Two-dimensional nonlinear optical materials predicted by network visualization

2019 ◽  
Vol 4 (3) ◽  
pp. 586-596
Author(s):  
Guoyu Yang ◽  
Kechen Wu

Machine learning and network visualization were applied to predict two-dimensional nonlinear optical materials by selecting key elements and connections.

2012 ◽  
Vol 92 (3) ◽  
pp. 982-987 ◽  
Author(s):  
Xiaolong Zhang ◽  
Ming Li ◽  
Zuosen Shi ◽  
Lisha Zhao ◽  
Rulong Jin ◽  
...  

2017 ◽  
Vol 44 (7) ◽  
pp. 0703004 ◽  
Author(s):  
王俊 Wang Jun ◽  
张晓艳 Zhang Xiaoyan ◽  
张赛锋 Zhang Saifeng ◽  
赵培均 Zhao Peijun ◽  
张龙 Zhang Long

2015 ◽  
Vol 6 (48) ◽  
pp. 8325-8330 ◽  
Author(s):  
Yi Ren ◽  
Jeffrey S. Moore

Covalent conjugation of tetrathiafulvalene (TTF) moieties to macromolecular backbones combines unique properties of polymers, such as processability and high functional group density, with the outstanding redox properties of TTF to expand applications in organic electronics, chemical sensors, molecular switches, and nonlinear optical materials among others.


2000 ◽  
Author(s):  
P. M. Tentzepis ◽  
P. Chen ◽  
I. V. Tomov ◽  
A. S. Dvornikov ◽  
D. A. Oulianov

2021 ◽  
Vol 142 ◽  
pp. 107231
Author(s):  
Palwasha Khan ◽  
Tariq Mahmood ◽  
Khurshid Ayub ◽  
Sobia Tabassum ◽  
Mazhar Amjad Gilani

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