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Bode Plots Construction01:24

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The Bode plot is an essential tool in control system analysis, mapping the frequency response of a system through a magnitude plot and a phase plot, both against a logarithmic frequency axis. To construct a Bode plot, consider the transfer function H(ω):
958

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Imaging Conductivity Changes in Monolayer Graphene Using Electrical Impedance Tomography.

Anil Kumar Khambampati1, Sheik Abdur Rahman1, Sunam Kumar Sharma1

  • 1Department of Electronic Engineering, Jeju National University, Jeju 63243, Korea.

Micromachines
|December 4, 2020
PubMed
Summary
This summary is machine-generated.

A new difference imaging approach using electrical impedance tomography (EIT) effectively detects defects in graphene films. This method accurately maps conductivity changes, overcoming modeling errors for quality assessment in electronic applications.

Keywords:
difference imagingelectrical conductivityelectrical impedance tomographygrapheneinverse problem

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Area of Science:

  • Materials Science and Engineering
  • Electrical Engineering
  • Non-destructive Testing

Background:

  • Graphene's unique electronic properties drive interest in novel electronic devices.
  • Large-scale synthesis of monolayer graphene, often via chemical vapor deposition (CVD), is crucial for applications.
  • Defects like wrinkles and cracks in CVD graphene degrade electrical performance, necessitating non-destructive quality assessment.

Purpose of the Study:

  • To develop a non-destructive method for detecting defects in graphene films.
  • To address challenges in electrical impedance tomography (EIT) reconstruction caused by modeling errors.
  • To estimate conductivity changes in graphene to identify defects introduced during synthesis or handling.

Main Methods:

  • Utilized electrical impedance tomography (EIT) for non-destructive conductivity mapping.
  • Proposed a difference imaging approach to estimate conductivity changes relative to a reference state.
  • Validated the method through numerical simulations and experimental tests on a 2.5 × 2.5 cm graphene sample.

Main Results:

  • The difference imaging approach successfully estimated conductivity distribution changes in graphene.
  • The proposed method demonstrated robustness against common EIT modeling errors (e.g., electrode location, contact resistance).
  • Accurate defect localization on the graphene surface was achieved by analyzing conductivity variations.

Conclusions:

  • The difference imaging EIT method provides an accurate and non-destructive way to assess graphene quality.
  • This technique is valuable for identifying defects in large-scale graphene films used in electronics.
  • The approach effectively mitigates modeling uncertainties inherent in traditional EIT inverse problems.