Theory of signal and noise in double-gated nanoscale electronic pH sensors.

The maximum sensitivity of classical nanowire (NW)-based pH sensors is defined by the Nernst limit of 59 mV/pH. For typical noise levels in ultra-small single-gated nanowire sensors, the signal-to-noise ratio is often not sufficient to resolve pH changes necessary for a broad range of applications. Recently, a new class of double-gated devices was demonstrated to offer apparent "super-Nernstian" response (>59 mV/pH) by amplifying the original pH signal through innovative biasing schemes. However, the pH-sensitivity of these nanoscale devices as a function of biasing configurations, number of electrodes, and signal-to-noise ratio (SNR) remains poorly understood. Even the basic question such as "Do double-gated sensors actually resolve smaller changes in pH compared to conventional single-gated sensors in the presence of various sources of noise?" remains unanswered. In this article, we provide a comprehensive numerical and analytical theory of signal and noise of double-gated pH sensors to conclude that, while the theoretical lower limit of pH-resolution does not improve for double-gated sensors, this new class of sensors does improve the (instrument-limited) pH resolution.

Coupled heterogeneous nanowire-nanoplate planar transistor sensors for giant (>10 V/pH) Nernst response.

We offer a comprehensive theory of pH response of a coupled ISFET sensor to show that the maximum achievable response is given by ΔV/ΔpH = 59 mV/pH × α, where 59 mV/pH is the intrinsic Nernst response and α an amplification factor that depends on the geometrical and electrical properties of the sensor and transducer nodes. While the intrinsic Nernst response of an electrolyte/site-binding interface is fundamental and immutable, we show that by using channels of different materials, areas, and bias conditions, the extrinsic sensor response can be increased dramatically beyond the Nernst limit. We validate the theory by measuring the pH response of a Si nanowire-nanoplate transistor pair that achieves >10 V/pH response and show the potential of the scheme to achieve (asymptotically) the theoretical lower limit of signal-to-noise ratio for a given configuration. We suggest the possibility of an even larger pH response based on recent trends in heterogeneous integration on the Si platform.

Silicon nanowires with high-k hafnium oxide dielectrics for sensitive detection of small nucleic acid oligomers.

Nanobiosensors based on silicon nanowire field effect transistors offer advantages of low cost, label-free detection, and potential for massive parallelization. As a result, these sensors have often been suggested as an attractive option for applications in point-of-care (POC) medical diagnostics. Unfortunately, a number of performance issues, such as gate leakage and current instability due to fluid contact, have prevented widespread adoption of the technology for routine use. High-k dielectrics, such as hafnium oxide (HfO(2)), have the known ability to address these challenges by passivating the exposed surfaces against destabilizing concerns of ion transport. With these fundamental stability issues addressed, a promising target for POC diagnostics and SiNWFETs has been small oligonucleotides, more specifically, microRNA (miRNA). MicroRNAs are small RNA oligonucleotides which bind to mRNAs, causing translational repression of proteins, gene silencing, and expressions are typically altered in several forms of cancer. In this paper, we describe a process for fabricating stable HfO(2) dielectric-based silicon nanowires for biosensing applications. Here we demonstrate sensing of single-stranded DNA analogues to their microRNA cousins using miR-10b and miR-21 as templates, both known to be upregulated in breast cancer. We characterize the effect of surface functionalization on device performance using the miR-10b DNA analogue as the target sequence and different molecular weight poly-l-lysine as the functionalization layer. By optimizing the surface functionalization and fabrication protocol, we were able to achieve <100 fM detection levels of the miR-10b DNA analogue, with a theoretical limit of detection of 1 fM. Moreover, the noncomplementary DNA target strand, based on miR-21, showed very little response, indicating a highly sensitive and highly selective biosensing platform.

High-k dielectric Al2O3 nanowire and nanoplate field effect sensors for improved pH sensing.

Over the last decade, field-effect transistors (FETs) with nanoscale dimensions have emerged as possible label-free biological and chemical sensors capable of highly sensitive detection of various entities and processes. While significant progress has been made towards improving their sensitivity, much is yet to be explored in the study of various critical parameters, such as the choice of a sensing dielectric, the choice of applied front and back gate biases, the design of the device dimensions, and many others. In this work, we present a process to fabricate nanowire and nanoplate FETs with Al(2)O(3) gate dielectrics and we compare these devices with FETs with SiO(2) gate dielectrics. The use of a high-k dielectric such as Al(2)O(3) allows for the physical thickness of the gate dielectric to be thicker without losing sensitivity to charge, which then reduces leakage currents and results in devices that are highly robust in fluid. This optimized process results in devices stable for up to 8 h in fluidic environments. Using pH sensing as a benchmark, we show the importance of optimizing the device bias, particularly the back gate bias which modulates the effective channel thickness. We also demonstrate that devices with Al(2)O(3) gate dielectrics exhibit superior sensitivity to pH when compared to devices with SiO(2) gate dielectrics. Finally, we show that when the effective electrical silicon channel thickness is on the order of the Debye length, device response to pH is virtually independent of device width. These silicon FET sensors could become integral components of future silicon based Lab on Chip systems.

Statistical interpretation of "femtomolar" detection.

We calculate the statistics of diffusion-limited arrival-time distribution by a Monte Carlo method to suggest a simple statistical resolution of the enduring puzzle of nanobiosensors: a persistent gap between reports of analyte detection at approximately femtomolar concentration and theory suggesting the impossibility of approximately subpicomolar detection at the corresponding incubation time. The incubation time used in the theory is actually the mean incubation time, while experimental conditions suggest that 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.