Article
Statistical characterization of time-dependent variability defects using the maximum current fluctuation
Author/s | Saraza Canflanca, Pablo
Martín Martínez, J. Castro-López, Rubén Roca, E. Rodríguez, R. Fernández Fernández, Francisco Vidal Nafria, Montserrat |
Department | Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo |
Publication Date | 2021-06-17 |
Deposit Date | 2024-09-10 |
Published in |
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Abstract | This article presents a new methodology to extract, at a given operation condition, the statistical distribution of the number of active defects that contribute to the observed device time-dependent variability, as well ... This article presents a new methodology to extract, at a given operation condition, the statistical distribution of the number of active defects that contribute to the observed device time-dependent variability, as well as their amplitude distribution. Unlike traditional approaches based on complex and time-consuming individual analysis of thousands of current traces, the proposed approach uses a simpler trace processing, since only the maximum and minimum values of the drain current during a given time interval are needed. Moreover, this extraction method can also estimate defects causing small current shifts, which can be very complex to identify by traditional means. Experimental data in a wide range of gate voltages, from near-threshold up to nominal operation conditions, are analyzed with the proposed methodology. |
Funding agencies | Agencia Estatal de Investigación. España |
Project ID. | PID2019-103869RB
TEC2016-75151-C3-R |
Citation | Saraza Canflanca, P., Martín Martínez, J., Castro-López, R., Roca, E., Rodríguez, R., Fernández Fernández, F.V. y Nafria, M. (2021). Statistical characterization of time-dependent variability defects using the maximum current fluctuation. IEEE Transactions on Electron Devices, 68 (8), 4039-4044. https://doi.org/10.1109/TED.2021.3086448. |
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