Multi-scale modeling of 2D GaSe FETs with strained channels

Reconfigurable frequency multipliers based on graphene field-effect transistors

Run-time device-level reconfigurability has the potential to boost the performance and functionality of numerous circuits beyond the limits imposed by the integration density. The key ingredient for the implementation of reconfigurable electronics lies in ambipolarity, which is easily accessible in a substantial number of two-dimensional materials, either by contact engineering or architecture device-level design. In this work, we showcase graphene as an optimal solution to implement high-frequency reconfigurable electronics. We propose and analyze a split-gate graphene field-effect transistor, demonstrating its capability to perform as a dynamically tunable frequency multiplier. The study is based on a physically based numerical simulator validated and tested against experiments. The proposed architecture is evaluated in terms of its performance as a tunable frequency multiplier, able to switch between doubler, tripler or quadrupler operation modes. Different material and device parameters are analyzed, and their impact is assessed in terms of the reconfigurable graphene frequency multiplier performance.

Graphene BioFET sensors for SARS-CoV-2 detection: a multiscale simulation approach

Biological Field-Effect Transistors (BioFETs) have already demonstrated enormous potential for detecting minute amounts of ions and molecules. The use of two-dimensional (2D) materials has been shown to boost their performance and to enable the design of new applications. This combination deserves special interest in the current pandemic caused by the SARS-CoV-2 virus which demands fast, reliable and cheap detection methods. However, in spite of the experimental advances, there is a lack of a comprehensive and in-depth computational approach to capture the mechanisms underlying the sensor behaviour. Here, we present a multiscale platform that combines detailed atomic models of the molecules with mesoscopic device-level simulations. The fine-level description exploited in this approach accounts for the charge distribution of the receptor, its reconfiguration when the target binds to it, and the consequences in terms of sensitivity on the transduction mechanism. The results encourage the further exploration of improved sensor designs and 2D materials combined with diverse receptors selected to achieve the desired specificity.