STTR Phase I: Conversion of Low-Value Polyethylene into Surfactant-Relevant Olefins

The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is the development of a thermochemical process that converts high-volume, low-value plastics into valuable chemicals as raw materials for surfactant production. This technology establishes a plastics-to-surfactant pathway and creates a circular materials loop. The process uses controlled temperature gradients under relatively mild reaction conditions to selectively deconstruct polyethylene into smaller polymers with defined chain lengths. This technology would provide a scalable pathway to produce high-value alpha-olefins and related hydrocarbon products used in surfactants, lubricants, adhesives, and plastic additives. This project aims to design and develop a fully automated, continuous process-development reactor for chain-length-selective thermal degradation of mixed polyolefin plastics. The system will utilize a spatial temperature gradient and mild degradation conditions to precisely control the chain-length distribution of hydrocarbon products. It will also investigate the tolerance of various contaminants and additives commonly present in low-value plastics, assessing their impact on process performance at larger scales in a continuous configuration. The project will deploy an automated temperature gradient control system to ensure process repeatability and enable high-throughput combinatorial screening. By refining control over the temperature gradient, the project seeks to optimize reaction product chain length distribution and abundance. Furthermore, it will explore how different temperature profiles influence chain scission kinetics and the resulting product characteristics. Following optimization of yield and product purity, the process will be scaled by a factor of five. 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.