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Agar Biopolymer Films for Biodegradable Packaging: A Reference Dataset for Exploring the Limits of Mechanical Performance

Materials 2022 36 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Valentina Hernández-Muñoz, Davor Ibarra-Pérez, Davor Ibarra-Pérez, Johan F. Triana, Valentina Hernández-Muñoz, Bastian Martínez-Soto, Bastian Martínez-Soto, Matías Faúndez, Matías Faúndez, Diego A. Vasco, Alysia Garmulewicz Leonardo Gordillo, Felipe Herrera, Claudio García‐Herrera, Alysia Garmulewicz

Summary

Researchers developed a reference dataset for agar biopolymer films as biodegradable packaging alternatives, systematically testing mechanical performance with different plasticizer concentrations and providing a design-of-experiments framework to help optimize film properties for practical packaging applications.

Polymers
Body Systems

This article focuses on agar biopolymer films that offer promise for developing biodegradable packaging, an important solution for reducing plastics pollution. At present there is a lack of data on the mechanical performance of agar biopolymer films using a simple plasticizer. This study takes a Design of Experiments approach to analyze how agar-glycerin biopolymer films perform across a range of ingredients concentrations in terms of their strength, elasticity, and ductility. Our results demonstrate that by systematically varying the quantity of agar and glycerin, tensile properties can be achieved that are comparable to agar-based materials with more complex formulations. Not only does our study significantly broaden the amount of data available on the range of mechanical performance that can be achieved with simple agar biopolymer films, but the data can also be used to guide further optimization efforts that start with a basic formulation that performs well on certain property dimensions. We also find that select formulations have similar tensile properties to thermoplastic starch (TPS), acrylonitrile butadiene styrene (ABS), and polypropylene (PP), indicating potential suitability for select packaging applications. We use our experimental dataset to train a neural network regression model that predicts the Young's modulus, ultimate tensile strength, and elongation at break of agar biopolymer films given their composition. Our findings support the development of further data-driven design and fabrication workflows.

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