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激光诱导击穿光谱结合碳分子发射的时间分辨等离子体分析用于煤中碳分析

Laser-Induced Breakdown Spectroscopy Combined with Temporal Plasma Analysis of C Molecular Emission for Carbon Analysis in Coal.

作者信息

Rajavelu Hemalaxmi, Vasa Nilesh J, Seshadri Satyanarayanan

机构信息

Department of Engineering Design, 37268Indian Institute of Technology Madras, Chennai, India.

Department of Applied Mechanics, 37268Indian Institute of Technology Madras, Chennai, India.

出版信息

Appl Spectrosc. 2021 Jul;75(7):893-900. doi: 10.1177/00037028211012399. Epub 2021 May 13.

Abstract

A benchtop laser-induced breakdown spectroscopy is demonstrated to determine the elemental carbon content present in raw coal used for combustion in power plants. The spectral intensities of molecular CN and C emission are measured together with the atomic carbon (C) and other inorganic elements (Si, Fe, Mg, Al, Ca, Na, and K) in the laser-induced breakdown spectroscopy spectrum of coal. The emission persistence time of C molecule emission is measured from the coal plasma generated by a nanosecond laser ablation with a wavelength of 266 nm in the Ar atmosphere. The emission persistence time of molecular C emission along with the spectral intensities of major ash elements (Fe, Si, Al, and Ca) and carbon emissions (atomic C, molecular CN, and C) shows a better relationship with the carbon wt% of different coal samples. The calibration model to measure elemental carbon (wt%) is developed by combining the spectral characteristics (spectral intensity) and the temporal characteristics (emission persistence time of C molecule emission). The temporal characteristic studies combined with the spectroscopic data in the partial least square regression model have resulted in an improvement in the root mean square error of validation, and the relative standard deviation is reduced from 10.8% to 4.1% and from 11.3% to 6.0%, respectively.

摘要

一种台式激光诱导击穿光谱技术被用于测定发电厂燃烧用原煤中的元素碳含量。在煤的激光诱导击穿光谱中,测量了分子CN和C发射的光谱强度,以及原子碳(C)和其他无机元素(Si、Fe、Mg、Al、Ca、Na和K)。在氩气气氛中,用波长为266 nm的纳秒激光烧蚀产生的煤等离子体中,测量了C分子发射的持续时间。分子C发射的持续时间以及主要灰分元素(Fe、Si、Al和Ca)和碳发射(原子C、分子CN和C)的光谱强度与不同煤样的碳质量分数呈现出更好的关系。通过结合光谱特征(光谱强度)和时间特征(C分子发射的持续时间),建立了测量元素碳(质量分数)的校准模型。在偏最小二乘回归模型中,时间特征研究与光谱数据相结合,使验证的均方根误差得到改善,相对标准偏差分别从10.8%降至4.1%,从11.3%降至6.0%。

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