Study of parasitic resistance effects in nanowire and nanoribbon biosensors
- Ioannis Zeimpekis†1Email author,
- Kai Sun†1,
- Chunxiao Hu1,
- Owain Thomas2,
- Maurits RR de Planque1,
- Harold MH Chong1,
- Hywel Morgan1 and
- Peter Ashburn1
© Zeimpekis et al.; licensee Springer. 2015
Received: 24 November 2014
Accepted: 30 January 2015
Published: 21 February 2015
In this work, we investigate sensor design approaches for eliminating the effects of parasitic resistance in nanowire and nanoribbon biosensors. Measurements of pH with polysilicon nanoribbon biosensors are used to demonstrate a reduction in sensitivity as the sensor length is reduced. The sensitivity (normalised conductance change) is reduced from 11% to 5.5% for a pH change from 9 to 3 as the sensing window length is reduced from 51 to 11 μm. These results are interpreted using a simple empirical model, which is also used to demonstrate how the sensitivity degradation can be alleviated by a suitable choice of sensor window length. Furthermore, a differential sensor design is proposed that eliminates the detrimental effects of parasitic resistance. Measurements on the differential sensor give a sensitivity of 15%, which is in good agreement with the predicted maximum sensitivity obtained from modeling.
KeywordsBiosensor Nanowire Nanoribbon Parasitic resistance Differential biosensor pH sensor
Over the past 40 years, Ion Sensitive Field Effect Transistors (ISFETs) have been widely researched for applications as ion [1,2], pH , and protein sensors . More recently, nanowire and nanoribbon biosensors [5,6] have been developed as improved devices because their high surface-to-volume ratio gives high sensitivity. Nanowires can be fabricated using bottom-up  or top-down [8-13] processes. The bottom-up approach has the advantage of simplicity, but there is no precise control of nanowire size and position, and this makes it difficult to achieve low resistance ohmic contacts. Top-down approaches overcome these shortcomings and can be based around silicon CMOS  or thin-film transistor (TFT)  technologies. Both approaches are compatible with mass manufacture and allow heavily doped contact regions to be incorporated to reduce contact resistance. However, the cost of a biosensor is determined by the number of steps in the manufacturing process, so the inclusion of heavily doped contacts increases cost.
The sensitivity of a biosensor is defined as the relative change in conductance after attachment of the target biomolecule and is inversely proportional to the doping concentration in the nanowire or nanoribbon . Consequently, biosensors that are designed for high sensitivity have a relatively large resistivity, and high values of contact resistance are likely unless additional heavily doped contact regions are incorporated into the manufacturing process. Moreover, to accommodate measurements in a liquid environment, biosensor metallization and contact regions are covered with a passivation layer to protect them from the analyte solution. The passivated regions are not influenced by the attachment of target biomolecules to the surface of the sensor and therefore act as a parasitic resistance. When protein sensing is performed, the relative current changes can be rather small for some proteins . In this situation, signal read-out considerations require sensor operation at higher currents, where the effects of parasitic resistance can be important. To date, there have been no published studies of the effect of parasitic resistance on the performance of nanowire or nanoribbon biosensors.
The aim of this work is to investigate the effects of parasitic resistance on biosensor sensitivity. Thin-film polysilicon nanoribbon biosensors are fabricated with different sensing window lengths, and it is shown that the sensitivity is lower for shorter sensing windows. These results are interpreted using a simple empirical model that relates biosensor sensitivity to parasitic resistance and sensing window length. Finally, a differential biosensor design is demonstrated that eliminates the detrimental effects of parasitic resistance and delivers a value of sensitivity equal to the maximum predicted by the model. This high value of sensitivity is achieved without the need to incorporate heavily doped contact regions.
Polysilicon nanoribbon biosensors were fabricated with different channel lengths using the TFT process detailed in our previous work  and measured in dry and wet ambient. Electrical characterization was performed using an Agilent B1500A I/V-based probe-station (Agilent Technologies Singapore (International) Pte. Ltd., Singapore). The sensors were measured in a Faraday cage enclosure box to minimize interference. For the characterization of the sensors, electrical contact was made on the TiN electrodes using Cascade micropositioner probes. The backside of the substrate was grounded through the probe-station chuck to prevent biasing of the channel through it. Transmission line measurements (TLMs) were performed on test structures, and values of sheet resistance (R s,dry) and contact resistance (R c) were extracted to be 448 kΩ/sq and 447 kΩ, respectively. From these values, the total parasitic resistance (R par) was calculated to be 1.6 MΩ. For wet sensing with pH buffers, a liquid gate was formed by pipetting liquid in the sensing window while a potential was applied using a Ag/AgCl electrode immersed in the solution. pH measurements were carried out using universal buffer mixture (UBM) solutions of pH 3, 5, 7, and 9. Those measurements were initiated by introducing pH 9 in the sensor window while applying a 50 mV bias to a Ag/AgCl electrode and a channel potential of 100 mV. After a 10 min stabilization time, the measurement was reset and the buffers were introduced sequentially from high to low pH and back to high pH to complete a full titration. All sensing measurements were performed at the same sensor biasing point so that values of sensitivity could be quantitatively compared.
Results and discussion
where R 0 and G 0 are the resistance and the conductance at a reference level (pH 9 in this work), respectively.
Comparison of measured sensitivity of the differential biosensor with modeled maximum values (for parasitic resistance equal to zero)
Differentially measured sensitivity
Predicted maximum sensitivity
The sensing window lengths of the devices measured in this work were chosen so that the performance of the individual sensors in the differential pair could be separately demonstrated. The requirement for the differential sensor to work is that both sensors have the same parasitic resistance but different sensing window lengths. In practice, a smaller differential biosensor footprint could be achieved if the sensing window length of one sensor was set to zero. When performing the differential measurement, the zero length sensor would then cancel the parasitic resistance of the finite length sensor. This approach allows the differential sensor design to be miniaturized, while maintaining the maximum sensitivity.
This paper has studied the effect of parasitic resistance on biosensor sensitivity. The results show that a high value of parasitic resistance reduces the sensitivity of the sensor, while a long sensing window reduces this sensitivity degradation. A model has been formulated to describe this relationship and used to identify how the sensing window length can be chosen to minimize the negative effects of parasitic resistance. Furthermore, a differential biosensor design has been proposed, and the measurements have indicated that the deleterious effects of parasitic resistance have been eliminated.
The authors would like to acknowledge the Technology Strategy Board (TSB) and the Engineering and Physical Sciences Research Council (EPSRC: EP/K502327/1) for funding this work. We would also like to thank Ben Hadwen, Sally Anderson, Gregory Gay and Chris J. Brown of Sharp Laboratories Europe for many useful discussions.
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