370839 A General Mathemathical Programming Formulation for the Synthesis of Polimer Nanofibers

Monday, November 17, 2014
Galleria Exhibit Hall (Hilton Atlanta)
Julia Hernandez-Vargas, CHEMICAL ENGINEERING, UNIVERSIDAD MICHOACANA DE SAN NICOLAS DE HIDALGO, MORELIA, Mexico, Janett Betzabe Gonzalez-Campos, Institute of Chemical and Biological Researches, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Mexico and José María Ponce-Ortega, Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacan, Mexico

The optimal synthesis of nanofibers has been the subject of several research efforts in recent days. This is because nanofibers represent a high potential to be used in biomedical applications due to the high surface area respect to the volume and their microporous structure, for this reason nanofibers are currently the fastest growing segment of the nanotechnology market. This is because they have potential applications in medicine, including artificial organ components, tissue engineering, implant materials, drug delivery and wound dressing. Among all the current techniques available for the synthesis of nanofibers electrospinning is the most widely studied technique. Different parameters influence the electrospinning process to yield nanofibers with good quality and diameter, and several studies have focused in analyzing the effect of these variables on morphology and fiber’s diameter which are key parameters for potential biomedical applications. However, it is important to note that the cost has not been previously considered as key parameter in the synthesis of nanofibers.

Therefore, this paper presents a general mathematical programming formulation to determine the optimal operating conditions to synthesize nanofibers through the electrospinning process at the minimum cost. Mathematical programming has the advantage that it allows to manipulate a lot of variables and constraints to determine the optimal solution of a given problem and particularly, disjunctive programming formulations allow to easily representing a complex combinatorial problem. Several relationships based on experimental data for different natural polymers to determine the nanofiber diameter and costs are proposed. Also, a general optimization approach is proposed to trade off the relationships between cost and nanofiber diameter. A case study including the specific relationships for three natural polymers and five operating conditions is presented. The proposed approach is general and it can be applied to different cases.

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