Volume 16 Issue 8
Published on August 2025The emergence of AI technology has brought about tremendous changes in human life. The traditional ways of working and living in the past have been further optimized by AI, evolving into more advanced forms of development. In terms of sustainable development, artificial intelligence technology has shown promising prospects, paving the way for increasingly long-term and viable progress in the future. This paper adopts a combined research approach, integrating literature review, case analysis, and qualitative research, to systematically explore the technological application paths and practical challenges of artificial intelligence in the field of sustainable development. While AI provides robust technical support for sustainable development, this paper argues that it is crucial to balance efficiency improvements with ethical risks through technical iterations, upgrading human skills, and optimizing policy frameworks. By doing so, we can achieve in-depth optimization of human-machine collaboration and promote long-term, sustainable development.
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This paper provides a comprehensive review of supercapacitors as an emerging energy storage device, highlighting the various issues and challenges they face. It discusses the progress in energy storage mechanisms, electrode materials, electrolytes, separator materials, and practical applications. The paper summarizes the advantages and disadvantages of electric double-layer capacitance, pseudocapacitance, and hybrid capacitance mechanisms. It evaluates the application prospects of carbon-based materials, metal oxides, and conductive polymers in electrode design; the optimization strategies for aqueous electrolytes, organic electrolytes, and ionic liquids; and the application requirements for biomass-based separators, synthetic polymer-based separators, and inorganic composite separators. In practical applications, supercapacitors demonstrate their function as high-energy storage devices and have shown promising integration in vehicular batteries and lithium-ion battery systems.
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In the context of rapid digital transformation, artificial intelligence (AI) and big data have become pivotal forces reshaping decision-making processes across industries such as healthcare, finance, retail, manufacturing, and transportation. This paper investigates the integration of AI and big data, aiming to explore their combined impact on organizational efficiency and predictive accuracy. The research adopts a comprehensive literature review methodology, analyzing scholarly articles, industry reports, and real-world applications to evaluate how these technologies are applied, the challenges they present, and future directions. Through this method, the study identifies key trends in the deployment of AI-powered analytics, including predictive modeling, personalized services, and automated operations. It also addresses critical issues such as ethical concerns, data security, and scalability. The findings suggest that while AI and big data significantly enhance operational performance, their responsible implementation requires robust frameworks for fairness, transparency, and privacy protection. This study concludes by emphasizing the need for collaborative efforts among governments, academia, and industry to ensure equitable access and sustainable technological advancement.
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