Anti-coking Cu-Ni bimetallic catalyst for hydrogen production: Thermodynamic and experimental study of methanol autothermal reforming

Huang, Jiazhun; Zhong, Biqi; Liang, Zhenwei; He, Qianyu; Zheng, Zefeng; Han, Qing; Liu, Yujia

doi:10.1016/j.ces.2023.119231

Cited by 7 publications

(3 citation statements)

References 59 publications

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“…The results indicated that with more Pr species, there were more Ni 0 species remaining after the ATR test, and was consistent with the conclusion obtained from H 2 -TPR, where addition of Pr facilitated the reduction of the Ni oxide into Ni 0 particles. On the NSP40 catalyst, an exothermic weight loss peak (−1.12%) at 196 °C was found and can be attributed to combustion of amorphous carbon species, 49 while the exothermic weight loss peak (−0.82%) at 650 °C can be ascribed to the oxidation of fiber carbon. 50…”

Section: Resultsmentioning

confidence: 99%

Solid solution-type Sm–Pr–O supported nickel-based catalysts for auto-thermal reforming of acetic acid: the role of Pr in solid solution

Liu,

Huang,

Ding

et al. 2024

New J. Chem.

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Section: Resultsmentioning

confidence: 99%

Solid solution-type Sm–Pr–O supported nickel-based catalysts for auto-thermal reforming of acetic acid: the role of Pr in solid solution

Liu,

Huang,

Ding

et al. 2024

New J. Chem.

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“…In our previous work, theoretical calculations were carried out for methanol autothermal reforming using Aspen Plus software and nonideal equations of state (e.g., Peng–Robinson equation), and the simulations were aimed at evaluating the optimal conditions. We obtained the results that water-to-carbon (S/C) molar ratio = 2 and oxygen-to-carbon (O 2 /C) molar ratio = 0.2 are the optimal reaction conditions . Hence, the water/carbon and oxygen/carbon ratios for the catalyst activity test in this article were determined as S/C = 2 and O 2 /C = 0.2.…”

Section: Experimental Sectionsmentioning

confidence: 95%

“…We obtained the results that water-to-carbon (S/C) molar ratio = 2 and oxygen-to-carbon (O 2 /C) molar ratio = 0.2 are the optimal reaction conditions. 29 Hence, the water/carbon and oxygen/carbon ratios for the catalyst activity test in this article were determined as S/C = 2 and O 2 /C = 0.2.…”

Section: Catalytic Activity In Osrmmentioning

confidence: 99%

Effect of CeO₂ Morphology in Catalytic Performance via Methanol Oxidative Steam Reforming for Hydrogen Production

Zhong,

Liang,

Huang

et al. 2024

Ind. Eng. Chem. Res.

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Methanol-based hydrogen production, including reforming, offers the advantage of yielding products with lower CO, CH 4 , and CO 2 contents, thereby reducing environmental pollution. CeO 2 is extensively employed in catalytic reforming due to its rich oxygen vacancies. However, the morphology of CeO 2 influences the oxygen vacancy content, as well as the dispersion and stability of active metal species, ultimately affecting the catalyst's performance. In this letter, we synthesized three Ni/CeO 2 catalysts with distinct morphologies (sheet, particle, and cube) and explored their catalytic activity in the oxidative steam reforming of methanol for hydrogen generation. Among the three catalysts, Ni/CeO 2 −NS exhibited a superior surface area and the high oxygen vacancy content effectively anchors Ni on the surface of CeO 2 − NS, which can better activate water and oxygen molecules in methanol oxidative steam reforming. It exhibited the highest H 2 production rate (3568.8−3729.74 mmol gcat −1 min −1 ) and methanol conversion (99.13−99.71%) at 450−600 °C. Furthermore, only marginal mass losses were observed for Ni/CeO 2 −NS (1.81%), indicating minimal carbon decomposition.

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Evaluation of neural network models and quality forecasting based on process time‐series data

Wang,

Liu,

Dong

et al. 2023

Can J Chem Eng

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Complex industrial process modelling is critically important within the context of industrial intelligence. In recent years, soft sensor techniques based on neural networks have become increasingly popular for modelling nonlinear industrial processes. This paper proposes an integrated framework of neural network modelling and evaluation for nonlinear dynamic processes. This framework achieves an integrated solution for modelling, prediction, evaluation, and network structure parameter selection. It can be applied to noisy sensors and dense data in the time domain. The framework's proposed evaluation mechanism employs two novel evaluation metrics, the variational auto‐encoder (VAE)‐based Kullback–Leibler (KL) divergence metric and the maximum likelihood estimation‐based J metric, which both evaluate the model by mining the statistical properties of the residuals. The framework models the dynamic process with a model order based‐gated recurrent units (MOb‐GRU) neural network and a modified transformer model. Numerical experiments demonstrate that the evaluation mechanism functions properly in scenarios with multiple signal‐to‐noise ratios and multiple noise statistical properties and that the framework produces accurate modelling results.

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Anti-coking Cu-Ni bimetallic catalyst for hydrogen production: Thermodynamic and experimental study of methanol autothermal reforming

Cited by 7 publications

References 59 publications

Solid solution-type Sm–Pr–O supported nickel-based catalysts for auto-thermal reforming of acetic acid: the role of Pr in solid solution

Solid solution-type Sm–Pr–O supported nickel-based catalysts for auto-thermal reforming of acetic acid: the role of Pr in solid solution

Effect of CeO₂ Morphology in Catalytic Performance via Methanol Oxidative Steam Reforming for Hydrogen Production

Evaluation of neural network models and quality forecasting based on process time‐series data

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Anti-coking Cu-Ni bimetallic catalyst for hydrogen production: Thermodynamic and experimental study of methanol autothermal reforming

Cited by 7 publications

References 59 publications

Solid solution-type Sm–Pr–O supported nickel-based catalysts for auto-thermal reforming of acetic acid: the role of Pr in solid solution

Solid solution-type Sm–Pr–O supported nickel-based catalysts for auto-thermal reforming of acetic acid: the role of Pr in solid solution

Effect of CeO2 Morphology in Catalytic Performance via Methanol Oxidative Steam Reforming for Hydrogen Production

Evaluation of neural network models and quality forecasting based on process time‐series data

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Effect of CeO₂ Morphology in Catalytic Performance via Methanol Oxidative Steam Reforming for Hydrogen Production