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Record W2521080280 · doi:10.1002/ceat.201600380

Ultrasound‐Assisted Synthesis of Cu and Cu/Ni Nanoparticles on NaP Zeolite Support as Antibacterial Agents

2016· article· en· W2521080280 on OpenAlex
Jamshid Behin, Ali Shahryarifar, Hossein Kazemian

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

VenueChemical Engineering & Technology · 2016
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsAntibacterial activityEthylene glycolBacillus subtilisNanoparticleNuclear chemistryZeolitePEG ratioChemistryMaterials scienceMetalSubstrate (aquarium)Central composite designResponse surface methodologyNanotechnologyChromatographyBacteriaCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Synthesis, characterization, and antibacterial properties of Cu and Cu/Ni nanoparticles loaded on NaP zeolite against Bacillus subtilis and Escherichia coli were investigated. Synthesis of Cu and Ni nanoparticles of the NaP substrate was carried out by conventional and sonochemical methods in ethylene glycol medium. A Box‐Behnken design of experiment was employed to analyze the influence of nanoparticle loading, Cu content of nanoparticles, and concentration of metallic salts solution on the antibacterial activity of the synthesized product. The synthesized samples provided an about one‐third higher activity against B. subtilis compared to E. coli . Ultrasonic irradiation significantly improved the antibacterial activity against E. coli and B. subtilis . Time‐ and concentration‐dependent bacterial tests of the synthesized sample under optimum conditions were performed with a central composite design of experiment.

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)0.001
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 score0.005
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.223
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