石墨烯纤维：制备、性能与应用

doi:10.3866/PKU.WHXB202007093

物理化学学报 >> 2022, Vol. 38 >> Issue (2): 2007093.doi: 10.3866/PKU.WHXB202007093

所属专题：石墨烯的功能与应用

石墨烯纤维：制备、性能与应用

蹇木强¹^,², 张莹莹³, 刘忠范¹^,²^,*()

¹ 北京大学化学与分子工程学院，北京分子科学国家研究中心，北京大学纳米化学研究中心，北京 100871
² 北京石墨烯研究院，北京 100095
³ 清华大学化学系，有机光电子与分子工程教育部重点实验室，北京 100084

收稿日期:2020-07-31 录用日期:2020-08-24 发布日期:2020-08-27
通讯作者: 刘忠范 E-mail:zfliu@pku.edu.cn
作者简介:刘忠范，1962年出生。1990年获东京大学博士学位；现为北京大学教授，博士生导师，北京石墨烯研究院院长，中国科学院院士。主要研究方向为石墨烯的CVD生长方法与应用
基金资助:
国家重点基础研究发展规划项目(973)(2016YFA0200103);国家自然科学基金(51432002);国家自然科学基金(51290272);国家自然科学基金(51672153);国家自然科学基金(21975141);国家自然科学基金(51972184);北京分子科学国家研究中心(BNLMS-CXTD-202001);中国博士后科学基金(2019M660322)

Graphene Fibers: Preparation, Properties, and Applications

Muqiang Jian¹^,², Yingying Zhang³, Zhongfan Liu¹^,²^,*()

¹ Center of Nano Chemistry, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
² Beijing Graphene Institute (BGI), Beijing 100095, China
³ Key Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, China

Received:2020-07-31 Accepted:2020-08-24 Published:2020-08-27
Contact: Zhongfan Liu E-mail:zfliu@pku.edu.cn
About author:Zhongfan Liu, Email: zfliu@pku.edu.cn; Tel.: +86-10-62758600
Supported by:
the National Key Basic Research Program of China(2016YFA0200103);the National Natural Science Foundation of China(51432002);the National Natural Science Foundation of China(51290272);the National Natural Science Foundation of China(51672153);the National Natural Science Foundation of China(21975141);the National Natural Science Foundation of China(51972184);the Beijing National Laboratory for Molecular Sciences(BNLMS-CXTD-202001);the China Postdoctoral Science Foundation(2019M660322)

摘要/Abstract

摘要：

石墨烯纤维是一种由石墨烯片层紧密有序排列而成的一维宏观组装材料。通过合理的结构设计和可控制备，石墨烯纤维能够将石墨烯在微观尺度的优异性能有效传递至宏观尺度，展现出优异的力学、电学、热学等性能，从而应用于功能织物、传感、能源等领域。目前，石墨烯纤维主要通过湿法纺丝、限域水热组装等方法制备得到，其性能可以通过对材料体系和制备工艺的优化而进一步提升。本文首先介绍了石墨烯纤维的制备方法，然后详细阐述了石墨烯纤维的性能，讨论了其性能提升策略，并总结了石墨烯纤维的应用，最后对石墨烯纤维的未来发展、挑战和前景进行了展望。

关键词: 石墨烯纤维, 制备, 纺丝方法, 性能, 应用

Abstract:

Graphene fiber is a macroscopic carbonaceous fiber composed of microscopic graphene sheets, and has attracted extensive attention. Graphene building blocks form a highly ordered structure, resulting in fibers with the same properties as graphene, such as superior mechanical and electrical performance, low weight, excellent flexibility, and ease of functionalization. Moreover, graphene fibers are compatible with traditional textile technologies, facilitating the development of wearable electronics, flexible energy devices, and smart textiles. Graphene fibers were first prepared in 2011 by wet spinning of graphene oxide (GO) solution, which was dispersed in water. Various fabrication methods have been developed to assemble graphene sheets into fibers since then and different strategies have been proposed to optimize their structure and performance. Graphene fibers have applications in numerous fields, including conductors, sensors, actuators, smart textiles, and flexible energy devices. This review aims to provide a comprehensive picture of the preparation approaches, properties, and applications of graphene fibers. Firstly, the preparation processes, unique structures, and properties of three typical carbonaceous fibers-arbon fibers, carbon nanotube (CNT) fibers, and graphene fibers-re compared. It can be seen that graphene fibers possess the unique structures, such as the large grain sizes and highly aligned structure, endowing them with the outstanding properties. Then a variety of fabrication techniques have been summarized, including wet spinning, dry spinning, dry-jet wet spinning, space-confined hydrothermal assembly, film conversion approach, and template-assisted chemical vapor deposition (CVD). Wet spinning is a common method to fabricate high-performance graphene fibers and is promising for the large-scale production of graphene fibers. Besides, various strategies for improving the mechanical, electrical, and thermal properties of graphene fibers are introduced in detail, including well-chosen graphene building blocks, optimized fabrication processes, and high-temperature treatments. Although the electrical and thermal transport properties of typical graphene fibers are better than those of carbon fibers, the strength and modulus of graphene fibers are inferior. Therefore, the enhancement of the mechanical properties of graphene fibers by optimizing the composition of precursors, controlling and adjusting the assembly processes, and exploring feasible post-treatment procedures are essential. Meanwhile, the review outlines the applications of graphene fibers in high-performance conductors, functional fabrics, flexible sensors, actuators, fiber-shaped supercapacitors and batteries. Finally, the persisting challenges and the future scope of graphene fibers are discussed. We believe that graphene fibers will become a new structural and functional material that can be applied in numerous fields in the future, aided by the continuous development of materials and techniques.

Key words: Graphene fiber, Preparation, Spinning, Property, Application

蹇木强, 张莹莹, 刘忠范. 石墨烯纤维：制备、性能与应用[J]. 物理化学学报, 2022, 38(2), 2007093. doi: 10.3866/PKU.WHXB202007093

Muqiang Jian, Yingying Zhang, Zhongfan Liu. Graphene Fibers: Preparation, Properties, and Applications[J]. Acta Phys. -Chim. Sin. 2022, 38(2), 2007093. doi: 10.3866/PKU.WHXB202007093

链接本文: https://www.whxb.pku.edu.cn/CN/10.3866/PKU.WHXB202007093

https://www.whxb.pku.edu.cn/CN/Y2022/V38/I2/2007093

图/表 9

图1

表1

图2

图3

表2

石墨烯纤维的制备方法和性能"

Preparation	composition	Tensile Strength/MPa	Young's Modulus/GPa	Failure Strain/%	Electrical Conductivity/(S·m^?1)	Thermal Conductivity/(W·m^?1·K^?1)	Ref.
Wet spinning
353 K, HI reduced	rGO	140	7.7	5.8	2.5 × 10⁴	–	9
353 K, HI reduced	rGO	182	8.7	~3.2	3.5 × 10⁴	–	75
493 K in vacuum	rGO	115 ± 19	9.0 ± 2.1	–	2.8 × 10²	1435	63
363 K, HI reduced	rGO+Ag	–	–	–	9.3 × 10⁴	–	73
353 K, HI reduced	rGO (large GO flakes)	360.1 ± 12.7	12.8 ± 0.8	–	3.2 × 10⁴	–	59
353 K, HI reduced	rGO (giant GO flakes)	501.5	11.2	6.7	4.1 × 10⁴	–	60
353 K, HI reduced	rGO	365	21	~3.0	2.7 × 10⁴	–	76
2073 K or 3013 K	rGO (large and small	1080 ± 61	135 ± 8	~1.4	2.21 (± 0.06) × 10⁵	1290 ± 53	61
in Ar	GO sheets)	1080 ± 61	135 ± 8	~1.4	2.21 (± 0.06) × 10⁵	1290 ± 53	61
353 K, HI reduced	rGO + PCDO	842.6 ± 59.4	–	3.5	2.92 × 10⁴	–	70
3273 K in Ar	rGO + K	–	–	–	2.24 × 10⁷	–	77
3273 K in Ar	rGO	2200	400	0.5	8 × 10⁵	–	11
1273 K in N₂	rGO + phenolic resin	1450	120	1.8	8.4 × 10⁴	–	65
3273 K in Ar	rGO + Ca	–	–	–	Superconductive (11K)	–	78
363 K, HI reduced	rGO + PSE-AP	740.1	~3.8	–	4.33 × 10⁴	–	69
HI reduced	rGO+chitosan	743.6	~6.1	–	1.79 × 10⁴	–	66
1273 K in H₂	rGO+PDA	650	80.3	0.73	1.32 × 10⁵	–	67
2773 K in Ar	rGO (microfluidics)	1900 ± 100	309 ± 16	~0.65	1.04 (± 0.17) × 10⁶	1575 ± 81	64
Dry spinning
353 K, HI reduced	rGO	375 ± 20	11.6	9.4	1.32 × 10⁴	–	29
353 K, HI reduced	rGO	120	–	~6	7.5 × 10³	–	79
Dry jet wet spinning
1323 K in Ar	Graphene nanoribbons	378 ± 5	36.2 ± 3.8	1.1 ± 0.13	2.85 × 10⁴	–	30
Hydrothermal
1073 K in vacuum	rGO	420	–	~2.4	1.0 × 10³	–	31
493 K, 6 h	rGO	197	–	4.2	1.2 × 10³	–	80
493 K, 6 h	rGO/CNT	84	–	3.3	1.02 × 10⁴	–	80
1473 K in Ar	rGO+PDA	724 ± 57	37.1 ± 1.9	2.31 ± 0.7	6.16 (± 0.47) × 10⁴	–	68
Film conversion
3073 K	rGO	39.2	3.17	1.5	4.16 × 10⁴	–	35
3273 K in Ar	rGO	3.9 ± 0.5	–	~1.3	3.18 × 10⁴	1.90 × 10²	81
CVD
1273 K for growth	graphene	–	–	–	1.27 × 10⁴	–	56

表2

图4

图5

图6

图7

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Materials	Theoretical properties			Present properties			Applications
Materials	Tensile strength/GPa	Young's modulus/GPa	Electrical conductivity/(× 10⁶ S·m^?1)	Tensile Strength/GPa	Young's modulus/GPa	Electrical conductivity/(× 10⁶ S·m^?1)	Applications
Carbon fibers	> 100	1000	–	7 (T1000)	588 (M60J)	0.06–0.14 ²	Structural materials
CNT fibers	> 100	1000	100	9.6 ¹²	397 ¹³	0.03–10.9 ¹³	Structural-functional materials
Graphene fibers	~130	1100	100	2.2 ¹¹	400 ¹¹	0.03–22.4 ¹⁴	Structural-functional materials

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石墨烯纤维：制备、性能与应用

Graphene Fibers: Preparation, Properties, and Applications

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