Smart Re-Manufacturing of Recycled Plastics and Polymers using Sensor-based and High-throughput Experimentation Formats

The emergence of a circular economy associated with products derived from recycled plastics and polymers and the continued demand for creating sustainable polymer manufacturing systems has provided new opportunities and incentives for the quality-controlled re-processing and manufacturing of recycled materials, such as recycled plastics and polymer, such as using smart manufacturing principles. Likewise, there remains a need to identify environmentally benign (i.e., green) material formulations and processes for sustainable re-manufacturing based on smart manufacturing principles of sensing, automation, and data analytics. However, traditional approaches for process monitoring of plastic re-manufacturing operations are generally limited with respect to lack of online sensing technology for characterization of the reprocessed polymer material's quality, specifically composition and properties, and lack of rapid, efficient, and high-throughput experimental-based material screening and design are foundational challenges that limit industrial progress. Toward addressing these challenges, the United States started the Materials Genome Initiative aims to accelerate the pace and efficiency of discovering new materials, such as derived from recycled plastics and polymers, through the creation of new experimental tools and processes, such as for autonomous experimentation. While progress has been made in several material domains, including electronic and soft materials, relative less work has been done in the area of recycled plastics and polymers, such as for diverse materials, including electrospun or structural materials used in tissue engineering or construction applications, respectively.A key factor motivating this work is the limited availability of experimental tools, particularly sensing platforms capable of enabling process monitoring and material synthesis, characterization, and screening in integrated online, low-volume, and high-throughput formats for polymeric waste. This dissertation expands the online sensing and high-throughput screening tools smart re-processing and -manufacturing of recycled plastics and polymer, with particular focus on solvent-based re-processing methods. In particular, this dissertation is driven by a novel platform sensing technology of the piezoelectric-excited milli-cantilever (PEMC), which exhibits a self-exciting and sensing design and dip-stick form factor that enables the monitoring and characterization of recycled polymers and plastics in on-line, low-volume, and high-throughput formats. By characterizing the dynamic and net change responses of PEMC sensors after 60 minutes of electrospun material deposition, this study established performance metrics to evaluate polymer solutions, thermoplastic coatings, and solvent-based polymer re-processing applications. Next, PEMC sensors were leveraged for screening of composition-property relations of polymer-reinforced concrete using a low-volume measurement format, extending the applications of PEMC sensors to characterization of composite structural materials with recycled polymers. Finally, leveraging the established dynamic range for solvent and composite based recycling, PEMC sensors were utilized in a low-volume, high-throughput format to screen green solvents and blend formulations for polymeric waste. This dissertation advances a sensing platform technology based on piezoelectric milli-cantilevers for the accelerated discovery and engineering of recycled materials, particularly in solvent and composite systems

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Macromolecular Science and Engineering

Department dc:contributor.department

Graduate School

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2026

Author dc:creator

• Anderson, Lester

Chair dc:contributor.committeechair

• Johnson, Blake

Committee members dc:contributor.committeemember

• Kong, Zhenyu
• Jia, Xiaoting
• Goldstein, Aaron S.

• sensing
• high-throughput experimentation
• Materials Genome Initiative
• recycled materials
• green solvents
• sustainable manufacturing
• re-manufacturing
• re-processing
• process monitoring
• material design
• circular economy

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:45140

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/141130