Neuron-inspired structure towards ultra-high thermal conductivity of Mg-based materials

IF 14.2 1区 材料科学 Q1 ENGINEERING, MULTIDISCIPLINARY Composites Part B: Engineering Pub Date : 2025-05-15 Epub Date: 2025-02-24 DOI:10.1016/j.compositesb.2025.112345
Fanjin Yao , Bo Hu , Zixin Li , Lexian Li , Jiaxuan Han , Zhenfei Jiang , Dejiang Li , Xiaoqin Zeng
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Abstract

The remarkable lightweight characteristics of magnesium (Mg) offer significant advantages in 5G communication, 3C products, and new energy vehicles. Yet, the unsatisfactory thermal conductivity of Mg alloys presents formidable challenges in accommodating the advancement of high power density, highly integrated, and miniaturized electronic components in the era of intelligence. Here, inspired by the neurons in the human brain, cell body-like graphite flakes (GF) and axon-like carbon fibers (CF) are constructed into a neuron-inspired structure through pre-mixed & laid powder stir casting (PPSC). Drawing inspiration from the myelin sheath of neurons, a biomimetic interfacial structure is constructed in situ to ensure efficient heat conduction. The neuron-inspired Mg-based materials at a GF:CF volume ratio of 1:3 display an ultrahigh and isotropic thermal conductivity of 200.5 W/(m·K) (393 % of the common cast Mg alloys, AZ91D) and an exceptional low density of 1.80 g/cm3. This epitomizes the zenith of comprehensive properties among all thermal management materials reported to date. The ingeniously devised neuron-inspired structure, myelin sheath biomimetic interface, and tunable GF-CF volume ratio co-contribute to the superior thermal conductivity. This work offers an advanced biomimetic strategy towards the development of next-generation lightweight thermal management materials.

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神经元启发结构实现镁基材料的超高导热性
镁(Mg)显著的轻量化特性在5G通信、3C产品和新能源汽车中具有显著优势。然而,镁合金的热导率令人不满意,这对适应智能时代高功率密度、高集成度和小型化电子元件的发展提出了巨大的挑战。在这里,受人脑神经元的启发,细胞体样石墨薄片(GF)和轴突样碳纤维(CF)通过预混合构建成神经元启发结构。铺粉搅拌铸造(PPSC)从神经元的髓鞘中汲取灵感,在原位构建仿生界面结构以确保有效的热传导。GF:CF体积比为1:3的神经元启发Mg基材料显示出200.5 W/(m·K)的超高各向同性导热系数(为普通铸造镁合金AZ91D的393%)和1.80 g/cm3的超低密度。这是迄今为止报道的所有热管理材料综合性能的顶峰。巧妙设计的神经元启发结构,髓鞘仿生界面和可调的GF-CF体积比共同贡献了优越的导热性。这项工作为下一代轻质热管理材料的开发提供了一种先进的仿生策略。
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来源期刊
Composites Part B: Engineering
Composites Part B: Engineering 工程技术-材料科学:复合
CiteScore
24.40
自引率
11.50%
发文量
784
审稿时长
21 days
期刊介绍: Composites Part B: Engineering is a journal that publishes impactful research of high quality on composite materials. This research is supported by fundamental mechanics and materials science and engineering approaches. The targeted research can cover a wide range of length scales, ranging from nano to micro and meso, and even to the full product and structure level. The journal specifically focuses on engineering applications that involve high performance composites. These applications can range from low volume and high cost to high volume and low cost composite development. The main goal of the journal is to provide a platform for the prompt publication of original and high quality research. The emphasis is on design, development, modeling, validation, and manufacturing of engineering details and concepts. The journal welcomes both basic research papers and proposals for review articles. Authors are encouraged to address challenges across various application areas. These areas include, but are not limited to, aerospace, automotive, and other surface transportation. The journal also covers energy-related applications, with a focus on renewable energy. Other application areas include infrastructure, off-shore and maritime projects, health care technology, and recreational products.
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