Collaborative Research: DESC: Type 1: Software-Hardware Recycling and Repair Dataset Infrastructure (SHReDI) for Sustainable Computing

Electronic waste (e-waste) is the fastest-growing waste stream worldwide, with a significant portion ending up in landfills. This is particularly concerning since electronics manufacturing uses materials from regions with insufficient environmental and social safeguards. Furthermore, valuable materials in e-waste, including gold, silver, copper, and platinum, are often consigned to burning or landfills. This collaborative project aims to enhance e-waste recovery by transforming electronics design practices and optimizing e-waste logistics. The project’s novelties are in the development of low-cost wireless tags and computational models for accurately quantifying the costs and environmental impacts associated with e-waste recovery and recycling. Researchers at Oregon State University and the University of Florida will develop wireless tags that will provide recyclers with easy-to-read information about material types, quantities, and recommended recycling processes based on the decision-making models developed during this project. The project’s impacts are higher recycling rates and improved recycling efficiency for electronic waste. Additionally, the tag information will allow tracking of recycled e-waste based on producers, enabling public policy that accurately assigns recycling costs to electronics manufacturers. The project also includes a wide range of educational and outreach activities, emphasizing mentoring students from underrepresented groups and enhancing access to research outcomes through curriculum development, K-12 outreach, and undergraduate summer research experiences. The research objective of this project is to develop an integrated circuit (IC) hardware system, along with data collection and decision support metrics, to establish a quantitative information ecosystem for electronic device reuse and recycling. This collaborative project brings together investigators with complementary expertise in integrated circuit design, sustainable manufacturing, remanufacturing, and e-waste management. The project envisions leveraging critical device data such as material content and usage behavior to quantify reusability metrics and develop decision-making models to inform consumers, repairers, and recyclers on end-of-use strategies. The integrated hardware-and-modeling research tasks will extend the boundaries of active radio-frequency ID (RFID) design and enable mathematical models for critical constraints imposed by e-waste reverse logistics. By utilizing individual device data from RFID tags, decision-making models will be developed to enhance remanufacturing operations and formulate strategies for managing producer responsibility more effectively. By combining highly scalable and easily deployable hardware with end-of-life decision support models, the project will demonstrate the feasibility of a circular ecosystem that can significantly increase the reuse and recovery rates of e-waste. 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: 2621968 | Program: 01002324DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Arun Natarajan | Institution: Yale University, NEW HAVEN, CT | Award Amount: $345,792 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2621968 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2621968.html