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相关概念视频

Atomic Spectroscopy: Effects of Temperature01:27

Atomic Spectroscopy: Effects of Temperature

287
Atomization, converting samples into gas-phase atoms and ions, is essential for atomic spectroscopy. The flame temperature required for atomization affects the efficiency of the atomic spectroscopic methods by increasing the atomization efficiency and the relative population of the excited and ground states.
At thermal equilibrium, the relative populations of excited and ground state atoms can be estimated using the Maxwell–Boltzmann distribution. For example, an increase in temperature...
287
Atomic Emission Spectroscopy: Lab01:29

Atomic Emission Spectroscopy: Lab

144
AES is a powerful analytical technique, especially effective when used with plasma sources, producing abundant spectra in characteristic emission lines. The Inductively Coupled Plasma (ICP), in particular, yields superior quantitative analytical data due to its high stability, low noise, low background, and minimal interferences under optimal experimental conditions. However, newer air-operated microwave sources are emerging as promising alternatives that could be more cost-effective than...
144
Atomic Emission Spectroscopy: Overview01:20

Atomic Emission Spectroscopy: Overview

1.5K
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...
1.5K
Flame Photometry: Overview01:02

Flame Photometry: Overview

444
Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
444
Atomic Emission Spectroscopy: Instrumentation01:22

Atomic Emission Spectroscopy: Instrumentation

330
The instrumentation of atomic emission spectrometry (AES) involves various components, including atomization devices that convert samples into gas-phase atoms and ions. There are two main types of atomization devices: continuous and discrete atomizers.  Continuous atomizers, like plasmas and flames, introduce samples in a constant stream, while discrete atomizers inject individual samples using syringes or autosamplers. The most common discrete atomizer is the electrothermal atomizer.
330

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High-resolution Thermal Micro-imaging Using Europium Chelate Luminescent Coatings
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基于数据的模型的比较分析,用于空间分辨温度测量,使用辐射光谱学.

Ruiyuan Kang1, Dimitrios C Kyritsis2, Panos Liatsis3

  • 1Directed Energy Research Center, Technology Innovation Institute, Abu Dhabi, UAE.

PloS one
|January 24, 2025
PubMed
概括

这项研究引入了一种新的数据驱动方法,用于使用辐射光谱测量空间分辨率的温度测量. 功能工程与机器学习模型相结合,有效地测量非均的温度分布,即使在未知气体度的情况下也是如此.

科学领域:

  • 频谱学是一种光谱学.
  • 数据科学数据科学数据科学
  • 热力学是一种热力学.

背景情况:

  • 视线辐射光谱在测量非均场中的温度方面存在局限性.
  • 空间分辨率的温度测量对于理解复杂系统至关重要.

研究的目的:

  • 开发和评估数据驱动的模型,用于使用辐射光谱测量空间分辨率的温度测量.
  • 将特征工程与经典机器学习的性能与端到端卷积神经网络 (CNN) 的性能进行比较.

主要方法:

  • 研究了两种类型的数据驱动方法:使用经典机器学习和CNN的功能工程.
  • 评估了与15个经典机器学习模型相结合的15个特征组.
  • 评估了11个CNN模型用于温度分布测量.

主要成果:

  • 功能工程与机器学习相结合,超过了直接的CNN应用程序.
  • 物理引导的转换,信号表示和主要组件分析被证明是最有效的特征提取.
  • 使用提取特征的轻混合器组合模型实现了最佳性能 (RMSE: 64.3,RE: 0.017,RRMSE: 0.025,R: 0.994).

结论:

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  • 拟议的方法,利用特征工程和光混合器模型,准确地测量来自低分辨率光谱的不均温度分布.
  • 这种方法即使在物种度分布未知的情况下也有效,克服了传统光谱学的局限性.