Publications by Antonio D'Amico

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This paper presents an in-depth DC characterization of a 22 nm FDSOI CMOS technology down to deep cryogenic temperature, i.e., 2.95 K. The impact of the back-gate voltage (V-back) on device performance, i.e., threshold voltage (V-T) and carrier transport, ...

This paper presents the RF characterization and modeling of a 22nm FDSOI technology down to 3.3K for quantum computing applications. The equivalent small-signal components are extracted analytically and automatically from the de-embedded two-port Y -parame ...

In this paper, the influence of temperature and back-gate bias is experimentally investigated on 22 nm FDSOI CMOS process. Cryogenic DC characterization was carried out under various back-gate voltages, V back , from 2.95 K back to 300 K. An abrupt drop-of ...

The work presents the comprehensive design-oriented EKV model for FDSOI technologies, including the backgate effects and geometry dependence. Despite its simplicity, the model correctly captures not only the dependence of the threshold voltage versus the b ...

This paper presents the open-source Python-based parameter extractor (SEKV-E) for the simplified EKV (sEKV) model, which enables the modern low-power circuit designs with the inversion coefficient design methodology. The tool extracts the essential sEKV pa ...

This study presents the first in depth characterization of deep cryogenic electrical behavior of a commercial 16 nm CMOS FinFET technology. This technology is well suited for a broad range of applications, including quantum computing, quantum sensing, and ...

Antonio D'Amico

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Back-gate effects on DC performance and carrier transport in 22 nm FDSOI technology down to cryogenic temperatures

Cryogenic RF Characterization and Simple Modeling of a 22 nm FDSOI Technology

In-depth Cryogenic Characterization of 22 nm FDSOI Technology for Quantum Computation

Comprehensive Design-oriented FDSOI EKV Model

SEKV-E: Parameter Extractor of Simplified EKV I-V Model for Low-Power Analog Circuits

Cryogenic Characterization of 16 nm FinFET Technology for Quantum Computing