Basalt is a mineral-based, high-performance, sustainable reinforcement with a novel combination of high performance and competitive cost, offering superior chemical durability and thermal stability compared to E-glass, while being significantly more cost-effective than carbon fiber. This review summarises recent advances in “lava-to-lightweight” connecting production of basalt fibers (melt spinning, drawing, and sizing) to composite production pathways, performance and applications. The literature is classified into common design levers: (i) effective length of load transfer (fiber length continuity), (ii) reinforcement architecture and alignment, (iii) engineering of interphase (size, chemical coupling, hierarchical coatings), and (iv) wear, impact and aggressive environments damage and durability pathways. Basalt fiber–reinforced composites exhibit mechanical performance between glass and carbon fiber composites, with tensile strengths up to 417 MPa, higher than natural fiber composites and comparable to or slightly higher than glass fiber composites but lower than carbon fiber composites. This positions basalt fibers as a balanced reinforcement with superior durability and competitive strength-to-cost performance. The strength and stiffness of these composites mainly depend on how the fibers are arranged and fiber-matrix adhesion. Their long-term durability is affected by moisture and chemical ingress into the composite, which can cause the matrix to hydrolyse and weaken the fiber-matrix bond, especially under repeated wet-and-dry conditions. Their application readiness is evaluated across key areas: mobility, aerospace, marine, construction/infrastructure, and electrical/electronic. However, challenges identified include the lack of standardized testing, limited data on long-term performance in real environments, and unclear recycling or disposal options at the end of their service life. Lastly, sustainability factors are summarised for production energy, emissions, and recyclability opportunities, and a roadmap is proposed for scale-up through process monitoring, data-driven optimisation, and qualification standards.
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Olonisakin et al. (2026) studied this question.
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