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June 4, 2026Applied Sciences0 citationsOpen Access

Multi-Dimensional Charge Diffusion–Collection Model in Semiconductor Devices Subjected to Single Ionizing Particles

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AAAlexandre AutranDMDaniela MunteanuJAJean-Luc Autran

Key Points

  • The research aims to develop a comprehensive model for charge collection in semiconductors when exposed to ionizing particles.
  • Proposed a unified model of charge collection in one, two, and three dimensions.
  • Derived expressions for carrier density, diffusion current, and collected charge using diffusion equations.
  • Provided a Python implementation to facilitate practical applications of the model.
  • The collected current peaks before the carrier density for all dimensions.
  • Established analytical expressions for collection efficiency and recombination factor.
  • Outlined procedures for simulating single events and correlating with soft error rates.

Abstract

Analytical modeling of charge collection is essential for predicting single-event effects in integrated circuits subjected to radiation. This work proposes a unified model of charge collection by diffusion in semiconductors in one, two, and three dimensions, accounting for recombination effects. We derive exact expressions for the carrier density, diffusion current, and collected charge using the solution of the diffusion equation for a point source. We formulate the collected charge using Bessel functions, which allow for a more general and fully analytical description of the problem. The model emphasizes the role of geometry by explicitly accounting for the dimensionality of the problem. It also establishes that, for any dimension, the collected current peaks before the carrier density does. We also propose analytical expressions for the collection efficiency and the recombination factor, with simplified forms in the absence of recombination. A minimal Python implementation is provided to facilitate the practical application of the model. Finally, we outline how to use the proposed model to perform realistic simulations of single events and relate the results to the soft error rate of a given device.

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Cite This Study

Autran et al. (2026) studied this question.

synapsesocial.com/papers/6a211852d499ed480b170f22https://doi.org/10.3390/app16115551
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