Session S4

Session S4: Biosensing I

Time:                 Tuesday, May 13, 10:30-12:00
Chair:                 Junseok Chae, Arizona State University
Co-Chair:          Chaitali Chakrabarti, Arizona State University

S4-1: Integrating Microcantilever with AC Electroosmosis for Concentrating Nano-Particle
Nazmul Islam Northern Arizona University, Flagstaff AZ
AC electroosmosis (ACEO) can operate at relatively low voltages, which is suitable for integrated lab-on-a-chip systems. Particle trapping by ACEO has no dependence on particle properties, so nano particle trapping can be possible. However, current real-time detection typically has a detection limit several orders of magnitude higher than an infectious dose. Consequently, pre-concentrating biological analytes such as proteins, viruses, and bacteria, is important in real-time detection. The sensitivity and detection time could be improved by orders of magnitude if a concentration trap could be embedded with cantilevers. For this reason, we have integrated micro-cantilever with ACEO trap in a microfluidic chamber. A nanometer layer of charges/ions is induced by an electric field at the interfaces of electrolytes and solids. If there also exist electric fields parallel to the electrodes, the induced ions will migrate under the influences of the tangential fields, and produce osmotic microflows due to fluid viscosity. The conductive gold layer on microcantilever is required to generate microfluidic convection of nano-particles from solution bulk onto microcantilever surfaces that enhances sensitivity of the system. By combining both experimental investigation and theoretical analysis, this research work demonstrates a microcantilever particle trap at nano-scale.

S4-2: Enhanced Biochemical Signal Extraction from Rotating Paramagnetic Chains
Prasun Mahanti, Thomas Taylor, Douglas Cochran and Mark Hayes Arizona State University, Tempe AZ
Biochemical Signal Extraction from fluorescence immunoassay video analysis inherently has the characteristics of spatial and temporal variability that can cause problems in the signal extraction. During the signal extraction phase this aids in adding more of the background and noise lowering the signal to noise ratio of isolated signal and deteriorating the performance of the technique. A novel method of signal extraction is suggested which involves modeling the background and taking into consideration these factors. This is seen to enhance the signal to noise ratio considerably in comparison to the previous benchmarks.

S4-3: Development of a Molecular Assay for Screening of Chemopreventive Compounds Targeting Nrf2
Zhaohui Wang, Vinay Gidwani, Zheng Sun, Donna Zhang and Pak Kin Wong University of Arizona, Tucson AZ
Emerging molecular studies have shown that the transcription factor Nrf2 plays an essential role in cancer chemoprevention. Here, we report the development of a molecular probe biosensor for rapid detection of ARE-bound Nrf2 protein. The development will provide a molecular assay for screening of chemopreventive compounds, which can be adopted for automated high-throughput screening. Specifically, a double-stranded DNA probe is designed based on the ARE sequence. The DNA probes are labeled with a fluorophore and a quencher, which are brought into close proximity. A single-stranded DNA competitor is also designed. The existence of the Nrf2 stabilizes the probe and prevents the competitor from separating the fluorophore-quencher complex. Therefore, the concentration of the Nrf2 proteins can be measured quantitatively based on the fluorescence intensity.

S4-4: Microdevices and Front-end Interface Circuitry for Hearing Aids
Sangsoo Je, Jere Harrison, Ilker Deligoz, Bertan Bakkaloglu, Sayfe Kiaei and Junseok Chae Arizona State University, Tempe AZ
We report MEMS (micro-electro-mechanical-systems) devices and front-end interface circuitry for small-size hearing aids. MEMS microphones operate capacitively to convert acoustic inputs to a variable capacitor. The variable capacitor is interfaced with sigma-delta interface circuitry for adaptive control and reducing the noise floor. The size of the microphone is only 2 mm in diameter; yet sensitive enough to sense extremely-minute acoustic sound to deliver. The interface circuitry implements the 4th order continuous sigma-delta modulator to convert raw analog data to low-noise digital bit stream for subsequent DSP units.

S4-5: System Level Integration of Chemical Sensing Platforms
Erica Forzani and NJ Tao Arizona State University, Tempe AZ
We present our recent results and experience in the integration of chemical sensing platforms at system level. Quartz crystal tuning forks and conducting polymer nanojunctions have been integrated in portable devices for the detection and assessment of several chemical vapors in indoor-outdoor environments and health biomarkers. The optimization of the sensing device performance at the chemical, electrical, computing and communication levels is discussed. We share our experience, involving optimization of sensitivity, chemical selectivity, sensor response time and stability, signal detection, data processing, storage and transmission as well as the evaluation of power consumption, device size and cost efficiency. Examples of portable and wireless chemical sensing devices for monitoring of chemical toxicants in work environment, indoor-outdoor air quality, and breath analysis are presented. We also point out the performance of the high-throughput portable device that resulted in a simple and easy-to-use analytical research tool for screening materials’ chemical reactivity in a broad range of commercial products, gas and volatile liquid streams.

S4-6: Cluster Formation in Particle-Laden Microchannel Flow
Tarun Gudipaty, Luthur Siu Lun Cheung, Linan Jiang and Yitshak Zohar University of Arizona, Tucson AZ
Microchannels are susceptible to blockage by solid particles. The lifetime of microfluidic devices depends on their ability to maintain flow without interruption, while certain applications require microdevices for transport of liquids containing particles. Based on the present experiments, aggregation of clusters was observed for flow of liquid with 0.01 volume concentration of polystyrene particles, about 1.5µm in nominal diameter, through a microchannel 15 µm high. The phenomenon of interest is the formation and growth of clusters in the flow of a dilute suspension of hard spheres. The spatial distribution and time evolution of clusters along the microchannel is presented. Based upon the current results, more clusters are found at the inlet/outlet regions than in the center of the microchannels, while the clusters grow almost linearly in time.

S4-7: Real–Time Monitoring of Diesel and Gasoline Exhaust Exposure
Bharatan Konnanath, Andreas Spanias, Bertan Bakkaloglu, Hyuntae Kim, Joseph Wang, Jeffrey La Belle, Karel Cizek Arizona State University, Tempe AZ, Ashok Mulchandani, Nosang Myung and Marc Deshusses University of California, Riverside CA
The overall aim of this collaborative research is to monitor exposure to diesel exhaust compounds using a wearable gas sensor-array. Two different types of gas nano-sensors have been developed, namely conductometric and amperometric sensors. These are used to detect exhaust fumes. A microelectronic component is also being developed for data collection and power management. The signal processing module performs signal analysis, feature extraction and pattern recognition. The challenge is that exhaust fumes are composed of a complex mixture of gases which are hard to detect and classify and that the sensors being developed exhibit variable levels of cross-sensitivity to the different analytes. First, we perform feature extraction using Principal Component Analysis (PCA) that has the dual advantage of compressing feature dimensionality and reducing certain types of noise. Then three different classification algorithms are employed: Multi Layer Perceptron, Learning Vector Quantization, and Linear Discriminant Analysis. We compare the results of these algorithms with regard to detection accuracy, sensitivity to cross-reactive sensors, robustness to false alarms, and computational complexity.