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相关概念视频

Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

295
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...
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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...
1.1K
IR Spectrum01:19

IR Spectrum

923
When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
Transmittance is defined as the ratio of the radiant power passing through a sample to that from the radiation's source. Multiplying the transmittance by 100 gives the percent transmittance (%T), which varies between 100% (no absorption) and 0%...
923
Spectrophotometry: Introduction01:16

Spectrophotometry: Introduction

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Spectrophotometry is the quantitative measurement of the absorption, reflection, diffraction, or transmission of electromagnetic radiation through a material as a function of the intensity and wavelength of the radiation. A spectrophotometer is a device used to measure the change in the radiation intensity caused by its interaction with the material.
The essential components of a spectrophotometer include a source of electromagnetic radiation, a slot for placing a material to be analyzed, and a...
2.9K
Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

305
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...
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IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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相关实验视频

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Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy
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在各种仪器中SERS频谱转换的功能回归.

Tao Wang1, Yanjun Yang2, Haoran Lu1

  • 1Department of Statistics, Franklin College of Arts and Sciences, University of Georgia, Athens, Georgia 30602, USA. pingma@uga.edu.

The Analyst
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概括

这项研究引入了一个新的框架,SpectraFRM,以标准化来自不同仪器的表面增强拉曼光谱 (SERS) 数据. 这种方法提高了准确性,并有助于识别微量分子,使SERS更可靠.

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科学领域:

  • 分析化学 分析化学
  • 频谱学是一种光谱学.
  • 化学测量 化学测量 化学测量

背景情况:

  • 表面增强拉曼光谱 (SERS) 提供快速,便携式的微量分子检测.
  • 仪器变化使SERS数据分析和仪器之间的比较变得复杂.
  • 标准化对于在不同平台上可靠的SERS应用程序至关重要.

研究的目的:

  • 开发一个新的框架,在各种仪器中转换SERS频谱.
  • 为了能够准确地比较来自不同光谱仪的SERS数据.
  • 通过使用标准化的SERS光谱来增强分析物的机器学习分类.

主要方法:

  • 为了跨仪器的光谱映射,开发了一种被惩罚的功能回归模型 (SpectraFRM).
  • 非参数函数形式被用于响应,预测和系数来建模非线性关系.
  • 在四个仪器中对20个分析物的数据进行了交叉验证.

主要成果:

  • SpectraFRM为SERS的光谱峰值和基线提供了可解释的校正.
  • 与原始数据相比,在光谱分析中实现了大约11%的误差减少.
  • 一个额外的特征提取步骤提高了10%的分析物识别精度.

结论:

  • SpectraFRM提供了一种灵活,稳固和准确的方法来标准化SERS光谱.
  • 该框架有效地解决了来自不同仪器的频谱变化.
  • 这种方法有可能大大提高SERS技术的可靠性和广泛采用.