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Published on: February 3, 2018
Non-Destructive 3D Elemental Characterization of Multilayer Materials by ANN-Assisted Ion Beam Analysis
Victoria Corregidor1,2, Nuno P Barradas1,2, Rui C da Silva1,3
1Departamento de Engenharia e Ciências Nucleares, Instituto Superior Técnico, Universidade de Lisboa, 2695-066 Bobadela, Portugal.
This study introduces a new AI framework for non-destructive 3D elemental mapping in complex materials. It reveals subsurface structures in advanced devices, overcoming limitations of surface-sensitive techniques.
Area of Science:
- Materials Science
- Analytical Chemistry
- Artificial Intelligence
Background:
- Advanced materials rely on complex 3D structures, but subsurface analysis is challenging.
- Current non-destructive techniques are often surface-limited, hindering characterization of buried interfaces.
Purpose of the Study:
- To develop a novel framework for non-destructive 3D elemental characterization of complex materials.
- To enable detailed analysis of subsurface compositional architectures in opaque systems.
Main Methods:
- Integration of artificial neural networks with ion beam analysis techniques: Particle-Induced X-ray Emission (PIXE) and Elastic Backscattering Spectrometry (EBS).
- Combining complementary spectral data with data-driven analysis for depth-resolved elemental mapping.
- Application to a Gallium Antimonide (GaSb) thermophotovoltaic device with multilayer metallic contacts.
Main Results:
- Successful reconstruction of 3D elemental distributions, including beneath thick gold layers in a GaSb device.
- Demonstrated enhanced sensitivity and reliable compositional feature classification using neural networks.
- Achieved full 3D visualization and quantitative/qualitative mapping by fusing PIXE and EBS data.
Conclusions:
- The AI-powered ion beam analysis framework offers a scalable strategy for 3D compositional analysis of diverse materials.
- This approach expands non-destructive characterization capabilities for energy, electronics, and functional materials.
- Highlights the synergy between advanced data-driven methods and ion beam techniques.
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