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Bradley D. Olsen

Publications and source records attributed to Bradley D. Olsen.

3 recordsLinked to original sources

Quantification of Cyclic Topology in Polymer Networks Using 3D Nets

Polymer networks invariably possess topological inhomogeneities in the form of loops and dangling ends. The macroscopic properties of such materials are directly dependent on the local cyclic topology around nodes and chains. Here, a new formalism to model polymer network topology is presented based on the concept of 3D nets that enables computation of these local cyclic topologies. A cycle counting algorithm is developed which characterizes the relevant local topological cycles around every node, enabling comparison of networks to ideal nets based on local cycle distributions. Comparison of networks formed by different simulation algorithms, using a topology-based distance metric, reveals that polymer networks possess a fundamental cycle size which depends on the topological proximity of crosslinkers during bond formation. This parameter identifies distinct topological classes of networks and provides an effective method to simulate a wide array of networks starting from suitable 3D nets. This approach can be readily generalized beyond polymer networks, enabling quantification of the cyclic topology and facilitating study of topology-property correlations.

cond-mat.mtrl-sci↗

Simulate Time-integrated Coarse-grained Molecular Dynamics with Multi-Scale Graph Networks

Molecular dynamics (MD) simulation is essential for various scientific domains but computationally expensive. Learning-based force fields have made significant progress in accelerating ab-initio MD simulation but are not fast enough for many real-world applications due to slow inference for large systems and small time steps (femtosecond-level). We aim to address these challenges by learning a multi-scale graph neural network that directly simulates coarse-grained MD with a very large time step (nanosecond-level) and a novel refinement module based on diffusion models to mitigate simulation instability. The effectiveness of our method is demonstrated in two complex systems: single-chain coarse-grained polymers and multi-component Li-ion polymer electrolytes. For evaluation, we simulate trajectories much longer than the training trajectories for systems with different chemical compositions that the model is not trained on. Structural and dynamical properties can be accurately recovered at several orders of magnitude higher speed than classical force fields by getting out of the femtosecond regime.

cs.LG↗

Scattering from Colloid-Polymer Conjugates with Excluded Volume Effect

In this work we present scattering functions of conjugates consisting of a colloid particle and a self-avoiding polymer chain. This model is directly derived from the two point correlation function with the inclusion of excluded volume effects. The dependence of the calculated scattering function on the geometric shapes of the colloid and polymer stiffness is investigated. In comparison to existing experimental results, our model is found to be able to describe the scattering signature of the colloid-polymer conjugates and provide additional conformational information. This model explicitly elucidates the link between the global conformation of a conjugate and the microstructure of its constituent components.

cond-mat.soft↗