6533b821fe1ef96bd127c206

RESEARCH PRODUCT

Sub-threshold signal processing in arrays of non-identical nanostructures

subject

description

Weak input signals are routinely processed by molecular-scaled biological networks composed of non-identical units that operate correctly in a noisy environment. In order to show that artificial nanostructures can mimic this behavior, we explore theoretically noise-assisted signal processing in arrays of metallic nanoparticles functionalized with organic ligands that act as tunneling junctions connecting the nanoparticle to the external electrodes. The electronic transfer through the nanostructure is based on the Coulomb blockade and tunneling effects. Because of the fabrication uncertainties, these nanostructures are expected to show a high variability in their physical characteristics and a diversity-induced static noise should be considered together with the dynamic noise caused by thermal fluctuations. This static noise originates from the hardware variability and produces fluctuations in the threshold potential of the individual nanoparticles arranged in a parallel array. The correlation between different input (potential) and output (current) signals in the array is analyzed as a function of temperature, applied voltage, and the variability in the electrical properties of the nanostructures. Extensive kinetic Monte Carlo simulations with nanostructures whose basic properties have been demonstrated experimentally show that variability can enhance the correlation, even for the case of weak signals and high variability, provided that the signal is processed by a sufficiently high number of nanostructures. Moderate redundancy permits us not only to minimize the adverse effects of the hardware variability but also to take advantage of the nanoparticles' threshold fluctuations to increase the detection range at low temperatures. This conclusion holds for the average behavior of a moderately large statistical ensemble of non-identical nanostructures processing different types of input signals and suggests that variability could be beneficial for signal processing. We demonstrate also that circuits composed of coupled non-identical nanoparticles can act as elementary nano-oscillators that show synchronization properties for sub-threshold stimuli. The results obtained should be of conceptual interest for the design of reliable signal processing schemes with non-identical nanostructures.