CSE Dissertation Proposal Defense: Mingquan Yuan

Dec 12, 2017
10 a.m.
Jolley Hall, Room 309

"Biosensing by Growing Antennas and Error-Correcting Codes"

Mingquan Yuan
Adviser: Shantanu Chakrabartty

Around 48 million people in the United States (1 in 6) were affected by, and 3000 of them die of foodborne diseases annually. This not only leads to the fatalities but also results in huge losses related to the medical care and product recalls. End-to-end supply chain monitoring can be one of the keys to prevent these foodborne disease outbreaks and product recalls. However, practically it is infeasible to do testing and analyzing for all food samples at every point in the supply-chain because of several reasons: 1) traditional laboratory test is time consuming and expensive; 2) food is typically enclosed in the packaged environment; 3) volume of food products moving throughout the supply chain everyday is huge.

Fortunately, two economical converging trends makes this end-to-end supply chain monitoring possible.

The first trend is that passive radio-frequency identification (RFID) tags and quick response (QR) codes are now universally accepted for food packaging. In the meantime, the price of passive RFID tags have reduced by orders of magnitude when compared to the cost of packaging or materials over the last decade (less than $0.10 per tag). As a result, it is now economically viable to embed or attach a passive tag to every package of food-item.

The second trend is that the new generation of smart-phones have been equipped with the capabilities like interrogating RFID tags or decoding QR codes and uploading scanned information to the cloud.

The missing part is the ability to reliably detect pathogens or contaminants in food samples using passive RFID tag or QR code.

In this proposal we propose to investigate a new remote biosensing approach by ``growing" part of transducer structures (RF antennas or QR code-words) based on self-assembly which is only triggered in the existence of target analyte.

This sensing approach can be viewed as a process that evolves from a high-entropy state (detuned RF antenna or disassembled QR code) to a low-entropy state (tuned antenna or assembled QR code). This is opposite to the direction of natural processes according to the second law of thermodynamics. Thus, this self-assembly based sensing approach should be robust to environmental artifacts. Verifying this hypothesis will be the key objective of this research proposal.