国芯网[原:中国半导体论坛] 振兴国产半导体产业！ 不拘中国、 放眼世界 ！ 关注 世界半导体论坛 ↓ ↓ ↓ 各有关单位 : 材料工业是国民经济的基础产业，新材料是材料工业发展的先导，人工智能与材料科学的 结合应用已经成为推动科技创新和工业进步的重要力量。为重塑材料科学研究新范式，推动人 工智能 + 材料科学交叉型复合人才培养，我中心将继续举办 " 人工智能赋能材料科学关键技 术应用 " 高级研修班。现将有关事宜通知如下。 一、研修内容 1. 人工智能引领材料科学发展新范式 ; 2. 人工智能赋能材料数据的获取、处理与标准化 ; 3. 人工智能助力新材料发现与设计 ; 4. 人工智能赋能材料结构与性能预测 ; 5. 人工智能在材料表征与检测中的应用 : 6. 多尺度高通量计算在材料科学中的应用 ; 7. 基于人工智能的材料科学自动化实验与设计 ; 8. 人工智能赋能材料科学核心技术原理简述 ; 9. 基于机器学习的材料科学领域应用与实践 : 10. 深度学习在材料科学中的应用与案例解析 ; 11. 强化学习赋能材料科学关键技术应用 ; 12. 神经形态与类脑计算在材料科学中的应用 : AI正在改变材料科学的 ...

Core Insights - The materials industry is at a critical historical juncture, requiring a transformation to leverage AI technology for overcoming development bottlenecks and advancing from a materials power to a materials stronghold [1][3]. Group 1: AI-Driven Material Innovation - AI is enhancing material innovation by enabling rapid iteration, atomic-level manufacturing, and breakthroughs in high-stability materials for extreme environments [3][4]. - Emerging industries such as new energy and robotics are creating new demands for high-end materials, including advanced polyolefins and biodegradable materials [3][4]. - Material innovation is pivotal in the intersection of AI and the new technological revolution, with China positioned to transition from "catching up" to "leading" in this field [3][4]. Group 2: Industrial Paradigm Shift - AI is driving a systemic reconstruction of industrial development paradigms, particularly in the materials sector, through three dimensions: technological innovation, production manufacturing, and organizational management [4][5]. - The shift from traditional experience-based R&D to AI-driven digital and intelligent processes significantly enhances efficiency and precision in material design and testing [4][5]. - AI facilitates real-time global optimization in manufacturing, transforming production models from discrete to continuous and proactive [5]. Group 3: New Research Paradigms in Material Science - The materials science research paradigm is undergoing a fourth transformation, evolving from experience-driven to data and AI-driven approaches [6][8]. - Global practices demonstrate the disruptive value of AI in material research, with significant advancements in predicting new materials and optimizing existing ones [6][8]. Group 4: Empowering New Material Production and Applications - AI is transitioning the new materials industry from single-segment optimization to collaborative lifecycle applications, addressing core pain points in production and management [8][9]. - The materials industry is expected to see three major trends: reduced R&D costs, intelligent manufacturing, and the emergence of a digital twin ecosystem [8][9]. Group 5: Systematic Implementation Pathways - To harness AI's strategic value, a systematic implementation pathway is necessary, including data governance, high-quality data set construction, and a national materials data space [10][11]. - Establishing a layered AI model system and enhancing AI literacy among industry professionals are crucial for supporting the intelligent transformation of the materials sector [10][11]. Group 6: Future Outlook - The materials industry in China is poised for a revolutionary era of innovation driven by AI, with significant reductions in R&D cycles and production costs, ultimately supporting the nation's goals of becoming a manufacturing and technological powerhouse [12].