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相关概念视频

Atomic Emission Spectroscopy: Interference01:30

Atomic Emission Spectroscopy: Interference

182
In atomic emission spectroscopy (AES), high-temperature atomizers excite a broad range of elements and molecules that generate complex emissions from sources such as oxides, hydroxides, and flame combustion products in the flame or plasma. Several strategies can be employed to minimize spectral interferences caused by overlapping emission lines or bands. These include increasing instrument resolution, choosing alternative emission lines, optimally placing the detector in low-background regions,...
182
Atomic Emission Spectroscopy: Lab01:29

Atomic Emission Spectroscopy: Lab

161
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...
161
Atomic Emission Spectroscopy: Overview01:20

Atomic Emission Spectroscopy: Overview

2.1K
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...
2.1K
Atomic Emission Spectroscopy: Instrumentation01:22

Atomic Emission Spectroscopy: Instrumentation

378
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.
378
Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

213
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....
213
Atomic Absorption Spectroscopy: Radiation and Light Sources01:13

Atomic Absorption Spectroscopy: Radiation and Light Sources

388
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...
388

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电子能量损失光谱的机器学习数据增强策略:生成对抗网络.

Daniel Del-Pozo-Bueno1,2, Demie Kepaptsoglou3,4, Quentin M Ramasse3,5

  • 1LENS-MIND, Departament d'Enginyeria Electrònica i Biomèdica, Universitat de Barcelona, 1-11 Martí i Franquès, 08028 Barcelona, Spain.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
|April 29, 2024
PubMed
概括

本研究引入了数据增强生成对抗网络 (DAG),以从有限的样本中创建现实的电子能量损失光谱 (EELS) 数据. 生成的数据有效地训练人工神经网络 (ANN) 和支持矢量机器 (SVM) 用于光谱分类.

关键词:
数据增强数据增强电子能量损失光谱学 电子能量损失光谱学生成性的对抗性网络.机器学习是机器学习.支持矢量机器支持矢量机器

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科学领域:

  • 材料科学 材料科学 材料科学
  • 数据科学数据科学数据科学
  • 频谱学是一种光谱学.

背景情况:

  • 监督机器学习 (ML) 需要大量高质量的数据来进行有效的算法训练.
  • 电子能量损失光谱 (EELS) 数据通常是有限的,这对ML模型开发构成了挑战.

研究的目的:

  • 开发一种新的数据增强 (DA) 策略,用于使用生成对抗网络 (GAN) 的EELS数据.
  • 为了使ML分类器能够训练具有有限EELS光谱数据的ML分类器.

主要方法:

  • 实施数据增强生成对抗网络 (DAG) 方法.
  • 探索最佳GAN配置以生成现实的EELS频谱.
  • 利用生成的光谱来训练人工神经网络 (ANN) 和支持矢量机器 (SVM).

主要成果:

  • DAG成功地从一个小数据集 (大约100个光谱) 中生成了现实的EELS光谱.
  • 在DAG生成的数据上训练的分类器在分类实验EEL光谱方面取得了成功.

结论:

  • 开发的DAG战略有效地解决了EELS的数据稀缺问题.
  • 生成的EELS光谱可用于为现实应用培训强大的ML分类器.