Effect of sodium silicate on drinking water biofilm development
Bibliographic record
Abstract
Abstract Sodium silicates have been studied for sequestration of iron, coagulation, and corrosion control, but their impact on biofilm formation has not been documented in detail. This study investigated the impact of sodium silicate corrosion control on biomass accumulation in drinking water systems in comparison to orthophosphate, a common corrosion inhibitor. Biofilm growth was measured by determining ATP concentrations, and the bacterial community was characterized using 16S ribosomal RNA (rRNA) sequencing. A pilot-scale study with cast-iron pipe loops, annular reactors (ARs), and polycarbonate coupons demonstrated significantly lower biofilm ATP concentrations in the sodium silicate-treated AR than the orthophosphate-treated AR when the water temperature exceeded 20°C. However, an elevated sodium silicate dose (48 mg L -1 of SiO 2 ) disturbed and dispersed the biofilm formed inside the AR, resulting in elevated effluent ATP concentrations. Two separate experiments confirmed that biomass accumulation was higher in the presence of orthophosphate at high water temperatures (20°C) only. No significant differences were identified in biofilm ATP concentrations at lower water temperatures (below 20°C). Differences in bacterial communities between the orthophosphate- and sodium silicate-treated systems were not statistically significant, even though orthophosphate promoted higher biofilm growth. However, the genera Halomonas and Mycobacterium —which include opportunistic pathogens—were present at greater relative abundances in the orthophosphate-treated system compared to the sodium silicate system. Graphical abstract Orthophosphate promotes more biofilm growth in comparison to sodium silicates at water temperatures above 20°C. Water impact statement Sodium silicates have been used in drinking water treatment for decades, both as sequestrants and as corrosion inhibitors. However, their impact on biofilm formation is poorly understood, and this risks drinking water quality. This study aims to further clarify the effects of corrosion inhibitors on biofilm development, including inhibitors that are not phosphate-based.
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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".