Reusability, optimization, and adsorption studies of modified graphene oxide in the removal of Direct Red ۸۱ using response surface methodology
Publish place: Advances in Environmental Technology، Vol: 6، Issue: 4
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
View: 147
This Paper With 11 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_AET-6-4_001
تاریخ نمایه سازی: 18 آبان 1400
Abstract:
In the present study, graphene oxide (GO) was synthesized by the oxidation of graphite powder using the Hummers method. The GO was polymerized with poly methyl vinyl ketone (PMVK) and aniline (GO-MVK-ANI). It was utilized as the effective adsorbent towards the removal of Direct Red ۸۱ (DR ۸۱) in aqueous solutions. Response surface methodology (RSM) was applied for optimization and adsorption studies of Direct Red ۸۱ removal using GO-MVK-ANI. According to the RSM results, the effects of the main parameters (the adsorbent dose, contact time, and pH) in dye removal efficiency were investigated. The R۲ value of ۹۹.۹۹% indicated that the predictions of the RSM model were acceptable for Direct Red ۸۱ adsorption onto the adsorbent. The regeneration of GO-MVK-ANI for the dye adsorption showed fine efficacy in up to seven times of recyclability. The RSM model was used to evaluate the respective minimum and maximum values of ۵۶.۵۲% and ۹۹.۹۰% for the removal efficiencies of Direct Red ۸۱.
Keywords:
Authors
Avideh Azizi
Department of Environmental Engineering, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran
Elham Moniri
Department of Chemistry, Varain (Pishva) Branch, Islamic Azad University, Pishva, Iran
Amir Hessam Hassani
Department of Environmental Engineering, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran
Homayon Ahmad Panahi
Department of Chemistry, Central Tehran Branch, Islamic Azad University, Tehran, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :