Fundamental Design Considerations and Scaling Properties for Nanobiosensors.

Biotechnology and bio-sensing are often mentioned as the next frontier of electronics that could rival semiconductor industry’s broad and revolutionary impact on society. Since any disease is a signature of either a genetic defect or broken signaling pathways that occur far in advance of any overt signature detected by classical sensors, one of the grand challenges of modern bio-sensing is to find cost-effective, reliable, fast methods for gene sequencing (as an ultimate “Finger-print” of one’s biological make-up and possibly early intervention for genetic anomaly) and the detection/identification of the irreducible and emergent protein network for application in proteomics and system biology.

Modern bio-sensors based on nanoscale electrical devices promise highly sensitive detection of bio-molecules unmatched by existing classical techniques. The emergence of nanometer-scale fabrication techniques has enabled a dramatic reduction in device dimensions so that the bulk conduction mechanisms can now be controlled by surface properties, with a corresponding dramatic increase in the sensitivity of nano-scale bio-chemical sensors. Reduced dimensionality has enabled silicon-nanowire and carbon nanotube sensors to emerge as highly sensitive, label-free, and dynamic detectors for chemical and biological molecules that are ideally suited for integration in an array format.

Despite tangible research by many groups all over the world, the elements that dictate response of a nanoscale biosensor has remained -- until recently -- poorly understood. In this research, we develop a predictive theoretical framework for nano-bio sensors that will help with design and optimization of these systems. Specifically, we identify the key functional variables and unifying principles for such sensors for rapid and simple interpretation of experimental data and establish the limits of performance and scalability. Self consistent numerical simulations are performed to support the predictions from our analytical models.

One of the striking achievements of this research is that we have provided a systematic way for optimization of sensor systems rather than the traditional “trial-and-error experimentation”. Inter-disciplinary to the core, our research describes how the elementary use of fractal geometry of diffusion, percolative transport in random networks, electrolyte screening-limited response, etc. are finally allowing us to establish the performance potential of nanobiosensors. Indeed, our models provide a coherent theoretical interpretation for wide variety of puzzling experimental data that have so far defied intuitive explanation and have important implications for the design and optimization of nanoscale biosensors. The theoretical models we develop as a part of this research will be made available to the public domain as a simulation tool in nanoHUB.

BioSensorLab: An open access tool to evaluate and predict the performance parameters of nanoscale biosensors (developed by P. R. Nair and M. A. Alam)

2008 Dimitris N. Chorafas Foundation Outstanding Dissertation Award

2007-2008 ECE Outstanding Dissertation Award

Press Releases on my research:

Research Highlights: Future Medicine

Sensor design gets Systematic: EEtimes article

Study shows why nanoscale sensors outperform larger devices: Nanomaterials News

Model is first to compare the performance of ‘biosensors’: Purdue News

Mathematical model that relates the shape of biosensors to its performance: Frost & Sullivan Sensor Technology Alert

Performance limits of nanobiosensors: Nanowerk "Spotlight"

'Nanocantilevers' yield surprises critical for designing new detectors: Science Daily news PhysOrg