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Record W3122354834 · doi:10.1007/s12598-020-01659-z

Plasmonic photo‐assisted electrochemical sensor for detection of trace lead ions based on Au anchored on two‐dimensional g‐C <sub>3</sub> N <sub>4</sub> /graphene nanosheets

2021· article· en· W3122354834 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRare Metals · 2021
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceGrapheneDetection limitGraphitic carbon nitrideX-ray photoelectron spectroscopyPlasmonSurface plasmon resonanceAnalytical Chemistry (journal)OptoelectronicsNanoparticleNanotechnologyPhotocatalysisChemical engineering

Abstract

fetched live from OpenAlex

Abstract In this paper, a plasmonic photo‐assisted electrochemical sensor, Au anchored on two‐dimensional (2D) graphitic carbon nitride (g‐C 3 N 4 )/reduced graphene oxide (rGO) nanosheets (Au/g‐C 3 N 4 /rGO), was facile fabricated. The morphology and structure of the composite are characterized by transmission electron microscope, X‐ray photoelectron spectroscopy, X‐ray diffraction and ultraviolet–visible spectrophotometer (UV–Vis). Based on the semiconductor of g‐C 3 N 4 and optical properties of surface plasmon resonance for Au, the as‐prepared Au/g‐C 3 N 4 /rGO showed high sensitivity for the detection of trace lead ion [Pb(II)] by differential pulse anodic stripping voltammetry in the presence of visible light illumination. Under optimized conditions, the limit of detection (signal‐to‐noise ratio ( S / N ) = 3) Pb(II) detection can be low to 0.1 nmol·L −1 . In addition, the interference research and real soil sample detection were measured to confirm the possibility of practical 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.

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 categoriesMeta-epidemiology (narrow)
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 score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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