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Development of a High-Fidelity Framework to Describe the Process-Dependent Viscoelasticity of a Fast-Curing Epoxy Matrix Resin including Testing, Modelling, Calibration and Validation. Polymers (Basel) 2022; 14:polym14173647. [PMID: 36080722 PMCID: PMC9460885 DOI: 10.3390/polym14173647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 08/29/2022] [Accepted: 08/30/2022] [Indexed: 11/27/2022] Open
Abstract
Fast-curing epoxy resins enable substantial reduction of cycle times during production of thermoset polymer matrix composites. Due to the snap-cure behaviour, both characterisation and processing of these resins are associated with high complexity which motivates the development of a high-fidelity framework for the prediction of the process-dependent behaviour ranging from experiment to model validation. In order to determine influence of time, temperature, and degree of cure, a multitude of rheometer and dynamic mechanical analysis experiments are conducted and evaluated. Building on the experimental results, a material model based on a generalised Maxwell model is developed. It is calibrated on the results obtained in the tests and shown to describe the material’s behaviour with high accuracy under all investigated conditions. The model’s predictive capabilities are further tested by applying it to a dynamic mechanical analysis, exposing the model to previously unknown loading and temperature conditions. It is demonstrated that the model is capable of predicting such changing boundary conditions with high accuracy.
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Giuntoli A, Hansoge NK, van Beek A, Meng Z, Chen W, Keten S. Systematic Coarse-graining of Epoxy Resins with Machine Learning-Informed Energy Renormalization. NPJ COMPUTATIONAL MATERIALS 2021; 7:168. [PMID: 34824867 PMCID: PMC8612124 DOI: 10.1038/s41524-021-00634-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 09/16/2021] [Indexed: 05/29/2023]
Abstract
A persistent challenge in predictive molecular modeling of thermoset polymers is to capture the effects of chemical composition and degree of crosslinking (DC) on dynamical and mechanical properties with high computational efficiency. We established a new coarse-graining (CG) approach that combines the energy renormalization method with Gaussian process surrogate models of the molecular dynamics simulations. This allows a machine-learning informed functional calibration of DC-dependent CG force field parameters. Taking versatile epoxy resins consisting of Bisphenol A diglycidyl ether combined with curing agent of either 4,4-Diaminodicyclohexylmethane or polyoxypropylene diamines, we demonstrated excellent agreement between all-atom and CG predictions for density, Debye-Waller factor, Young's modulus and yield stress at any DC. We further introduce a surrogate model enabled simplification of the functional forms of 14 non-bonded calibration parameters by quantifying the uncertainty of a candidate set of high-dimensional/flexible calibration functions. The framework established provides an efficient methodology for chemistry-specific, large-scale investigations of the dynamics and mechanics of epoxy resins.
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Affiliation(s)
- Andrea Giuntoli
- Dept. of Civil & Environmental Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208-3109
- Center for Hierarchical Materials Design, Northwestern University, 2205 Tech Drive, Evanston, IL 60208-3109
| | - Nitin K. Hansoge
- Dept. of Mechanical Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208-3109
- Center for Hierarchical Materials Design, Northwestern University, 2205 Tech Drive, Evanston, IL 60208-3109
| | - Anton van Beek
- Dept. of Mechanical Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208-3109
- Center for Hierarchical Materials Design, Northwestern University, 2205 Tech Drive, Evanston, IL 60208-3109
| | - Zhaoxu Meng
- Dept of. Mechanical Engineering, Clemson University, 208 Fluor Daniel EIB, Clemson, SC 29634-0921
| | - Wei Chen
- Dept. of Mechanical Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208-3109
- Center for Hierarchical Materials Design, Northwestern University, 2205 Tech Drive, Evanston, IL 60208-3109
| | - Sinan Keten
- Dept. of Civil & Environmental Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208-3109
- Dept. of Mechanical Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208-3109
- Center for Hierarchical Materials Design, Northwestern University, 2205 Tech Drive, Evanston, IL 60208-3109
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