Advancing 3D Printing through Integration of Machine Learning with Algae-Based Biopolymers

Abstract

The integration of machine learning (ML) with algae-derived biopolymers in 3D printing is a burgeoning area with the potential to revolutionize various industries. This review article delves into the challenges and advancements in this field, starting with the critical problem it addresses the need for sustainable and efficient additive manufacturing processes. Algae-based biopolymers, such as alginate and carrageenan, are explored for their viability in 3D printing, highlighting their environmental benefits and technical challenges. The role of ML in enhancing material selection, predictive modeling, and quality control is examined, showcasing how this synergy leads to significant improvements in 3D printing processes. Key findings include the enhanced mechanical properties of algae-based biopolymers and the optimization of printing parameters through ML algorithms. Examples like the use of Spirulina in creating a range of materials and the application of carrageenan in bone tissue engineering are discussed. The conclusion underscores the transformative impact of combining ML with algae-based biopolymers in 3D printing, paving the way for innovative, sustainable solutions in additive manufacturing. Despite existing challenges, this integration holds promise for a future of advanced, eco-friendly manufacturing techniques.