Fundamental Studies of Femtosecond Laser Interactions with Solids and Their Applications to Laser Ablation Inductively Coupled Plasma Mass Spectrometry for Environmental Analysis
Bibliographic record
Abstract
Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been successfully applied in many research areas. Compared to conventional analytical techniques, it has the advantages of minimum sample preparation and high spatial resolution capabilities. Elemental and isotopic fractionation, matrix effects and the absence of matrix-matched standards are problems that limit applications of this technique for routine analysis. The introduction of femtosecond laser pulses has improved the analytical capabilities of this technique in terms of precision, accuracy and detection limits. However, laser ablation involves complex processes that are not fully understood and requires extensive studies on laser-solid interaction, particle formation, particle transport and ionization of particles in the ICP ion source. The aim of my Ph.D. is to understand the mechanisms of laser-solid interaction which can be an important step to improve the analytical capabilities of LA-ICP-MS. Effect of different gases such as hydrogen and nitrogen mixed with Ar gas before the ablation cell and the effect of nitrogen on mass bias effects in Pb isotope ratios determination using fs-LA-MC (multiple collectors)-ICP-MS have also been investigated. Another goal of my work is to validate the application of fs-LA-ICP-MS for the analysis of natural sediment cores using a simple sample preparation of different sediment reference materials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".