thermal cracker
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2018 ◽  
Vol 20 (23) ◽  
pp. 16193-16201 ◽  
Author(s):  
Dae-Hyung Cho ◽  
Woo-Jung Lee ◽  
Jae-Hyung Wi ◽  
Won Seok Han ◽  
Sun Jin Yun ◽  
...  

We propose a method to fabricate two-dimensional (2D) molybdenum disulfide (MoS2) layers to overcome issues in typical fabrication processes by promoting the sulfurization reaction of molybdenum (Mo).


Author(s):  
Zohreh Feli ◽  
Ali Darvishi ◽  
Ali Bakhtyari ◽  
Mohammad Reza Rahimpour ◽  
Sona Raeissi
Keyword(s):  

ETRI Journal ◽  
2016 ◽  
Vol 38 (2) ◽  
pp. 265-271 ◽  
Author(s):  
Dae-Hyung Cho ◽  
Woo-Jung Lee ◽  
Jae-Hyung Wi ◽  
Won Seok Han ◽  
Tae Gun Kim ◽  
...  

2015 ◽  
Vol 66 (1) ◽  
pp. 76-81 ◽  
Author(s):  
Soo-Jeong Park ◽  
Yong-Duck Chung ◽  
Woo-Jung Lee ◽  
Dae-Hyung Cho ◽  
Jae-Hyung Wi ◽  
...  

2014 ◽  
Vol 2 (35) ◽  
pp. 14593-14599 ◽  
Author(s):  
Dae-Hyung Cho ◽  
Woo-Jung Lee ◽  
Sang-Woo Park ◽  
Jae-Hyung Wi ◽  
Won Seok Han ◽  
...  

The proposed safe and cheap method for enhanced sulfur reaction enables the formation of high-quality chalcogenide thin films.


Author(s):  
Reza Nabavi ◽  
G. P. Rangaiah ◽  
Aligholi Niaei ◽  
Darioush Salari

Ethylene and propylene, building blocks of the petrochemical industries, are mostly produced by steam cracking of hydrocarbons. In our recent work (Nabavi, Rangaiah, Niaei and Salari, Multiobjective Optimization of an Industrial LPG Thermal Cracker using a First Principles Model, Ind. Eng. Chem. Res. 2009, 48, 9523-9533), operation of an industrial liquefied petroleum gas (LPG) cracker was optimized for several sets of two and three objectives. In this work, optimization of an LPG cracker design is investigated for multiple objectives. The objectives considered are maximization of annual ethylene and propylene production, selectivity and run length, and minimization of severity and total heat duty per year. The elitist non-dominated sorting genetic algorithm adapted with the jumping gene operator, NSGA-II-aJG is used to solve the multi-objective optimization problems. The results of design optimization for multiple objectives are compared with those for operation optimization.


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