{"title":"AGLAE 新设施利用机器学习技术对古代层状物体进行先进的二维-PIXE/RBS 处理","authors":"Astrid Tazzioli , Quentin Lemasson , Alexandre Girard , Laurent Pichon , Brice Moignard , Claire Pacheco","doi":"10.1016/j.nimb.2024.165469","DOIUrl":null,"url":null,"abstract":"<div><p>Studying without sampling the fine layering of heritage objects, usually heterogeneous in composition and with an uneven surface requires new methodologies. Single spot analyses are not representative and may lead to misinterpretation; thus, they are not sufficient to conclude on the layering. 2D-imaging is essential to analyze a bigger area to recover the characteristics of heritage objects. However, processing 2D-RBS images pixel per pixel requires a long computing time. To automate the processing of 2D-IBA images at New AGLAE, the use of artificial intelligence enables the consideration of all the spectra from the different detectors and across the entire area simultaneously. Unsupervised learning algorithms for clustering bring together the pixels with similar characteristics, effectively capturing the essential features of the 2D-images. The signal corresponding to each cluster can then be processed to obtain both the chemical composition and layer thicknesses of the analyzed areas. Thus, a spatial distribution of the stratigraphy is obtained.</p></div>","PeriodicalId":19380,"journal":{"name":"Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms","volume":"555 ","pages":"Article 165469"},"PeriodicalIF":1.4000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advanced 2D-PIXE/RBS processing with Machine Learning at the New AGLAE facility for ancient layered objects\",\"authors\":\"Astrid Tazzioli , Quentin Lemasson , Alexandre Girard , Laurent Pichon , Brice Moignard , Claire Pacheco\",\"doi\":\"10.1016/j.nimb.2024.165469\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Studying without sampling the fine layering of heritage objects, usually heterogeneous in composition and with an uneven surface requires new methodologies. Single spot analyses are not representative and may lead to misinterpretation; thus, they are not sufficient to conclude on the layering. 2D-imaging is essential to analyze a bigger area to recover the characteristics of heritage objects. However, processing 2D-RBS images pixel per pixel requires a long computing time. To automate the processing of 2D-IBA images at New AGLAE, the use of artificial intelligence enables the consideration of all the spectra from the different detectors and across the entire area simultaneously. Unsupervised learning algorithms for clustering bring together the pixels with similar characteristics, effectively capturing the essential features of the 2D-images. The signal corresponding to each cluster can then be processed to obtain both the chemical composition and layer thicknesses of the analyzed areas. Thus, a spatial distribution of the stratigraphy is obtained.</p></div>\",\"PeriodicalId\":19380,\"journal\":{\"name\":\"Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms\",\"volume\":\"555 \",\"pages\":\"Article 165469\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0168583X24002398\",\"RegionNum\":3,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INSTRUMENTS & INSTRUMENTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168583X24002398","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
Advanced 2D-PIXE/RBS processing with Machine Learning at the New AGLAE facility for ancient layered objects
Studying without sampling the fine layering of heritage objects, usually heterogeneous in composition and with an uneven surface requires new methodologies. Single spot analyses are not representative and may lead to misinterpretation; thus, they are not sufficient to conclude on the layering. 2D-imaging is essential to analyze a bigger area to recover the characteristics of heritage objects. However, processing 2D-RBS images pixel per pixel requires a long computing time. To automate the processing of 2D-IBA images at New AGLAE, the use of artificial intelligence enables the consideration of all the spectra from the different detectors and across the entire area simultaneously. Unsupervised learning algorithms for clustering bring together the pixels with similar characteristics, effectively capturing the essential features of the 2D-images. The signal corresponding to each cluster can then be processed to obtain both the chemical composition and layer thicknesses of the analyzed areas. Thus, a spatial distribution of the stratigraphy is obtained.
期刊介绍：
Section B of Nuclear Instruments and Methods in Physics Research covers all aspects of the interaction of energetic beams with atoms, molecules and aggregate forms of matter. This includes ion beam analysis and ion beam modification of materials as well as basic data of importance for these studies. Topics of general interest include: atomic collisions in solids, particle channelling, all aspects of collision cascades, the modification of materials by energetic beams, ion implantation, irradiation - induced changes in materials, the physics and chemistry of beam interactions and the analysis of materials by all forms of energetic radiation. Modification by ion, laser and electron beams for the study of electronic materials, metals, ceramics, insulators, polymers and other important and new materials systems are included. Related studies, such as the application of ion beam analysis to biological, archaeological and geological samples as well as applications to solve problems in planetary science are also welcome. Energetic beams of interest include atomic and molecular ions, neutrons, positrons and muons, plasmas directed at surfaces, electron and photon beams, including laser treated surfaces and studies of solids by photon radiation from rotating anodes, synchrotrons, etc. In addition, the interaction between various forms of radiation and radiation-induced deposition processes are relevant.
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