MOSS: AI Platform for Discovery of Corrosion-Resistant Materials
Author:
Affiliation:
1. Worcester Polytechnic Institute, Worcester, MA, USA
2. DEVCOM Army Research Laboratory, Aberdeen Proving Ground, MD, USA
Funder
NSF (National Science Foundation)
DEVCOM Army Research Laboratory
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3583780.3614748
Reference23 articles.
1. Brahim Aïssa and Maha Mohamed Khayyat. 2014. Self-Healing Materials Systems as a Way for Damage Mitigation in Composites Structures Caused by Orbital Space Debris. In Handbook of Research on Nanoscience Nanotechnology and Advanced Materials. IGI Global 1--25. Brahim Aïssa and Maha Mohamed Khayyat. 2014. Self-Healing Materials Systems as a Way for Damage Mitigation in Composites Structures Caused by Orbital Space Debris. In Handbook of Research on Nanoscience Nanotechnology and Advanced Materials. IGI Global 1--25.
2. David M. Bastidas . 2020. Corrosion and Protection of Metals. Metals 10, 4 ( 2020 ). https://doi.org/10.3390/met10040458 10.3390/met10040458 David M. Bastidas. 2020. Corrosion and Protection of Metals. Metals 10, 4 (2020). https://doi.org/10.3390/met10040458
3. Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types
4. Effects of macro-scale corrosion damage feature on fatigue crack initiation and fatigue behavior
5. Masked Autoencoders Are Scalable Vision Learners
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