Development of AI-based Design Methodology for Innovative Metamaterials

혁신적 메타물질 개발을 위한 인공지능 기반 설계 기술 개발

  • 이재훈 (가천대학교 기계공학과) ;
  • 김남중 (가천대학교 기계공학과)
  • Published : 2023.09.15

Abstract

Keywords

References

  1. Song, JunHo, et al. "Artificial Intelligence in the Design of Innovative Metamaterials: A Comprehensive Review." International Journal of Precision Engineering and Manufacturing (2023): 1-20. 
  2. "Materials Project - Home." https://materialsproject.org/ (accessed Apr. 03, 2023). 
  3. "MATDAT.com." https://www.matdat.com/ (accessed Apr. 03, 2023). 
  4. "NOMAD Repository & Archive - NOMAD Lab." https://cms.nomad-lab.eu/services/repo-arch (accessed Apr. 04, 2023). 
  5. "MoSDeF." https://mosdef.org/ (accessed Apr. 03, 2023). 
  6. Oliveri, G., & Overvelde, J. T. B. (2020). Inverse design of mechanical metamaterials that undergo buckling. Advanced Functional Materials, 30(12), 1909033. https://doi.org/10.1002/ADFM.201909033 
  7. Yun, S., Ahn, Y., & Kim, S. (2022). Tailoring elastomeric meshes with desired 1D tensile behavior using an inverse design algorithm and material extrusion printing. Additive Manufacturing, 60, 2214-8604. https://doi.org/10.1016/j.addma.2022.103254 
  8. Zheng, X., Te Chen, T., Guo, X., Samitsu, S., & Watanabe, I.(2021).Controllable inverse design of auxetic metamaterials using deep learning. Materials and Design. https://doi.org/10.1016/J.MATDES.2021.110178 
  9. Kollmann, H. T., Abueidda, D. W., Koric, S., Guleryuz, E., & Sobh, N. A. (2020). Deep learning for topology optimization of 2D metamaterials. Materials and Design. https://doi.org/10. 1016/J.MATDES.2020.109098  https://doi.org/10.1016/J.MATDES.2020.109098
  10. Ducamp, M., & Coudert, F.-X. (2022). Prediction of thermal properties of zeolites through machine learning. The Journal of Physical Chemistry C. https://doi.org/10.1021/acs.jpcc.1c09737 
  11. Challapalli, A., &Li, G. (2021). Machine learning assisted design of new lattice core for sandwich structures with superior load carrying capacity. Scientifc Reports, 11, 18552. https://doi.org/10.1038/s41598-021-98015-7 
  12. Hansen, A., Renner, M., Griesbeck, A. G., & Busgen, T. (2020). From3D to 4D printing: a reactor for photochemical experiments using hybrid polyurethane acrylates for vat-based polymerization and surface functionalization. Chemical Communications, 56(96), 15161-15164. https://doi.org/10.1039/D0CC06512A 
  13. Goo, B., Hong, C. H., &Park, K. (2020). 4D printing using anisotropic thermal deformation of 3D-printed thermoplastic parts. Materials and Design, 188, 108485. https://doi.org/10.1016/J.MATDES.2020.108485