Road Salt Reduction from Source Water Using 3-Compartment Borohydride/ Hydrogen Peroxide Desalination Cell
Bibliographic record
Abstract
The road salt that is applied to sidewalks, driveways, roads and parking lots makes its way to our local waterways killing freshwater biotas as well as decreasing structures working life through increasing corrosion rates. Recycling road salt is essential to reduce the ever-increasing amounts used in Quebec and Ontario, Canada. Using electrochemical desalination cells is investigated to regenerate the salt. The optimization includes solvent selection, establishing a compact design and increasing the removal rate with as little energy requirement as possible. This paper reports the optimum combined conditions obtained so far. In a 2-compartment cell, Direct Borohydride Fuel Cell (DBFC), based on sodium borohydride (NaBH4) and hydrogen peroxide provided better current and power densities in comparison to Direct Methanol Fuel Cell (DMFC), based on methanol and peroxide. This agrees with several review papers comparing these two fuel cell types. For further testing NaBH4 was substituted with potassium borohydride (KBH4) in a 3-compartment cell, t producing a highly-desalinated effluent. The sodium ions (Na+) and chloride ions (Cl-) were 98.7% and 99.2% removed, respectively. The maximum open circuit voltage (OCV) is 1.49 V, but quickly drops to 1.23 V. Future work includes incorporation of microbes (mixed culture) in the anodic compartment against a variation of several microalgae species in the cathodic compartment such as Desulfovibrio vulgaris, Geobacter sulfurreducens and Shewanella putrefaciens.
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 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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".