MétaCan
Menu
Back to cohort
Record W3171658596 · doi:10.3390/ma14123223

Enhanced Optical and Antibacterial Activity of Hydrothermally Synthesized Cobalt-Doped Zinc Oxide Cylindrical Microcrystals

2021· article· en· W3171658596 on OpenAlexfundno aff
Awais Khalid, Pervaiz Ahmad, Abdulrahman I. Alharthi, Saleh Muhammad, Mayeen Uddin Khandaker, Mohammad Rashed Iqbal Faruque, Abdulhameed Khan, Israf Ud Din, Mshari A. Alotaibi, K. Alzimami, Abdulrahman Alfuraih, D.A. Bradley

Bibliographic record

VenueMaterials · 2021
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsnot available
FundersInstitute of Population and Public HealthKing Saud University
KeywordsZincCobaltDopingMaterials scienceAntibacterial activityCobalt oxideChemical engineeringNuclear chemistryNanotechnologyInorganic chemistryChemistryMetallurgyOptoelectronicsBacteria

Abstract

fetched live from OpenAlex

Cobalt (Co) doped zinc oxide (ZnO) microcrystals (MCs) are prepared by using the hydrothermal method from the precursor’s mixture of zinc chloride (ZnCl2), cobalt-II chloride hexahydrate (CoCl2·6H2O), and potassium hydroxide (KOH). The smooth round cylindrical morphologies of the synthesized microcrystals of Co-doped ZnO show an increase in absorption with the cobalt doping. The antibacterial activity of the as-obtained Co-doped ZnO-MCs was tested against the bacterial strains of gram-negative (Escherichia coli, Klebsiella pneumonia) and gram-positive bacteria (Staphylococcus aureus, Streptococcus pyogenes) via the agar well diffusion method. The zones of inhibition (ZOI) for Co-doped ZnO-MCs against E. coli and K. pneumoniae were found to be 17 and 19 mm, and 15 and 16 mm against S. Aureus and S. pyogenes, respectively. The prepared Co-doped ZnO-MCs were thus established as a probable antibacterial agent against gram-negative bacterial strains.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003

Distilled classifier scores by category (both heads)

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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations57
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueMaterialsSame topicZnO doping and propertiesFrench-language works237,207