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Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

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Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used....
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When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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Flame Photometry: Overview01:02

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Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
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Ultraviolet–visible (UV–visible or UV–Vis) spectroscopy is an analytical technique that investigates the interaction between matter and UV–Vis light within the electromagnetic spectrum. This method is widely used for its versatility, simplicity, and relatively quick data acquisition, making it valuable for both qualitative and quantitative analysis. When UV–Vis radiation passes through a material,  molecules absorb light depending on the energy required for...
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The absorbance of UV and visible (UV–visible) radiations is measured using a UV–visible spectrophotometer. Deuterium lamps, which emit UV radiation, and tungsten lamps, which produce radiation in the visible region, are used as light sources in UV–visible spectrophotometers. A monochromator or prism is used for diffraction grating, i.e., to split the incoming radiation into different wavelengths. A system of slits is used to focus the desired wavelength on the sample cell.
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Infrared spectroscopy, also known as vibrational spectroscopy, is mainly used to determine the types of bonds and functional groups in molecules. In aldehydes and ketones, the carbonyl (C=O) bond shows an absorption around 1710 cm-1. The C=O bond vibration of an aldehyde occurs at lower frequencies than that of a ketone. In addition to the C=O absorption in an aldehyde, the aldehydic C–H bond also gives two peaks in the 2700–2800 cm-1 range. This absorption, coupled with the...
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基于塑料光谱学的数据增强和分类算法的比较.

Jiachao Luo1, Qunbiao Wu1, Jin Cao2

  • 1School of Mechanical Engineering, Jiangsu University of Science and Technology, Jiangsu, 212100, China. just_wqb@just.edu.cn.

Analytical methods : advancing methods and applications
|January 16, 2025
PubMed
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这项研究引入了一种新的塑料光谱生成模型,以提高塑料分类的准确性. 数据增强显著提高了模型性能,1D-ResNet实现了FTIR数据的峰值精度.

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科学领域:

  • 环境科学 环境科学
  • 分析化学 分析化学
  • 计算机科学 计算机科学

背景情况:

  • 塑料废物管理是一个关键的全球环境问题.
  • 光谱学和深度学习提供了有效的塑料分类方法.
  • 有限的数据和算法比较阻碍了进步.

研究的目的:

  • 为数据增强提出塑料光谱生成模型.
  • 系统地分析和比较各种分类算法.
  • 提高塑料废物分类的准确性和效率.

主要方法:

  • 预处理光谱数据,使用立方插值,规范化,S-G过,线性分离和SNV.
  • 开发基于C-GAN的模型,用于生成多类塑料光谱.
  • 比较机器学习 (SVM,RF) 和深度学习 (GoogleNet,ResNet) 的算法.

主要成果:

  • 预处理提高了分类准确性,通过PCA可视化.
  • 在C-GAN模型生成一致和有效的塑料光谱.
  • 数据增强使分类准确度提高了至少3%.
  • 1D-ResNet实现了FTIR数据的峰值准确度 (0.991),增强了两倍.
  • 一维输入模型通常表现优于二维模型.
  • 深度学习在大型数据集上表现出色,而传统的ML在小型数据集上表现稳定.

结论:

  • 通过光谱生成模型增强数据对于改善塑料分类至关重要.
  • 1D-ResNet在识别频谱特征以进行准确的分类方面表现出卓越的性能.
  • 传统的ML和深度学习都有作用,取决于数据集的大小.