Scanning acoustic microscopy for material evaluation.
Jong-Young KwakPublished in: Applied microscopy (2020)
Scanning acoustic microscopy (SAM) or Acoustic Micro Imaging (AMI) is a powerful, non-destructive technique that can detect hidden defects in elastic and biological samples as well as non-transparent hard materials. By monitoring the internal features of a sample in three-dimensional integration, this technique can efficiently find physical defects such as cracks, voids, and delamination with high sensitivity. In recent years, advanced techniques such as ultrasound impedance microscopy, ultrasound speed microscopy, and scanning acoustic gigahertz microscopy have been developed for applications in industries and in the medical field to provide additional information on the internal stress, viscoelastic, and anisotropic, or nonlinear properties. X-ray, magnetic resonance, and infrared techniques are the other competitive and widely used methods. However, they have their own advantages and limitations owing to their inherent properties such as different light sources and sensors.This paper provides an overview of the principle of SAM and presents a few results to demonstrate the applications of modern acoustic imaging technology. A variety of inspection modes, such as vertical, horizontal, and diagonal cross-sections have been presented by employing the focus pathway and image reconstruction algorithm. Images have been reconstructed from the reflected echoes resulting from the change in the acoustic impedance at the interface of the material layers or defects. The results described in this paper indicate that the novel acoustic technology can expand the scope of SAM as a versatile diagnostic tool requiring less time and having a high efficiency.
Keyphrases
- high resolution
- single molecule
- magnetic resonance
- high speed
- optical coherence tomography
- deep learning
- high throughput
- mass spectrometry
- magnetic resonance imaging
- high efficiency
- label free
- healthcare
- acute myocardial infarction
- electron microscopy
- heart failure
- computed tomography
- atomic force microscopy
- acute coronary syndrome
- convolutional neural network
- neural network
- atrial fibrillation
- heat stress
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- dual energy