The method was found to be useful in the prediction of polymer Tg.
The characteristic LSER descriptors are used for the prediction of polymer – polymer miscibility as well as for handling IGC data for multicomponent systems.
During March 20 24, 2016, over 50 engineers and scientists from across the globe attended the "Service Life Prediction of Polymer Materials: Over the Horizon" conference at the Hilton Santa Fe in Santa Fe, NM, USA.
This behaviour is partially well known, but often the underlying mechanisms are not understood to a degree, which would make a prediction of polymer behaviour possible based on short and long chain branching, as well as general architecture.
The model allows the computation of mass and energy inventories and the prediction of polymer molecular structure and morphology, including the molecular weight distribution, the chain composition distribution, the particle size distribution and the stereo-block distribution.
Taking Shengli oilfield as an example, the history matching and prediction of polymer flooding are carried out, it is indicated that there exists a good matching between the quantitative characterization model and the field data, and this model can be extrapolated.
This work improves the prediction of polymer viscosity in underground environment.
The proposed method can also be used for structure prediction of polymers to match a target Tg value, by keeping the thermal behavior of a terpolymer constant while independently choosing its chemistry.
In fact, in polymer flooding investigations, the precise prediction of the polymer solution viscosity is a critical task.
In this work we apply a population balance approach for the prediction of important polymer properties such as molecular-weight and copolymer composition distributions.
