C2C Assist: A Knowledge Graph-Constrained LLM for Cradle-to-Cradle Product Design

This paper introduces a cradle-to-cradle design assistant that combines a Neo4j knowledge graph with large language model (LLM) reasoning to guide sustainable product development. The graph encodes materials, end-of-life pathways, and design rules, while the LLM generates product-specific recommendations grounded in this structured knowledge. Expert evaluation across five product cases (toothbrush, sunglasses, smoothie maker, coffee machine, and air fryer) shows strong coverage of material health, circularity, and creative design options, but weaker performance in water and soil stewardship, air and climate protection, and overall conceptual consistency. Results demonstrate that graph-LLM integration improves the concreteness and usability of circular design guidance, positioning such systems as valuable partners in sustainable product innovation.