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Record W2884044775 · doi:10.1002/ceat.201800184

Temperature Effects on Concentration Polarization Thickness in Thin‐Film Composite Reverse Osmosis Membranes

2018· article· en· W2884044775 on OpenAlex
Yasmine Baghdadi, Sabla Y. Alnouri, Takeshi Matsuura, Belal J. Abu Tarboush

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemical Engineering & Technology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMembraneThin-film composite membraneReverse osmosisConcentration polarizationPolyamideForward osmosisOsmotic powerPressure-retarded osmosisChemical engineeringPermeationMaterials scienceComposite numberChromatographyChemistryComposite materialEngineering

Abstract

fetched live from OpenAlex

Abstract Continuous research and development of reverse osmosis (RO) technologies has led to the production of membranes that are very effective with high salt rejection abilities. As temperature is one of the factors that affects salt rejection capabilities in membranes, this paper investigates the effect of temperature on the thickness of the concentration polarization layer (CPL) deposited on thin‐film composite seawater RO membranes. Two types of membranes were studied: those with ex situ macromolecules and those with in situ macromolecules. FilmTec's reverse osmosis system analysis design software was used to predict the variation of salt rejection and permeate flow rate with temperature. The impact of these variations on the thickness of the CPL was analyzed for different polyamide concentrations in the membrane.

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.

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 score0.004
Threshold uncertainty score0.822

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 integrity0.0010.000
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 head0.003
GPT teacher head0.197
Teacher spread0.194 · 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