Ru(III)/Periodate System: Rapid Microbial Inactivation and Micropollutant Abatement in Seconds
Bibliographic record
Abstract
The worldwide presence of microbial and chemical pollutants has greatly threatened natural water ecosystems and public health. However, there are still very limited strategies for the rapid elimination of these hazardous contaminants in water. This study reported that the combination of ruthenium(III) (Ru(III), 10.0 μM) and periodate (PI, 50.0 μM) could inactivate bacteriophage MS2 and bacteria, reduce antibiotic resistance genes, and degrade organic micropollutants in water in seconds. Multiple lines of evidence suggested high-valent Ru-ligand complexes as the dominant oxidizing species in which PI and/or iodate might act as the ligand(s). The mechanistic studies indicated that the Ru(III)/PI-triggered inhibition of host attachment/genome injection and local membrane damage contributed to a 6 log MS2 and Escherichia coli reduction, respectively, in 10 s. Furthermore, the transformation products of representative emerging micropollutants were characterized, and their stepwise decomposition mechanisms were proposed. Interestingly, the Ru(III)/PI system also achieved high elimination of all of the above coexisting contaminants in real wastewater in 30 s. Taken together, this investigation provides an advanced oxidation strategy, i.e., the Ru(III)/PI system, which is unexpectedly governed by the high-valent Ru-ligand complexes. The proposed technology holds great promise in rapid water decontamination and may be useful in situations where rapid/urgent water treatment is required.
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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".