Simulation of femtosecond pulsed laser effects on MOS electronics using TCAD Sentaurus customized models

Palomo, F.R.; Fernández-Martínez, P.; Mogollon, J.M.; Hidalgo, S.; Aguirre, M.A.; Flores, D.; Lopez-Calle, I.; Agapito, Juan

doi:10.1002/jnm.736

Cited by 5 publications

(3 citation statements)

References 38 publications

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“…The eph generation due to the photon absorptions within de depleted p d -layer is a transient mechanism which could be simulated by using the heavy ions models included in Sentaurus TCAD tools [3]. However, the excessive number of device parameters taken into account for the design optimization demands an elevated number of simulations.…”

Section: Gain Prediction Methodologymentioning

confidence: 99%

Gain estimation of RT-APD devices by means of TCAD numerical simulations

Cortés

Fernández-Martínez

Flores

et al. 2011

Proceedings of the 8th Spanish Conference on Electron Devices, CDE'2011

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The design of Reach-Through Avalanche Photodiodes (RT-APD) for medium energy X-ray detection requires a previous optimization to guarantee elevated gain at the required operation conditions. A simple methodology to estimate the gain in RT-APD devices by using TCAD numerical simulations is proposed in this work. This technique offers the possibility to predict the gain in RT-APDs as a function of the most relevant design considerations.

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Section: Gain Prediction Methodologymentioning

confidence: 99%

Gain estimation of RT-APD devices by means of TCAD numerical simulations

Cortés

Fernández-Martínez

Flores

et al. 2011

Proceedings of the 8th Spanish Conference on Electron Devices, CDE'2011

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“…They are listed as [2][3][4][5][6][7][8][9][10][11][12]. Particular attention was paid for showing the most representative contributions of each conference topic.…”

Section: Photovoltaic Optoelectronic Devices and Displays (21 Contrimentioning

confidence: 99%

Special Issue: 7th Spanish Conference on Electron Devices (CDE2009)

García‐Loureiro

Millán

2010

Int J Numerical Modelling

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The CDE conference has become the main national forum for discussions on the current trends and future directions in the field of electronic devices. Most of the contributions presented in this conference came from Spanish universities and research centres, about 22% of the presentations were collaborations between Spanish and overseas institutions and 11% of the communications presented in the conference come from researchers of foreign universities. Finally, about 4% of the contributions were developed in the following Spanish companies: T-SOLAR S.A., Francisco Alberto S.A., Robotiker-Tecnalia and ISOFOTON S.A. Fifty participants in the conference, out of 150, were PhD students, provided with the opportunity of enhancing their knowledge and experience and establishing new links through interaction with other students and experts in their research field.The scientific program of the conference was organized in a single-session format and comprised 5 invited lectures, 40 contributed talks and 102 poster presentations. The program covers the following topics:1. Materials, technology and process simulation (25 contributions). 2. Device modelling and simulation (40 contributions). 3. Characterization and reliability (11 contributions). 4. Sensors, actuators, microsystems and MEMS (26 contributions).

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“…Technology computer-aided design (TCAD), which integrates process, device, and circuit simulators, has become indispensable for semiconductor device manufacturing. [1][2][3][4][5] TCAD is used to predict semiconductor device performance under given structural and process parameters and to optimize manufacturing DOI: 10.1002/adts.202300218 conditions. As semiconductor device sizes have become smaller in recent years, the number of process steps has increased, making TCAD more time-consuming.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning for Semiconductor Process Simulation Described by Coupled Partial Differential Equations

Sato

Kutsukake

Harada

et al. 2023

Advcd Theory and Sims

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Technology computer‐aided design (TCAD) simulation is an important tool for the development of semiconductor devices. Based on coupled partial differential equations (PDEs) for behaviors, TCAD can calculate objects such as impurities, point defects, and electronic carriers in semiconductors. However, over recent years semiconductor devices have become increasingly miniaturized and complicated, resulting in much longer calculation times for TCAD. Machine learning is one technology that may be used to overcome this simulation cost problem. In this study, a neural network architecture is proposed that considers the structure of the coupled PDEs. Features representing each concentration distribution of the calculation objects are extracted by convolution operations and their reaction is modeled by channel attention. The performance of the proposed architecture and of conventional neural network models is evaluated using a simulation dataset generated by 1D coupled PDEs that models the diffusion and reaction of vacancies and interstitial atoms. In addition, the advantage of the method is discussed through the analyses of error correlations of the two predictions and attention coefficients. The machine learning method developed in this study will be applicable to other physics described by coupled PDEs and is expected to speed up the computation of simulations in various fields.

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Simulation of femtosecond pulsed laser effects on MOS electronics using TCAD Sentaurus customized models

Cited by 5 publications

References 38 publications

Gain estimation of RT-APD devices by means of TCAD numerical simulations

Gain estimation of RT-APD devices by means of TCAD numerical simulations

Special Issue: 7th Spanish Conference on Electron Devices (CDE2009)

Machine Learning for Semiconductor Process Simulation Described by Coupled Partial Differential Equations

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