AI-DRIVEN OPTIMIZATION OF HYBRID BORON-CARBON FIBER COMPOSITES FOR AEROSPACE APPLICATIONS: A BREAKTHROUGH IN COMPRESSION-DOMINATED STRUCTURES

Aerospace composite structures have reached a fundamental performance plateau1, constrained by the inherent compression weakness of carbon fiber composites that limit structural efficiency in weight-critical applications. We present an AI-driven optimization framework that systematically addresses this three-decade stagnation through strategic hybridization of boron and carbon fibers. By characterizing twelve material configurations with precisely controlled architectures, we achieved unprecedented open-hole compression strength improvements of 94-107% compared to aerospace-grade carbon fiber composites. The optimized hybrid system exhibits a perfect balance between tension and compression properties (Open Hole Tension/Open Hole Compression ratio = 1.001) at a boron-to-carbon ratio of 0.73 and 65% total fiber volume fraction. Our validated AI models (R² > 0.87) accurately predicted this optimization landscape while revealing fundamental structure-property relationships. Enhanced boron fibers with reduced tungsten core diameter (9.6μm) demonstrated 16.9% improved tensile strength with 4.5% density reduction. This breakthrough enables greater than 20% weight savings in compression-dominated structures, representing the first disruptive advancement in aerospace polymer-matrix composites since carbon fiber implementation in the 1980s.