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July 31, 2026Scilight

Framework automates pit detection in CR-39 detectors for laser-driven ion research

Adam Liebendorfer

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Key Points

The study aims to develop an automated framework for detecting pits in CR-39 detectors to enhance efficiency in laser-driven ion research.
Combines pit shape data with Monte Carlo modeling.
Develops an algorithm to automate pit detection.
Uses optical micrographs for data visualization.
The automated method significantly reduces the time required for pit characterization.
The algorithm is fast and reliable, improving accuracy compared to manual methods.

Implication

Demonstrates efficient pit detection using an automated framework, indicating improved accuracy.

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Cite This Study

Adam Liebendorfer (2026) studied this question.

synapsesocial.com/papers/6a6eeb4d1b0468a7eeab4551 https://doi.org/10.1063/10.0044551

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