The 12th Global Conference on Polymer and Composite Materials (PCM 2025)

Abstract: The precise synthesis and versatile applications of carbon nanotubes (CNTs) are essential for advancing nanotechnology and leveraging their extraordinary properties across various domains [1, 2]. Machine learning has emerged as a powerful tool in CNT research, enabling optimization of synthesis and application development [3-5]. In this talk, we introduce a machine-learning-assisted approach to address the trade-off between crystallinity and growth efficiency in CNT synthesis [5]. Additionally, by utilizing a multi-step chemical vapor deposition (CVD) reactor combined with atmospheric microplasma, we achieved the production of highly crystalline CNTs [6-8]. In addition to synthesis, we demonstrate the practical applications of CNTs. High aspect ratio (60:1), free-standing, 1.2 mm-tall, 20 μm-diameter vertically aligned CNT post arrays were fabricated [9]. These CNT posts served as neural probes, exhibiting rapid electrochemical responses to methyl viologen and dopamine. Furthermore, they were incorporated into CNT-Cu composites for through-silicon-via interposers, showcasing copper-level electrical conductivity and silicon-level low thermal expansion [10]. Our work highlights the integration of advanced synthesis techniques and precise structural manipulation to address critical challenges in CNT research, including trade-offs in structural control and productivity. These advancements demonstrate the potential of CNTs in diverse applications, driving progress in nanomaterials science.

Keywords: Carbon nanotube, microplasma, crystallinity, neural probe, interposer

Acknowledgements: G.H. Chen acknowledges support from JSPS KAKENHI Grant Number JP23K04552.

Reference:
[1] G. H. Chen, et al., ACS Nano 7 (2013) 10218-10224.
[2] D.-M. Tang, et al., G. H. Chen, et al., Science 374 (2021) 1616-1620.
[3] G. H. Chen, D.-M. Tang, Nanomaterials 14 (2024) 1688.
[4] G. H. Chen, et al. J Mat Sci Technol 231 (2025) 30-35.
[5] D. Lin, et al., G. H. Chen*, ACS Nano 17 (2023) 22821-22829.
[6] T. Tsuji†, G. H. Chen†, et al., Mater Today Chem 44 (2025) 102576.
[7] G. H. Chen, et al., Chem Eng J 444 (2022) 136634.
[8] T. Tsuji†, G. H. Chen†, et al., Nanomaterials 11 (2021) 3461.
[9] G. H. Chen, et al., ACS Biomater Sci Eng 4 (2018) 1900-1907.
[10] G. H. Chen, et al., ACS Appl Nano Mater 4 (2021) 869-876.

Abstract: With the gradual depletion of shallow oil and gas resources, deep (>4,500m) and ultra-deep (>6,000m) oil and gas have become the main focus of oil and gas exploration and development in China. With the advancement of technology, the drilling depth has been gradually increased, and there are more than 200 oil and gas wells exceeding 8000m now in China. It is encouraging that China already has two wells deeper than 10,000 meters, one of which has been completed. However, the high temperature in the deep formation poses a great challenge to the temperature resistance of drilling fluids, which plays a vital role in carrying and suspending dill cuttings, stabilizing wellbores, and lubricating and cooing drill bits during drilling engineering. Water-soluble polymers mainly regulate rheology and control filtration in drilling fluids, but their performance falls under high-temperature and high salts conditions, which is a serious problem for safety and efficiency. This report will focus on the topic of high temperature resistant polymers used in drilling fluids. It will cover the technical challenges of deep well drilling, the challenges for polymers and research on high temperature resistant polymers (filtration control additive and plugging agent) from our team. Finally, the technical challenges that still need to be addressed will be presented.