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Record W4388133351 · doi:10.1177/00037028231202804

Quantifying Platinum and Palladium in Solid Ore Using Laser-Induced Breakdown Spectroscopy Assisted by the Laser-Induced Fluorescence (LIBS-LIF) Technique

2023· article· en· W4388133351 on OpenAlexafffund
Ismail Elhamdaoui, Samira Selmani, Mohamad Sabsabi, Marc Constantin, Paul Bouchard, François Vidal

Bibliographic record

VenueApplied Spectroscopy · 2023
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsUniversité LavalNational Research Council CanadaInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLaser-induced breakdown spectroscopyPalladiumAnalytical Chemistry (journal)PlatinumDetection limitCalibration curveCalibrationSpectroscopyFluorescenceLaser-induced fluorescenceMaterials scienceLaserFluorescence spectroscopyEmission spectrumChemistrySpectral lineOpticsChromatography

Abstract

fetched live from OpenAlex

The laser-induced breakdown spectroscopy assisted by laser-induced fluorescence (LIBS-LIF) in a two-step process was used to measure the concentration of platinum (Pt) and palladium (Pd) by surface analysis of a solid ore core from the Lac des Iles mine followed by analysis of the same core that was pulverized and compacted. This work focuses mainly on the measurement of Pt since the case of Pd has been extensively discussed in previous work. The excitation of Pt is performed at 235.71 nm with fluorescence emission observed near 269.84 nm. Calibration was performed with synthetic samples prepared from the same ore as the samples studied and the calibration curve shows good linearity in Pt content over several orders of magnitude. A limit of detection (LOD) of approximately 0.15 parts per million (ppm) over an average of 200 laser shots was demonstrated. In contrast, conventional LIBS provides a LOD of about 21 ppm over an average of 200 laser shots due to low signal-to-noise ratio and spectral interference from other elements and does not meet the requirements for estimating the average Pt concentration in the ore. The Pt concentrations obtained using LIBS-LIF on solid ore are generally in good agreement with those obtained in its pulverized and compacted form, as well as with laboratory measurements made by conventional chemical methods. However, the comparison of the results obtained for Pd using LIBS-LIF with the laboratory showed a less satisfactory agreement, probably due to its more inhomogeneous distribution in the ore.

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 categoriesMeta-epidemiology (narrow)
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 score0.029
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.030
GPT teacher head0.281
Teacher spread0.250 · 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.

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

Citations8
Published2023
Admission routes2
Has abstractyes

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