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Record W2909128681 · doi:10.1139/cjc-2018-0302

Peroxidase-like activity of palladium nanoparticles on hydrogen-bond supramolecular structures over a broader pH range and their application in glucose sensing

2019· article· en· W2909128681 on OpenAlexvenueno aff
Nian Zhou, Seyin Zou, Li Zou, Ruidi Shen, Yamin Zhou, Liansheng Ling

Bibliographic record

VenueCanadian Journal of Chemistry · 2019
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Nanomaterials in Catalysis
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsChemistryGlucose oxidasePalladiumPeroxidaseLinear rangeDetection limitNanoparticleSupramolecular chemistryBiosensorNuclear chemistryAnalytical Chemistry (journal)CatalysisOrganic chemistryChromatographyEnzymeChemical engineeringMoleculeBiochemistry

Abstract

fetched live from OpenAlex

To circumvent the complicated natural peroxidases, palladium nanoparticles embedded in melamine cyanurate (MCA-Pd NPs) were synthesized. MCA-Pd NPs catalyzed the oxidation of ABTS 2– by H 2 O 2 , and the solution turned green, which could be quantified via a typical absorption peak at 420 nm. MCA-Pd NPs had high peroxidase-like activity in a wider pH range than that of natural peroxidases. MCA-Pd NPs were used to develop a colorimetric sensor for H 2 O 2 over the pH range of 7.0 to 11.0, which had same linear range, and their linear regression equations had similar slopes. Moreover, MCA-Pd NPs were applied to establish the biosensor for glucose by using glucose oxidase (GOx); it had a linear range of 5.0–120 μmol/L, with a linear regression equation of A = 0.04926 + 0.00536C (C: μmol/L, R = 0.9960) and a detection limit of 0.3 μmol/L (3σ/slope). When we applied it to detect glucose level in human blood, satisfactory results were obtained.

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 score0.001
Threshold uncertainty score0.524

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 head0.006
GPT teacher head0.211
Teacher spread0.206 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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