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Record W4378422068 · doi:10.1109/jsen.2023.3279250

An Enhanced Measurement for Inorganics in Water Based on a Novel Planar Three-Electrode Sensor

2023· article· en· W4378422068 on OpenAlexaff
Xiaolei Wang, Yuhao Wang, Henry Leung, Subhas Chandra Mukhopadhyay, Yongqiang Cui, Di Bai

Bibliographic record

VenueIEEE Sensors Journal · 2023
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsUniversity of Calgary
FundersFundamental Research Funds for the Central UniversitiesNatural Science Foundation of Hubei ProvinceNational Natural Science Foundation of China
KeywordsConductivityElectrical impedanceElectrodeIonPlanarMaterials scienceAnalytical Chemistry (journal)Focused Impedance MeasurementEquivalent circuitElectronic engineeringOptoelectronicsChemistryComputer scienceElectrical engineeringVoltageEngineeringChromatography

Abstract

fetched live from OpenAlex

Although conductivity is prevalently used in water quality detection for inorganic ions, its utility could be weakened when various kinds of ions are involved as it merely embodies water bulk resistance indiscriminately. Aiming at detectability enhancement, the article proposes a novel measurement method utilizing interfacial impedance for further exploration of ions. Based on theoretical analysis and measuring model comparison, a current-controlled method with difference measurement was derived, as well as the equivalent circuit. Then, a novel three-electrode sensor with a planar structure was accordingly designed and fabricated. After measurement parameters optimizing by experiments of frequency response and amplitude response, the sensor was tested with a traditional two-electrode sensor and conductivity sensor. Experimental results not only testified the performance of the proposed one in interfacial impedance measurement but also revealed a reduction process of interfacial impedance with increasing conductivity. The influence of water temperature was tested, too. Impedance differences between anion and cation inspired further experiments involving more ion species, which demonstrated that diverse positive ions trended to have similar relationships between conductivity and interfacial impedance while the relationships differed due to types of negative ions. The relationships make the measurement a promising tool for ion detection in certain applications.

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)0.001
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 score0.219
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.035
GPT teacher head0.257
Teacher spread0.223 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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