Macromolecular Theory and Simulations
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Best of Macromolecular Journals
Best of Macros 2017 is now online. Click here to read about the selected articles and their authors.
Recently Published Articles
- Dynamics of Branched Polymers in Random Layered Flows with Intramolecular Hydrodynamic Coupling: Star and Dendrimer
Divya Katyal and Rama Kant
Version of Record online: 25 APR 2017 | DOI: 10.1002/mats.201700009
Theory for the anomalous diffusive behavior of flexible branched polymer in random flows is developed. Random flow induces transition from subdiffusive to superdiffusive behavior. Results illustrate faster movement of larger polymer compared to smaller. The inclusion of intramolecular hydrodynamic interactions in random flows further enhances the average square displacement and shortens the crossover time.
- Static and Dynamic Scaling Close to Gelation in Chain-Polymerization: Effect of Reactor Type
Chinmay Das, Daniel J. Read, Johannes M. Soulages and Pradeep P. Shirodkar
Version of Record online: 18 APR 2017 | DOI: 10.1002/mats.201700006
Copolymerization of two and four functional groups in semibatch reactor leads to diverging weight averaged molar mass and zero shear viscosity with an exponent −4.5 as gelation is approached with increasing amount of four functional groups. In contrast, in continuous stirred tank reactor, the number, weight, and z-averaged molar masses remain finite and viscosity diverges with an exponent −1.2.
- Step-Growth Polymerizing Systems of General Type “AfiBgi”: Calculating the Radius of Gyration and the g-Curve Using Generating Functions and Recurrences
L. Tom Hillegers and Johan J. M. Slot
Version of Record online: 11 APR 2017 | DOI: 10.1002/mats.201600093
For step-growth polymerized systems of general type “AfiBgi” a computer algebra method is presented that leads from the recipe straight to the graph of R2[s], the topology-averaged square radius of gyration of the polymeric molecules within the class of s-mers, and to the graph of g[s], the corresponding shrinking factor.
- Parameter Estimation for an Inverse Nonlinear Stochastic Problem: Reactivity Ratio Studies in Copolymerization
Yuncheng Du, Hector Budman and Thomas Duever
Version of Record online: 1 MAR 2017 | DOI: 10.1002/mats.201600095
Inverse problem is to estimate parameters from observed data through mathematical models. It is necessary to account for uncertainty resulting from variables of models and measurement noise to improve the accuracy of parameter estimation. An estimation methodology based on a generalized polynomial chaos and a maximum likelihood function to account for such uncertainty is presented.
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