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Predicting the Biodegradation of Magnesium Alloy Implants: Modeling, Parameter Identification, and Validation.
Amerinatanzi, Amirhesam; Mehrabi, Reza; Ibrahim, Hamdy; Dehghan, Amir; Shayesteh Moghaddam, Narges; Elahinia, Mohammad.
Afiliação
  • Amerinatanzi A; Dynamic and Smart Systems Laboratory, Mechanical Industrial and Manufacturing Engineering Department, The University of Toledo, Toledo, OH 43606, USA. amirhesam.amerinatanzi@utoledo.edu.
  • Mehrabi R; Dynamic and Smart Systems Laboratory, Mechanical Industrial and Manufacturing Engineering Department, The University of Toledo, Toledo, OH 43606, USA. reza.mehrabinejad@gmail.com.
  • Ibrahim H; Mechanical Engineering Department, The University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA. hamdy-ibrahim@utc.edu.
  • Dehghan A; School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, Corvallis, OR 97331, USA. dehghana@oregonstate.edu.
  • Shayesteh Moghaddam N; Mechanical & Aerospace Engineering, University of Texas at Arlington, Arlington, TX 76019, USA. narges.shayesteh@uta.edu.
  • Elahinia M; Dynamic and Smart Systems Laboratory, Mechanical Industrial and Manufacturing Engineering Department, The University of Toledo, Toledo, OH 43606, USA. mohammad.elahinia@utoledo.edu.
Bioengineering (Basel) ; 5(4)2018 Nov 29.
Article em En | MEDLINE | ID: mdl-30501102
ABSTRACT
Magnesium (Mg) and its alloys can degrade gradually up to complete dissolution in the physiological environment. This property makes these biomaterials appealing for different biomedical applications, such as bone implants. In order to qualify Mg and its alloys for bone implant applications, there is a need to precisely model their degradation (corrosion) behavior in the physiological environment. Therefore, the primary objective develop a model that can be used to predict the corrosion behavior of Mg-based alloys in vitro, while capturing the effect of pitting corrosion. To this end, a customized FORTRAN user material subroutine (or VUMAT) that is compatible with the finite element (FE) solver Abaqus/Explicit (Dassault Systèmes, Waltham, MA, USA) was developed. Using the developed subroutine, a continuum damage mechanism (CDM) FE model was developed to phenomenologically estimate the corrosion rate of a biocompatible Mg⁻Zn⁻Ca alloy. In addition, the mass loss immersion test was conducted to measure mass loss over time by submerging Mg⁻Zn⁻Ca coupons in a glass reactor filled with simulated body fluid (SBF) solution at pH 7.4 and 37 °C. Then, response surface methodology (RSM) was applied to calibrate the corrosion FE model parameters (i.e., Gamma (γ), Psi (ψ), Beta (ß), and kinetic parameter (Ku)). The optimum values for γ, ψ, ß and Ku were found to be 2.74898, 2.60477, 5.1, and 0.1005, respectively. Finally, given the good fit between FE predictions and experimental data, it was concluded that the numerical framework precisely captures the effect of corrosion on the mass loss over time.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article