Quantitative relationships between structure and glass transition temperature Tg and of polyethylene analogues has been studied. The study was done by using molecular modeling of polymer assumed in trimeric compound in their indiotactic form and the calculation was performed by semiempirical AM1 method. The physicochemical properties of molecule was focused on 11 descriptors i.e. atomic net charges of carbon atom as the head and tail of the polymer chain (qC1 and qC2), polarizability (α), moment dipole (μ), refractivity index, partition coefficient of n-octanol-water (log P), molecular weight (MW), volume van der Waals (VVDW), molecular surface area, Parachor index and solubility in the water (log SW). Correlation analysis of Tg polymers to...
New models and calculation schemes have been developed for the quantitative analysis of a number of ...
The glass transition temperatures of nine stoichiometric resin systems of tetraglycidyl-4,4′-diamino...
In this work convolutional-fully connected neural networks were designed and trained to predict the ...
The technique of Quantitative Structure Property Relationships has been applied to the glass transit...
The technique of Quantitative Structure Property Relationships has been applied to the glass transit...
ii A polymer has drastically different physical properties above versus below some characteristic te...
The glass transition temperature, Tg, is one of the most important properties of amorphous polymers....
The glass transition temperature is a vital property of polymers with a direct impact on their stabi...
The glass transition temperature, Tg, is one of the most important properties of amorphous polymers....
A new relationship, which correlates the glass transition temperature (T(g)) with other molecular pa...
SIMMARY A large data set of 117S polymers, with corresponding glass transition tempera-tures, is tab...
Group contribution methods have been widely used for the estimation and prediction of properties of ...
There are many experimental methods to determine the molecular weight of the polymers. The viscosity...
Glass transition temperature (Tg) is the temperature at which a polymer changes from crystalline st...
A nonlinear model and a linear model have been developed to correlate glass transition temperature (...
New models and calculation schemes have been developed for the quantitative analysis of a number of ...
The glass transition temperatures of nine stoichiometric resin systems of tetraglycidyl-4,4′-diamino...
In this work convolutional-fully connected neural networks were designed and trained to predict the ...
The technique of Quantitative Structure Property Relationships has been applied to the glass transit...
The technique of Quantitative Structure Property Relationships has been applied to the glass transit...
ii A polymer has drastically different physical properties above versus below some characteristic te...
The glass transition temperature, Tg, is one of the most important properties of amorphous polymers....
The glass transition temperature is a vital property of polymers with a direct impact on their stabi...
The glass transition temperature, Tg, is one of the most important properties of amorphous polymers....
A new relationship, which correlates the glass transition temperature (T(g)) with other molecular pa...
SIMMARY A large data set of 117S polymers, with corresponding glass transition tempera-tures, is tab...
Group contribution methods have been widely used for the estimation and prediction of properties of ...
There are many experimental methods to determine the molecular weight of the polymers. The viscosity...
Glass transition temperature (Tg) is the temperature at which a polymer changes from crystalline st...
A nonlinear model and a linear model have been developed to correlate glass transition temperature (...
New models and calculation schemes have been developed for the quantitative analysis of a number of ...
The glass transition temperatures of nine stoichiometric resin systems of tetraglycidyl-4,4′-diamino...
In this work convolutional-fully connected neural networks were designed and trained to predict the ...