MétaCan
Menu
Back to cohort
Record W2278995692 · doi:10.1149/ma2015-01/39/2075

Glassy Carbon Electrode As a Promising Sensor for Healthcare and Environmental Monitoring

2015· article· en· W2278995692 on OpenAlexaff
Sanghamitra Chatterjee, Aicheng Chen

Bibliographic record

VenueECS Meeting Abstracts · 2015
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsLakehead University
Fundersnot available
KeywordsMethylglyoxalCarbon nanotubeElectrodeCyclic voltammetryElectrochemical gas sensorMaterials scienceSquare waveGlassy carbonElectrochemistryChemistryNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

Glassy carbon electrode (GCE) has been explored in the present investigations and applied thereafter for biomedical applications and environmental monitoring. A novel electrochemical approach for the quantitative analysis of methylglyoxal as a biomarker in human plasma has been developed. An electrochemical sensor employing a single walled carbon nanotube modified GCE for the sensitive detection of methylglyoxal is delineated for the first time employing square wave voltammetry. This modified electrode exhibits potent and sustained electron-mediating behavior and a well-defined reduction peak in response to methylglyoxal was observed. The interfering effect of common coexisting metabolites in human whole blood has also been investigated. The developed assay was shown to be specific and sensitive for the analysis of plasma levels of methylglyoxal in healthy volunteer and diabetic patients. A simple, rapid and highly selective method for the determination of the most abundant α-dicarbonyl compound in wine and beer has been developed for the first time by employing square wave voltammetry. A novel electrochemical sensor, based on the electrodeposition of platinum nanoparticles onto single wall carbon nanotubes that were casted on a GCE substrate has been developed. This modified electrode was successfully applied for the quantitative analysis of methylglyoxal in wine and beer samples. The developed sensor possesses advantageous properties such as a high active surface area, stability, and a rapid electron transfer rate, which cumulatively demonstrate high performance toward the electrocatalytic reduction and detection of methylglyoxal. A promising direct and simultaneous electrochemical determination method of phenolic pollutants in wastewater samples was constructed successfully on GCE with advantages being rapid, simple, convenient, sensitive, in situ and inexpensive. The electrochemical characteristics of multi-component phenolic pollutants, such as phenol and 4-nitrophenol were investigated on GCE employing square wave voltammetry technique. Each of them displayed good linear relationship between their oxidation peak currents and their corresponding concentrations in a rather wide range coexisting with the other phenolic pollutant. The effect of different experimental and instrumental parameters such as solution pH and square wave frequency were examined. Square wave voltammetry was employed to investigate the electrochemical characteristic of phenol and 4-nitrophenol at GCE and successfully realize the electrochemical separation and simultaneous determination of multi-component phenols at GCE without any modification for the first time.

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)0.001
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0040.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.014
GPT teacher head0.228
Teacher spread0.214 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting AbstractsSame topicElectrochemical sensors and biosensorsFrench-language works237,207