Evaluating the Performance of PDMS-Brush Coatings to Control Microbial Growth at Elevated Humidity Conditions
Bibliographic record
Abstract
Excessive moisture indoors poses challenges to human health as it promotes fungal and bacterial growth. This study evaluated polydimethylsiloxane (PDMS) brushes, known for their liquid repellency, as a potential surface treatment to inhibit microbial colonization on interior gypsum drywall under elevated humidity conditions. Two coating methods were tested: vapor-phase deposition and waterborne application. Fungal growth was quantified using digital polymerase chain reaction (dPCR), while bacterial concentrations were measured using quantitative PCR. The highest post-incubation concentrations of fungal DNA were observed on drywall coated with vapor-phase PDMS (1.85 x 107 spore eq./cm2) and drywall coated with waterborne PDMS (7.77 x 106 spore eq./cm2), compared to untreated drywall (2.47 x 106 spore eq./cm2). Bacterial concentrations also increased post-incubation on PDMS brush-coated drywall. Statistical testing showed significant differences for fungal DNA quantities (p=0.04) but not for bacterial DNA quantities (p=0.20). Overall, these findings suggest that PDMS brushes may not be effective for mitigating microbial growth.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".