scholarly journals Pulverized river shellfish shells as a 904 cheap adsorbent for removing of malathion from water: Examination of the isotherms, kinetics, thermodynamics and optimization of the experimental conditions by the response surface method

2021 ◽  
Vol 69 (4) ◽  
pp. 871-904
Author(s):  
Zlate Veličković ◽  
Bogdan Vujičić ◽  
Vladica Stojanović ◽  
Predrag Stojisavljević ◽  
Zoran Bajić ◽  
...  

Introduction/purpose: In this study, we investigated the possibility of removing the organophosphorus pesticide malathion from water using a new adsorbent based on the biowaste of river shell shards from the Anodonta Sinadonta woodiane family, a material that accumulates in large quantities as waste on the banks of large rivers. Two adsorbents were tested - mechanically comminuted river shells (MRM) and mechanosynthetic hydroxyapatite from comminuted river shells (RMHAp). Methods: The obtained adsorbents were characterized and tested for the removal of the organophosphorus pesticide malathion from water. In order to predict the optimal adsorption conditions using the Response Surface Method (RSM), the authors investigated the influence of variable factors (adsorption conditions), pH values, adsorbent doses, contact times, and temperatures on the adsorbent capacity. Results: The best adsorption of malathion was achieved at mean pH values between 6.0 and 7.0. The adsorption data for malathion at 25, 35, and 45 °C were compared using the Langmuir, Freundlich, DubininRadushkevich (DR), and Temkin isothermal models, as well as pseudofirst order, pseudo-second order and Elovic kinetic models for modeling adsorption kinetics. The maximum Langmuir adsorption capacity for MRM and RMHAp at 25 °C was 46,462 mg g-1 and 78,311 mg g-1 , respectively. Conclusion: The results have showed that malathion adsorption on both adsorbents follows the pseudo-second kinetic model and the Freundlich isothermal model. The thermodynamic parameters indicate the endothermic, feasible, and spontaneous nature of the adsorption process.

2014 ◽  
Vol 134 (9) ◽  
pp. 1293-1298
Author(s):  
Toshiya Kaihara ◽  
Nobutada Fuji ◽  
Tomomi Nonaka ◽  
Yuma Tomoi

Materials ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 3552 ◽  
Author(s):  
Chun-Yi Zhang ◽  
Jing-Shan Wei ◽  
Ze Wang ◽  
Zhe-Shan Yuan ◽  
Cheng-Wei Fei ◽  
...  

To reveal the effect of high-temperature creep on the blade-tip radial running clearance of aeroengine high-pressure turbines, a distributed collaborative generalized regression extremum neural network is proposed by absorbing the heuristic thoughts of distributed collaborative response surface method and the generalized extremum neural network, in order to improve the reliability analysis of blade-tip clearance with creep behavior in terms of modeling precision and simulation efficiency. In this method, the generalized extremum neural network was used to handle the transients by simplifying the response process as one extremum and to address the strong nonlinearity by means of its nonlinear mapping ability. The distributed collaborative response surface method was applied to handle multi-object multi-discipline analysis, by decomposing one “big” model with hyperparameters and high nonlinearity into a series of “small” sub-models with few parameters and low nonlinearity. Based on the developed method, the blade-tip clearance reliability analysis of an aeroengine high-pressure turbine was performed subject to the creep behaviors of structural materials, by considering the randomness of influencing parameters such as gas temperature, rotational speed, material parameters, convective heat transfer coefficient, and so forth. It was found that the reliability degree of the clearance is 0.9909 when the allowable value is 2.2 mm, and the creep deformation of the clearance presents a normal distribution with a mean of 1.9829 mm and a standard deviation of 0.07539 mm. Based on a comparison of the methods, it is demonstrated that the proposed method requires a computing time of 1.201 s and has a computational accuracy of 99.929% over 104 simulations, which are improvements of 70.5% and 1.23%, respectively, relative to the distributed collaborative response surface method. Meanwhile, the high efficiency and high precision of the presented approach become more obvious with the increasing simulations. The efforts of this study provide a promising approach to improve the dynamic reliability analysis of complex structures.


2021 ◽  
Author(s):  
Alfikri Khair ◽  
Haryudini A. Putri ◽  
Suprapto Suprapto ◽  
Yatim L. Ni’mah

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