# Multicriteria Decision Analysis of the Influence of Natural Fibers on the Flexibility of Renewable Polyurethane Composites

## TL;DR

This paper studies how natural fibers affect the flexibility of renewable polyurethane composites using various tests and decision analysis.

## Contribution

A novel combination of subjective and multicriteria decision analysis is used to evaluate composite flexibility influenced by natural fibers.

## Key findings

- PU composites with cellulose fiber showed higher thermal stability, tensile strength, and lower flammability.
- PU/CF composites with 60/40 and 70/30 wt/wt% ratios were most suitable for flexible applications.
- Long coir fiber composites performed better than ground coir fiber in flexibility-related properties.

## Abstract

Renewable polyurethane (PU) composites were developed using castor oil and long coir (LCF), ground coir (GCF) or cellulose fiber (CF) at PU/fiber ratios of 50/50, 60/40 and 70/30 wt/wt%, respectively. The aim was to study the influence of natural fibers on composite flexibility via thermogravimetry, differential scanning calorimetry, scanning electron microscopy and water absorption, density, tensile strength, flexural and flammability tests. The set of properties was evaluated (1) subjectively by assigning importance values to the different properties and (2) via multicriteria decision analysis (MCDA). In general, the PU composites with cellulose fiber (PU/CF) exhibited higher thermal degradation temperatures, greater tensile moduli and toughness and less flammability. The composites with the best results for both analysis methods (property set analysis) were PU/CF:60/40 wt/wt% and 70/30 wt/wt%, obtained with cellulose fiber (low lignin content) and the highest PU percentage; these were the most suitable for applications that require flexibility, such as in interior design. When comparing the different coir fiber sizes, the composites containing more long coir fiber (PU/LCF 60/40 wt/wt% and 70/30 wt/wt%) presented the best results. The results of subjective property set analysis were validated using multicriteria analysis, resulting in a simple analysis for application.