Rapid and high-resolution visualization elements analysis of material surface based on laser-induced breakdown spectroscopy and hyperspectral imaging

高光谱成像 激光诱导击穿光谱 主成分分析 元素分析 光谱学 可视化 成像光谱学 图像分辨率 材料科学 激光器 激光烧蚀 分辨率(逻辑) 激光扫描 光学 化学 计算机科学 物理 人工智能 有机化学 量子力学
作者
Shangyong Zhao,Yuchen Zhao,Zongyu Hou,Zhe Wang
出处
期刊:Applied Surface Science [Elsevier BV]
卷期号:629: 157415-157415 被引量:8
标识
DOI:10.1016/j.apsusc.2023.157415
摘要

It is extremely important for material analysis to visualize the elemental distribution of the sample surface quickly, sensibly, and high-resolution. Most point-to-point methods, such as laser-induced breakdown spectroscopy (LIBS), are incapable of achieving high spatial resolution at a reasonable time cost, while surface scanning methods such as hyperspectral imaging (HSI) is insensitive to concentration and material composition. In this work, we proposed a method coupling LIBS with HSI for rapid and high-resolution elemental distribution analysis of material surface. The method of point-to-point laser ablation and region of interest (ROI) segmentation were primarily employed. We further processed the LIBS and HSI spectra and distinguished different ROIs of material surface using principal component analysis. Significant LIBS and HSI lines that contributed to the classification of ROIs were also identified. Moreover, we examined the relationship between the principal component scores of LIBS and HSI spectra based on the Spearman correlation coefficient. Finally, the element visualization images of LIBS and LIBS-HSI were presented and compared. Compared with LIBS imaging, LIBS-HSI imaging offers a better spatial resolution that is at least 90.75 folds higher and a scanning time that is at least 6 times shorter. These results, together with the experimental process, indicate that LIBS-HSI appears to be a promising contender for rapid and high-resolution visual element analysis of material surface.

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
白菜完成签到,获得积分10
1秒前
1秒前
油炸绿番茄完成签到,获得积分10
1秒前
夏傥发布了新的文献求助10
2秒前
2秒前
嗝嗝发布了新的文献求助10
3秒前
3秒前
吔94完成签到,获得积分10
4秒前
我是老大应助JJ采纳,获得10
5秒前
5秒前
6秒前
kkk完成签到,获得积分10
7秒前
8秒前
rick完成签到,获得积分10
8秒前
果称发布了新的文献求助10
9秒前
不再追忆完成签到 ,获得积分10
9秒前
NewMoon完成签到,获得积分10
9秒前
datou完成签到,获得积分20
10秒前
石破茧发布了新的文献求助30
10秒前
852应助花花采纳,获得10
10秒前
iuun完成签到 ,获得积分10
10秒前
10秒前
xiaomu完成签到,获得积分10
11秒前
随便发布了新的文献求助10
11秒前
yw1234发布了新的文献求助10
11秒前
务实的念波完成签到,获得积分10
12秒前
顾矜应助虚幻的小灵龙米采纳,获得10
12秒前
cdercder应助幽默身影采纳,获得10
12秒前
西洲长风发布了新的文献求助10
13秒前
小二郎应助南屿汐月采纳,获得10
14秒前
李一一完成签到 ,获得积分10
14秒前
15秒前
阔达德天完成签到,获得积分10
15秒前
杨枝修喵完成签到,获得积分10
16秒前
谨言慎行完成签到 ,获得积分10
16秒前
16秒前
16秒前
六月完成签到,获得积分10
17秒前
一一发布了新的文献求助10
19秒前
呦呦完成签到,获得积分10
19秒前
高分求助中
(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
Prompt Engineering for Clinicians: Harnessing AI in Everyday Medical Practice 600
University Physics for the Life Sciences 500
REAL-WORLD EFFICACY AND GENOMIC LANDSCAPE OF POLATUZUMA VEDOTIN-BASED FIRST-LINE THERAPY IN DIFFUSE LARGE B-CELL LYMPHOMA: A FOCUS ON TP53 MUTATIONS AND TREATMENT RESPONSE 500
Handbook of Luminescence Dating 500
Safety Pharmacology 500
《KNN基无铅压电陶瓷电学性能优化与物理机理研究》 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 计算机科学 化学工程 生物化学 物理 内科学 复合材料 催化作用 光电子学 物理化学 电极 细胞生物学 基因 遗传学
热门帖子
关注 科研通微信公众号,转发送积分 6954775
求助须知:如何正确求助?哪些是违规求助? 8638472
关于积分的说明 18319047
捐赠科研通 6399442
什么是DOI,文献DOI怎么找? 3083395
关于科研通互助平台的介绍 2129608
邀请新用户注册赠送积分活动 2060203