Bio-based rigid polyurethane foam from castor oil with excellent flame retardancy and high insulation capacity via cooperation with carbon-based materials
Source abstract
Abstract
In this work, we prepared the biomass castor oil-based rigid polyurethane foams (RPUF). The two bio-based RPUFs contain modified polyols from castor oil, one of which was transamidated castor oil with diethanolamine (BIO1) and another was further modified epoxidized polyols in BIO1 with phenylphosphonic acid. The cellular structure, thermal, flame retardant and mechanical properties of RPUF via incorporation of expandable graphite (EG) and graphene oxide (GO) on a total fixed amount of 6 wt% were studied by scanning electron microscopy (SEM), thermal conductivity, limiting oxygen index (LOI), vertical burning test (UL94) and cone calorimeter test (CCT), etc. The cellular structure indicated that GO facilitates the dispersion of EG and decreases the cell size of the foam. The thermal and fire behaviors indicated that GO increased the insulation capacity and the flame-retardant performance of RPUFs. The optimal sample BIO2/EG/GO obtained V-0 rating, whereas BIO2/EG obtained only V-2 rating on the UL94 test. Moreover, results from CCT showed that the BIO2/EG/GO effectively reduced heat release rate (HRR), total heat release (THR) and total smoke production (TSP) by 54%, 24% and 15%, respectively, in comparison with BIO1 and decreased the HRR and THR 46% and 6%, respectively, compared to BIO2 sample. The compressive performance of BIO2/EG/GO and BIO2/EG increased to 0.11 MPa compared to 0.07 MPa from BIO1. These interesting results proved a new strategy to develop a bio-based flame-retardant RPUF as fire safety thermal insulation materials by incorporating natural-based carbon materials.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Flame retardant materials and properties · Polymer composites and self-healing · Fire dynamics and safety research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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