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Record W2641212331 · doi:10.6000/1927-5129.2017.13.61

Effects of Fe-Doping on the Structural and Magnetic Properties of Indium Oxide Nanoparticles Synthesized by Bottom up Techniqu

2017· article· en· W2641212331 on OpenAlexvenueno aff
M. Naeem, K. Kamran, S. Qaseem, Sajid Ali, Shujaat Ali

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2017
Typearticle
Languageen
FieldEngineering
TopicCharacterization and Applications of Magnetic Nanoparticles
Canadian institutionsnot available
Fundersnot available
KeywordsCrystalliteMaterials scienceBixbyiteFerromagnetismAnalytical Chemistry (journal)IndiumLattice constantDopingMagnetizationTransmission electron microscopyNanoparticleParamagnetismCondensed matter physicsDiffractionNanotechnologyMagnetic fieldChemistryMetallurgy

Abstract

fetched live from OpenAlex

We study Fe doped In2O3 nanoparticles (NPs) from structural and magnetic point of view. X-ray diffraction (XRD) and transmission electron microscopy (TEM) reveal cubic bixbyite structure for both pure and Fe doped samples thereby confirming successful incorporation of Fe in host In2O3 lattice. Average crystallite size of pure and Fe doped (5% and 10%) In2O3 as calculated by Scherer’s formula shows slight increase from 21 nm for pure to 27 nm for the sample with 10% Fe content. The Williamson Hall (WH) method was also utilized to further determine crystallite size and Fe induced strain in In2O3 lattice. The crystallite sizes by WH plot are found to be 18 nm (for undoped), 22 nm (for 5% Fe) and 24 nm (for 10% Fe). These values are in good agreement with TEM results. Energy dispersive x-ray spectroscopy (EDX) indicates the existence of some oxygen vacancies in Fe doped In2O3 samples. Magnetic measurements show that all Fe doped In2O3 NPs exhibit typical ferromagnetic hysteresis loop with saturation magnetization Ms increasing with increasing Fe concentration. Temperature dependence of field cooled (FC) and zero field cooled (ZFC) magnetizations show no divergence and transition from ferromagnetism to paramagnetism in the temperature range of 5 to 300 K. This evidences a robust room-temperature-ferromagnetism (RTFM) in these NPs. The RTFM of our samples is attributed to the presence of oxygen vacancies in our samples.

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)0.000
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 score0.008
Threshold uncertainty score0.220

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 studies0.0000.001
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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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