Data from: ViscoNet: a lightweight FEA surrogate model for polymer nanocomposites viscoelastic response prediction

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Polymer-based nanocomposites (PNCs) are formed by dispersing nanoparticles (NPs) within a polymer matrix, which creates polymer interphase regions that drive property enhancement. However, data-driven PNC design is challenging due to limited data. To address the challenge, we present ViscoNet, a surrogate model for finite element analysis (FEA) simulations of PNC viscoelastic (VE) response. ViscoNet leverages pre-training and finetuning to accelerate predicting VE response of a new PNC system. By predicting the entire VE response, ViscoNet surpasses previous scalar-based surrogate models for FEA simulation, offering better fidelity and efficiency. We explore ViscoNet's effectiveness through generalization tasks, both within thermoplastics and from thermoplastics to thermosets, reporting a mean absolute percentage error (MAPE) of < 5% for rubbery modulus and < 1% for glassy modulus in all cases and 1.22% on tan δ peak height prediction. With only 500 FEA simulations for finetuning, ViscoNet can generate over 20k VE responses within 2 minutes with 1 CPU, compared to 97 days with 4 CPUs via FEA simulations. ... [Read More]

Data Citation

Brinson, C., Lin, A., Sheridan, R. J., & Hu, B. (2024). Data from: ViscoNet: a lightweight FEA surrogate model for polymer nanocomposites viscoelastic response prediction. Duke Research Data Repository. https://doi.org/10.7924/r4g166t5p

Creator: Brinson, Cate
Lin, Anqi
Sheridan, Richard J.
Hu, Bingyin
DOI: 10.7924/r4g166t5p
Subject: Material design
Surrogate model
Polymer nanocomposites
Viscoelasticity
Publication Date: November 4, 2024
ARK: ark:/87924/r4g166t5p
Affiliation: Pratt School of Engineering
Thomas Lord Department of Mechanical Engineering and Materials Science
Publisher: Duke Research Data Repository
Collection Dates: 2021-2023
Type: Dataset
Format: NPY
TXT
TSV
MAT
Related Materials: Lin, A., Sheridan, R. J., Hu, B., & Brinson, L. C. (2024). ViscoNet: a lightweight FEA surrogate model for polymer nanocomposites viscoelastic response prediction. Journal of the Mechanics and Physics of Solids, 105915. https://doi.org/10.1016/j.jmps.2024.105915.
Funding Agency: NSF-CSSI
Grant Number: OAC-1835677
Contact: Cate Brinson, Ph.D., cate.brinson@duke.edu, https://orcid.org/0000-0003-2551-1563
License: Creative Commons CC0 1.0 Universal
Title: Data from: ViscoNet: a lightweight FEA surrogate model for polymer nanocomposites viscoelastic response prediction
License: http://creativecommons.org/publicdomain/zero/1.0/
Repository: Duke Research Data Repository

Title	Date Uploaded	Visibility	Actions
README.txt	2024-11-04	Public	Download
abaqus_inp_tar.xz_files.tar	2024-11-04	Public	Get file from Globus
all_data.json	2024-11-04	Public	Download
check.py	2024-11-04	Public	Download
ep2_all_data.json	2024-11-04	Public	Download
EP2_master_curve.txt	2024-11-04	Public	Download
intph_img_npy_tar.xz_files.tar	2024-11-04	Public	Download
microstructure_mat_tar.xz_files.tar	2024-11-04	Public	Download
missing.json	2024-11-04	Public	Download
PC_dyn.txt	2024-11-04	Public	Download

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