CO2 Hydrate Formation Kinetics in the Presence of a Layered Double Hydroxide Nanofluid

被引:2
|
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.
引用
收藏
页码:1630 / 1638
页数:9
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