Abstract

Forest ecosystems play a significant role in mitigating global warming, primarily because wood is recognized as a crucial natural material for capturing carbon. However, the increasing global demand for wood conflicts with the idea of sustainable carbon capture, emphasizing the importance of recycling waste wood and utilizing it in multiple ways. Despite the potential of wood fibers to strengthen composites, the complexity of their preparation and their natural sugar content limit their applications in recycling waste wood. This study combines the Random Forest and NSGA II algorithms for comprehensive multi-objective optimization, focusing on enhancing the strength, resilience, and carbon capture capabilities of composites. In-depth microstructural analyses, along with elemental mapping, clarify how wood fibers contribute to toughening and resistance to cracking, affirming their vital role in improving the mechanical properties of composites. The study determined the optimal mixing ratio and mechanism of action of NaOH and CH3COOH treatments. The Pareto solution set derived from the algorithm aids intricate multi-objective balance analyses. Notably, discrepancies between experimental and optimized values remain minimal, and were recorded at 1.03%, 0.85%, 1.76%, and 2.31%, respectively, thus reinforcing model precision and trustworthiness. Cementitious wood fiber composites' merits set the stage for sustainable product innovations, transitioning theoretical insights into eco-conscious practical applications.

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