Time-Dependent Variability: A test-proven modelling approach for systems verification and power consumption minimization
Lead Research Organisation:
Liverpool John Moores University
Department Name: Engineering Tech and Maritime Operations
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Publications
Ji, Z.
(2014)
A new technique for probing the energy distribution of positive charges in gate dielectric
in 2014 Ieee International Conference on Microelectronic Test Structures (Icmts)
Zhang J
(2022)
Bias Temperature Instability of MOSFETs: Physical Processes, Models, and Prediction
in Electronics
Mehedi M
(2021)
On the Accuracy in Modeling the Statistical Distribution of Random Telegraph Noise Amplitude
in IEEE Access
Mehedi M
(2020)
An Assessment of the Statistical Distribution of Random Telegraph Noise Time Constants
in IEEE Access
Zhan X
(2019)
A Dual-Point Technique for the Entire I D -V G Characterization Into Subthreshold Region Under Random Telegraph Noise Condition
in IEEE Electron Device Letters
Manut A
(2016)
Impact of Hot Carrier Aging on Random Telegraph Noise and Within a Device Fluctuation
in IEEE Journal of the Electron Devices Society
Gao R
(2021)
A Comparative Study of AC Positive Bias Temperature Instability of Germanium nMOSFETs With GeO2/Ge and Si-cap/Ge Gate Stack
in IEEE Journal of the Electron Devices Society
Duan M
(2017)
Key Issues and Solutions for Characterizing Hot Carrier Aging of Nanometer Scale nMOSFETs
in IEEE Transactions on Electron Devices
Gao R
(2017)
NBTI-Generated Defects in Nanoscaled Devices: Fast Characterization Methodology and Modeling
in IEEE Transactions on Electron Devices
Gao R
(2017)
Reliable Time Exponents for Long Term Prediction of Negative Bias Temperature Instability by Extrapolation
in IEEE Transactions on Electron Devices
Description | 1. The relation between random telegraph noises (RTN) and NBTI aging has been clarified. It is shown that the increase of RTN by stresses reported in early works is an artefact. 2. A method has been proposed to predict the statistical variations of NBTI for nanometer sized devices. 3. The sources of errors have been identified for hot carrier modelling. 4. A robust kinetic model has been developed and test proven for hot carrier aging. 5. The different types of defects generated under hot carrier stresses have been identified. 6. The interaction between the hot carrier stress and PBTI stress have been clarified. 7. A new method has been developed for direct measurement of RTN-induced threshold voltage shift. |
Exploitation Route | The industrial partners of the project can use the models developed to simulate their circuits. The TCAD provider can use the model to extract industrial strength model for their simulators. |
Sectors | Digital/Communication/Information Technologies (including Software),Education,Electronics,Security and Diplomacy |
URL | https://www.ljmu.ac.uk/about-us/staff-profiles/faculty-of-engineering-and-technology/department-of-electronics-and-electrical-engineering/jian-zhang |
Description | 1. The method developed has been used to model the statistical variation of NBTI. 2. The kinetic model developed has been used to model the hot carrier aging and device lifetime. 3. The method developed for assessing the accuracy of extracted statistical properties has been used to select the number of devices under tests. 4. A prototype of True Random Number Generator has been developed using the generated RTN for IoT security. 5. The PI has been invited to deliver short courses based on the outputs of this project. |
First Year Of Impact | 2018 |
Sector | Digital/Communication/Information Technologies (including Software),Education,Electronics,Security and Diplomacy |
Impact Types | Economic |