Atomic spectrometry update: review of advances in the analysis of metals, chemicals and materials

IF 3.1 2区 化学 Q2 CHEMISTRY, ANALYTICAL Journal of Analytical Atomic Spectrometry Pub Date : 2024-10-18 DOI:10.1039/D4JA90052A
Eduardo Bolea-Fernandez, Robert Clough, Andy Fisher, Bridget Gibson and Ben Russell
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Abstract

This update covers the literature published between approximately June 2023 and April 2024 and is the latest part of a series of annual reviews. It is designed to provide the reader with an overview of the current state of the art with respect to the atomic spectrometric analysis of various metals, chemicals and materials. Data processing appears to be the hottest topic in many of the areas. This is especially true for LIBS and (TOF)-SIMS, where huge amounts of data can be acquired. Methods have been used to decrease the dimensions of the data whilst still retaining the most important information. This can then be input into a machine-learning algorithm so that the provenance of a sample, the sample type, or, in the case of TOF-SIMS data, a clear characterisation of the surface of the sample can be obtained while using less computing power and less processing time. Although these algorithms have been used for some years, their use is expanding into new areas. Another development is the combination of complementary techniques on the same instrument platform. This enables data from the two techniques to be obtained simultaneously and from the same spot on the sample. With regard to the different analytical techniques used, LIBS is continuing to increase in popularity, bolstering its reputation as being the rising superstar of the analytical world.

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原子光谱分析法最新进展:金属、化学品和材料分析进展回顾
本次更新涵盖了大约 2023 年 6 月至 2024 年 4 月期间出版的文献,是年度综述系列的最新部分。它旨在为读者提供有关各种金属、化学品和材料的原子光谱分析技术现状的概览。数据处理似乎是许多领域最热门的话题。尤其是在可以获取大量数据的 LIBS 和 (TOF)-SIMS 领域。我们已经采用了一些方法来减少数据的尺寸,同时仍然保留最重要的信息。然后将这些信息输入机器学习算法,这样就可以在使用较少计算能力和处理时间的情况下,获得样品的来源、样品类型,或 TOF-SIMS 数据,样品表面的清晰特征。虽然这些算法已经使用了数年,但其应用正在向新的领域扩展。另一项发展是在同一仪器平台上结合使用互补技术。这样就能同时从样品的同一个点获得两种技术的数据。就所使用的各种分析技术而言,LIBS 的普及率正在不断提高,使其作为分析界冉冉升起的超级明星的声誉更加响亮。
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来源期刊
CiteScore
6.20
自引率
26.50%
发文量
228
审稿时长
1.7 months
期刊介绍: Innovative research on the fundamental theory and application of spectrometric techniques.
期刊最新文献
Back cover Evaluation of miniaturized ultrasonic nebulization for high-efficiency sampling in characterization of silver nanoparticles by single particle inductively coupled plasma mass spectrometry† Atomic spectrometry update: review of advances in the analysis of metals, chemicals and materials Assessing the performance of handheld LIBS for predicting soil organic carbon and texture in European soils† Research on a bimodal fusion detection method for surface defects of metal AM components based on LIBS
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