Classifiable Limiting Mass Change Detection in a Graphene Resonator Using Applied Machine Learning

Nanomechanical resonator devices are widely used as ultrasensitive mass detectors for fundamental studies and practical applications. The resonance frequency of the resonators shifts when a mass is loaded, which is used to estimate the mass. However, the shift signal is often blurred by the thermal noise, which interferes with accurate mass detection. Here, we demonstrate the reduction of the noise interference in mass detection in suspended graphene-based nanomechanical resonators, by using applied machine learning. Featurization is divided into image and sequential datasets, and those datasets are trained and classified using 2D and 1D convolutional neural networks (CNNs). The 2D CNN learning-based classification shows a performance with f1-score over 99% when the resonance frequency shift is more than 2.5% of the amplitude of the thermal noise range.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.BN/Chirlmin Joo La

Modeling and Understanding the Compact Performance of h-BN Dual-Gated ReS₂ Transistor

In this study, high-performance few-layered ReS2 field-effect transistors (FETs), fabricated with hexagonal boron nitride (h-BN) as top/bottom dual gate dielectrics, are presented. The performance of h-BN dual gated ReS2 FET having a trade-off of performance parameters is optimized using a compact model from analytical choice maps, which consists of three regions with different electrical characteristics. The bottom h-BN dielectric has almost no defects and provides a physical distance between the traps in the SiO2 and the carriers in the ReS2 channel. Using a compact analyzing model and structural advantages, an excellent and optimized performance is introduced consisting of h-BN dual-gated ReS2 with a high mobility of 46.1 cm2 V−1 s−1, a high current on/off ratio of ≈106, a subthreshold swing of 2.7 V dec−1, and a low effective interface trap density (Nt,eff) of 7.85 × 1010 cm−2 eV−1 at a small operating voltage (<3 V). These phenomena are demonstrated through not only a fundamental current–voltage analysis, but also technology computer aided design simulations, time-dependent current, and low-frequency noise analysis. In addition, a simple method is introduced to extract the interlayer resistance of ReS2 channel through Y-function method as a function of constant top gate bias.QN/Steeneken La