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Environmental Dynamic Mechanical Analysis to Predict the Softening Behavior of Neural Implants.
Hosseini, Seyed Mahmoud; Voit, Walter E; Ecker, Melanie.
Afiliação
  • Hosseini SM; Department of Chemistry and Biochemistry, University of Texas at Dallas.
  • Voit WE; Department of Chemistry and Biochemistry, University of Texas at Dallas; Department of Materials Science and Engineering, University of Texas at Dallas; Center for Engineering Innovation, University of Texas at Dallas.
  • Ecker M; Department of Materials Science and Engineering, University of Texas at Dallas; Center for Engineering Innovation, University of Texas at Dallas; Department of Bioengineering, University of Texas at Dallas; melanie.ecker@utdallas.edu.
J Vis Exp ; (145)2019 03 01.
Article em En | MEDLINE | ID: mdl-30882794
ABSTRACT
When using dynamically softening substrates for neural implants, it is important to have a reliable in vitro method to characterize the softening behavior of these materials. In the past, it has not been possible to satisfactorily measure the softening of thin films under conditions mimicking body environment without substantial effort. This publication presents a new and simple method that allows dynamic mechanical analysis (DMA) of polymers in solutions, such as phosphate buffered saline (PBS), at relevant temperatures. The use of environmental DMA allows measurement of the softening effects of polymers due to plasticization in various media and temperatures, which therefore allows a prediction of the materials behavior under in vivo conditions.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Próteses e Implantes / Fenômenos Mecânicos / Próteses Neurais Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Vis Exp Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Próteses e Implantes / Fenômenos Mecânicos / Próteses Neurais Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Vis Exp Ano de publicação: 2019 Tipo de documento: Article