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Record W4384565507 · doi:10.14447/jnmes.v26i2.a08

Synthesis and Characterization of Zirconium Doped Nickel Oxide Nanoparticles Using Acalypha indica L Extract and Its Antimicrobial Activities

2023· article· en· W4384565507 on OpenAlexvenueno aff
V. Rajarajeswari, K. C. Seetha Lakshmi, P. Karpagavinayagam, R.R. Muthuchudarkodi, S. Thanikaikarasan

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2023
Typearticle
Languageen
FieldMedicine
TopicMedicinal Plants and Neuroprotection
Canadian institutionsnot available
Fundersnot available
KeywordsAntimicrobialTraditional medicineNanoparticleCharacterization (materials science)NickelDopingChemistryZirconium oxideNuclear chemistryMaterials scienceOxideMedicineNanotechnologyMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Nanomaterials have had one of the dimensions in the range of 1-100 nm and it's had wide range of application in various fields.The materials produces by the processing in the greener route have more sustain nature.Based on this, the investigation focused on plants based green synthesis of Zr-doped Nickel oxide nanoparticles (NiO Nps) using Acalypha indica Leaf extract for synthesis and its potential applications.The synthesized Zr doped NiO nanoparticles were characterized using Scanning electron microscopy (SEM), X-ray diffraction spectroscopy (XRD), and Fourier transform-infrared spectroscopy (FT-IR) and UV Visible spectroscopy (UV-Vis).The optical absorption calculated and confirmed by UV Visible spectroscopy, the wavelength range is 260 nm.The FCC indexing with its crystalline structure confirmed by XRD.The band at 470 confirmed the presence of NiO using FTIR, Prepared Nano sized materials present in 85 nm ensured through SEM analysis.AFM analysis of the synthesized materials represents the topography Zr doped NiO NPs deliberates good antibacterial activity.

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)0.001
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 score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.031
GPT teacher head0.273
Teacher spread0.242 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

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