A novel method for extracting the two-dimensional doping profile of a sub-half micron MOSFET

Khalil, N.; Faricelli, J.; Bell, David A.; Selberherr, S.

doi:10.1109/vlsit.1994.324422

Cited by 11 publications

(8 citation statements)

References 1 publication

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“…Examples of the combined use of electrical simulations and C-V measurements to assess the doping profile of certain semiconductor devices have already been presented in literature. For example, Khalil et al 1,2 have successfully applied the technique to determine the two-dimensional doping profile of a submicron MOSFET. However, the implementation of an inverse modeling is strictly related to the type of device and to its structure.…”

Section: Electrical Simulation Yesmentioning

confidence: 99%

Inverse doping profile extraction as an enabling tool for accurate SPAD modeling

Bonzi,

Laita,

Rech

et al. 2023

Advanced Photon Counting Techniques XVII

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Physical models are key tools for developing new SPADs structures. However, as most SPADs characteristics strongly depends on the electric field, a precise knowledge of the doping profile is required. Unfortunately, common profiling techniques are not accurate enough. To cope with this problem, we developed an inverse approach which resorts to the combined use of electrical simulations and capacitance-voltage measurements. We applied the technique to multiple SPADs and we used the extracted profile to calculate their breakdown voltages. Simulated results closely matching the experimental outcomes provide us a strong validation of the proposed extraction technique.

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Section: Electrical Simulation Yesmentioning

confidence: 99%

Inverse doping profile extraction as an enabling tool for accurate SPAD modeling

Bonzi,

Laita,

Rech

et al. 2023

Advanced Photon Counting Techniques XVII

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show abstract

“…The combined use of electrical simulations and C-V measurements to obtain the doping profile of a certain semiconductor device is not new in literature. [1][2][3][4][5] However, different implementations are required by the inverse modeling depending on the type of device and on its structure and, to the best of our knowledge, this is the first time such an approach is applied to SPAD modeling.…”

Section: Inverse Modelingmentioning

confidence: 99%

Accurate doping profile extraction for predictive SPAD design

Bonzi,

Laita,

Rech

et al. 2023

Emerging Imaging and Sensing Technologies for Security and Defence VIII

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Physical models play a fundamental role in the evolution of SPAD technology. However, as the majority of the detector properties strongly depends on the electric field, a thorough knowledge of the doping profile is mandatory. Conventional doping extraction methods proved to be not accurate enough, hence the need to develop a new profiling technique which allows us to reach the desired level of accuracy. To this aim, we adopted an inverse modeling approach based on the combined use of capacitance-voltage measurements and electrical simulations. We applied the method to several SPADs, which differ both in terms of doping profile and internal structure, and we used the extracted profile to simulate their breakdown voltages. Calculated results very close to the experimental data were obtained, providing us a convincing validation of the proposed extraction technique.

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“…The modeling of 2-dimensional dopant diffusion in these devices relies on the calibration of models using both SIMS and 2-dimensional physical characterization techniques, i.e., electron holography or scanning spreading resistance microscopy. The inverse modeling method for the extraction of 2-D dopant concentration in devices was first proposed using electrical device characteristics by Khalil et al, 6 and later extended by Hayashi et al 7 We report on direct observation of p-n junctions with and without a carbon co-implant in 45 nm CMOS n-FET devices by 2-D TEM off-axis electron holography and SIMS. In this work, an inverse modeling method was used to extract the active 2-D dopant distribution from the electron holography data in each device.…”

Section: Introductionmentioning

confidence: 95%