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Record W4415315429 · doi:10.1016/j.seppur.2025.135660

A joule-heated PTFE-CNT composite membrane fabricated by solution blow spinning for enhanced ammonia recovery

2025· article· en· W4415315429 on OpenAlexaff
Yaozhong Zhang, Ramin Farnood

Bibliographic record

VenueSeparation and Purification Technology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMembraneSpinningAmmoniaPorosityMass transferComposite numberMass transfer coefficientJoule heating

Abstract

fetched live from OpenAlex

A novel Joule-heated polytetrafluoroethylene‑carbon nanotube (PTFE-CNT) composite membrane was fabricated via solution blow spinning (SBS). The resulting membrane exhibited superhydrophobicity (152° water contact angle), good electrical conductivity (62.2 S/m), and high porosity (76 %). Application of 15 V induced Joule heating, raising the dry-state membrane temperature to 95 °C and yielding a 2.95-fold enhancement in ammonia flux alongside a 4.76-fold increase in the mass transfer coefficient compared to a commercial PTFE membrane under identical conditions. The membrane's hierarchical micro/ nanoscale porosity—achieved through a 15 wt% CNT loading—facilitated ammonia transport, while localized heating shifted NH 4 + /NH 3 equilibrium toward NH 3 , further accelerating mass transport. This approach eliminates the need for bulk heating and offers an energy-efficient alternative to ammonia recovery. • Joule-heated PTFE-CNT membrane boosts ammonia flux by up to 2.95-fold. • High porosity (76 %) and WCA >150° achieved via solution blow spinning. • Novel dual-level hierarchy porous structures enhances ammonia gas transport. • High CNT loading (15 wt%) enables localized membrane heating to 95.5 °C. • Mass transfer coefficient reached 4.76-fold versus commercial PTFE

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 score0.273
Threshold uncertainty score0.968

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 head0.009
GPT teacher head0.271
Teacher spread0.262 · 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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