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Related Concept Videos

Mass Analyzers: Overview01:13

Mass Analyzers: Overview

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The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
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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.
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This lesson details the instrumentation of a mass spectrometer—a physical instrument to perform mass spectrometry on analyte molecules and record the characteristic mass spectra. This is achieved via three chief functions:
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Interference leads to systematic error in atomic absorption (AA) measurements by enhancing or diminishing the analytical signal or the background. These interferences can be grouped into three main categories: spectral interference, chemical interference, and physical interference.
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Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
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Automated spectrometer alignment via machine learning.

Peter Feuer-Forson1, Gregor Hartmann1, Rolf Mitzner1

  • 1Helmholtz-Zentrum Berlin für Materialien und Energie GmbH, Albert-Einstein-Strasse 15, 12489 Berlin, Germany.

Journal of Synchrotron Radiation
|June 20, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method using optimisers and neural networks to automate spectrometer alignment. The technique significantly reduces alignment time from one hour to five minutes, applicable to various research instruments.

Keywords:
X-ray diffractioninstrumentationmachine learningreflection zone plate

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Area of Science:

  • Instrumentation and Measurement
  • Computational Physics
  • X-ray Optics

Background:

  • Instrument alignment is a critical yet time-consuming process in experimental research.
  • Automated alignment solutions are often lacking, despite component motorization.
  • Mobile soft X-ray spectrometers require frequent optimization during experiments.

Purpose of the Study:

  • To develop a novel, automated alignment method for mobile soft X-ray spectrometers.
  • To significantly reduce the time and effort required for instrument optimization.
  • To create a generalizable approach applicable to various beamline optical elements.

Main Methods:

  • Utilized optimisers combined with neural network surrogate models.
  • Trained neural networks exclusively on simulated ray-tracing data.
  • Determined simulation-experiment disparity via parameter optimization and real-time validation.

Main Results:

  • Reduced instrument alignment time from approximately one hour to about five minutes.
  • Demonstrated successful real-time validation using experimental beamline data.
  • Validated the effectiveness of the neural network surrogate model approach.

Conclusions:

  • The proposed method offers a substantial reduction in alignment overhead.
  • This approach is generalizable to other optical element alignments at research facilities.
  • Automation of alignment processes can significantly enhance research efficiency.