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Record W2945535189 · doi:10.20964/2019.06.38

Electrochemical Synthesis of CuxO/Cu2S Nanocomposites as Nonenzymatic Glucose Sensor

2019· article· en· W2945535189 on OpenAlexaff
Xu Xue, Huile Jin, Qian Ren, Aili Liu, Jun Li, Dewu Yin, Xin Feng, Xiaomei Dong, Jichang Wang, Shun Wang

Bibliographic record

VenueInternational Journal of Electrochemical Science · 2019
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsElectrochemistryNanocompositeElectrochemical gas sensorMaterials scienceChemical engineeringNanotechnologyChemistryElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

The focus of this study is to explore ways of accelerating the corrosion rate of copper anodes for the possible synthesis of copper nano-composites on the counter electrode, and the subsequent applications of such composites as nonenzymatic glucose sensor. Normally, a strong corrosion resistance of copper anodes emerges in alkaline solutions due to the formation of a passive copper hydroxide film, which prevents further corrosion. In this research the presence of sulfide ions in the electrolyte was found to dramatically promote the corrosion process and eventually led to the production of CuxO/Cu2S (where CuxO was consist of Cu2O and CuO) nanocomposites on the counter electrode during the electrochemical corrosion process. When the as-prepared copper nanocomposites electrodes were used to detect the oxidation of glucose, a strongly enhanced anodic process was obtained, in which the detection limit was found to be around 10 uM with a linear range of 10-1000 uM and a detection sensitivity of 2688 uA cm -2 mM -1 .

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)0.001
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 score0.003
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.003
GPT teacher head0.217
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 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

Citations6
Published2019
Admission routes1
Has abstractyes

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