Computer Model Used To Study and Design Miniature Biosensors

They are designed to capture and detect specific target molecules, allowing them to identify pathogens, DNA, or other substances. As such they have a myriad of uses, ranging from medical diagnostics, drug research and delivery, and environmental monitoring.

In efforts to design more sensitive devices, engineers have created sensors with various geometries: some capture the biomolecules on a flat or planar surface, others use a single cylindrical nanotube as a sensing element, and others use several nanotubes, arranged in a crisscrossing pattern like overlapping sticks.

Prof. Alam led a team from Purdue University (West Lafayette, IN, USA) in creating a mathematical model that can relate the shape of a biosensor to its performance. "Many universities and companies are conducting experiments in biosensors,” Prof. Alam said. "The problem is that until now there has been no way to consistently interpret the wealth of data available. Our work provides a completely different perspective on how to analyze data and how to interpret them.”

Prof. Alam additionally commented, "It's not what happens after the molecule is captured that determines how well the sensor works. It's how fast the sensor actually captures the molecule to begin with that matters most.” This distinction is important for the design of biosensors and it explains why biosensors with a single nanotube perform better than sensors containing several nanotubes or flat planar sensors. A single nanotube eliminates a phenomenon called "diffusion slow down.” As a result, target molecules move faster toward the nanotube. In addition, smaller sensors work better because they can capture the target molecules better, rather than detect them better. This means that target molecules move faster toward single nanotubes than other structures and also helps eliminate the diffusion slow down.

An impediment that prevented scientists from finding this before is that biosensor analysis is computationally too difficult to perform using conventional approaches. To overcome, the team at Purdue used a mathematical technique called "Cantor transformation” to simplify the calculations.

The scientists tested and validated their model with experimental data from other laboratories. The work was published in the December 21, 2007 edition of the journal Physical Review Letters.


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