通过激光诱导分解光谱学与基于可变选择策略的随机森林相结合,对石油焦炭特性进行快速定量分析
Shunfan Hu1, Jianming Ding1, Yan Dong2
1Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of Ministry of Education, College of Chemistry & Material Science, Northwest University Xi'an 710127 China tanghongsheng@nwu.edu.cn huali@nwu.edu.cn.
RSC advances
|May 22, 2024
概括
激光诱导分解光谱 (LIBS) 结合化学测量准确量化石油焦炭的特性,如灰含量和热量. 这种快速分析支持对人工石墨生产的需求不断增长.
科学领域:
- 分析化学 分析化学
- 材料科学 材料科学 材料科学
- 频谱学是一种光谱学.
背景情况:
- 石油焦炭对于人工石墨生产至关重要,这是"双碳"战略所推动的.
- 精确分析石油焦炭的物理化学特性 (灰含量,挥发性物质,热量) 是必不可少的.
- 现有的财产分析方法可能耗时且缺乏效率.
研究的目的:
- 开发一种快速而准确的方法来量化石油焦的物理化学特性.
- 探索元素组成和关键性质之间的相关性.
- 使用LIBS和化学测量建立一个强大的分析框架.
主要方法:
- 从46个石油焦炭样本中收集了激光诱导分解光谱 (LIBS) 光谱.
- 使用化学测量技术构建和优化了一个随机森林 (RF) 校准模型.
- 用人变量重要度测量 (VIM) 和变量重要度预测 (VIP) 用于变量选择.
主要成果:
- 对于灰含量 (0.9187),挥发性物质 (0.9820) 和热值 (0.9510) 的高确定系数 (RP2) 已实现.
- 报告的低预测误差:MREP为0.0881 (灰),0.0527 (挥发性物质),0.006 (热量值).
- 确定了与分析属性相关的关键元素光谱线.
结论:
- 结合LIBS和化学测量,为快速分析石油焦炭提供了强大的工具.
- 该方法支持人工石墨生产中的高效质量控制和评估.
- 这项研究表明了元素分析在预测材料性质方面的潜力.
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