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Record W2894066519 · doi:10.4236/wjnse.2018.83003

Measurements of Pulsed 532 nm Laser Breakdown Spectroscopy of Synthesized Magnetite Nanoferrofluid

2018· article· en· W2894066519 on OpenAlexaff
Mohammad E. Khosroshahi, Maryam Tajabadi

Bibliographic record

VenueWorld Journal of Nano Science and Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceLaser-induced breakdown spectroscopyAnalytical Chemistry (journal)SpectroscopyMagnetiteLaserTransmission electron microscopyEnergy-dispersive X-ray spectroscopyMagnetizationNuclear magnetic resonanceScanning electron microscopeOpticsMagnetic fieldNanotechnologyChemistryPhysics

Abstract

fetched live from OpenAlex

We describe the results of 532 nm pulse laser-induced breakdown spectroscopy (LIBS) of two samples of magnetite nanoparticles (SPIONs) nanoferrofluid synthesized at room (S1) and elevated temperatures (S2) and at three different laser energy levels and pulse frequency. The size of magnetite nanoparticles, size distribution, magnetic crystalline phase and magnetization were analyzed and measured using transmission electron microscopy (TEM), X-ray diffraction spectroscopy (XRD) and vibrating sample magnetometry (VSM). The SPIONs showed a distribution between 4 - 22 nm with a peak about 12 nm and saturation magnetization of about 65 emu/g. The Saha-Boltzmann analysis of spectra for medium energy level (1050 mJ) yields plasma temperatures of (3881 ± 200) K and (26,047 ± 200) K for Fe I and OV as the lowest and highest temperatures respectively. A range of corresponding electron density (Ne-) of (0.47 - 6.80) × 1020, (0.58 - 8.30) × 1020 and (0.69 - 9.96) × 1020 cm-3 were determined at 860, 1050 and 1260 mJ respectively using the estimated CCD pictures. The results confirmed a higher elements ratio for S1 than S2 and the signal intensity indicated a non-linear behaviour as a function of pulse frequency with the maximum ratio value at 3 Hz. At higher frequency of 6 Hz no such turning point was observed. The highest and lowest temperatures corresponded to Fe I and OV respectively. The LIBS technique can be utilized to study, characterize and determine the elements ratio required in most applications involving the synthesizing process.

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 score0.004
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.012
GPT teacher head0.223
Teacher spread0.210 · 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
Published2018
Admission routes1
Has abstractyes

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