Accelerated Discharge of Corona-Charged Nonwoven Fabrics
Bibliographic record
Abstract
Fibrous polymers with extremely low electrical conductivity such as polypropylene (PP), polycarbonate, polyurethane, and polyethylene are commonly employed as air-filter materials. The charge accumulated on such materials due to tribocharging effects inherent to the manufacturing process might be harmful either to the operator or to the electronic equipment of the production line. Whenever charge buildup cannot be avoided, it is important to have an effective method available in order to rapidly discharge the materials. The present work aims to evaluate the efficiency of active neutralization of charged nonwoven fabrics. The experiments have been carried out on 0.4-mm-thick PP and polyester fibrous media, with the average diameter of the two types of fibers being 28 and 19 , respectively. The nonwoven fabrics were charged by exposing them to a negative corona discharge generated by a wire-grid-plate electrode system. The samples, laid on the surface of the grounded electrode or suspended at a small distance (4.6 mm) above it, were then subjected to the action of the bipolar ions generated by a commercial neutralizer (model 6430, Ion Systems Inc., Berkeley, CA). The monitored variable was the surface potential detected by the probe of an electrostatic voltmeter. The controlled variables were the potential of the grid electrode, the neutralization time, and the distance between the neutralizer and the media. The results of the experiments enabled a crude evaluation of each factor effect. Research should continue, using the experimental design methodology, in order to establish the optimum conditions for charge neutralization.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".