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Record W4414845051 · doi:10.1016/j.desal.2025.119492

Chlorine production from brine using a novel superhydrophobic PTFE-PI-TiO₂ photocatalytic membrane contactor

2025· article· en· W4414845051 on OpenAlexaff
Yao-Zhong Zhang, Chun Yin Jerry Lau, Ramin Farnood

Bibliographic record

VenueDesalination · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChlorinePhotocatalysisMembraneWettingNanofiltrationBrineContact angleChloride

Abstract

fetched live from OpenAlex

This study presents a photocatalytic membrane contactor for the simultaneous generation and separation of chlorine gas from acidified brine. This system uses a novel superhydrophobic polyimide-reinforced polytetrafluoroethylene composite membrane containing TiO₂ nanoparticles (PTFE–PI–TiO₂) fabricated via solution blow spinning. Incorporation of polyimide binder with optimal TiO₂ loading yielded hierarchical micro- and nanoscale porous membranes with high porosity (78 to 84 %). Surface wettability analysis demonstrated stable Cassie-Baxter superhydrophobicity up to 15 wt% TiO₂ loading, enabling stable gas-phase transport through membrane pores. Under UV illumination, the PTFE–PI–TiO₂-15 membrane achieved a peak steady-state chlorine generation rate of 19.50 mmol·m −2 ·h −1 from 35 g L −1 NaCl solution at pH 1. Radical scavenger and EPR studies indicated that chlorine evolution proceeded via direct hole oxidation of chloride ions without radical intermediates. Mass transfer modeling suggests that chlorine flux was governed by surface-exposed photocatalytic activity rather than membrane transport limitations. This work establishes a scalable, energy-efficient approach for chlorine recovery from desalination brine, offering a sustainable solution for brine management and decentralized chemical production.

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 score0.043
Threshold uncertainty score0.991

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)0.0010.000

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 head0.023
GPT teacher head0.268
Teacher spread0.245 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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