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Magnesium degradation as determined by artificial neural networks ☆

Paper ID Volume ID Publish Year Pages File Format Full-Text
584 51 2013 8 PDF Available
Title
Magnesium degradation as determined by artificial neural networks ☆
Abstract

Magnesium degradation under physiological conditions is a highly complex process in which temperature, the use of cell culture growth medium and the presence of CO2, O2 and proteins can influence the corrosion rate and the composition of the resulting corrosion layer. Due to the complexity of this process it is almost impossible to predict the parameters that are most important and whether some parameters have a synergistic effect on the corrosion rate. Artificial neural networks are a mathematical tool that can be used to approximate and analyse non-linear problems with multiple inputs. In this work we present the first analysis of corrosion data obtained using this method, which reveals that CO2 and the composition of the buffer system play a crucial role in the corrosion of magnesium, whereas O2, proteins and temperature play a less prominent role.

Keywords
Magnesium degradation; Implants; In vitro; Cell culture conditions; Artificial neural networks
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Magnesium degradation as determined by artificial neural networks ☆
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Publisher
Database: Elsevier - ScienceDirect
Journal: Acta Biomaterialia - Volume 9, Issue 10, November 2013, Pages 8722–8729
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us