کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1694673 1519080 2014 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Organoclay maleated natural rubber nanocomposite. Prediction of abrasion and mechanical properties by artificial neural network and adaptive neuro-fuzzy inference
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات ژئوشیمی و پترولوژی
پیش نمایش صفحه اول مقاله
Organoclay maleated natural rubber nanocomposite. Prediction of abrasion and mechanical properties by artificial neural network and adaptive neuro-fuzzy inference
چکیده انگلیسی


• Maleated NR was used in NR/organoclay nanocomposite and intercalation was increased.
• A higher interfacial interaction between NR molecules and organoclay was observed.
• Tensile, modulus (storage, elastic and 100%) and abrasion resistance were improved.
• ANN and ANFIS intelligence methods were used to model the sample properties.
• Predicted results by modeling were in good agreement with the experimental ones.

Maleated natural rubber (MNR) was produced and employed in different amounts as compatibilizer in preparation of organoclay/natural rubber (OC/NR) nanocomposite. Oscillating disk rheometry, scanning electron microscopy (SEM), X-ray diffraction (XRD) analysis, rheomechanical spectroscopy, dynamic mechanical analysis, tensile and abrasion tests were used to evaluate the prepared samples. The obtained results showed that the use of MNR caused an increase in the maximum torque of rheometry, curing rate index and crosslink density. XRD analysis indicated that using of MNR, especially in the amount of 8 parts, resulted in a greater intercalation of OC layers. SEM showed a good dispersion of the OC as well as higher interfacial interaction between NR molecules and OC. These lead to improvement of modulus, tensile strength and abrasion resistance. Then the obtained results were modeled by artificial intelligence techniques. Comparison made between experimental and predicted values, indicated that the modeling results were in good agreement with the corresponding experimental amounts.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Clay Science - Volumes 97–98, August 2014, Pages 187–199
نویسندگان
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