The resulting large size of simulated training dataset provides an unprecedented opportunity to uncover hitherto-unknown structure–property relationships purely computationally, thereby predicting new polymers with desired dielectric properties.
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We have developed a computational framework for (i) high-throughput computational synthesis of polymer structures, (ii) evaluation of their dielectric properties using reactive molecular dynamics (RMD) simulations based on a new valence-aware polarizable reactive force field (ReaxPQ-v), and (iii) learning polymer structure–property relationships using machine-learning (ML) models. Informatics-driven computational design of advanced dielectric polymers (i.e., dielectric polymer genome) has remained a challenge. Presents the proceedings of four conferences as part of the 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20) Includes the research tracks Parallel and Distributed Processing, Scientific Computing, Modeling, Simulation and Visualization, and Grid, Cloud, and Cluster Computing Features papers from PDPTA’20, CSC’20, MSV’20, and GCC’20. Authors include academics, researchers, professionals, and students. The conferences are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. The conferences took place in Las Vegas, NV, USA, July 27-30, 2020.
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The book presents the proceedings of four conferences: The 26th International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'20), The 18th International Conference on Scientific Computing (CSC'20) The 17th International Conference on Modeling, Simulation and Visualization Methods (MSV'20) and The 16th International Conference on Grid, Cloud, and Cluster Computing (GCC'20).