Abstract

In the field of nanoelectronics, achieving high precision and reliability is critical for advancing technologies in diverse applications, such as sensors, biomedical devices, and quantum computing. Nanoelectronics instrumentation faces unique challenges due to the scaling of devices to nanometer dimensions, which results in increased susceptibility to noise, variability, and failure. Traditional verification and testing methods often fall short in ensuring the precision and reliability required at such scales. To address these challenges, advanced modeling, verification, and testing techniques have been developed to enhance the performance of nanoelectronic systems. This paper explores state-of-the-art techniques for modeling, verification, and testing that cater specifically to nanoelectronics. The proposed method combines physics-based modeling with statistical approaches to account for process variations and device imperfections. Formal verification methods are employed to ensure that the system meets stringent performance specifications, while accelerated stress testing techniques, such as temperature and voltage scaling, are used to simulate long-term reliability. Results from a case study demonstrate that by applying these techniques, a 15% improvement in precision was achieved, reducing measurement errors from 5% to 2.5%. Furthermore, reliability was enhanced, with a 20% increase in the mean time to failure (MTTF) for the nanoelectronic system. These results highlight the effectiveness of combining advanced modeling with rigorous verification and testing approaches in nanoelectronics, offering a pathway to more robust and reliable systems.