Issue 4, 2024

Castor-oil biobased foam: the effect of the composition on the physical and mechanical properties via a statistical mixture design

Abstract

PU foams are versatile materials that find applications in a wide range of products, from upholstery to packaging and construction. These foams consist primarily of two components, polyol and prepolymer, and their concentrations play a crucial role in determining their physical and mechanical properties. A second-order mixture design approach is used in this work to identify the significant components and their contributions on the physical–mechanical properties of biodegradable castor oil-based foams. The experimental design includes three components: two types of polyols and one prepolymer. These components are varied in nine distinct conditions to evaluate their effects on properties such as expansion rate, bulk density, compressive strength, and tensile strength. The Scheffé's quadratic model coefficients exhibit R-squared values higher than 0.84 in most cases. Chemical analysis using infrared spectroscopy confirms the successful formation of the urethane bond during the manufacturing process. The biobased foams developed in this work have densities ranging between 61 and 100 kg m−3, compressive modulus of 11–15 MPa and compressive strength between 273 and 429 kPa. The tensile modulus varies between 3.2 and 4.9 MPa, with a tensile strength in the range of 370–500 kPa. These results highlight the potential of biodegradable castor oil-based foams as promising alternative materials to traditional synthetic foams.

Graphical abstract: Castor-oil biobased foam: the effect of the composition on the physical and mechanical properties via a statistical mixture design

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Article information

Article type
Paper
Submitted
17 Okt. 2023
Accepted
19 Janv. 2024
First published
24 Janv. 2024
This article is Open Access
Creative Commons BY license

RSC Sustain., 2024,2, 975-987

Castor-oil biobased foam: the effect of the composition on the physical and mechanical properties via a statistical mixture design

L. F. Soares, J. César dos Santos, V. A. Araújo de Freitas, R. B. Dutra Pereira, T. H. Panzera and F. Scarpa, RSC Sustain., 2024, 2, 975 DOI: 10.1039/D3SU00374D

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