Poster Presentation Final
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The document describes simulations of a BioFET device for detecting DNA hybridization. The simulations tested different doping configurations and found that a PPP+ configuration increased sensitivity 30 times over a PPP configuration. Future work will involve fabricating a device based on these findings and measuring its electrical characteristics to detect hybridized DNA.
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![Detection of DNA Hybridization with a BioFET Sensor Acknowledgments Stanford EE REU 2008 Nishi Group Michael Chu Mentor: Kosar Parizi Faculty: Professor Yoshio Nishi Stanford University Electrical Engineering Objective The primary motivation for a Bio-Field Effect Transistor is the ability to function as a real-time and massively parallel sensor. We sought to design a BioFET device capable of detecting the hybridization of DNA. We particularly emphasize the implementation of a back bias to improve sensitivity. We also consider the effects of changing doping concentrations and patterns. Methods We used Sentaurus Structure Editor to integrate device components into a mesh. We used Sentaurus Device to run the simulation. We used TecPlot to verify the successful simulation of the doping types, as shown below. We see both npn and npp+ configurations. Figure 3. Shift of V G when charge density changes Figure 4. Our BioFET Figure 6. Two simulated doping patterns Results Shown below are the results of our simulations. Let’s compare the curves when V D = 1V. For PPP, the current at the threshold of 1 V is 7 x 10 -10 A. For PPP+, the current at .75 V is 1.6 x 10 -8 A. The improvement in sensitivity is determined by the difference in sub-threshold slopes of the curves. So slope PPP+ / slope PPP = 30.5 ≈ 30 times more sensitive ! Figure 7. Comparison of IV curves for different devices. Conclusions & Future Work Using simulations, we have determined that the doping configuration which would allow the greatest device sensitivity is PPP+. We will check P+ on the source (P+PP+) as one more test. Therefore, we can now begin fabrication of such a device and measure its IV characteristics. References T. Sakata et al., Jap. J. of App. Phys., Vol 44, No. 4B, 2005, pp. 2854-2859 D. Kim et al. Biosensors and Bioelectronics. Vol 20, 2004, pp 69-74 J. Fritz et al. PNAS. Vol. 99, 2002, pp 14142-14146. J. Hahm et al. Nano Letters. Vol 4. No.1. 2004. pp. 51-54. Background In the rapidly thriving industry of medical devices, a BioFET can be implemented for the detection and identification of diseases such as cancer. The key fundamental concept with this device is that the gate bias is controlled by the negatively charged DNA. Hybridization increases this negative charge which is changed into an electrical signal via the field effect. Hypothetical IV G Curves for a: MOSFET BIOFET --- At a ref V G --- Funct. Surface --- DNA Immob. --- Hybrid. Of DNA PDMS Microfluidic Channel --- At a ref VG --- Funct. Surface --- DNA Immob. --- Hybrid. Of DNA N-P-N N-P-N N-P-P+ N-P-P+ ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],50 nm Figure 5. Electrode Schematic Note the specific gate region defined by the aqueous solution conducting a voltage from the solution electrode Solution Electrode Aqueous Solution (conductive) Gate Source Body Drain I D V G V t Increase in P doping Figure 2. Effect of doping concentration on current for a double sided gate device. The threshold voltage is directly related to the thickness of the silicon Between the two doping patterns we change the doping type of the drain. Not shown here is PPP+, the configuration with the best sensitivity. Double Sided Gate Structure Map of Device Doping Source | Bulk | Drain 50 um Figure 1. Generic BioFET Note the similarities to the conventional MOSFET (Sakata et al.) I D V G ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]](https://image.slidesharecdn.com/posterpresentationfinal-12915853795847-phpapp01/85/Poster-Presentation-Final-1-320.jpg)
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Characterization of EIT system is crucial for validation and calibration. Parameters used for characterization are divided into two groups- first dealing with data quality (SNR, accuracy) and second dealing with image quality (CNR, RNG, reconstructed area).These parameters are useful while selecting a particular EIT system for any new application. Injected current directly affects the data and hence the quality of reconstructed image. Therefore we have studied effect of amplitude of injected current on the EIT data and reconstructed image experimentally. Guidelines are evolved for setting the EIT system to collect useful data for further characterization. We report a set of experiments carried out to characterize a Lab VIEW based 16- electrode 2D EIT system developed in our laboratory. SNR and accuracy for all 208 channels involved in the Sheffield measurement pattern has been calculated. Resolution of EIT system is an important parameter and it depends on both data and image quality and is a combined index for the performance. Uniformity of resolution over the object is also important to preserve shape characteristics of target. We have obtained the resolution of our system experimentally at the centre as well as near the electrodes. It is shown to follow the limits proposed by Seagar relating to the model used for reconstruction and by Isaacson relating to the noise in the measurement.
Partial Discharges using Variable Frequency PRPDA Technique
At the applied voltage a disc-shaped cavity with partial discharges are measured at variable frequency (0.01-50 Hz). By varying the frequency it was observed that measured PD phase, magnitude of distributions and number of PDs per voltage cycles are varied. In the cavity, sequence of Partial discharge is simulated dynamically. For that purpose a model is presented with charge consistent. Simulated results shows that cavity surface and emission properties are effected by varying the magnitude of applied frequency, mainly conductivity of surface. This paper is illustrating the frequency dependence of PD in a cavity. The paper illustrates how the applied voltage amplitude and the cavity size can influence the frequency dependence PD activity.
Simulation and Partial Discharge Measurement in 400kv Typical GIS Substation
http://www.iosrjournals.org/iosr-jeee/pages/v8i3.html
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