Investigation on enhancement of filler dispersion and prediction of mechanical behavior of hexagonal boron nitride/epoxy nanocomposites through machine learning and deep learning models

Two‐dimensional hexagonal boron nitride (hBN) based nanocomposites exhibit excellent mechanical and thermal properties for various electronics, automotive, and aerospace applications. The present work gives a novel approach to fabricating hexagonal boron nitride/epoxy nanocomposites using isopropano...

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Veröffentlicht in:	Polymer composites 2024-05, Vol.45 (7), p.6287-6304
Hauptverfasser:	Varughese, Jerrin Joy, M. S., Sreekanth
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Boron Boron nitride Casting machines Deep learning Dispersants Fillers Flexural strength Isopropanol Ketones Machine learning Mathematical models Mechanical properties Modulus of elasticity Modulus of rupture in bending morphology nanocomposite Nanocomposites Neural networks Photomicrographs Regression Support vector machines Tensile strength thermal properties Thermal stability Thermodynamic properties
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