L
Laurent Artola
Researcher at University of Toulouse
Publications - 64
Citations - 1159
Laurent Artola is an academic researcher from University of Toulouse. The author has contributed to research in topics: Single event upset & Soft error. The author has an hindex of 15, co-authored 62 publications receiving 1033 citations.
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Estimation of analog/RF figures-of-merit using device design engineering in gate stack double gate MOSFET
TL;DR: In this article, the analog performance as well as some new RF figures of merit are reported for the first time of a gate stack double gate (GS-DG) metal oxide semiconductor field effect transistor (MOSFET) with various gates and channel engineering.
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Impact of scaling on the soft error sensitivity of bulk, FDSOI and FinFET technologies due to atmospheric radiation
TL;DR: The results suggest muon-induced upset affects the soft error rate from 32-nm SRAM operated at a nominal supply voltage and has a significant impact for circuits fabricated in smaller process technologies (22-nm and 14-nm).
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Impact of the Radial Ionization Profile on SEE Prediction for SOI Transistors and SRAMs Beyond the 32-nm Technological Node
Melanie Raine,Guillaume Hubert,Marc Gaillardin,Laurent Artola,P. Paillet,Sylvain Girard,J-E Sauvestre,Arnaud Bournel +7 more
TL;DR: In this paper, the relative contribution of the radial ionization profile on SEE prediction is investigated using MUSCA-SEP3, in comparison with the classical approach considering the ion track as a series of punctual charges.
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Single-Event Transient Modeling in a 65-nm Bulk CMOS Technology Based on Multi-Physical Approach and Electrical Simulations
Guillaume Hubert,Laurent Artola +1 more
TL;DR: In this article, a SET predictive methodology based on coupled MUSCA SEP3 and electrical simulations (CADENCE tool) is presented, validated by SET measurements on an inverters chain based on 65-nm bulk CMOS technology, and two designs were considered (respectively for same-well and separatewell designs).
Journal ArticleDOI
SEU Prediction From SET Modeling Using Multi-Node Collection in Bulk Transistors and SRAMs Down to the 65 nm Technology Node
Laurent Artola,Guillaume Hubert,Kevin M. Warren,Marc Gaillardin,Ronald D. Schrimpf,Robert A. Reed,Robert A. Weller,J. R. Ahlbin,P. Paillet,Melanie Raine,Sylvain Girard,Sophie Duzellier,Lloyd W. Massengill,Francoise Bezerra +13 more
TL;DR: In this article, a new methodology of prediction for SEU based on SET modeling is proposed based on the ADDICT model for predicting single event transients and upsets in bulk transistors and SRAMs down to 65 nm.