Scalable Manufacturing of Smart Sensors for Visual Detection of Hazardous Chemicals

This award supports the development of a new class of low-cost, reusable, user-friendly sensors that can visually detect hazardous chemicals through distinct color changes. Sensors are essential in modern society for applications ranging from environmental monitoring and threat detection to medical diagnostics and industrial process control. However, many existing technologies depend on complex instrumentation, are costly, and require specialized training, limiting their accessibility in real-world settings. This project addresses this gap by creating simple, portable sensors capable of detecting harmful substances in air and solid matrices, including toxic plasticizers in consumer plastics and volatile chemicals in the environment. These smart, color-changing sensors will provide immediate visual feedback without the need for external power or sophisticated equipment, enabling widespread deployment in homes, workplaces, and resource-limited environments. Beyond improving public health and safety, the project will strengthen manufacturing innovation, support workforce development through interdisciplinary training in advanced manufacturing and materials engineering, accelerate technology transfer through partnerships with industry, and broaden participation in science through outreach activities. The outcomes are expected to contribute to national health, economic competitiveness, and technological leadership. The project will establish a scalable manufacturing platform for chromogenic sensors by integrating macroporous photonic crystal architecture with multi-stimuli-responsive shape memory polymers. The research will pursue three interconnected objectives: (1) develop a continuous doctor blade coating process for high-throughput fabrication of nanostructured sensor films; (2) elucidate processing–structure–property relationships through systematic experimentation, nanomechanical characterization, and coupled analytical and numerical modeling; and (3) design and evaluate sensor prototypes for detecting analytes in solid matrices and vapor phases. The sensors function through analyte-triggered nanoscale structural recovery in the smart shape memory polymers, resulting in controlled shifts in photonic crystal spacing and corresponding structural color changes. Experimental methods will be complemented by fluid dynamics modeling of the coating process and multiphysics finite element simulations of coupled mechanical, transport, and nanooptical phenomena. The project will also employ in-situ optical techniques to monitor real-time chromogenic transitions and nanoscale structural evolution during analyte exposure. Expected outcomes include fundamental insights into nontraditional, athermal shape memory behavior, process-informed design principles for scalable manufacturing of functional nanostructured materials, and high-performance chromogenic sensor systems with enhanced sensitivity, selectivity, and durability. 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. NSF Award ID: 2537626 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Peng Jiang | Institution: University of Florida, GAINESVILLE, FL | Award Amount: $500,000 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2537626 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2537626.html