We demonstrate epoxy-silver nanoparticle composites with high thermal conductivity κ
enabled by self-constructed nanostructured networks (SCNN) forming during the curing …

In this study, a new method was developed for the characterization of the interface
morphology in polymer/particle composites. This method, not limited to a specific polymer or …

In this review, a comprehensive and systematic effort is made to incorporate the most
significant and popular models for calculation of the effective thermal conductivity of complex …

In this work, we investigate the thermal conductivity of a three-component composite
consisting of FeCr metal core–aluminum oxide shell particles with a highly mesoporous …

In the present work, existing permeation models for mixed matrix membranes (MMMs) are
introduced in two categories. A new permeation model is proposed based on thermal …

Artificial neural networks (ANNs) are flexible computing networks and universal optimizers
that can be applied to modelling of different material properties. Modelling of the effective …

In the present study, the adaptive neuro-fuzzy inference system (ANFIS) is developed for the
prediction of effective thermal conductivity (ETC) of different fillers filled in polymer matrixes …

The effective thermal conductivity (ETC) of polymer composites is studied using artificial
neural networks. Artificial neural networks are a form of artificial intelligence, which attempt …

Theoretical model for predicting effective thermal conductivity (ETC) of metal filled polymer
composites has been developed. The concept of averaging the temperature field within …

This book addresses the fundamentals of CO2 storage for long-term sequestration in a
subsurface geologic formation. In general, membrane gas separation can find a large room …