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Record W7014455923

The path of LIBS instrumentations : past, present and future

2013· article· en· W7014455923 on OpenAlexaffvenue

Bibliographic record

VenueNPARC · 2013
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsLaser-induced breakdown spectroscopySoftware portabilityInstrumentation (computer programming)Sensitivity (control systems)Analytical techniqueCharacterization (materials science)Sample (material)
DOInot available

Abstract

fetched live from OpenAlex

Laser-Induced Breakdown Spectroscopy (LIBS) is a method of optical emission spectroscopy that uses laser-generated plasma as the source of vaporization, atomization and excitation. A bibliographic study around the LIBS literature shows clearly the number of application areas related to LIBS and laser based techniques is still growing. There is no doubt that LIBS has become a fascinating technology with great promise. The benefits include no sample preparation, no consumables, every sample, real-time analysis, standoff measurements, and more. LIBS provides ppm sensitivity for elemental analysis and even offers molecular characterization based on database libraries and chemometrics. Since the invention of the laser in the sixties, a few instruments based on LIBS have been developed but have not found widespread use. However, in the last decade, there has been significant technological developments in the components (lasers, spectrometers, detectors) used in LIBS instruments as well as emerging needs to perform real time measurements under conditions to which conventional techniques cannot be applied. This opens the door for many applications and possibilities of developing field-deployable instruments. In this presentation we will review the technological developments in the components used for LIBS instrumentations for different industrial sectors. Based on these applications, we will discuss the LIBS instrumentation in terms of robustness, analytical performance and portability in comparison to conventional techniques. In addition, we will present the determination of isotope ratios using LIBS in air at atmospheric pressure for partially resolved uranium-235/uranium-238 and hydrogen/deuterium isotope shift lines in such conditions. Some approaches to improve the LIBS sensitivity developed in our laboratory and elsewhere, such as double pulse mode, laser induced fluorescence coupled to LIBS, resonance enhanced LIBS, resonant ablation, will be also presented.

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)0.009
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0020.004
Scholarly communication0.0060.014
Open science0.0020.004
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0050.004

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 head0.005
GPT teacher head0.199
Teacher spread0.193 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2013
Admission routes2
Has abstractyes

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