Using 1/f noise to prevent the failure of nanoscale dielectric materials used in state-of-the-art chips

Dielectric breakdown phenomena are one of the main failure mechanisms responsible for the reliability degradation of state-of-the-art semiconductor devices. The routine method to study these failures is via Time-Dependent Dielectric Breakdown (TDDB). In TDDB, higher-stress experimental data is used to predict the behaviour of the dielectric at lower-stress conditions, using an extrapolation procedure. A limitation of this approach is the lack of physical insights. One can also question the validity of the extrapolation which, in many cases, cannot be justified.  
 
In this project, we explore an alternative method, based on 1/f noise, to obtain the same information as TDDB, in a faster and less destructive manner. The 1/f noise method examines the microscopic fluctuations arising in the dielectric leakage current. These fluctuations are due to crystallographic vacancies or ‘traps’, which continually and randomly modulate the precise value of the current flowing through the dielectric. These fluctuations are expected to contain valuable information on the physics of dielectric breakdown. This alternative 1/f noise approach can then be used to complement TDDB, in order to acquire a fundamental understanding of the dielectric’s behaviour at both higher- and lower-stress conditions.  

What will you do? 

• Perform noise-stress-noise measurements, where first 1/f noise is measured on a pristine sample, after which it is degraded with a constant voltage stress, and then measured again with 1/f noise, etc.
• Consider different experimental conditions (e.g. voltage, area, temperature, etc.)
• Develop a physical model, based on 1/f noise, to relate the lower-stress data to the higher-stress data, and calibrate the model with the corresponding TDDB data

Who are you?

• You have a basic knowledge of semiconductor materials physics
• You have a science or engineering background with basic programming skills
• You are interested in experimental work, in state-of-the-art facilities at imec

References

1. N. Saini et al., IEEE IITC/MAM (2023). https://doi.org/10.1109/IITC/MAM57687.2023.10154814
2. H. Choi et al. IEEE EDL (2009). https://doi.org/10.1109/LED.2009.2015586
3. R. Degraeve et al., IEEE TED (1998). https://doi.org/10.1063/1.2147714
4. https://en.wikipedia.org/wiki/Pink_noise
5. K. Croes et al., ECS JSSST (2014). http://dx.doi.org/10.1149/2.0101501jss 

Type of work: 50 % experimental, 30 % data analysis, 20 % interpretation

Language requirements:  English 

Type of Project: Internship 

Bachelor's program/required background: Physics, Electrical Engineering, Nanotechnology, Materials Science, Materials Engineering 

For more information or application, please contact Davide Tierno (davide.tierno@imec.be) and Nishant Saini (nishant.saini@imec.be)