About the book Highlighting a broad range multiscale modeling and methods for anticipating the morphologies and the properties of interfaces and multiphase materials, this reference covers the methodology of predicting polymer properties and its potential application to a wider variety of polymer types ...
Highlighting a broad range multiscale modeling and methods for anticipating the morphologies and the properties of interfaces and multiphase materials, this reference covers the methodology of predicting polymer properties and its potential application to a wider variety of polymer types than previously thou...
A new group-contribution modified cell model equation of state (GCMCM EOS) has been developed to predict pressure–volume–temperature (PVT) properties of polymer melts. The equation uses monomer group contributions to estimate the characteristic parameters in the modified cell model (MCM EOS) propos...
A. Askadskii, Computational Materials Science of Polymers (Cambridge International Science, Cambridge, 2003), p. 696. Google Scholar J. Bicerano, Prediction of Polymer Properties (Marcel Dekker, New York, 1996), p. 528. Google Scholar D. W. Van Krevelen, Properties of Polymers. Their Est...
Therefore, this study aims to reveal the rheological performance of high polymer-modified asphalt binder and to develop a prediction model based on the correlation between its rheological properties and chemical composition. Polymer-modified asphalt binders with varying styrene–butadiene–styrene polymer ...
Despite the usage of machine learning accelerating the properties prediction of polymer materials, obtaining a large number of samples to achieve accurate and fast predictions remains a challenge because of the complex and lengthy experimental process. In this work, an advanced prediction model for the...
Since our initial goal is to assist the design of high dielectric constant polymers for energy storage, the polymer dataset supplies the equilibrium (relaxed) structures of the materials associated with relevant calculated properties, including the atomization energy Eat, the dielectric constant ε and ...
The mechanical properties of a crosslinking isocyanate–hydroxy system were predicted by a combination of the measured curing kinetics and a model for polymer network growth. The kinetic parameters were determined from FTIR using the linear rising temperature method (the activation energy = 52 kJ/mol...
This article provides a comprehensive review of the suitability of the various micro-mechanical models for accurately predicting the tensile properties, namely, tensile strength (TS) and Young’s modulus (YM) of the biocomposites. A brief overview of the developed conventional micro-mechanical models ...
Enantioselectivity prediction in asymmetric catalysis has been a long-standing challenge in synthetic chemistry because of the high-dimensional nature of the structure–enantioselectivity relationship. A lack of understanding of the synthetic space results in laborious and time-consuming efforts in the discov...