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Related Concept Videos

Atomic Emission Spectroscopy: Lab01:29

Atomic Emission Spectroscopy: Lab

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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...
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Inductively Coupled Plasma Atomic Emission Spectroscopy: Principle01:19

Inductively Coupled Plasma Atomic Emission Spectroscopy: Principle

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Inductively coupled plasma (ICP) is the most widely used plasma source in atomic emission spectroscopy (AES), also known as Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). The ICP source, or torch, consists of three concentric quartz tubes with argon gas flowing through them. A spark from a Tesla coil initiates the ionization of argon, generating a high-temperature plasma.
The ions and electrons produced interact with the fluctuating magnetic field created by a water-cooled...
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Inductively Coupled Plasma-Mass Spectrometry (ICP-MS): Interferences01:20

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS): Interferences

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Inductively coupled plasma–mass spectrometry (ICP–MS) is a highly selective and sensitive technique for accurate elemental analysis. Though the analysis of ICP–MS mass spectra is comparatively straightforward, it is affected by spectroscopic and non-spectroscopic interferences. Spectroscopic interferences arise when the plasma contains ionic species with an m/z value the same as the analyte ion. Spectroscopic interference can be categorized as isobaric, polyatomic ions, and...
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Inductively Coupled Plasma–Mass Spectrometry (ICP–MS): Overview01:19

Inductively Coupled Plasma–Mass Spectrometry (ICP–MS): Overview

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In inductively coupled plasma–mass spectrometry (ICP–MS), an inductively coupled plasma (ICP) torch is used as an atomizer and ionizer. Solid samples are dissolved and volatilized before being introduced into the high-temperature argon plasma, while solution samples are nebulized and passed through the high-temperature argon plasma. Plasma dissociates the analytes and ionizes their component atoms to form a mixture of positive ions and molecular species. The positive ions are then...
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Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

296
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....
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Atomic Emission Spectroscopy: Instrumentation01:22

Atomic Emission Spectroscopy: Instrumentation

594
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.
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Principal component-generalized spectrum-machine learning approach for quantifying gallium in a surrogate plutonium

Ashwin P Rao, Anil K Patnaik

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    This study introduces a novel data science method for precise nuclear material analysis. The principal component-generalized spectrum-machine learning (PC-GS-ML) approach significantly enhances the quantification of gallium in cerium matrices.

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    Area of Science:

    • Analytical Chemistry
    • Data Science
    • Nuclear Materials Analysis

    Background:

    • Atomic emission spectra of complex materials like nuclear materials are often convoluted.
    • Accurate chemical analysis requires advanced methods to interpret spectral features.
    • Existing techniques may lack the precision and sensitivity for certain quantitative analyses.

    Purpose of the Study:

    • To develop and implement an advanced spectral analysis method for precise quantitative analysis of nuclear materials.
    • To enable the accurate quantification of gallium (Ga) within cerium (Ce) matrices.
    • To improve upon existing methods in terms of precision and sensitivity.

    Main Methods:

    • Implementation of spectral analysis combining principal component analysis (PCA) with supervised machine learning (ML) regressions.
    • Development of the principal component-generalized spectrum-machine learning (PC-GS-ML) approach.
    • Application of PC-GS-ML to laser-induced breakdown spectroscopy (LIBS) data for Ga quantification in Ce matrices.

    Main Results:

    • The PC-GS-ML approach demonstrated superior model accuracy compared to traditional spectral features or PCA-reduced features alone.
    • Prediction errors as low as 0.08 wt% Ga were achieved.
    • An order of magnitude improvement in Ga quantification error was observed compared to previous studies.

    Conclusions:

    • The PC-GS-ML method offers a significant advancement in the quantitative analysis of nuclear materials.
    • This approach provides superior precision and sensitivity for determining gallium concentrations in cerium matrices.
    • The findings highlight the potential of integrating data science with atomic spectroscopy for complex material characterization.