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CO2 Hydrate Formation Kinetics in the Presence of a Layered Double Hydroxide Nanofluid
被引:3
|作者:
Ansari, Ayaj Ahamad
[1
]
Ravesh, Randeep
[1
]
Chakraborty, Samarshi
[1
,2
]
Panigrahi, Pradipta Kumar
[1
]
Das, Malay Kumar
[1
]
机构:
[1] Indian Inst Technol Kanpur, Dept Mech Engn, Kanpur 208016, India
[2] Vellore Inst Technol, Sch Chem Engn, Vellore 632014, India
关键词:
Artificial neural networks;
Chemical affinity;
Gas hydrates;
Layered double hydroxide nanofluid;
Storage capacity;
SILVER NANOPARTICLES;
ENERGY-CONSUMPTION;
MODEL;
CAPTURE;
DISSOCIATION;
PREDICTION;
IMPACT;
WATER;
THF;
D O I:
10.1002/ceat.202200502
中图分类号:
TQ [化学工业];
学科分类号:
0817 ;
摘要:
The effects of a hybrid nanofluid (Cu-Al layered double hydroxide (LDH)) on the CO2 hydrate formation kinetics was investigated at three different nanofluid concentrations (0.25-1.0 wt %). The Cu-Al LDH nanofluid was prepared using a one-step co-precipitation technique. The addition of the LDH nanofluid reduces the induction time and enhances the hydrate formation kinetics. The maximum reduction in the induction time (by 91.08 %) was observed at the optimal nanofluid concentration of 0.5 wt %, compared to water. A chemical affinity model was implemented to predict the experimental data for CO2 hydrate formation in the presence of the different LDH nanofluid concentrations. An artificial neural network-based Levenberg-Marquardt model predicts the experimental data with higher accuracy than the scaled conjugate gradient model. The results indicate a strong dependency of the hydrate formation kinetics on the LDH nanofluid concentrations.
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页码:1630 / 1638
页数:9
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