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Integrated circuits are vulnerable to particle radiation due to shrinking sizes. This study introduces a new method to accurately predict soft errors caused by charge sharing effects, improving circuit reliability.

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Area of Science:

  • Semiconductor technology
  • Integrated circuit reliability
  • Radiation effects in electronics

Background:

  • Modern semiconductor technology faces increased susceptibility to particle radiation due to reduced operating and threshold voltages.
  • Shrinking process sizes exacerbate charge sharing effects, making single event effects a primary cause of integrated circuit failures.
  • Effective sensitivity evaluation methods are crucial for optimizing integrated circuit design and enhancing irradiation reliability.

Purpose of the Study:

  • To develop an accurate method for evaluating the sensitivity of integrated circuits to particle radiation.
  • To address the growing challenge of soft errors caused by charge sharing effects in advanced semiconductor devices.
  • To improve the prediction and mitigation of single event effects in integrated circuits.

Main Methods:

  • Established a device model for charge sharing effects and performed simulations.
  • Developed a neural network model to predict charge amounts in primary and secondary devices.
  • Proposed and validated a comprehensive automated method for calculating soft errors in unit circuits using TCAD simulations.

Main Results:

  • The proposed automated method for soft error calculation achieved an error margin of 2.8-4.3% when validated against TCAD simulations.
  • The study successfully modeled charge sharing effects and predicted charge amounts using a neural network.
  • Demonstrated the accuracy and effectiveness of the developed soft error calculation method.

Conclusions:

  • The developed automated method provides an accurate and effective approach for calculating soft errors in integrated circuits.
  • The findings contribute to optimizing integrated circuit design and improving experimental methods for single event effects.
  • This research enhances the understanding and mitigation of radiation-induced failures in semiconductor devices.