Fabrication of MnWO۴ modified ZnS nanocomposite as an effective nanoadsorbent: Experimental investigation and neural network modeling

  • سال انتشار: 1402
  • محل انتشار: مجله بین المللی فناوری نانو در آب و محیط زیست، دوره: 8، شماره: 1
  • کد COI اختصاصی: JR_JWENT-8-1_008
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 159
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نویسندگان

Balasubramani Kavitha

P.G and Research Department of Chemistry, C.P.A. College, Bodinayakanur, Tamilnadu, India.

Sharumathi Selvam

P.G and Research Department of Chemistry, C.P.A. College, Bodinayakanur, Tamilnadu, India.

Sivakumar Subburam

Department of Computer Science, C.P.A. College, Bodinayakanur, Tamilnadu, India.

چکیده

The purpose of this study was to determine the adsorptive characteristics of a MnWO۴/ZnS nanocomposite for removing Amaranth dye from aqueous solution. A simple chemical precipitation approach was used to make the MnWO۴/ZnS nanocomposite. The crystal structure, morphology, and pore size of the resulting nanocomposites were evaluated by UV-vis-DRS, FT-IR, XRD, SEM, EDAX and BET. In a laboratory batch adsorption experiment, the effect of operational parameters such as adsorbent dose, starting dye concentration, agitation speed, contact time, and temperature was investigated to optimise the conditions for maximum amaranth removal. To reduce the number of trials and the associated costs, an artificial neural network (ANN) was used to forecast dye removal effectiveness. For amaranth dye, a contact time of ۱۸۰ minutes, an adsorbent dosage of ۰.۳۵ g/l, and an initial dye concentration of ۱۰ M resulted in a ۹۶ percent dye removal. Different models were used to fit the equilibrium isotherm data. Langmuir and Temkin models have high R۲ and are in good agreement with the experimental data (۰.۹۹۶۶ and ۰.۹۹۲۷). T and film diffusion may be involved in the sorption process, according to the kinetic analysis. When the experimental data was compared to the dye adsorption efficiency predicted by the artificial neural network model, it was discovered that this model can accurately predict the behaviour of the amaranth dye adsorption process on MnWO۴/ZnS under various conditions.

کلیدواژه ها

MnWO۴/ZnS, Artificial neural network, amaranth dye

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