A data analysis method to rapidly characterize gallium concentration in plutonium matrices using LIBS

锕系元素 激光诱导击穿光谱 材料科学 光谱学 分析化学(期刊) 核工程 放射化学 化学 冶金 核化学 物理 工程类 环境化学 量子力学
作者
Dung M. Vu,John D. Auxier,Elizabeth J. Judge,Kelly E. Aldrich,Brendan J. Gifford,D. Saumon,Amanda J. Neukirch,Jerrad P. Auxier,J. E. Barefield,S. M. Clegg,Ronald K. Martinez,Bryan C. Paulus,Lisa K. Fulks,J. Colgan
出处
期刊:Spectrochimica Acta Part B: Atomic Spectroscopy [Elsevier BV]
卷期号:203: 106650-106650 被引量:3
标识
DOI:10.1016/j.sab.2023.106650
摘要

The processing of actinide samples is a complex and costly endeavor that requires compositional analysis at various stages. Laser-induced breakdown spectroscopy (LIBS) has been used to analyze actinide-containing samples in many nuclear applications including waste management, fuel processing and forensics. The LIBS spectrum obtained from actinide materials are generally extremely complex, exhibiting many thousands of strong emission lines. This makes it difficult to identify other elements within the sample of interest, given the rich and dominant actinide spectrum. In this article we describe a recent effort to identify and quantify impurities and alloying constituents in plutonium matrices using a hand-held LIBS instrument that is used to rapidly and efficiently measure an emission spectrum from a material sample. We tabulate the emission line positions and intensities of plutonium. We report the development of machine-learning software that can identify gallium and quantify its concentration in plutonium matrices. This work has the potential to provide a rapid and nearly non-destructive technique that allows more confidence in characterizing the composition of materials that are present within complex actinide associated targets. We describe how our LIBS measurements and data analysis methods have successfully quantified the gallium concentration in a variety of samples.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
暖暖发布了新的文献求助10
刚刚
1秒前
2秒前
美满又蓝应助布噜布噜采纳,获得10
2秒前
文若发布了新的文献求助10
2秒前
2秒前
Polly完成签到,获得积分10
3秒前
3秒前
初景应助chen采纳,获得20
3秒前
3秒前
bjyx完成签到 ,获得积分10
4秒前
蹦跳的小虾米应助晓飞采纳,获得10
4秒前
11发布了新的文献求助10
4秒前
缓慢豌豆完成签到,获得积分10
4秒前
dove00完成签到,获得积分10
5秒前
Peng发布了新的文献求助10
5秒前
5秒前
keke完成签到 ,获得积分10
5秒前
NexusExplorer应助独特的青易采纳,获得10
5秒前
5秒前
帅气的高跟鞋完成签到,获得积分10
6秒前
6秒前
五花肉丝完成签到,获得积分10
6秒前
7秒前
Ahong完成签到,获得积分10
8秒前
陈陈发布了新的文献求助10
8秒前
9秒前
Ava应助三年六班李子明采纳,获得10
9秒前
东方岚120完成签到,获得积分10
9秒前
9秒前
燕子发布了新的文献求助10
9秒前
巴拉完成签到,获得积分10
9秒前
xuan发布了新的文献求助10
10秒前
ju发布了新的文献求助10
10秒前
凌时爱吃零食应助mannich采纳,获得10
10秒前
10秒前
千千浅完成签到,获得积分10
10秒前
11秒前
伟卫完成签到,获得积分10
11秒前
11秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
政治传播过程中的外交与说服——以中苏友好协会为例的历史考察 566
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7580420
求助须知:如何正确求助?哪些是违规求助? 9159978
关于积分的说明 19597009
捐赠科研通 7163143
什么是DOI,文献DOI怎么找? 3265875
关于科研通互助平台的介绍 2430782
邀请新用户注册赠送积分活动 2256832