High-throughput screening and machine learning for the efficient growth of high-quality single-wall carbon nanotubes

Nano Research ◽  
2021 ◽  
Author(s):  
Zhong-Hai Ji ◽  
Lili Zhang ◽  
Dai-Ming Tang ◽  
Chien-Ming Chen ◽  
Torbjörn E. M. Nordling ◽  
...  
Keyword(s):  
Machine Learning ◽  
Carbon Nanotubes ◽  
High Throughput ◽  
High Throughput Screening ◽  
Single Wall Carbon Nanotubes ◽  
High Quality ◽  
Single Wall Carbon

Growth of high-quality single-wall carbon nanotubes without amorphous carbon formation

2004 ◽  
Vol 84 (2) ◽  
pp. 269-271 ◽  
Author(s):  
R. G. Lacerda ◽  
A. S. Teh ◽  
M. H. Yang ◽  
K. B. K. Teo ◽  
N. L. Rupesinghe ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Amorphous Carbon ◽  
Single Wall Carbon Nanotubes ◽  
Carbon Formation ◽  
High Quality ◽  
Single Wall Carbon

scholarly journals Synthesis of high quality nitrogen-doped single-wall carbon nanotubes

2015 ◽  
Vol 58 (8) ◽  
pp. 603-610 ◽  
Author(s):  
Peng-Xiang Hou ◽  
Man Song ◽  
Jin-Cheng Li ◽  
Chang Liu ◽  
Shi-Sheng Li ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Single Wall Carbon Nanotubes ◽  
High Quality ◽  
Single Wall Carbon ◽  
Nitrogen Doped

Catalytic decomposition of n-heptane for the growth of high quality single wall carbon nanotubes

2006 ◽  
Vol 428 (4-6) ◽  
pp. 416-420 ◽  
Author(s):  
D. Grimm ◽  
A. Grüneis ◽  
C. Kramberger ◽  
M. Rümmeli ◽  
T. Gemming ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Catalytic Decomposition ◽  
Single Wall Carbon Nanotubes ◽  
High Quality ◽  
Single Wall Carbon

scholarly journals Machine Learning and High-Throughput Robust Design of P3HT-CNT Composite Thin Films for High Electrical Conductivity

2020 ◽  
Author(s):  
Daniil Bash ◽  
Yongqiang Cai ◽  
Chellappan Vijila ◽  
Swee Liang Wong ◽  
Yang Xu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Carbon Nanotubes ◽  
Electrical Conductivity ◽  
High Throughput ◽  
Inorganic Materials ◽  
Single Wall Carbon Nanotubes ◽  
Local Optimum ◽  
Charge Delocalization ◽  
Experimental Scheme ◽  
Thin Film Preparation

<p>Combining high-throughput experiments with machine learning allows quick optimization of parameter spaces towards achieving target properties. In this study, we demonstrate that machine learning, combined with multi-labeled datasets, can additionally be used for scientific understanding and hypothesis testing. We introduce an automated flow system with high-throughput drop-casting for thin film preparation, followed by fast characterization of optical and electrical properties, with the capability to complete one cycle of learning of fully labeled ~160 samples in a single day. We combine regio-regular poly-3-hexylthiophene with various carbon nanotubes to achieve electrical conductivities as high as 1200 S/cm. Interestingly, a non-intuitive local optimum emerges when 10% of double-walled carbon nanotubes are added with long single wall carbon nanotubes, where the conductivity is seen to be as high as 700 S/cm, which we subsequently explain with high fidelity optical characterization. Employing dataset resampling strategies and graph-based regressions allows us to account for experimental cost and uncertainty estimation of correlated multi-outputs, and supports the proving of the hypothesis linking charge delocalization to electrical conductivity. We therefore present a robust machine-learning driven high-throughput experimental scheme that can be applied to optimize and understand properties of composites, or hybrid organic-inorganic materials.</p>

Mass production of high-quality single-wall carbon nanotubes by H2–N2 arc discharge

2005 ◽  
Vol 14 (3-7) ◽  
pp. 729-732 ◽  
Author(s):  
Yoshinori Ando ◽  
Xinluo Zhao ◽  
Sakae Inoue ◽  
Tomoko Suzuki ◽  
Takenori Kadoya
Keyword(s):  
Carbon Nanotubes ◽  
Mass Production ◽  
Arc Discharge ◽  
Single Wall Carbon Nanotubes ◽  
High Quality ◽  
Single Wall Carbon

Simple, cost-efficient and high throughput method for separating single-wall carbon nanotubes with modified cotton

Carbon ◽  
2021 ◽  
Vol 178 ◽  
pp. 157-163
Author(s):  
Timur Khamidullin ◽  
Shamil Galyaltdinov ◽  
Alina Valimukhametova ◽  
Vasiliy Brusko ◽  
Artur Khannanov ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
High Throughput ◽  
Single Wall Carbon Nanotubes ◽  
Single Wall Carbon ◽  
High Throughput Method ◽  
Cost Efficient
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