Shu-Yu Guo

Mr. Shu-Yu Guo

Institute of Metal Research, Chinese Academy of Sciences, Shenyang, Liaoning, China

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 August 2022 in Molecules
Verified
Journal Article
Open access
PDF file
SGShu-Yu Guo
Shu-Yu Guo
PHPeng-Xiang Hou
Peng-Xiang Hou
Feng ZhangFeng Zhang
Feng Zhang
CLChang Liu
Chang Liu
HCHui-Ming Cheng
Hui-Ming Cheng
Single-wall carbon nanotubes (SWCNTs) have a high aspect ratio, large surface area, good stability and unique metallic or semiconducting electrical conductivity, they are therefore considered a promising candidate for the fabrication of flexible gas sensors that are expected to be used in the Internet of Things and various portable and wearable electronics. In this review, we first introduce the sensing mechanism of SWCNTs and the typical structure and key parameters of SWCNT-based gas sensors. We then summarize research progress on the design, fabrication, and performance of SWCNT-based gas sensors. Finally, the principles and possible approaches to further improving the performance of SWCNT-based gas sensors are discussed.

18 March 2021 in Nano Research
Verified
Journal Article
Closed access
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ZJZhong-Hai Ji
Zhong-Hai Ji
LZLili Zhang
Lili Zhang
DTDai-Ming Tang
Dai-Ming Tang
CCChien-Ming Chen
Chien-Ming Chen
TNTorbjörn E. M. Nordling
Torbjörn E. M. Nordling
HCHui-Ming Cheng
Hui-Ming Cheng
It has been a great challenge to optimize the growth conditions toward structure-controlled growth of single-wall carbon nanotubes (SWCNTs). Here, a high-throughput method combined with machine learning is reported that efficiently screens the growth conditions for the synthesis of high-quality SWCNTs. Patterned cobalt (Co) nanoparticles were deposited on a numerically marked silicon wafer as catalysts, and parameters of temperature, reduction time and carbon precursor were optimized. The crystallinity of the SWCNTs was characterized by Raman spectroscopy where the featured G/D peak intensity (IG/ID) was extracted automatically and mapped to the growth parameters to build a database. 1,280 data were collected to train machine learning models. Random forest regression (RFR) showed high precision in predicting the growth conditions for high-quality SWCNTs, as validated by further chemical vapor deposition (CVD) growth. This method shows great potential in structure-controlled growth of SWCNTs.

4 July 2023 in Nanomaterials
Verified
Journal Article
Open access
PDF file
PXPiao Xie
Piao Xie
YSYun Sun
Yun Sun
CCChao Chen
Chao Chen
SGShu-Yu Guo
Shu-Yu Guo
YZYiming Zhao
Yiming Zhao
HCHui-Ming Cheng
Hui-Ming Cheng
Semiconducting single-walled carbon nanotubes (s-SWCNTs) with large diameters are highly desired in the construction of high performance optoelectronic devices. However, it is difficult to selectively prepare large-diameter s-SWCNTs since their structure and chemical stability are quite similar with their metallic counterparts. In this work, we use SWCNTs with large diameter as a raw material, conjugated polymer of regioregular poly-(3-dodecylthiophene) (rr-P3DDT) with long side chain as a wrapping agent to selectively separate large-diameter s-SWCNTs. It is found that s-SWCNTs with a diameter of ~1.9 nm are effectively enriched, which shows a clean surface. By using the sorted s-SWCNTs as a channel material, we constructed thin-film transistors showing charge-carrier mobilities higher than 10 cm2 V−1 s−1 and on/off ratios higher than 103.