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Chen S, Jiang Y, Zhu Z, Zhang Q, Zhang C, Zhang Q, Qian W, Zhang S, Wei F. Fluidization and Application of Carbon Nano Agglomerations. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2306355. [PMID: 38115551 PMCID: PMC10885674 DOI: 10.1002/advs.202306355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 11/30/2023] [Indexed: 12/21/2023]
Abstract
Carbon nanomaterials are unique with excellent functionality and diverse structures. However, agglomerated structures are commonly formed because of small-size effects and surface effects. Their hierarchical assembly into micro particles enables carbon nanomaterials to break the boundaries of classical Geldart particle classification before stable fluidization under gas-solid interactions. Currently, there are few systematic reports regarding the structural evolution and fluidization mechanism of carbon nano agglomerations. Based on existing research on carbon nanomaterials, this article reviews the fluidized structure control and fluidization principles of prototypical carbon nanotubes (CNTs) as well as their nanocomposites. The controlled agglomerate fluidization technology leads to the successful mass production of agglomerated and aligned CNTs. In addition, the self-similar agglomeration of individual ultralong CNTs and nanocomposites with silicon as model systems further exemplify the important role of surface structure and particle-fluid interactions. These emerging nano agglomerations have endowed classical fluidization technology with more innovations in advanced applications like energy storage, biomedical, and electronics. This review aims to provide insights into the connections between fluidization and carbon nanomaterials by highlighting their hierarchical structural evolution and the principle of agglomerated fluidization, expecting to showcase the vitality and connotation of fluidization science and technology in the new era.
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Affiliation(s)
- Sibo Chen
- Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China
| | - Yaxin Jiang
- Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China
| | - Zhenxing Zhu
- Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China
| | - Qi Zhang
- Beijing Research Institute of Chemical Industry, SINOPEC, Beijing, 100013, China
| | - Chenxi Zhang
- Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China
- Ordos Laboratory, Inner Mongolia, 017000, China
| | - Qiang Zhang
- Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China
| | - Weizhong Qian
- Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China
- Ordos Laboratory, Inner Mongolia, 017000, China
| | - Shijun Zhang
- Beijing Research Institute of Chemical Industry, SINOPEC, Beijing, 100013, China
| | - Fei Wei
- Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China
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Wang Y, Huang W, Zhang Z, Fan L, Huang Q, Wang J, Zhang Y, Zhang M. Ultralow-power flexible transparent carbon nanotube synaptic transistors for emotional memory. NANOSCALE 2021; 13:11360-11369. [PMID: 34096562 DOI: 10.1039/d1nr02099d] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Emulating the biological behavior of the human brain with artificial neuromorphic devices is essential for the future development of human-machine interactive systems, bionic sensing systems and intelligent robotic systems. In this paper, artificial flexible transparent carbon nanotube synaptic transistors (F-CNT-STs) with signal transmission and emotional learning functions are realized by adopting the poly(vinyl alcohol) (PVA)/SiO2 proton-conducting electrolyte. Synaptic functions of biological synapses including excitatory and inhibitory behaviors are successfully emulated in the F-CNT-STs. Besides, synaptic plasticity such as spike-duration-dependent plasticity, spike-number-dependent plasticity, spike-amplitude-dependent plasticity, paired-pulse facilitation, short-term plasticity, and long-term plasticity have all been systematically characterized. Moreover, the F-CNT-STs also closely imitate the behavior of human brain learning and emotional memory functions. After 1000 bending cycles at a radius of 3 mm, both the transistor characteristics and the synaptic functions can still be implemented correctly, showing outstanding mechanical capability. The realized F-CNT-STs possess low operating voltage, quick response, and ultra-low power consumption, indicating their high potential to work in low-power biological systems and artificial intelligence systems. The flexible artificial synaptic transistor enables its potential to be generally applicable to various flexible wearable biological and intelligent applications.
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Affiliation(s)
- Yarong Wang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Weihong Huang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Ziwei Zhang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Lingchong Fan
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Qiuyue Huang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Jiaxin Wang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Yiming Zhang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Min Zhang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
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