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Mapping sodium-ion battery research to sustainable development goals using machine learning approaches

Publication Type : Review Article

Publisher : Elsevier BV

Source : Journal of Energy Storage

Url : https://doi.org/10.1016/j.est.2025.116910

Keywords : Sustainable development goal, Renewable energy, Energy policy, Nanotechnology, Sodium ion, Battery storage, Machine learning

Campus : Amaravati, Amritapuri, Kochi

School : School of Business

Center : Technologies & Education (AmritaCREATE)

Year : 2025

Abstract : Amidst escalating global energy demands and mounting environmental pressures, sodium-ion batteries (SIBs) have emerged as a compelling alternative to lithium-ion technologies. Leveraging abundant, non-toxic materials, SIBs hold significant promise in advancing the United Nations Sustainable Development Goals (SDGs)—notably SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action). This study presents a comprehensive, multi-layered analysis of SIB research since the Rio + 20 summit, combining bibliometric mapping, BERTopic-based topic modeling, and machine learning-enabled SDG classification. Our findings reveal a clear technological trajectory: from early experimentation with transition metal oxides and titanium-based anodes to more sophisticated innovations including high-entropy cathodes, phosphorus-doped carbon nanorods, Prussian blue analogs, and MXene-integrated composites. These materials exhibit enhanced electrochemical performance, energy density, and cycle life, reflecting a deepening commitment to scalable and efficient storage solutions. Simultaneously, thematic mapping indicates increasing alignment with sustainability priorities—but also underscores emerging tensions between affordability, performance, and material sustainability. Geographically, the field is driven by research leaders such as China, the United States, and Germany, while countries including India, Iran, and Nigeria are expanding their contributions, indicating a growing, if uneven, global research footprint. Although industrial relevance is increasingly reflected through applied research themes, direct evidence of academic–industry collaboration remains limited, signaling an opportunity for deeper engagement. The study also highlights trade-offs across SDGs—for example, between rapid scalability (SDG 7) and lifecycle impacts (SDG 12/15)—that warrant closer scrutiny through policy and regulatory innovation. In response, we propose a future research framework that integrates technological innovation, economic feasibility, environmental sustainability, and governance. This roadmap outlines strategic priorities in eco-design, circularity, equitable deployment, and cross-sector partnerships to guide the responsible acceleration of SIB technologies within global sustainability agendas.

Cite this Research Publication : Raghu Raman, Dhamodaran Santhanagopalan, Dávid Lóránt Dénes, Prema Nedungadi, Seeram Ramakrishna, Krishnashree Achuthan, Mapping sodium-ion battery research to sustainable development goals using machine learning approaches, Journal of Energy Storage, Elsevier BV, 2025, https://doi.org/10.1016/j.est.2025.116910

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