From Sustainable Materials to User-Centered Sustainability: Material Experience in Art Healing

Abstract

This study develops sustainable materials using hydrogel as the matrix and explores the transition from sustainable materials to user-centered sustainability, with a particular focus on achieving art healing through material experience. The findings reveal that "Aesthetic" property exert the greatest influence on art healing in the context of multimodal material experiences involving visual, tactile, and smell, followed by "Intrinsic" property, whereas "Physical" property have a comparatively limited effect. Furthermore, the study proposes a material experience framework that enables designers to systematically and holistically understanding material characteristics. It highlights the importance of considering users' psychological perceptions and emotional needs in the material design process.

Figures (6)

• Figure 1: A conceptual Framework Based on Material Experience: The Evolution from Sustainable Materials to User-Centered Sustainability
• Figure 2: Sustainable Material Design for Art Healing. Sustainable materials are prepared by adding sustainable fillers to hydrogel matrix. A total of 28 sustainable materials, including one non-filler only matrix and 27 composites were prepared
• Figure 3: Exploring the Transition from Sustainable Materials to User-Centered Sustainability through Art Healing: Structural Equation Modeling Path Diagram
• Figure 4: Results of hierarchical cluster analysis based on intergroup linkage method with Squared Euclidean Distance, based on the characteristics of the three factors, a total of seven clusters and eleven sub-clusters were identified. Cluster A consists of wood and fruit residues (fine particles, coarse particles). Cluster B includes seaweed and dried fruits and nuts. Cluster C comprises traditional Chinese medicine residues. Cluster D contains leather. Cluster E includes unfilled materials, bagasse, soybeans, and mung beans. Cluster F consists of wood (with spatial structure). Cluster G includes fibrous and flaky plants
• Figure 5: The upper section shows the mean factor score distribution of the 28 stimuli across the three factors, as well as their projections onto two-dimensional planes formed by each pair of factors. The resulting from the hierarchical cluster analysis is also labeled. The lower section presents the results of the correlation analysis between each pair of factors and the distribution of the stimuli