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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 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 score0.261
Threshold uncertainty score0.209

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 studies0.0000.000
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 head0.005
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 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

Citations0
Published2013
Admission routes2
Has abstractyes

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