scholarly journals Tuning of Catalytic Activity by Thermoelectric Materials for Carbon Dioxide Hydrogenation

2017 ◽  
Vol 8 (5) ◽  
pp. 1701430 ◽  
Author(s):  
Abdenour Achour ◽  
Kan Chen ◽  
Michael J. Reece ◽  
Zhaorong Huang
2018 ◽  
Vol 6 (32) ◽  
pp. 15510-15516 ◽  
Author(s):  
Kun Xiong ◽  
Guilin Zhou ◽  
Haidong Zhang ◽  
Yu Shen ◽  
Xianming Zhang ◽  
...  

We report a facile and controllable method to enhance the catalytic activity and stability of Mo2C–C for CO2 hydrogenation by incorporating N-functional groups on the interface of Mo2C–C.


ACS Catalysis ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 2121-2133
Author(s):  
Chao Zhang ◽  
Chenxi Cao ◽  
Yulong Zhang ◽  
Xianglin Liu ◽  
Jing Xu ◽  
...  

2021 ◽  
Author(s):  
Matthew Quesne ◽  
C. Richard A. Catlow ◽  
Nora Henriette De Leeuw

We present several in silico insights into the MAX-phase of early transition metal silicon carbides and explore how these affect carbon dioxide hydrogenation. Periodic desity functional methodology is applied to...


Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3965
Author(s):  
Daniel Chuquin-Vasco ◽  
Francis Parra ◽  
Nelson Chuquin-Vasco ◽  
Juan Chuquin-Vasco ◽  
Vanesa Lo-Iacono-Ferreira

The objective of this research was to design a neural network (ANN) to predict the methanol flux at the outlet of a carbon dioxide dehydrogenation plant. For the development of the ANN, a database was generated, in the open-source simulation software “DWSIM”, from the validation of a process described in the literature. The sample consists of 133 data pairs with four inputs: reactor pressure and temperature, mass flow of carbon dioxide and hydrogen, and one output: flow of methanol. The ANN was designed using 12 neurons in the hidden layer and it was trained with the Levenberg–Marquardt algorithm. In the training, validation and testing phase, a global mean square (RMSE) value of 0.0085 and a global regression coefficient R of 0.9442 were obtained. The network was validated through an analysis of variance (ANOVA), where the p-value for all cases was greater than 0.05, which indicates that there are no significant differences between the observations and those predicted by the ANN. Therefore, the designed ANN can be used to predict the methanol flow at the exit of a dehydrogenation plant and later for the optimization of the system.


2016 ◽  
Vol 18 (9) ◽  
pp. 6763-6772 ◽  
Author(s):  
Manuel Corva ◽  
Zhijing Feng ◽  
Carlo Dri ◽  
Federico Salvador ◽  
Paolo Bertoch ◽  
...  

Stable hydrocarbon surface species in the carbon dioxide hydrogenation reaction were identified on Ir(111) under near-ambient pressure conditions.


2016 ◽  
Vol 16 (2) ◽  
pp. 2024-2027
Author(s):  
Ho-Geun Ahn ◽  
Hwan-Gyu Lee ◽  
Min-Chul Chung ◽  
Kwon-Pil Park ◽  
Ki-Joong Kim ◽  
...  

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