Characterization of nanometer-sized, mechanically exfoliated graphene on the H-passivated Si(100) surface using scanning tunnelling microscopy

We have developed a method for depositing graphene monolayers and bilayers with minimum lateral dimensions of 2-10 nm by the mechanical exfoliation of graphite onto the Si(100)-2x1:H surface. Room temperature, ultra-high vacuum (UHV) tunnelling spectroscopy measurements of nanometer-sized single-layer graphene reveal a size dependent energy gap ranging from 0.1-1 eV. Furthermore, the number of graphene layers can be directly determined from scanning tunnelling microscopy (STM) topographic contours. This atomistic study provides an experimental basis for probing the electronic structure of nanometer-sized graphene which can assist the development of graphene-based nanoelectronics.Comment: Accepted for publication in Nanotechnolog

Noise characterization of analog to digital converters for amplitude and phase noise measurements

International audienceImprovements on electronic technology in recent years have allowed the application of digital techniques in phase noise metrology where low noise and high accuracy are required, yielding flexibility in systems implementation and setup. This results in measurement systems with extended capabilities, additional functionalities and ease of use. In most digital schemes the Analog to Digital Converters (ADCs) set the ultimate performance of the system, therefore the proper selection of this component is a critical issue. Currently, the information available in literature describes in depth the ADC features only at frequency offsets far from the carrier. However, the performance close to the carrier is a more important concern. As a consequence, the ADC noise is in general analyzed on the implemented phase measurement setup. We propose a noise model for ADCs and a method to estimate its parameters. The method retrieves the Phase Modulation and Amplitude Modulation noise by sampling around zero and maximum amplitude, a test sine-wave synchronous with the ADC clock. The model allows discriminating the ADC noise sources and obtaining the phase noise and amplitude noise power spectral densities from 10 Hz to one half of the sampling frequency. This ap-proach reduces data processing, allowing an efficient ADC evaluation in terms of hardware complexity and computational cost