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相关概念视频

Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

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When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
Different compounds display unique properties due to their...
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Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

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Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...
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IR Spectrometers01:25

IR Spectrometers

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There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
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IR Spectroscopy: Molecular Vibration Overview01:24

IR Spectroscopy: Molecular Vibration Overview

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When Infrared (IR) radiation passes through a covalently bonded molecule, the bonds transition from lower to higher vibrational levels. The fundamental vibrational motions that result in infrared absorption can be classified as stretching or bending vibrations.
Stretching vibrations are vibrational motions that occur along the bond line, changing the bond length or distance between two bonded atoms. They are further distinguished as symmetric or asymmetric. In symmetric stretching, the...
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IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration01:16

IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration

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A covalently bonded heteronuclear diatomic molecule can be modeled as two vibrating masses connected by a spring. The vibrational frequency of the bond can be expressed using an equation derived from Hooke's law, which describes how the force applied to stretch or compress a spring is proportional to the displacement of the spring. In this case, the atoms behave like masses, and the bond acts like a spring.
According to Hooke's law, the vibrational frequency is directly proportional to...
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Variability: Analysis01:11

Variability: Analysis

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Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
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O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
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可解释性扰动器用于近红外光谱分析中的变量选择.

Chaoshu Duan1,2, Xuyang Liu1,2, Wensheng Cai1,2

  • 1Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, P. R. China.

Journal of chemical information and modeling
|October 6, 2023
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概括

一种新的扰波器方法通过选择关键变量来增强近红外 (NIR) 光谱分析. 这种方法优化了定量模型,并改善了复杂样本的光谱解释.

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科学领域:

  • 分析化学 分析化学
  • 化学测量 化学测量 化学测量
  • 机器学习 机器学习

背景情况:

  • 近红外 (NIR) 光谱分析对于定量建模至关重要.
  • 变量选择对于优化NIR模型和增强可解释性至关重要.
  • 深度学习为复杂的数据分析提供了先进的方法.

研究的目的:

  • 在NIR光谱分析中开发一种用于变量选择的新扰剂方法.
  • 利用深度学习策略来改进对光谱数据的解释.
  • 在定量模型中创建一个评估变量重要性标准.

主要方法:

  • 一个深度学习预测器被训练来建立从spectra.com的目标预测.
  • 使用预测器的输出训练了一个扰乱器,以导出扰乱阳性 (P +) 和扰乱负 (P -) 特性.
  • 使用扰乱层的权重 (σ) 评估了变量重要性.
  • 使用交叉验证来确定定量模型的最佳变量子集.

主要成果:

  • 在三个NIR数据集上,扰动器方法实现了与现有方法相比或优于现有方法的性能 (根平均二次误差).
  • 选择的光谱变量证明了可解释性,识别了与预测目标相关的关键特征.
  • 该方法有效优化了定量模型,并提供了对光谱解释的见解.

结论:

  • 开发的扰动器方法是优化定量NIR模型的有效工具.
  • 这种方法提供了一种有效的方式来解释多组件样本的光谱.
  • 深度学习和扰动策略的整合提高了光谱分析中的模型性能和可解释性.