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Atomic Emission Spectroscopy: Overview01:20

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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...
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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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Scanning Electron Microscopy01:07

Scanning Electron Microscopy

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A scanning electron microscope (SEM) is used to study the surface features of a sample by using an electron beam that scans the sample surface in a two-dimensional manner. Typically, areas between ~1 centimeter to 5 micrometers in width can be imaged. SEM can be used to image bacteria, viruses, tissues as well as larger samples like insects. Conventional SEM gives a magnification ranging from 20X to 30,000X and spatial resolution of 50 to 100 nanometers.
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Optimal experiment design for element specific atom counting using multiple annular dark field scanning transmission

D G Sentürk1, A De Backer1, T Friedrich1

  • 1Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium; NANOlab Center of Excellence, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium.

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Summary

This study optimizes atom counting in scanning transmission electron microscopy (STEM) by using statistical detection theory. Combining specific annular dark-field (ADF) detector regimes minimizes errors when identifying multiple atom types in atomic columns.

Keywords:
4D STEMAtom-countingAtomic resolution scanning transmission electron microscopyHeterogeneous nanostructuresOptimal experiment design

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Area of Science:

  • Materials Science
  • Physics
  • Chemistry

Background:

  • Accurate elemental identification in atomic columns is crucial for nanomaterial characterization.
  • Scanning Transmission Electron Microscopy (STEM) with Annular Dark-Field (ADF) detectors is a powerful tool for atomic resolution imaging.
  • Distinguishing between different atom types within the same atomic column presents a significant analytical challenge.

Purpose of the Study:

  • To investigate the benefits of using multiple 2D ADF detector regimes in STEM for improved atom counting of different chemical species.
  • To quantify the probability of error in determining the number of atoms of various types within atomic columns.
  • To establish optimal experimental designs for atom counting by minimizing error probabilities.

Main Methods:

  • Application of statistical detection theory to formulate atom-counting as a hypothesis test.
  • Quantification of error probability considering electron counting noise and scattering cross-sections.
  • Simulation of core-shell nanoparticles (Au@Ag, Au@Pt) to evaluate detector regime combinations.
  • Comparison with pixelated 4D STEM detector performance.

Main Results:

  • The combination of a narrow low-angle ADF detector with a wider annular detector regime is found to be optimal for distinguishing two atom types.
  • The effectiveness of this optimal configuration increases with a larger difference in atomic numbers (Z) between elements.
  • Subdividing detector regimes into three areas further improves accuracy for heterogeneous nanostructures with three or more atom types.
  • The proposed method shows potential for reducing incident electron dose compared to pixelated 4D STEM detectors.

Conclusions:

  • Optimizing ADF detector configurations significantly enhances the accuracy of multi-element atom counting in STEM.
  • Statistical detection theory provides a robust framework for designing optimal imaging strategies in electron microscopy.
  • These findings offer a pathway to more precise characterization of complex nanomaterials and heterogeneous nanostructures.