An Analytical Model of Single-Event Transients in Double-Gate MOSFET for Circuit Simulation

Aneesh, Y. M.; Sriram, S.; Pasupathy, K. R.; Bindu, B.

doi:10.1109/ted.2019.2926883

Cited by 20 publications

(6 citation statements)

References 25 publications

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“…It features a steep rising edge and a gentle falling edge (as shown in Figure 5). The single-event current source model used in this paper is the double-exponential current source model [19], which can accurately simulate the bombardment of sensitive nodes in circuits by high-energy particles, making it suitable for circuit-level simulation methods [20]. Many outstanding works in the field of single-particle research are based on this model.…”

Section: Establishment Of the Single-event Transient Pulse Source Modelmentioning

confidence: 99%

A Method for Automatically Predicting the Radiation-Induced Vulnerability of Unit Integrated Circuits

Dong,

Lu,

Yang

et al. 2024

Micromachines

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With the rapid development of semiconductor technology, the reduction in device operating voltage and threshold voltage has made integrated circuits more susceptible to the effects of particle radiation. Moreover, as process sizes decrease, the impact of charge sharing effects becomes increasingly severe, with soft errors caused by single event effects becoming one of the main causes of circuit failures. Therefore, the study of sensitivity evaluation methods for integrated circuits is of great significance for promoting the optimization of integrated circuit design, improving single event effect experimental methods, and enhancing the irradiation reliability of integrated circuits. In this paper, we first established a device model for the charge sharing effect and simulated it under reasonable conditions. Based on the simulation results, we then built a neural network model to predict the charge amounts in primary and secondary devices. We also propose a comprehensive automated method for calculating soft errors in unit circuits and validated it through TCAD simulations, achieving an error margin of 2.8–4.3%. This demonstrated the accuracy and effectiveness of the method we propose.

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Section: Establishment Of the Single-event Transient Pulse Source Modelmentioning

confidence: 99%

A Method for Automatically Predicting the Radiation-Induced Vulnerability of Unit Integrated Circuits

Dong,

Lu,

Yang

et al. 2024

Micromachines

View full text Add to dashboard Cite

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“…The SPICE-level evaluation approach is widely used. Based on the SPICE device model and the netlist of the evaluated circuit, a separate current source is introduced directly at the sensitive node of the circuit to simulate the transient current caused by incident particles [23][24][25]. Then, it simulates the corresponding circuit response to obtain soft errors.…”

Section: Ser Evaluation Overviewmentioning

confidence: 99%

Machine Learning-Based Soft-Error-Rate Evaluation for Large-Scale Integrated Circuits

Song,

Shao,

Chi

et al. 2023

Electronics

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Transient pulses generated by high-energy particles can cause soft errors in circuits, resulting in spacecraft malfunctions and posing serious threats to the normal operation of spacecraft. For integrated circuits used in space applications, it is necessary to first evaluate soft errors caused by transient pulses. Conventional soft-error-rate evaluation tools are designed to simulate the generation of transient pulses using many accurate models, while the propagation of transient pulses is primarily simulated by circuit-level simulation tools. Due to the limitations of simulation tools, conventional evaluation approaches are limited to the circuit scale. The simulation runtime is unbearable for large-scale integrated circuits. This paper presents an approach for evaluating the soft error rate using machine learning. A back propagation neural network is implemented in the proposed approach. It helps to determine the probability of transient pulse propagation. Compared with the conventional soft-error-rate evaluation results, the proposed approach demonstrates a strong correlation in both trend and magnitude. The average difference between the results obtained using the proposed evaluation method and the experimental results is 23.5%, which is 7.5% higher than that between the results obtained using the conventional evaluation method and the experimental results. Compared to the conventional evaluation method, the proposed approach improves the runtime by an order of magnitude. The proposed approach also benefits the locating of highly sensitive circuit nodes in large-scale integrated circuits. Circuit design and radiation hardening are both useful applications.

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“…Another method is to model SETs by solving basic physics equations like Poisson's equation and the continuity equation [9][10][11][12]. In 2018, Malherbe et al presented a new model of SETs for full-depleted silicon-on-insulator (FDSOI) technology based on direct resolution of the drift-diffusion equations on a 1D grid [10].…”

Section: Introductionmentioning

confidence: 99%

“…In 2018, Malherbe et al presented a new model of SETs for full-depleted silicon-on-insulator (FDSOI) technology based on direct resolution of the drift-diffusion equations on a 1D grid [10]. In 2019, Aneesh et al proposed a physics-based SET model by solving the 2D Poisson's equation in DG (double-gate) MOSFETs [11]. Models like these have a relatively high accuracy and the ability to consider multiple influencing factors in actual applications.…”

Section: Introductionmentioning

confidence: 99%

An Improved Model of Single-Event Transients Based on Effective Space Charge for Metal–Oxide–Semiconductor Field-Effect Transistor

Zhang,

Lu,

Liu

et al. 2023

Micromachines

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In this paper, a single-event transient model based on the effective space charge for MOSFETs is proposed. The physical process of deposited and moving charges is analyzed in detail. The influence of deposited charges on the electric field in the depletion region is investigated. The electric field decreases in a short time period due to the neutralization of the space charge. After that, the electric field increases first and then decreases when the deposited charge is moved out. The movement of the deposited charge in the body mainly occurs through ambipolar diffusion because of its high-density electrons and holes. The derivation of the variation in electric field in the depletion region is modeled in the physical process according to the analysis. In combination with the ambipolar diffusion model of excessive charge in the body, a physics-based model is built to describe the current pulse in the drain terminal. The proposed model takes into account the influence of multiple factors, like linear-energy transfer (LET), drain bias, and the doping concentration of the well. The model results are validated with the simulation results from TCAD. Through calculation, the root-mean-square error (RMSE) between the simulation and model is less than 3.7 × 10−4, which means that the model matches well with the TCAD results. Moreover, a CMOS inverter is simulated using TCAD and SPICE to validate the applicability of the proposed model in a circuit-level simulation. The proposed model captures the variation in net voltage in the inverter. The simulation result obviously shows the current plateau effect, while the relative error of the pulse width is 23.5%, much better than that in the classic model. In comparison with the classic model, the proposed model provides an RMSE of 7.59 × 10−5 for the output current curve and an RMSE of 0.158 for the output voltage curve, which are significantly better than those of the classic model. In the meantime, the proposed model does not produce extra simulation time compared with the classic double exponential model. So, the model has potential for application to flow estimation of the soft error rate (SER) at the circuit level to improve the accuracy of the results.

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An Analytical Model of Single-Event Transients in Double-Gate MOSFET for Circuit Simulation

Cited by 20 publications

References 25 publications

A Method for Automatically Predicting the Radiation-Induced Vulnerability of Unit Integrated Circuits

A Method for Automatically Predicting the Radiation-Induced Vulnerability of Unit Integrated Circuits

Machine Learning-Based Soft-Error-Rate Evaluation for Large-Scale Integrated Circuits

An Improved Model of Single-Event Transients Based on Effective Space Charge for Metal–Oxide–Semiconductor Field-Effect Transistor

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