Predictive models are pivotal tools for the development of new SPADs. To verify the effectiveness of such models, the generated results must be compared with experimental data on large set of SPADs. In doing so, a precise knowledge of the doping profile along the detector active region is mandatory, being physical processes involved in SPADs’ operation generally strongly dependent on the electric field. Unfortunately, widely-adopted profiling techniques do not provide an accuracy sufficient for predictive SPAD modeling. To cope with this limitation, we developed an inverse method that, by means of electrical simulations and capacitance-voltage measurements, is able to refine approximated doping profiles. We used this method to calculate the breakdown voltages of multiple SPADs. Simulated results closely matching the experimental data provide us a convincing validation of the proposed technique.
Inverse doping profile extraction for predictive SPAD modeling
Bonzi, Andrea;Laita, Gabriele;Rech, Ivan;Gulinatti, Angelo
2023-01-01
Abstract
Predictive models are pivotal tools for the development of new SPADs. To verify the effectiveness of such models, the generated results must be compared with experimental data on large set of SPADs. In doing so, a precise knowledge of the doping profile along the detector active region is mandatory, being physical processes involved in SPADs’ operation generally strongly dependent on the electric field. Unfortunately, widely-adopted profiling techniques do not provide an accuracy sufficient for predictive SPAD modeling. To cope with this limitation, we developed an inverse method that, by means of electrical simulations and capacitance-voltage measurements, is able to refine approximated doping profiles. We used this method to calculate the breakdown voltages of multiple SPADs. Simulated results closely matching the experimental data provide us a convincing validation of the proposed technique.File | Dimensione | Formato | |
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