Towards data-efficient mechanical design of bicontinuous composites using generative AI-Reference-Cited by-同舟云学术

Towards data-efficient mechanical design of bicontinuous composites using generative AI

Published:2024-01 Issue:1 Volume:14 Page:100492
ISSN:2095-0349
Container-title:Theoretical and Applied Mechanics Letters
language:en
Short-container-title:Theoretical and Applied Mechanics Letters

Author:

Masrouri Milad,Qin Zhao^ORCID

Funder

NSF CMMI

Syracuse University

National Science Foundation

Publisher

Elsevier BV

Reference79 articles.

1. Mechanical comparison of new composite materials for aerospace applications;Barile;Compos. B En.g,2019

2. Advanced composite materials of the future in aerospace industry;Maria;Incas Bull.,2013

3. Lightweight composite materials for automotive -a review lightweight composite materials for automotive - a review;Patel;Int. Res. J. Eng. Technol. (IRJET),2020

4. Composite measures of health care provider performance: a description of approaches;Shwartz;Milbank Q.,2015

5. Engineered mycelium composite construction materials from fungal biorefineries: a critical review;Jones;Mater. Des.,2020

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Generative AI model trained by molecular dynamics for rapid mechanical design of architected graphene;Extreme Mechanics Letters;2024-11

2. Experimental and numerical analysis of natural fillers loaded and E-glass reinforced epoxy sandwich composites;Journal of Materials Research and Technology;2024-09

3. Machine learning-assisted wood materials: Applications and future prospects;Extreme Mechanics Letters;2024-09

4. Strain concentration factor of heterogeneous materials and analytical influence functions based on Eshelby tensor;Theoretical and Applied Mechanics Letters;2024-07