BSAC Co-Director Jun-Chau Chien is the recipient of the NSF CAREER award for his work Chip-Scale Multi-Modal RF-to-Millimeter-Wave Biosensing!
National Science Foundation (NSF) Early Career Development (CAREER) Awards are among the NSF's most prestigious awards in support of the early career-development activities of teacher-scholars who most effectively integrate research and education in their work.
ABSTRACT
Bacterial infections remain a leading cause of mortality in both developed and developing nations. Current diagnostic approaches rely on cell culturing to detect and identify bacterial strains, a process that can take days or even weeks, delaying appropriate treatment. Therefore, there is an urgent need for rapid diagnostic methods that eliminate the need for cell culturing. Recent advancements in biotechnology, such as antibody-based bacterial recognition and genetic amplification techniques, have shown high sensitivity and specificity; however, these methods often require costly reagents, specialized equipment, and skilled personnel, making the process labor-intensive, time-consuming, and expensive. This project thus aims to develop a miniaturized, sensitive, and user-friendly sensing platform by leveraging integrated circuit (IC) chips and microfluidic integration. The resulting system will be highly portable, with potential for widespread use in clinics, hospitals, and emergency rooms to enable rapid diagnostics. Additionally, the research incorporates an educational and outreach program to introduce these technologies to students from K-12 through graduate levels, contributing to future engineering workforce in healthcare industry.
This project aims to develop electromagnetic (EM) bacteria sensing systems covering RF-to-millimeter-wave frequencies that combine physics-based and biochemistry-based detection methods. The physics-based approach uses broadband dielectric spectroscopy to distinguish bacterial phenotypes by their unique molecular signatures, while the biochemistry-based approach targets strain-specific surface biomarkers tagged with magnetic nanoparticles. Achieving both requires ultrasensitive detection to resolve small spectral variations and to detect single magnetic nanoparticles. The project will achieve these goals with three engineering innovations: (1) Development of ultrasensitive biosensing electronics using high-Q resonators and circuit techniques to overcome traditional noise-power trade-offs, thereby enhancing detection limits. (2) Integration of microfluidic channels within a silicon chip to precisely align the sensing transducers with the underlying electronics to boost the sensitivity. This will be achieved by removing the micro-meter-sized metal routing inside a silicon chip using wet etchants as well as dry etching using ion plasma. (3) System design and integration to perform broadband spectroscopic measurements and magnetic sensing to capture the unique signatures of various bacterial strains and their specific surface biomarkers. The diagnostic accuracy will be further enhanced with deep learning techniques to extract bacteria-specific features. The integration of both platforms will thus enable rapid and accurate bacterial detection for timely treatment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.