Representation of adsorption data for the isopropanol-water system using neural network techniques

Farouq Mjalli*, Sameer Al-Asheh, Fawzi Banat, Nasir Al-Lagtah

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةArticleمراجعة النظراء

9 اقتباسات (Scopus)

ملخص

Molecular sieves and palm stone, a newly developed bio-based adsorbent, were used to break an azeotropic isopropanol-water system via an adsorptive distillation process. Equilibrium data at different inlet water contents are presented. The data were obtained with a fixed bed adsorptive distillation process using Type 3A and Type 4A molecular sieves and palm stone. An artificial neural network (ANN) technique was used to represent the isotherm equilibrium data of this azeotropic system. The ANN prediction results were compared with the Guggenheim-Anderson-de Boer (GAB) isotherm model. It was possible to break the isopropanol-water azeotrope using this separation process with the adsorbents used in this work. Water uptake increases as the water content in the feed decreases from 16 % to 10 %. Although the GAB isotherm model was found to be applicable to the water vapor sorption data on the adsorbents examined, the ANN model fitted the equilibrium data more efficiently.

اللغة الأصليةEnglish
الصفحات (من إلى)1529-1539
عدد الصفحات11
دوريةChemical Engineering and Technology
مستوى الصوت28
رقم الإصدار12
المعرِّفات الرقمية للأشياء
حالة النشرPublished - ديسمبر 2005
منشور خارجيًانعم

ASJC Scopus subject areas

  • ???subjectarea.asjc.1600.1600???
  • ???subjectarea.asjc.1500.1500???
  • ???subjectarea.asjc.2200.2209???

بصمة

أدرس بدقة موضوعات البحث “Representation of adsorption data for the isopropanol-water system using neural network techniques'. فهما يشكلان معًا بصمة فريدة.

قم بذكر هذا