The chemical dynamics of nanosensors capable of single-molecule detection.

Recent advances in nanotechnology have produced the first sensor transducers capable of resolving the adsorption and desorption of single molecules. Examples include near infrared fluorescent single-walled carbon nanotubes that report single-molecule binding via stochastic quenching. A central question for the theory of such sensors is how to analyze stochastic adsorption events and extract the local concentration or flux of the analyte near the sensor. In this work, we compare algorithms of varying complexity for accomplishing this by first constructing a kinetic Monte Carlo model of molecular binding and unbinding to the sensor substrate and simulating the dynamics over wide ranges of forward and reverse rate constants. Methods involving single-site probability calculations, first and second moment analysis, and birth-and-death population modeling are compared for their accuracy in reconstructing model parameters in the presence and absence of noise over a large dynamic range. Overall, birth-and-death population modeling was the most robust in recovering the forward rate constants, with the first and second order moment analysis very efficient when the forward rate is large (>10(-3) s(-1)). The precision decreases with increasing noise, which we show masks the existence of underlying states. Precision is also diminished with very large forward rate constants, since the sensor surface quickly and persistently saturates.