An Assessment of the Use of Static Magnetic Field for Sodium Fluoride Defluoridation and Removal of Escherichia Coli and Rotavirus Pathogens from Water
Bibliographic record
Abstract
The use of chemicals such as chlorine in water purification leaves harmful biproducts in the water while filtration techniques such as reverse osmosis, ultrafiltration, nanofiltration, and forward filtration are costly and require external energy for their operation. Ceramic water filters that would have addressed these issues are brittle and incapable of filtering viruses. In this work, we report on the efficiency of water purification using a 0.8 T static magnetic field from permanent magnets in defluoridation of sodium fluoride and purification of Escherichia coli, and Rotavirus. The contaminated water was circulated at varying velocities of 0.1 ml/s to 2.0 ml/s at an ambient temperature of 16.0 °C to 40.0 °C for 0.5 hours to 9.0 hours. It was found that when ionized water was circulated under the static magnetic field for nine hours, its pH was lowered by 9.7% and the velocity of water in circulation did not affect the purification efficiency. The static magnetic field equally lowered the replication of Escherichia coli and Rotavirus by 9.8% and 7.1% respectively. Furthermore, 14.1% of defluoridation of water was also achieved. Thus, a 0.8 T static magnetic field was not able to purify water to recommended levels.
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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".