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中国又出黑马?4大钢铁技术问世,登顶成世界第一,美日求合作
Sou Hu Cai Jing· 2025-08-29 07:41
先说轻量化的"高韧低密度钢"——这玩意听起来有点像科幻材料,密度比普通钢低了10%,但强度和韧性却几乎没打折。中信泰富联手北方材料研究院,仅 用不到三年就把它从实验室搬进了工厂。2022年实现量产,成本还压到了不锈钢的水平。 这可不是纸上谈兵。国际上,日本早在2005年就启动了类似项目,韩国浦项也试过,但都没能量产。美国甚至砸下2000万美元,预计2025年才摸到门槛。这 意味着,中国领先的至少是一个"五年计划"的距离。航空航天、汽车、船舶等行业都在抢着要,美日企业也不扭捏了,纷纷上门谈授权合作。 在全球钢铁的牌桌上,中国又一次打出了一手王炸。不是靠价格战,也不是靠产量堆出来的优势,而是靠硬核技术——四项突破性的钢铁创新接连问世,让 原本由美日主导的高端钢铁格局突然变天。 世界第一,不再只是产量上的虚名,而是技术实打实的领先。更有意思的是,曾经高高在上的西方巨头,如今开始主动敲门来谈合作。 长期以来,中国钢铁产业给人的印象就是"多":年产量超过全球一半,堆得起山也铺得满地。可在高端领域,却总是差了口气,不是被卡脖子,就是被拒之 门外。 但这几年,中国钢铁突然发力,不是一个点的突破,而是四项核心技术齐头并进,从 ...
东北大学王国栋院士团队:探索钢铁生产的AI新路径
Xin Hua She· 2025-06-20 03:24
Core Viewpoint - The article highlights the efforts of a research team led by Wang Guodong at Northeast University to innovate and digitize the steel production process, emphasizing the importance of AI integration in addressing industry challenges and enhancing production efficiency [1][2][3]. Group 1: Digital Transformation in Steel Industry - The digital production line being developed allows for flexible production of different steel types and specifications under the same composition system, with plans to establish about 20 integrated digital model lines in the next five years [1]. - The team has been working on creating a digital twin model to accurately depict the "black box" of steel production processes, enabling deep learning applications in the industry [2]. Group 2: Technological Innovations and Benefits - The intelligent system developed for blast furnace ironmaking has been implemented at a steel plant, resulting in a 30% improvement in furnace temperature stability and a 5% reduction in CO2 emissions per ton of iron, generating an annual benefit of 120 million yuan [2]. - The research center has focused on disruptive and cutting-edge technologies, achieving advancements in digital ironmaking, smart blast furnaces, and generative AI hot rolling production lines [2]. Group 3: Collaborative Research and Future Outlook - A collaborative model involving scientists and engineers has been established, allowing for seamless integration of research outcomes into production operations, thereby enhancing the efficiency of production lines [3]. - The team aims to continue focusing on key aspects of the industrial chain, leveraging digital transformation and AI to support infrastructure upgrades and improve product quality in the steel sector [3].