Conformational transitions in the Ramachandran space of amino acids using the dynamic rotational isomeric state (DRIS) model

We present a computational method to investigate conformational transitions of the twenty amino acids based on molecular dynamics (MD) simulations and the dynamic rotational isomeric state (DRIS) model. Local dynamics of twenty amino acids resulting from rotational transitions between isomeric states are analyzed.

Using Multiscale Modeling to Predict Material Response of Polymeric Materials

Presented is a multiscale modeling method applied to light activated shape memory polymers (LASMP). LASMP are a new class of shape memory polymer (SMP) being developed for applications where a thermal stimulus is undesired. Rotational Isomeric State (RIS) theory is used to build a molecular scale model of the polymer chain yielding a list of distances between the predicted cross-link locations, or r-values. The r-values are then fit with Johnson probability density functions and used with Boltzmann statistical mechanics to predict stress as a function of strain of the phantom network. Junction constraint theory is then used to calculate the stress contribution due to interactions with neighboring chains, resulting in previously unattainable numerically accurate Young’s modulus predictions based on the molecular formula of the polymer. The system is modular in nature and thus lends itself well to being adapted for specific applications. The results of the model are presented with experimental data for confirmation of correctness along with discussion of the potential of the model to be used to computationally adjust the chemical composition of LASMP to achieve specified material characteristics, greatly reducing the time and resources required for formula development.

Multiscale Modeling of Nafion Mechanical Properties

Multiscale modeling is used to investigate the mechanical characteristics of ionic polymers with the intent of ultimately expanding understanding of the interplay between multiscale stiffness and electromechanical response. Strategies for manipulating electromechanical transduction of ionic polymers include, but are not limited to: variation of hydration and/or the equivalent weight. In general, variations resulting in increased electroactive response also result in decreased mechanical stiffness and can decrease to the point of limiting mechanical integrity. This effort begins with the supposition that a better understanding of the ionic polymer multiscale material stiffness will enable bypass of this perceived trade-off. Rotational Isomeric State (RIS) theory is used to predict the conformation of a typical polymer hydrophobic backbone for a fully hydrated, sodium exchanged, Nafion 1200 EW case. The RIS method generates a large number of crosslink-to-crosslink chain lengths. The distribution is assessed via Johnson distributions and in turn, employed in a Boltzmann statistical thermodynamics framework to assess mechanical stiffness. The approach explores the impact of morphology on stiffness via imposing as assumed morphology a priori.

A multiscale model applied to ionic polymer stiffness prediction

A multiscale modeling approach applied to the stiffness prediction of polymers with high cross-link density is discussed. The material of focus in this work is the ionic polymer Nafion®. The approach applies rotational isomeric state theory in combination with a Monte Carlo methodology to develop a simulation model for polymer chain conformation. From this a large number of end-to-end chain lengths between cross links are generated; the probability density function of these lengths is estimated with the most appropriate Johnson family method. This estimation is used in a Boltzmann statistical thermodynamics approach to the multiscale prediction of stiffness. This work addresses the importance of the simulated polymer chain length in the generation of stable predictions. The multiscale prediction is found to be physically reasonable; the approach has the potential of serving as a first-order prediction tool for properties that are experimentally difficult or impossible to measure.

Multiscale Modeling of Light Activated Shape Memory Polymer

Presented is the development of a multi-scale model predicting the material response of a light activated shape memory polymer. Rotational Isomeric State (RIS) theory is used to build a molecular scale model of the polymer chain backbone, tracking the distances between cross-links. Cross-link to cross-link distances are then used with Boltzmann statistical mechanics to predict material response, generating Young’s modulus and stress-strain relation predictions. Young’s modulus is predicted by the model to be 0.049 and 3.2 MPa for the soft and hard states of the polymer respectively. Experimentally determined properties are also presented with reported moduli of 2.0 and 11.4 MPa in the soft and hard states respectively.