关键词: 海水提铀, 人工智能, 探究式教学, 科教融合

Abstract: This paper introduces an inquiry-based teaching-research integrated model, titled “Seeking Uranium Treasures in the Ocean”, which employs the resource utilization of uranium extraction from seawater as the core instructional vehicle. The model is designed to address key challenges in the Nuclear Power Plant Radiochemistry course, including the abstract nature of theoretical content, the limited integration of cutting-edge research into classroom instruction, and insufficient opportunities for student inquiry. The proposed framework follows a progressive teaching pathway comprising problem guidance, intelligent screening, experimental inquiry, and innovative extension. Within this process, frontier topics—such as low-concentration uranium enrichment, interference from competing ions, functional material screening, and adaptability to real seawater conditions—are transformed into structured classroom tasks. Under instructor guidance, students apply methods including machine learning, computational chemistry, and experimental validation to conduct material analysis and performance evaluation. By converting a frontier research topic into a teachable, operable, and assessable learning process, this model enables students to better grasp the practical applications of radiochemistry knowledge while strengthening their competencies in literature retrieval, data analysis, experimental design, mechanistic interpretation, and scientific communication. This study offers a valuable reference for inquiry-based instruction, science-education integration, and digital teaching reform in radiochemistry-related courses.

Key words: Uranium extraction from seawater, Artificial intelligence, Inquiry-based teaching, Science-education integration