STUDYING PROTON CONDUCTIVTIY OF SULFONATED/FLUORINATED PROTON EXCHANGE MEMBRANES BY ARTIFICIAL NEURAL NETWORKING

سال انتشار: 1401
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 193

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شناسه ملی سند علمی:

CCHCONF01_023

تاریخ نمایه سازی: 1 شهریور 1401

چکیده مقاله:

Proton conductivity of proton exchange membranes is the determining factor of performance and efficiency for the related energy conversion, harvesting, and storage systems. The presence of both sulfonated and fluorinated groups in the structure of polymer is proposed to achieve improved conductivity and stability, simultaneously. Applying theoretical assessment techniques will be also useful to design a high performance membrane. To this end, proton conductivity of membrane samples based on sulfonated/fluorinated polysulfones are studied using artificial neural network (ANN). Fluorinated regions are put in the composition of sulfonated polymers via three strategies including synthesis of sulfonated/partially fluorinated polymers, blending sulfonated and fluorinated polymers, and composite membranes of electrospun fluorinated mat impregnated with a sulfonated matrix. Sulfonation degree (WR_S), content of fluorinated groups (WR_F), and the trend of membrane cost are studied asdetermining factors of conductivity. According to ANN, there is a direct relationship between WR_S with proton conductivity. Regarding WR_F, the optimal value must be allocated to achieve suitable conductivity. Membrane cost including WR_S, WR_F, and diol structure has the highest impact on proton conductivity.

نویسندگان

Maryam Mohammadi

Iran Polymer and Petrochemical Institute, Faculty of Polymer Science, Department of Polyurethane and Advanced Materials, Tehran, Iran

Narges Mohammadi

Universidad de Seville, Department of Mechanical Engineering and Materials, Seville, Spain

Shahram Mehdipour-Ataei

Iran Polymer and Petrochemical Institute, Faculty of Polymer Science, Department of Polyurethane and Advanced Materials,Tehran, Iran