Session: 13-03-01: General: Mechanics of Solids, Structures and Fluids I

Paper Number: 167219

Suppressing Mechanical Property Variability in Recycled Plastics via Bio-Inspired Design 

The escalating plastic waste crisis demands urgent global action, yet mechanical recycling—the most prevalent strategy—is severely underutilized. Only a small fraction of total plastic waste undergoes mechanical recycling, primarily due to significant variability in the recycled plastics’ mechanical properties. This inconsistency stems from compositional fluctuations and impurities introduced throughout the material’s lifecycle and the recycling process. Such variability deters industries with strict performance specifications from adopting recycled plastics on a broader scale, undermining sustainability initiatives.

In this talk I will present a bio-inspired composite design approach that suppresses mechanical property variability in recycled plastics. Drawing inspiration from natural materials like nacre, which achieve exceptional mechanical performance despite inherent randomness, our strategy integrates stiff recycled plastic platelets with soft polymeric interfaces. This “brick-and-mortar” architecture not only mitigates the detrimental effects of compositional fluctuations and impurities but also delivers a material performance that rivals that of virgin plastics.

The first segment of the talk will introduce the fundamental framework and underlying mechanics of our bio-inspired design. We will detail a tension-shear-chain model that captures the deformation mechanisms and failure modes of the composite structure under uniaxial tension. By carefully selecting network size, platelet dimensions, and interfacial mechanical properties, our design achieves enhanced stiffness and improved conformability while effectively suppressing material randomness. Our simulations reveal that this approach yields up to an 89.5% reduction in the variability of the effective elastic modulus and a 42% decrease in the variability of elongation at break, all while preserving critical mechanical properties such as the elastic modulus.

The second segment of the talk will showcase experimental results and include a case study on industrial stretch wrap. Here, we demonstrate how the composite structure meets stringent performance requirements by delivering consistent stiffness and enhanced conformability for complex shapes. We will discuss the experimental protocols, data analysis, and validation efforts that confirm the robustness of our model. In doing so, we highlight how our chemistry-agnostic, mechanics-based approach offers a scalable solution that circumvents the limitations of traditional, chemistry-specific modifications.

Overall, this talk will illustrate how combining fundamental mechanics with bio-inspired design strategies paves the way for a new era of recycled plastics that offer predictable and reliable performance. This interdisciplinary approach holds immense potential to significantly expand the applications of recycled materials, thereby promoting sustainability and resource efficiency across diverse industrial sectors. By harnessing nature’s time-tested design principles, we can overcome longstanding challenges in recycled plastics and drive transformative advancements in material mechanics and environmental stewardship.

Presenting Author: Christos Athanasiou Georgia Tech

Presenting Author Biography: Prof. Athanasiou is an expert in the field of mechanics of materials having achieved unique contributions by combining advanced characterization methods with artificial intelligence to enable accurate fracture behavior predictions of complex materials. He is an expert in designing customized characterization methods and performing mechanical testing across multiple material length scales and under complex environmental conditions. His current focus is on investigating the mechanics of sustainable materials and structures, contributing to the net-zero 2050 target.

Authors:

Christos Athanasiou Georgia Tech
Dimitrios Georgiou Georgia Tech
Danqi Sun Georgia Tech
Xing Liu New Jersey Institute of Technology