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Record W2315632561 · doi:10.1002/cjce.22478

Synthesis and characterization of copper succinate and copper oxide nanoparticles by electrochemical treatment: Optimization by Taguchi robust analysis

2016· article· en· W2315632561 on OpenAlex
Susmita Das, Vimal Chandra Srivastava

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCopper-based nanomaterials and applications
Canadian institutionsnot available
Fundersnot available
KeywordsCopperTaguchi methodsScanning electron microscopeFourier transform infrared spectroscopyCalcinationCopper oxideMaterials scienceNanoparticleElectrochemistryNuclear chemistryOxideChemical engineeringAnalytical Chemistry (journal)MetallurgyChemistryComposite materialNanotechnologyElectrodeChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Cylindrical rod‐shaped copper succinate nanoparticles were prepared using the electrochemical method. Taguchi robust design was applied to optimize experimental parameters such as succinic ion concentration (C o ), current applied (I ap ), and pH (pH). The obtained copper succinate nano‐rods were further thermally treated at different temperatures to produce copper oxide (CuO) nano‐disks. At optimum conditions of I ap = 0.5 A, pH = 7, and C o = 0.25, the maximum productivity of copper nanoparticles before and after calcination at 500 °C was 1.53 g and 1.06 g, respectively. Products were characterized by Fourier transform infrared spectroscopy (FTIR), X‐ray diffraction (XRD), scanning electron microscopy (SEM), and UV‐visible spectrophotometry to determine their various physicochemical characteristics.

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 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 score0.002
Threshold uncertainty score0.270

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 head0.005
GPT teacher head0.173
Teacher spread0.169 · 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