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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

2.7K
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 Spectrometers01:14

UV–Vis Spectrometers

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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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Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

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Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used....
231
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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Atomic Emission Spectroscopy: Overview01:20

Atomic Emission Spectroscopy: Overview

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Atomic emission spectroscopy (AES) is an analytical technique used to determine the elemental composition of a sample by analyzing the light emitted from excited atoms. In AES, atoms in a sample are excited to higher energy levels by thermal energy from high-temperature sources, such as plasma, arcs, or sparks. When these excited atoms return to lower energy states, they emit light at specific wavelengths characteristic of each element. The resulting atomic emission spectrum, which consists of...
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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...
384

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相关实验视频

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Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research
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高灵敏度的极紫外线短暂吸收光谱,通过机器学习实现.

Tobias Gutberlet, Hung-Tzu Chang, Sergey Zayko

    Optics express
    |December 2, 2023
    PubMed
    概括

    我们开发了一种新的机器学习方法,以显著减少光谱中的噪声,提高了短暂吸收测量的数据质量十倍. 这种先进的技术提高了研究微妙物质动态的灵敏度.

    科学领域:

    • 频谱学是一种光谱学.
    • 机器学习 机器学习
    • 材料科学 材料科学 材料科学

    背景情况:

    • 光谱学实验经常受到噪声的影响,限制了测量的灵敏度.
    • 传统的降噪方法,如开/关引用,具有局限性,特别是对于宽带光源.

    研究的目的:

    • 采用机器学习来引入一种新的光谱检测方案.
    • 为了在XUV短暂吸收光谱学中证明改进的噪声抑制.

    主要方法:

    • 在样品相互作用之前和之后测量探测器光谱.
    • 使用机器学习来捕捉光谱组件之间的相关性.
    • 应用人工神经网络用于像素智能降噪.

    主要成果:

    • 与传统方法相比,实现了噪声抑制的十倍提高.
    • 证明有效的降噪,不需要对参考光谱进行波长校准.
    • 成功地将该方案应用于XUV短暂吸收测量.

    结论:

    • 新的无声化方案为光谱学提供了显著的噪声降低.
    • 该方法可以适应各种实验,特别有利于低重复率源.

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  • 增强的灵敏度使材料中电子和晶格动态的详细研究成为可能.