Artificial neural networks applied to quantitative elemental analysis of organic material using PIXE
| Author | dc.contributor.author | Correa, Rafael | |
| Author | dc.contributor.author | Chesta, Miguel Ángel | es_CL |
| Author | dc.contributor.author | Dinator Ramírez, María Inés | es_CL |
| Author | dc.contributor.author | Morales Peña, José | es_CL |
| Author | dc.contributor.author | Requena, I. | es_CL |
| Author | dc.contributor.author | Vila Pinto, Irma | |
| Admission date | dc.date.accessioned | 2008-12-23T16:09:20Z | |
| Available date | dc.date.available | 2008-12-23T16:09:20Z | |
| Publication date | dc.date.issued | 2006-08 | |
| Cita de ítem | dc.identifier.citation | NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS Volume: 248 Issue: 2 Pages: 324-328 Published: AUG 2006 | en |
| Identifier | dc.identifier.issn | 0168-583X | |
| Identifier | dc.identifier.uri | https://repositorio.uchile.cl/handle/2250/118778 | |
| Abstract | dc.description.abstract | An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced emission) spectra of organic substances. Following the training stage ANN was applied to a subset of similar samples thus obtaining the elemental concentrations in muscle, liver and gills of Cyprinus carpio. Concentrations obtained with the ANN method are in full agreement with results from one standard analytical procedure, showing the high potentiality of ANN in PIXE quantitative analyses. | en |
| Lenguage | dc.language.iso | en | en |
| Publisher | dc.publisher | ELSEVIER | en |
| Keywords | dc.subject | HIGH-ENERGY | en |
| Título | dc.title | Artificial neural networks applied to quantitative elemental analysis of organic material using PIXE | en |
| Document type | dc.type | Artículo de revista |
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