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Record W4416724469 · doi:10.1021/acs.iecr.5c01964

Importance of the Operating Conditions on the Photothermal Effect in Solar Pervaporation Desalination

2025· article· en· W4416724469 on OpenAlexaff
Yusi Li, Elisabeth R. Thomas, Mariana Hernandez-Molina, Stewart Conrad Mann, Kimya Rajwade, Tianmiao Lai, W. Shane Walker, François Perreault, Mary Laura Lind

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2025
Typearticle
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsUniversité du Québec à Montréal
FundersDivision of Engineering Education and CentersArizona State UniversityBureau of ReclamationNational Water Research InstituteNational Aeronautics and Space Administration
KeywordsPervaporationMembranePhotothermal therapyDesalinationSunlightFlux (metallurgy)Solar energyVolume (thermodynamics)Humidity

Abstract

fetched live from OpenAlex

This study evaluated the potential of photothermal carbon black (CB) coatings to use direct solar light as an energy source for pervaporation desalination. We used simulated sunlight to irradiate the CB-coated membrane and measured water flux and salt rejection. The feed was recirculated at a rate of 1 mL/s to replicate the industrial recirculation condition. We observed no statistically significant difference in water fluxes of the CB-coated membranes tested with and without a simulated sunlight irradiation of 0.8 sun intensity (0.82 ± 0.34 and 0.79 ± 0.16 kg/(h m 2 ), respectively). Furthermore, the average permeances of the uncoated and coated membranes were similar. The results indicate that with rapid recirculating large volume feed photothermal heating from CB coatings is insufficient to increase the pervaporation flux of water because the heat generated by the CB heating on the surface of the membrane is largely dissipated into the bulk of the recirculating feed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.079
GPT teacher head0.374
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

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