Deposition-Pellet Preparation Technique for Powder Samples Measurement Using Laser-Induced Breakdown Spectroscopy
Bibliographic record
Abstract
Laser-Induced Breakdown Spectroscopy (LIBS) is a spectroscopy-based measurement technique that is capable of rapid and accurate qualitative, as well as quantitative, analysis of elemental ingredients either in solid (either for organic or inorganic compounds), liquid, or gaseous samples. Unfortunately, this is not the case for powdered samples, where the focused laser beam will disperse the powder. This can be overcome by making the powder into pellets. But it has an inherent drawback, i.e., the minimum amount of powder is about 0.2 g to obtain a good detectable signal. To cope with this unfavorable condition, especially for the amount of powder less than 0.1 mg, we proposed a sub-target deposition method to make the pellets in this reported work. Using this method, the analyzed powder was deposited into an indented hole on a pellet substrate of KBr with the following optimum conditions, i.e., pellet's pressing pressure of 400 kPa, laser energy of 120 mJ, and a sample's heating temperature of 70℃. Microanalyses of standard powdered samples of PbO, CuO, and ZnO have been carried out with estimated detection limits of 4.7 μg, 4.6 μg, and 3.9 μg, respectively. So, this method can be used to analyze small amounts (in the microgram range) of powdered samples.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".