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相关概念视频

Ultraviolet and Visible (UV–Vis) Spectroscopy: Overview01:02

Ultraviolet and Visible (UV–Vis) Spectroscopy: Overview

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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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UV–Vis Spectroscopy: Molecular Electronic Transitions01:16

UV–Vis Spectroscopy: Molecular Electronic Transitions

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In Ultraviolet–Visible (UV–Vis) spectroscopy, the absorption of electromagnetic radiation is used to probe the electronic structure of molecules. This technique provides insights into molecular electronic transitions, particularly the movement of electrons between different molecular orbitals. Radiation is absorbed if the energy of the electromagnetic radiation passing through the molecule is precisely equal to the energy difference between the excited and ground states. During this...
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UV–Vis Spectroscopy of Conjugated Systems01:32

UV–Vis Spectroscopy of Conjugated Systems

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Organic compounds with conjugated double bonds show strong absorption features in the UV–visible region of the electromagnetic spectrum attributed to π → π* electronic excitations. Generally, a UV–vis absorption spectrum is recorded as a plot of absorbance vs wavelength. The wavelength of maximum absorbance, which manifests as a peak in the absorption spectrum, is denoted as λmax.
One of the factors influencing λmax is the extent...
6.9K
UV–Vis Spectrometers01:14

UV–Vis Spectrometers

1.3K
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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UV–Vis Spectroscopy: Woodward–Fieser Rules01:29

UV–Vis Spectroscopy: Woodward–Fieser Rules

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UV–Visible absorption spectra of conjugated dienes arise from the lowest energy π → π* transitions. The light-absorbing part of the molecule is called the chromophore, and the substituents directly attached to the chromophore are called auxochromes. A strong correlation exists between the absorption maxima, λmax, and the structure of a conjugated π system. The Woodward–Fieser rules predict the value of λmax for a given...
23.9K
IR and UV–Vis Spectroscopy of Aldehydes and Ketones01:29

IR and UV–Vis Spectroscopy of Aldehydes and Ketones

5.3K
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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一种机器学习方法,通过UV-Vis光谱有效预测聚合物衰老.

Haishan Yu1, DaDi Zhang1, Lei Cui1

  • 1National Synchrotron Radiation Laboratory, University of Science and Technology of China, 42 Hezuohua Road, Hefei, Anhui 230029, China.

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本研究提出了一种具有成本效益的机器学习 (ML) 方法,用于使用颜色和波长数据预测聚合物溶液的老化. ExtraTree模型实现了高精度,为传统光谱学提供了切实可行的替代方案.

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科学领域:

  • 聚合物科学 聚合物科学
  • 频谱学是一种光谱学.
  • 机器学习 机器学习

背景情况:

  • 传统的紫外可见 (UV-Vis) 光谱法用于聚合物分析是精确的,但成本高昂且效率低下.
  • 评估聚合物溶液老化对于材料质量控制和性能预测至关重要.

研究的目的:

  • 开发一种创新且具有成本效益的方法,用于预测聚合物溶液因老化而导致的UV-Vis光谱变化.
  • 为此预测,利用易于访问的特征描述符和机器学习 (ML) 算法.

主要方法:

  • 输入特征包括波长和聚合物溶液的蓝色 (B),绿色 (G) 和红色 (R) 颜色值.
  • 七个经典的ML模型被训练并使用10倍交叉验证进行评估.
  • 用皮尔森相关系数 (r) 和平均绝对误差 (MAE) 等指标评估模型性能.

主要成果:

  • 所有七种ML模型都在预测光谱变化方面表现出色.
  • ExtraTree模型表现出卓越的预测能力,达到0.9859的r和0.0457.7的MAE.
  • 拟议的方法为评估聚合物溶液老化提供了一个快速和经济的替代方案.

结论:

  • 开发的ML方法有效地使用简单的颜色和波长数据预测聚合物溶液的老化.
  • 与传统的光谱技术相比,这种方法提供了一种实用,快速和具有成本效益的解决方案.
  • 这些发现支持在材料科学中使用ML进行高效的属性评估.