Data from: Sustainable manufacturing and tensile strength of aerospace geopolymers reinforced with carbon and basalt fabrics

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Authors: Edgar Adrián Franco Urquiza, Victor A. Gomez-Culebro, Tomas Madera-Santana, Cecilia D. Treviño‐Quintanilla, Gabriel Luna‐Bárcenas, D. Mendoza-Cachú
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Abstract

Geopolymer composites reinforced with plain weave carbon fiber and basalt fabrics were developed and characterized to evaluate their viability in the aerospace sector. The geopolymer matrix was synthesized from alkali-activated metakaolin, and the composites were manufactured via manual impregnation and compression molding. The influence of fiber type and geopolymer content on volumetric shrinkage, tensile mechanical behavior, flammability, and cosmic radiation resistance was analyzed. The results show that the fiber fabrics significantly restrict the volumetric shrinkage of the geopolymer matrix, maintaining the dimensional stability of the manufactured panels. The carbon fiber-reinforced composites exhibited significantly higher elastic modulus and tensile strength values than the basalt fiber-reinforced composites, reaching maximum strengths on the order of 200 MPa. Furthermore, a higher geopolymer matrix content was observed to enhance the mechanical performance of the composites. Flammability tests demonstrated that all evaluated materials exhibited complete fire resistance and self-extinguishing behavior, regardless of reinforcement type. Furthermore, gamma irradiation did not produce significant changes in the samples' chromatic parameters, indicating adequate resistance to radioactive environments. Taken together, the results confirm the high potential of these advanced and sustainable structural composites for aerospace applications.

Fields of Study & Subjects

Concrete and Cement Materials Research Advanced ceramic materials synthesis Material Properties and Applications

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
10 February 2026
Language
EN
Document type
Dataset