What is it about?
The aim of this study was to predict the effects of different parameters on the conductivity of mineralized PAN-based carbon nanofibers by the artificial neural network (ANN) method.
Featured Image
Why is it important?
The predicting approaches have an undeniable role in the fabrication and optimization of nanomaterials. Among the predicting methods, artificial neural network (ANN) has gained much attention due to its precise prediction and also flexibility in determining the parameters. Mineralized carbon nanofibers have outstanding properties such as high mechanical strength, remarkable electrical conductivity, osteoinductivity, and osteoconductivity. These futures made mineralized PAN-based carbon nanofibers an ideal material for bone graft and filling.
Perspectives
Read the Original
This page is a summary of: Effective parameters on conductivity of mineralized carbon nanofibers: an investigation using artificial neural networks, RSC Advances, January 2016, Royal Society of Chemistry,
DOI: 10.1039/c6ra21596c.
You can read the full text:
Resources
Contributors
The following have contributed to this page