NSF Convergence Accelerator Track L: Smartphone Time-Resolved Luminescence Imaging and Detection (STRIDE) for Point-of-Care Diagnostics

Board Of Regents, Nshe, Obo University Of Nevada, Reno, Reno NV

Investigators

Abstract

Point-of-care (POC) sensors are powerful in-field tools to quickly diagnose infectious disease early enough to prevent rapid spread, detect foodborne pathogens in food-chains in real-time to ensure food quality and reduce food waste, distinguish trace biomarkers in cellular/tissue levels to alter physicians for early treatment, etc. With the applications of artificial intelligence (AI) and mobile devices (e.g., smartphones) in POC sensor development, mobile-device-assisted POC sensors with advanced AI are rapidly emerging as an attractive approach to developing POC sensors with improved analytical performance. To overcome challenges encountered by currently available POC sensors, the proposing team recently developed manganese-doped semiconductor nanocrystals that can enable time-resolved luminescence measurement that achieves high sensitivity, a highly desirable sensor property. The goal of this project is to establish a POC platform technology using Smartphone Time-Resolved Luminescence Imaging and Detection (STRIDE) enabled by these nanocrystals and AI, demonstrate its versatile applicability in various bio-detections, and further translate this technology to develop energy-efficient, miniaturized, and portable biochemical sensing applications. The project will generate multiple key intellectual properties as well as a diverse, well-trained, and globally competent workforce in POC technology. Both intellectual properties and workforce will facilitate economic growth, create new employment opportunities, and contribute to US leadership in POC diagnostic technologies. The goal of the proposed work is to establish a marketable POC platform technology using Smartphone Time-Resolved Luminescence Imaging and Detection (STRIDE) enabled by Mn-doped nanocrystals (NCs) and AI. Through the collaboration with academia, a national lab, private sectors, and business centers, the project team seeks to (1) further understand the photophysics of Mn-doped NCs and enhance their optical properties; (2) build a portable, smartphone-based, and AI-assisted time-resolved luminescence measurement (TRLM) instrument with low cost and high sensitivity; (3) establish a POC platform technology that integrates the new smartphone-based and AI-assisted TRLM instrument with Mn-doped NCs specifically for infectious pathogen detection, food quality analysis, and cancer diagnosis; (4) develop an integrated education and workforce development plan; and (5) initiate broad connections with academia/industries to advance the team’s novel technology for scientific collaboration and commercialization. The project will improve health for all by revolutionizing POC care with highly portable, easy to use, low-cost diagnostic tools that provide rapid results, improve access, and promote early detection of infectious diseases, foodborne pathogens, and cancer biomarkers. The workforce trained through this project will contribute to a diverse, globally competent workforce in cutting-edge technologies, and the educational outreach of this project will promote opportunities in robust STEM education for all. 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.