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Record W3138206305 · doi:10.1080/02786826.2021.1901846

Performance of nanofibrous media in portable air cleaners

2021· article· en· W3138206305 on OpenAlexaff
Raheleh Givehchi, Bowen Du, Maryam Razavi, Zhongchao Tan, Jeffrey A. Siegel

Bibliographic record

VenueAerosol Science and Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsPublic Health OntarioUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsFiltration (mathematics)AerosolMaterials scienceFilter (signal processing)PorosityComposite materialAir filterEnvironmental scienceChemistryEngineeringMathematicsMechanical engineering

Abstract

fetched live from OpenAlex

The benefits of nanofibrous media have been extensively explored in laboratory-scale research but are less clear in real filtration applications. Thus, this study investigated the links between the size-resolved filtration efficiency of nanofibrous media mounted in portable air cleaners in a chamber test and results from the media mounted in a cone-shape filter holder in a more conventional duct test. Results showed a similar trend for the filtration efficiency curves for these two experimental tests, despite differences in test type, challenge aerosol, instrumentation, and the calculation of filtration efficiency. Long-term operation, surface area blockage, and isopropyl alcohol treatment adversely impacted the filtration efficiency of the tested nanofibrous media in the chamber test, with a different magnitude of impact for three different media tested. The filtration efficiencies were lower than most of the previously reported data in the literature, which may be due to the differences in medium type, fiber diameter, filter thickness, porosity, face velocity, filter charge, and the number of filter layers. This study suggests the needs for determining the performance of nanofibrous media in terms of filtration efficiency and quality factor in real environmental systems.Copyright © 2021 American Association for Aerosol Research

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.195
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2021
Admission routes1
Has abstractyes

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Same venueAerosol Science and TechnologySame topicAerosol Filtration and Electrostatic PrecipitationFrench-language works237,207