کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
232572 465292 2014 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Photocatalytic degradation of chlorhexidine—A chemical assessment and prediction of optimal condition by response surface methodology
ترجمه فارسی عنوان
تخریب فوتوکاتالیستی کلرهگزیدینا - ارزیابی شیمیایی و پیش بینی شرایط بهینه توسط روش سطح پاسخ
کلمات کلیدی
کلرهگزیدین دیگو لوونات، زباله دارویی، عکس کانی سازی، فوتوکاتالیست، بهینه سازی فرآیند
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی مهندسی شیمی (عمومی)
چکیده انگلیسی

Present study demonstrates an intensive experimental study on the photo-mineralization of an antiseptic drug component, chlorhexidine digluconate in batch slurry photo reactor in presence of ultra-violet light and using titanium dioxide as catalyst. Chlorhexidine digluconate belongs to the typical class of antiseptic drug components that generally used in disinfectants, cosmetics and pharmaceutical products. This study aims to analyze the influence of operating parameters, and their interactive effect on the overall removal efficiency of the targeted drug component from waste stream, and prediction of the optimum condition for up-scaling the technique and design of the photocatalytic reactor. Response surface methodology has been used to develop a multi-variant regression model and to assess the influence of individual parameters as well as the interactive effects. Substrate to catalyst ratio, UV intensity and medium pH were chosen as independent variables to optimize the percent removal of chlorhexidine digluconate as response. Optimal conditions obtained from statistical analysis at substrate to catalyst ratio 1.25, UV intensity 87.5 μW cm−2 at pH 10.5 have shown percent removal of 67.47 with desirability factor of 0.989. Model predicted values were found in good agreement with the experimental values, and the behavior of the model equation has supported the experimental observation with minor deviation. Separate validation experiment at predicted optimal condition ascertained the high predictive ability of the model equation.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Water Process Engineering - Volume 2, June 2014, Pages 79–86
نویسندگان
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