Hernández Valentina, Ibarra Davor, Triana Johan F, Martínez-Soto Bastian, Faúndez Matías, Vasco Diego A, Gordillo Leonardo, Herrera Felipe, García-Herrera Claudio, Garmulewicz Alysia
Department of Management, Faculty of Management and Economics, University of Santiago of Chile (USACH), Avenida Libertador Bernardo O'Higgins 3363, Estación Central, Santiago 9170022, Chile.
Department of Mechanical Engineering, University of Santiago of Chile (USACH), Avenida Libertador Bernardo O'Higgins 3363, Santiago 9170022, Chile.
Materials (Basel). 2022 Jun 1;15(11):3954. doi: 10.3390/ma15113954.
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.
本文聚焦于琼脂生物聚合物薄膜,其有望用于开发可生物降解包装,这是减少塑料污染的一项重要解决方案。目前,关于使用简单增塑剂的琼脂生物聚合物薄膜的机械性能的数据尚缺。本研究采用实验设计方法,分析琼脂 - 甘油生物聚合物薄膜在一系列成分浓度下的强度、弹性和延展性表现。我们的结果表明,通过系统地改变琼脂和甘油的用量,可以实现与配方更复杂的琼脂基材料相当的拉伸性能。我们的研究不仅显著拓宽了关于简单琼脂生物聚合物薄膜可实现的机械性能范围的可用数据量,而且这些数据还可用于指导进一步的优化工作,这些工作从在某些性能维度上表现良好的基本配方开始。我们还发现,特定配方具有与热塑性淀粉(TPS)、丙烯腈 - 丁二烯 - 苯乙烯(ABS)和聚丙烯(PP)相似的拉伸性能,表明其在特定包装应用中的潜在适用性。我们使用实验数据集训练一个神经网络回归模型,该模型根据琼脂生物聚合物薄膜的成分预测其杨氏模量、极限拉伸强度和断裂伸长率。我们的研究结果支持进一步的数据驱动设计和制造工作流程的开发。