Quantitative analysis of tin alloy combined with artificial neural network prediction
| Autor: | Jagdish P. Singh, Seong Y. Oh, Fang-Yu Yueh |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Detection limit
Internal standard X-ray spectroscopy Materials science Calibration curve business.industry Materials Science (miscellaneous) Alloy Analytical chemistry chemistry.chemical_element engineering.material Industrial and Manufacturing Engineering Optics chemistry Impurity engineering Business and International Management Spectroscopy business Tin |
| Zdroj: | Applied Optics. 49:C36 |
| ISSN: | 1539-4522 0003-6935 |
| DOI: | 10.1364/ao.49.000c36 |
| Popis: | Laser-induced breakdown spectroscopy was applied to quantitative analysis of three impurities in Sn alloy. The impurities analysis was based on the internal standard method using the Sn I 333.062-nm line as the reference line to achieve the best reproducible results. Minor-element concentrations (Ag, Cu, Pb) in the alloy were comparatively evaluated by artificial neural networks (ANNs) and calibration curves. ANN was found to effectively predict elemental concentrations with a trend of nonlinear growth due to self-absorption. The limits of detection for Ag, Cu, and Pb in Sn alloy were determined to be 29, 197, and 213 ppm, respectively. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|