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相关概念视频

Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

396
The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...
396
Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

406
A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
406
2D NMR: Overview of Homonuclear Correlation Techniques01:16

2D NMR: Overview of Homonuclear Correlation Techniques

199
Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
COSY90 is the standard two-dimensional (2D) COSY experiment that...
199
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.1K
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...
1.1K
2D NMR: Overview of Heteronuclear Correlation Techniques01:18

2D NMR: Overview of Heteronuclear Correlation Techniques

181
Heteronuclear correlation spectroscopy is an analytical technique that investigates the coupling between different types of nuclei, often a proton and an X-nucleus, such as carbon-13 or nitrogen-15. This method is commonly used in nuclear magnetic resonance (NMR) spectroscopy to gain insights into complex chemical compounds' structural and compositional aspects. A typical heteronuclear correlation spectrum displays X-nucleus chemical shifts on one axis and a proton spectrum on the other...
181

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相关实验视频

Updated: Jul 5, 2025

Method Development for Contactless Resonant Cavity Dielectric Spectroscopic Studies of Cellulosic Paper
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改进的3D异步相关数据预处理方法用于中国手工造纸的拉曼光谱.

Chunsheng Yan1, Zhongyi Cheng2, Linquan Cao3

  • 1Zhejiang University Library, Hangzhou, 310058, China; State Key Laboratory of Extreme Photonics and Instrumentation, Hangzhou 310058, China.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
|January 14, 2024
PubMed
概括
此摘要是机器生成的。

一种新的3D异步关联方法 (3D-ACM) 增强了拉曼光谱分析,用于分类中国手工造纸. 这种技术显著提高了光谱分辨率和机器学习模型的性能,用于材料识别.

关键词:
三维异步相关联方法 (3D-ACM)数据预处理数据的预处理.希尔伯特的转换变换机器学习 机器学习拉曼光谱法 拉曼光谱法张量器的产物是张量器的产物.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 频谱学是一种光谱学.
  • 数据科学数据科学数据科学

背景情况:

  • 对像中国手工纸这样的材料进行准确的分类至关重要.
  • 传统的光谱分析方法可能缺乏足够的分辨率和隐藏信息提取能力.

研究的目的:

  • 引入和评估一种新的3D异步相关方法 (3D-ACM),用于增强材料分类.
  • 评估3D-ACM在与各种用于光谱数据分析的机器学习模型相结合时的性能.

主要方法:

  • 在拉曼光谱数据上开发了一个涉及张量积和希尔伯特变换运算的3D-ACM.
  • 在预处理的数据中应用了六种机器学习模型 (PCA-LR,SVM-LR,KNN,RF,CNN).
  • 使用R平方值评估模型性能.

主要成果:

  • 3D-ACM显著增加了光谱分辨率,并揭示了隐藏的信息.
  • 机器学习模型 (PLS-LR,KN,RF,CNN) 在使用3D-ACM时实现了接近或等于1的R平方值.
  • 性能与PCA等无监督方法相提并论.

结论:

  • 3D-ACM是一种用于光谱数据预处理的多功能数学技术.
  • 它为材料分类和识别提供了卓越的性能,无需额外的实验设置.
  • 3D-ACM对材料科学和数据分析的未来应用有着显著的前景.