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Record W2909808982 · doi:10.21608/asat.2015.23006

Preparation and Characterization of Electrically Switched Ion Exchange Films

2015· article· en· W2909808982 on OpenAlexafffund
F. Tawfic., Emma Dickson, Young-Je Kim, Waleed Mekky

Bibliographic record

VenueInternational Conference on Aerospace Sciences and Aviation Technology · 2015
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Defense
KeywordsCharacterization (materials science)Materials scienceIon exchangeIonOptoelectronicsNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Wastewater treatment by conventional methods as ion exchange, coagulation and precipitation is very important. A relatively new method for wastewater treatment is introduced; this method is known as electrically switched ion exchange (ESIX). ESIX can be used to separate metal ion contaminants from industrial wastewater. The ESIX method involves sequential application of reduction and oxidation potentials to an ion exchange film to induce the respective loading and unloading of Cs+. The metal ion separated from the wastewater and unloaded from the electrode by modulating the potential applied to the film. This technology is superior to conventional methods (e.g conventional ion exchange) as it requires very little energy for ionic separation. In this study, two films of nickel hexacyanoferrate were prepared on nickel electrodes with different preparation procedures. Each film shows different performance in Cs+ separation. Scanning electron microscopy was used to characterize the modified film surfaces. Cyclic voltammetry was used to investigate the ion exchange capacity and stability. These two films show a high capacity and stability for Cs+ separation.

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 score0.084
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.300
Teacher spread0.273 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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