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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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Applications of IR Spectroscopy: Overview01:11

Applications of IR Spectroscopy: Overview

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The non-destructive nature and ability to provide valuable chemical information make IR spectroscopy a versatile technique with broad applications in various scientific and industrial fields. IR spectroscopy is commonly used to identify and characterize organic and inorganic compounds. It provides information about the functional groups present in a molecule and the bonding between atoms. This helps in the structural elucidation of compounds during organic synthesis, pharmaceutical research,...
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IR Spectrum01:19

IR Spectrum

1.1K
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%...
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IR Spectrometers01:25

IR Spectrometers

1.2K
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...
1.2K
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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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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High-definition Fourier Transform Infrared FT-IR Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology
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探索红外 (IR) 光谱分析的步骤:预处理, (经典) 数据建模和深度学习.

Azadeh Mokari1,2, Shuxia Guo1, Thomas Bocklitz1,2,3

  • 1Leibniz Institute of Photonic Technology, Member of Research Alliance "Leibniz Health Technologies", 07745 Jena, Germany.

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概括

红外 (IR) 光谱为生物医学分析提供独特的分子指纹. 先进的人工智能 (AI) 算法对于克服光谱干扰和提取有意义的生物和化学信息至关重要.

关键词:
分析技术的分析技术.人工智能的人工智能是人工智能.基线是指一个基线.数据建模数据建模深度学习是一种深度学习.红外光谱学 红外光谱学机器学习是机器学习.噪音 噪音 噪音 噪音预处理技术 预处理技术

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科学领域:

  • 生物医学分析分析
  • 频谱学是一种光谱学.
  • 人工智能的人工智能

背景情况:

  • 红外 (IR) 光谱测量分子振动状态,为样本分析提供独特的光谱指纹.
  • 红外光谱在生物学,化学和医学中广泛使用,用于微生物识别和临床诊断等应用.
  • 散射和基线转移等干扰因素使直接光谱解释使用贝尔-兰伯特定律变得复杂.

研究的目的:

  • 审查近期光谱预处理和IR光谱数据建模方面的进展.
  • 讨论人工智能 (AI) 的应用,包括经典机器学习和深度学习,用于分析复杂的红外光谱.
  • 突出克服光谱干扰和从IR数据中提取高级生物/化学信息的方法.

主要方法:

  • 复习用于光谱预处理和数据建模的经典机器学习技术.
  • 探索深度学习方法来分析IR光谱数据.
  • 讨论减轻干扰效应 (如散射和基线扭曲) 的方法.

主要成果:

  • 基于AI的算法对于准确解释受干扰影响的IR光谱至关重要.
  • 先进的数据分析技术可以将光谱信号转化为可操作的生物和化学洞察力.
  • 经典机器学习和深度学习都显示出提高IR光谱分析的前景.

结论:

  • 红外光谱是生物医学分析的强大工具,但需要复杂的数据处理.
  • 通过解决光谱干扰,人工智能是释放红外光谱学的全部潜力的关键.
  • 未来的研究应该专注于开发和完善用于光谱预处理和数据建模的AI驱动方法.