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Record W4387507767 · doi:10.1039/d3an01267k

An ion-selective chemiresistive platform as demonstrated for the detection of nitrogen species in water

2023· article· en· W4387507767 on OpenAlexafffund
Maryam Darestani-Farahani, Fanqing Ma, Vinay Patel, P. Ravi Selvaganapathy, Peter Kruse

Bibliographic record

VenueThe Analyst · 2023
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaGlobal Water FuturesCanada First Research Excellence FundMcMaster UniversityOntario Centres of Excellence
KeywordsDetection limitAdsorptionNitriteChemistryAqueous solutionIonAmmoniumInorganic chemistryElectrodeNitrateMembraneAnalytical Chemistry (journal)ChromatographyOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

) membranes. The nitrate sensors are able to measure nitrate ions in a range of 2.2-220 ppm with a detection limit of 0.3 ppm. The nitrite sensors respond between 67 ppb and 67 ppm of nitrite ions (64 ppb detection limit). The ammonium sensors can measure ammonium concentrations in a wide range from 10 ppb to 100 ppm (0.5 ppb detection limit). The fast responses to nitrate and nitrite are due to a mechanism involving electrostatic gating repulsion between negative charge carriers of the film and anions while ammonium detection arises from two mechanisms based on electrostatic gating repulsion and adsorption of ammonium ions at the surface of the p-doped chemiresistive film. The adsorption phenomenon slows down the recovery time of the ammonium sensor. This sensor design is a new platform to continuously monitor ions in industrial, domestic, and environmental water resources by robust chemiresistive devices.

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 score0.088
Threshold uncertainty score0.202

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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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

Citations10
Published2023
Admission routes2
Has abstractyes

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