Spatial and Compositional Biases Introduced by Position Sensitive Detection Systems in APT: A Simulation Approach.

Area of Science:

• Materials Science
• Analytical Chemistry
• Computational Modeling

Background:

• Contemporary position-sensitive detectors in atom probe tomography (APT) have limited capacity for multiple event detection.
• This limitation leads to significant compositional biases in material analyses with high numbers of multiple events, particularly in complex materials.
• Existing statistical correction algorithms are insufficient for heterogeneous materials with varying elemental evaporation fields.

Purpose of the Study:

• To systematically investigate the impact of the APT detection system on material analysis.
• To develop a simulation tool for predicting compositional and spatial biases.
• To enhance the understanding of signal loss mechanisms in APT experiments for complex materials.

Main Methods:

• Modeling the evaporation mechanism of materials during APT experiments.
• Simulating the entire APT detection system.
• Developing a computational tool to predict detection system-induced biases.

Main Results:

• The simulation tool allows for the prediction of compositional and spatial biases.
• Identified the critical role of detector limitations in material analysis accuracy.
• Provided insights into signal loss mechanisms specific to complex material systems.

Conclusions:

• A deeper understanding of the APT detection system is crucial for accurate analysis of complex materials.
• The developed simulation tool offers a method to mitigate compositional biases.
• This work paves the way for more reliable material characterization using APT.