Screening-Limited Response of NanoBiosensors

Despite tremendous potential of highly sensitive electronic detection of bio-molecules by nanoscale biosensors for genomics and proteomic applications, many aspects of experimentally observed sensor response (S) are unexplained within consistent theoretical frameworks of kinetic response or electrical screening. In this paper, we combine analytic solutions of Poisson-Boltzmann and reaction-diffusion equations to show that the electrical response of nanobiosensor varies logarithmically with the concentration of target molecules, time, the salt concentration, and inversely with the fractal dimension of sensor surface. Our analysis provides a coherent theoretical interpretation of wide variety of puzzling experimental data that have so far defied intuitive explanation.Comment: 7 pages, 2 figure

Fundamentals of PV Efficiency Interpreted by a Two-Level Model

Elementary physics of photovoltaic energy conversion in a two-level atomic PV is considered. We explain the conditions for which the Carnot efficiency is reached and how it can be exceeded! The loss mechanisms - thermalization, angle entropy, and below-bandgap transmission - explain the gap between Carnot efficiency and the Shockley-Queisser limit. Wide varieties of techniques developed to reduce these losses (e.g., solar concentrators, solar-thermal, tandem cells, etc.) are reinterpreted by using a two level model. Remarkably, the simple model appears to capture the essence of PV operation and reproduce the key results and important insights that are known to the experts through complex derivations.Comment: 7 pages, 6 figure

Theory of charging and charge transport in “intermediate” thickness dielectrics and its implications for characterization and reliability

Thin film dielectrics have broad applications, and the performance degradation due to charge trapping in these thin films is an important and pervasive reliability concern. It has been presumed since the 1960s that current transport in intermediate-thickness (IT) oxides (∼10–100 nm) can be described by Frenkel-Poole (FP) conduction (originally developed for ∼mm-thick films) and algorithms based on the FP theory can be used to extract defect energy levels and charging-limited lifetime. In this paper, we review the published results to show that the presumption of FP-dominated current in IT oxides is incorrect, and therefore, the methods to extract trap-depths to predict lifetime should be revised. We generalize/adapt the bulk FP current conduction model by including additional tunneling-based current injection. Steady state characteristics are obtained by a flux balance between contacts and the IT oxide. An analytical approximation of the generalized FP model yields a steady state leakage current J ∝ exp(−B√E)(1 − C√E − D/E), where B, C, and D are material-specific constants. This reformulation provides a new algorithm for extracting defect levels to predict the corresponding charging limited device lifetime. The validity and robustness of the new algorithm are confirmed by simulations and published experimental data

Statistical Interpretation of Femto-Molar Detection

Over the last decade, many experiments have demonstrated that nanobiosensors based on Nanotubes and Nanowires are significantly more sensitive compared to their planar counterparts. Yet, there has been persistent gap between reports of analyte detection at ~femto-Molar concentration and theory suggesting the impossibility of sub-pM detection at the corresponding incubation time. This divide has persisted despite the sophistication of the theoretical models. In this paper, we calculate the statistics of diffusion-limited arrival-time distribution by a Monte Carlo method to suggest a statistical resolution of the enduring puzzle: The incubation time in the theory is the mean incubation time, while experiments suggest device stability limited the minimum incubation time. The difference in incubation times - both described by characteristic power-laws - provides an intuitive explanation of different detection limits anticipated by theory and experiments. These power laws broaden the scope of problems amenable to the first-passage process used to quantify the stochastic biological processes