Fuente: Journal of applied polymer Lugar: RESEARCH ARTICLE Box 1—Material design

○Polymer matrices: PP, ABS.
○Bio-additives: coffee dust (2%), tea fiber (2%).
○Reinforcement: glass fiber (12%).

Box 2—Composite fabrication

○Injection molding process.
○Developed composites: PPC, PPCGF, ABSTF, ABSTFG.

Box 3—Characterization and data analytics

○Mechanical tests: tensile, flexural, impact.
○Data processing using Python and machine learning.
○Correlation analysis and PCA.

Box 4—Key outcome

○Glass fiber significantly enhances stiffness and strength.
○Bio-additives enable sustainable polymer composites suitable for kitchenware applications.



ABSTRACT
The escalating global consumption of plastics necessitates a paradigm shift toward sustainable materials that do not compromise on performance. This research pioneers the development of bio-additive polymer composites for kitchenware, employing a data-driven methodology to optimize their formulation and properties. Four distinct composites were engineered using polypropylene (PP) and acrylonitrile butadiene styrene (ABS) matrices, bio-enhanced with coffee dust or tea fiber (2%), and reinforced with glass fiber (12%). These formulations PPC, PPCGF, ABSTF, and ABSTFG were fabricated via injection molding and rigorously characterized through tensile, flexural, and impact testing. A cornerstone of this study was the implementation of a Python-based analytical framework for the critical evaluation of the sample data. Custom algorithms were developed to process and correlate the multi-faceted experimental results, mechanical properties, melt flow, and 3D optical dimensions. This computational approach enabled the application of machine learning models to identify optimal process parameters and predict mechanical performance. Furthermore, correlation analysis and principal component analysis (PCA) quantitatively deconstructed the complex interplay of material constituents, validating the dominant role of glass fiber in enhancing composite stiffness and strength. The findings not only demonstrate a viable pathway for high-performance, eco-compatible composites but also establish a robust digital blueprint for accelerated material innovation.