Optimization of bisphenol A removal from water using NaP: HAp nanocomposite and modeling of experimental results by artificial neural networks

سال انتشار: 1396
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 340

متن کامل این مقاله منتشر نشده است و فقط به صورت چکیده یا چکیده مبسوط در پایگاه موجود می باشد.
توضیح: معمولا کلیه مقالاتی که کمتر از ۵ صفحه باشند در پایگاه سیویلیکا اصل مقاله (فول تکست) محسوب نمی شوند و فقط کاربران عضو بدون کسر اعتبار می توانند فایل آنها را دریافت نمایند.

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

NZEOLITE04_089

تاریخ نمایه سازی: 11 شهریور 1397

چکیده مقاله:

The increasing population and urbanization of society caused to increase production and distribution of toxic chemicals, containing the endocrine-disrupting chemicals (EDCs) into the environment [1]. Many EDCs excluding natural estrogens (e.g. estrone (E1), 17b-strodial (E2), and estriol (E3)), synthesized estrogen (e.g.ethinylestradiol (EE2)), and industrial compounds (e.g. bisphenol A (BPA) and nonylphenol) are organic compounds that they have various adverse health effect as be reported in recent years [2]. One of the known endocrine disruptors is Bisphenol A (BPA; 2, 2-bis(4-hydroxyphenyl) propane that has an important toxicity to aquatic organisms in the range of 1–10 ϻg/ml for freshwater and marine species [3,4]. BPA is widely used as a raw material in the production of polycarbonate plastics, polyesters, phenol resins, polyacrylates, epoxy resins and lacquer coatings on food cans [5]. Due to the widespread utilization of BPA, there is increasing interest in effective remediation technologies for its removal from contaminated water. Some methods such as, adsorption [6], membrane separation [7], solvent extraction [8] and photo degradation [9] are used. Among these methods, Adsorption is widely used to remove refractory trace compounds with a high potential of adsorption because of simplicity and high efficiency. In this study NaP:HAp nanocomposite was used as an effective adsorbent for removal of BPA and Also in this study, an artificial neural networks (ANNs) model type (i) was developed to predict the performance adsorption process over synthesized adsorbent based on data from bath experiments. A comparison between the predicted results of the designed ANN model and experimental data was also conducted.

نویسندگان

b shoshtari-yeganeh

Department of Chemistry, Faculty of Science, Arak University, Arak۳۸۱۵۶-۸- ۸۳۴۹; Iran

m zendehdel

Department of Chemistry, Faculty of Science, Arak University, Arak۳۸۱۵۶-۸- ۸۳۴۹; Iran

g Cruciani

Department of Physics and Earth Sciences, University of Ferrara , Via G. Saragat ۱, I-۴۴۱۲۲ Ferrara, Italy