Device variability and circuit redundancy in signal processing based on nanoswitches.

Signal processing based on molecular switches whose conductance can be tuned by an external stimulus between two (on and off) states has been proposed recently (Cervera et al 2008 J. Appl. Phys. 104 084317). The basic building block is a metal nanoparticle linked to two electrodes by an organic ligand and a nanoswitch. The net charge delivered by this nanostructure exhibits a sharp resonance when the alternating potential applied between the electrodes has the same frequency as the periodic variation between the on and off conductance states induced on the nanoswitch. This resonance can be used to process an external signal by selectively extracting the weight of the different harmonics. However, because of the fabrication process at the nanoscale, the nanostructures will show a significant variability in the physical characteristics. By using a phenomenological model that includes this variability, the stochastic nature of electron transference, and the thermal noise, we demonstrate that reliable signal processing can still be achieved by adapting the number of nanoswitches per bit of information (circuit redundancy) to the nanostructure tolerance (device variability). Extensive kinetic Monte Carlo simulations show that a moderate level of redundancy can compensate for significant nanostructure variability. This result gives support to the concept of ensembles of redundant switches as reliable components for signal processing at the nanoscale.