Micromechanical Modeling‐Guided Genetic Algorithm Optimization of Alfa‐Fiber/Polypropylene Biocomposites Toward a Glass‐Fiber Stiffness Benchmark

Alfa fiber–reinforced polypropylene (PP) biocomposites were developed as recyclable, lower‐density alternatives to polypropylene containing 30 wt% glass fiber (PP–GF30), addressing weakly validated links between fiber fraction, retained aspect ratio and interfacial coupling that often constrain formulation design. A compact design‐of‐experiments (DOE)–physics–optimization workflow was implemented to deliver a formulation‐explicit route to glass‐fiber‐class stiffness. Materials were melt‐compounded and injection‐molded using a Taguchi L9 plan varying Alfa content (5–30 wt%), maleic‐anhydride‐grafted polypropylene (MAPP) compatibiliser (0–8 wt%) and nominal fiber length (1–5 mm), and tensile properties were measured (ISO 527‐2). Stiffness was governed primarily by fiber volume fraction and retained aspect ratio, strength increased with MAPP‐enhanced load transfer, and ductility decreased with fiber loading but was partly preserved at intermediate MAPP levels. Physics‐informed micromechanical surrogates reproduced experimental means with ~1.1% mean absolute error for Young's modulus, ≤ 2.4% for ultimate tensile strength at higher fiber levels and ≤ 10.1% for elongation at break, enabling constrained genetic algorithm optimization in an extended formulation space beyond the Taguchi levels. The optimum candidate (44.1 wt% Alfa, 3.0 wt% MAPP, 5.0 mm nominal fiber length) achieved 7.0 GPa modulus, 59.9 MPa strength and 1.99% elongation at break at 1.059 g cm −3 , matching PP–GF30 stiffness with a 5.4% density reduction.