Individual Variability and Average Reliability in Parallel Networks of Heterogeneous Biological and Artificial Nanostructures

We simulate the collective electrical response of heterogeneous ensembles of biological and artificial nanostructures whose individual threshold potentials show a significant variability. This problem is of current interest because nanotechnology is bound to produce nanostructures with a significant experimental variability in their individual physical properties. This diversity is also present in biological systems that are however able to process information efficiently. The nanostructures considered are the ion channels of biological membranes, nanowire field-effect transistors, and metallic nanoparticle-based single electron transistors. These systems are simulated with canonical models that incorporate the basic threshold characteristics observed in the respective experimental current-voltage curves. In each case, the different shape, size, and charge distributions of the nanostructures result in statistical distributions for the individual threshold potentials, characterized by experimental average and width distribution values, rather than in identical replicates of the same unit. Despite the significant variability, the simulations suggest that useful average responses can still be achieved with summing networks of heterogeneous nanostructures because the collective behavior may compensate for individual failures and variability. Since threshold potential systems are commonplace in biology, the results obtained are also significant for understanding the role of diversity in biologically inspired networks.