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Record W2035292142 · doi:10.1039/c3lc51255j

Out-of-plane ion concentration polarization for scalable water desalination

2013· article· en· W2035292142 on OpenAlexafffund
Brendan D. MacDonald, Max M. Gong, Peigen Zhang, David Sinton

Bibliographic record

VenueLab on a Chip · 2013
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsUniversity of TorontoUniversity of Ontario Institute of Technology
FundersGrand Challenges Canada
KeywordsDesalinationWater desalinationIonPolarization (electrochemistry)Concentration polarizationScalabilityMembraneVolumetric flow ratePlanarMultiplexingMaterials scienceChemistryMechanicsOptoelectronicsAnalytical Chemistry (journal)PhysicsComputer scienceElectronic engineeringChromatographyEngineering

Abstract

fetched live from OpenAlex

We present a scalable, out-of-plane desalination approach using ion concentration polarization. A depletion boundary separates salt ions and purified water into distinct vertical layers. The out-of-plane design enables multiplexing in three dimensions, providing the functional density required for practical application. For membrane widths of 125-200 μm, and applied voltage of 5 V, the energy requirement is 4.6 Wh L(-1) for 20 mM solution, and 13.8 Wh L(-1) for 200 mM. Energy efficiency is found to be insensitive to flow rate as the depletion boundary adjusts to yield a commensurate volume of purified water. Scaled-up devices are presented, which have a 3-fold improvement in functional density over planar systems.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.208
Teacher spread0.195 · 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

Citations53
Published2013
Admission routes2
Has abstractyes

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