A machine learning enabled hybrid optimization framework for efficient coarse-graining of a model polymer  

作　　者：Zakiya Shireen Hansani Weeratunge Adrian Menzel Andrew W.Phillips Ronald G.Larson Kate Smith-Miles Elnaz Hajizadeh 

机构地区：[1]Department of Mechanical Engineering,Faculty of Engineering and Information Technology,The University of Melbourne,Melbourne,Australia [2]Platforms Division,Defence Science and Technology Group,Melbourne,Australia [3]Department of Chemical Engineering,University of Michigan,Ann Arbor,MI,USA [4]School of Mathematics and Statistics,The University of Melbourne,Melbourne,Australia

出　　处：《npj Computational Materials》2022年第1期2128-2138,共11页计算材料学（英文）

基　　金：This research is supported by the Commonwealth of Australia as represented by the Defence Science and Technology Group of the Department of Defence.

摘　　要：This work presents a framework governing the development of an efficient,accurate,and transferable coarse-grained(CG)model of a polyether material.The framework combines bottom-up and top-down approaches of coarse-grained model parameters by integrating machine learning(ML)with optimization algorithms.In the bottom-up approach,bonded interactions of the CG model are optimized using deep neural networks(DNN),where atomistic bonded distributions are matched.In the top-down approach,optimization of nonbonded parameters is accomplished by reproducing the temperature-dependent experimental density.We demonstrate that developed framework addresses the thermodynamic consistency and transferability issues associated with the classical coarse-graining approaches.The efficiency and transferability of the CG model is demonstrated through accurate predictions of chain statistics,the limiting behavior of the glass transition temperature,diffusion,and stress relaxation,where none were included in the parametrization process.The accuracy of the predicted properties are evaluated in context of molecular theories and available experimental data.

关 键 词：optimization GRAIN integrating 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]