The urgency to transition from linear to circular economic models has spurred growing interest in technologies that enable sustainability. However, prior studies leveraging patent data to track circular economy (CE) innovation have remained fragmented, limited by sectoral silos, regional focus, or reliance on secondary sources. This study addresses these gaps by presenting a comprehensive, cross-sectoral technology roadmap grounded in large-scale patent analytics. The research employs a seven-phase methodology including data mining from 39,145 CE patents, semantic embedding via transformer models, BERTopic-based clustering, logistic lifecycle modeling, and expert panel validation to identify 42 distinct technology clusters. These clusters are positioned across defined innovation lifecycle stages (emergent, growth, mature, saturated) and linked to associated products and market applications. Key findings reveal substantial heterogeneity in CE innovation maturity: while clusters like printer cartridge remanufacturing and valve refurbishment are commercially saturated, others such as power-to-hydrogen and wind-turbine blade circularity remain in early development. The resulting multi-layered roadmap connects technologies to product systems and market sectors across short-, mid-, and long-term horizons. Implications span strategic investment targeting, R&D prioritization, and evidence-based policy design, enabling stakeholders to navigate the complex technological ecosystem of the circular economy more effectively. By offering a scalable, empirically grounded framework that explicitly bridges technology, product, and market layers, this research advances methodological standards for innovation mapping and supports decision-making aligned with circularity and sustainability transitions.
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