Fabrication of iron-based multiporous structures by combining in-situ reduction with sintering
Source abstract
Abstract
Porous iron-based materials are attractive for structural, acoustic, and thermal management applications due to their low cost, availability, and tunable performance. This study introduces a simple and cost-effective route for fabricating multiporous iron structures by combining in-situ reduction and sintering of hematite (Fe 2 O 3 ) powders with graphite as space holder. The approach integrates submicrometric iron oxide powders with granulated space-holder, yielding a dual-scale architecture of nanopores within the struts and micrometric pores replicating graphite morphology. Complete removal of the space holder was achieved at ≥800 °C with relatively fast heating rates (5 °C/min). Subsequent hydrogen treatment promoted complete reduction of hematite to metallic iron across the 850–1050 °C range, as confirmed by XRD and mass loss analyses. Based on thermogravimetric analysis data, kinetic parameters were determined and Avrami-Erofeev equation was found most suitable for describing each reduction step. Microstructural characterization revealed that densification of the struts is strongly dependent on sintering temperature and the phase-specific diffusion coefficients of iron. A non-monotonic mechanical response was observed across the temperature range, explained by the interplay between reduction kinetics, pore evolution, and phase-dependent diffusion. These findings demonstrate that porous iron structures can be tailored through space-holder engineering and submicrometric oxide powders combined with in-situ reduction–sintering. The methodology provides a scalable pathway for producing iron-based multiporous materials with controlled porosity and optimal mechanical strength.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Iron and Steelmaking Processes · Advanced materials and composites · Heat and Mass Transfer in Porous Media
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (34)
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