کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4998302 1460063 2017 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Ultrasonic extraction of natural dye from Rubia Cordifolia, optimisation using response surface methodology (RSM) & comparison with artificial neural network (ANN) model and its dyeing properties on different substrates
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی تکنولوژی و شیمی فرآیندی
پیش نمایش صفحه اول مقاله
Ultrasonic extraction of natural dye from Rubia Cordifolia, optimisation using response surface methodology (RSM) & comparison with artificial neural network (ANN) model and its dyeing properties on different substrates
چکیده انگلیسی


- Mining of natural dye from Rubia Cordifolia by extraction process.
- Modelling and comparison of the dye extracted with CCD & ANN.
- Higher dye ratio was obtained using ultrasonic extraction.
- TLC and FT-IR Spectroscopy for compound identification.
- Extracted dye applied for dyeing leather & cotton fabric with different mordants.

Extraction of natural dye from the roots of Rubia Cordifolia by conventional extraction, as well as by using ultrasonic extraction, has been performed in this study. Process variables, namely ultrasonic frequency (25, 40, 58 kHz), solid-to-liquid ratio (1:5, 1:10, 1:15) and extraction time (2, 2.5, 3 h) were studied, and the optimum condition was determined using three-factor Central Composite Design (CCD). The optimum extraction condition obtained from CCD was 25 kHz ultrasonic frequency, 1:15 solid-to-liquid ratio and extraction time of 3 h. The experimental result obtained at the optimum condition is in good agreement with the predicted value. An Artificial Neural Network(ANN) model was also developed, and the predictions are compared with values obtained from Response Surface Methodology (RSM) model. The extracted compounds were identified using TLC and FT-IR Spectroscopy. The extracted dye was used for dyeing leather and cotton fabric along with different mordants to obtain different shades.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemical Engineering and Processing: Process Intensification - Volume 114, April 2017, Pages 46-54
نویسندگان
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