. In particular, gold mine effluent represents a significant source of ammonia and nitrogen-based contaminants. Current biological and abiotic treatment processes are difficult to employ at the scale required at mine sites due to the high operating costs, or are limited in effectiveness due to a lack of natural resources required to facilitate the treatment. This article evaluates the use of electrooxidation as a cost effective alternative to treating ammonia-laden wastewater in mining applications. Two mixed metal oxide electrodes are assessed in this article: IrO<inline-formula><tex-math notation="LaTeX">$_{2}$</tex-math></inline-formula>/Ti and RuO<inline-formula><tex-math notation="LaTeX">$_{2}$</tex-math></inline-formula>/Ti anodes. A Monte Carlo simulation is performed to determine a probabilistic range of capital and operating expenditure for a mining operation deploying an electrooxidation wastewater treatment system. The lowest capital cost of operating the electrochemical treatment occurs at a current density of 200 A/m<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>, where the number of cells required for treatment is minimized.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.002 | 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 teacher head, 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".