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相关概念视频

Atomic Absorption Spectroscopy: Overview01:27

Atomic Absorption Spectroscopy: Overview

2.5K
Atomic absorption spectroscopy (AAS) is a technique used to analyze elements by measuring electromagnetic radiation (EMR) absorbed by atoms, which causes them to transition to a higher-energy orbit. The most crucial step in AAS is atomization, where the analyte is converted into gas-phase atoms, typically through a flame or furnace. Some of these atoms become thermally excited in the flame, while most remain in the ground state.
When irradiated by EMR of a particular wavelength, these...
2.5K
Atomic Absorption Spectroscopy: Instrumentation01:22

Atomic Absorption Spectroscopy: Instrumentation

975
An atomic absorption spectrophotometer (AAS) comprises several components: a radiation source, an atomizer, a monochromator, and a detector. The radiation source can be a hollow-cathode lamp (HCL) or an electrodeless-discharge lamp (EDL), both of which provide a narrow emission line of the required wavelength. However, some instruments use continuum sources and high-resolution monochromators to achieve a narrow range of radiation.
The atomizer used in AAS can be either a flame atomizer or an...
975
Atomic Absorption Spectroscopy: Radiation and Light Sources01:13

Atomic Absorption Spectroscopy: Radiation and Light Sources

554
Atomic absorption spectroscopy (AAS) relies on the Beer-Lambert law, which requires that the radiation source emits a narrow range of wavelengths to match the absorption characteristics of the analyte atom. The primary criteria for choosing an appropriate radiation source in AAS is to provide a precise and intense emission at specific wavelengths that will allow accurate detection of the analyte.
Two common narrow-range 'line' sources used in AAS are hollow-cathode lamps (HCLs) and...
554
Atomic Absorption Spectroscopy: Lab01:21

Atomic Absorption Spectroscopy: Lab

563
For AAS measurements, samples must be introduced as clear solutions, often requiring extensive preliminary treatment to dissolve materials like soils, animal tissues, and minerals. Common methods for sample preparation include treatment with hot mineral acids, wet ashing, combustion in closed containers, high-temperature ashing, or fusion with reagents.
 Solutions containing organic solvents, such as low-molecular-mass alcohols, esters, or ketones, enhance absorbances by increasing...
563
Molecular Spectroscopy: Absorption and Emission01:14

Molecular Spectroscopy: Absorption and Emission

3.4K
Molecules possess discrete energy levels called quantum states. Unlike atoms, which have simpler energy levels, molecules possess additional rotational and vibrational energy levels.  Each energy level is separated by an energy gap, with the gaps between adjacent electronic, vibrational, and rotational levels varying significantly. The three types of energy levels in a diatomic molecule are shown in Figure 1.
3.4K
Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

534
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...
534

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Quantifying X-Ray Fluorescence Data Using MAPS
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基于机器学习的X射线吸收光谱数据分析的新框架:XASDAML.

Xue Han1, Haodong Yao1, Fei Zhan1

  • 1Multi-disciplinary Research Division, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, People's Republic of China.

Journal of synchrotron radiation
|July 21, 2025
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概括

射线吸收光谱 (XAS) 分析得到了机器学习平台XASDAML的增强. 该工具有效处理大型XAS数据集,预测结构性质,并发现材料模式.

关键词:
在X射线吸收光谱学 (XAS) 中.集成的数据处理系统.这是一个模块化机器学习框架.

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Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research
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ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
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科学领域:

  • 材料科学 材料科学 材料科学
  • 分析化学 分析化学
  • 计算化学计算化学

背景情况:

  • 射线吸收光谱 (XAS) 对于材料表征至关重要.
  • 随着同步机设备数据复杂度的增加,需要先进的计算工具.
  • 现有的XAS数据处理方法在处理大规模数据集时遇到困难.

研究的目的:

  • 介绍XASDAML,这是一个用于集成XAS数据处理的机器学习平台.
  • 开发一个灵活和可访问的计算框架,用于XAS分析.
  • 在XAS研究中提高研究效率和数据洞察力.

主要方法:

  • 开发了一个基于机器学习的模块化平台 (XASDAML),集成到 Jupyter Notebook 接口中.
  • 实现了光谱结构描述器生成,预测建模和性能验证.
  • 利用主要组件分解和聚类来进行XAS数据集的统计分析.

主要成果:

  • 从铜EXAFS数据中,XASDAML成功地预测了协调数和辐射分布函数.
  • 分析了Fe(phen) 3的XANES光谱,以揭示旋转交叉状态中的债券长度变化.
  • 展示了强大的工具包功能,包括统计描述器分析和光谱可视化.

结论:

  • XASDAML提供了一个标准化,可扩展的框架,用于将机器学习集成到XAS分析中.
  • 该平台提高了研究效率,并促进了对材料结构的更深入了解.
  • 为了满足XAS研究日益扩大的需求,XASDAML作为一个多功能计算资源.