Artificial intelligence and machine learning in design of mechanical materials
Massachusetts Institute of Technology · National Cheng Kung University
Abstract
Artificial intelligence, especially machine learning (ML) and deep learning (DL) algorithms, is becoming an important tool in the fields of materials and mechanical engineering, attributed to its power to predict materials properties, design de novo materials and discover new mechanisms beyond intuitions. As the structural complexity of novel materials soars, the material design problem to optimize mechanical behaviors can involve massive design spaces that are intractable for conventional methods. Addressing this challenge, ML models trained from large material datasets that relate structure, properties and function at multiple hierarchical levels have offered new avenues for fast exploration of the design…
Citation impact
- FWCI
- 20.04
- Percentile
- 100%
- References
- 169
Authors
4Topics & keywords
- Mechanical design
- Materials science
- Machine design
- Artificial intelligence
- Nanotechnology
- Mechanical engineering
- Computer science
- Engineering
Funding
- MOMinistry of Science and Technology, TaiwanAward: MOST 109-2222-E-006-005-MY2, MOST 109-2224-E-007-003-
- NINational Institutes of HealthAwards: U01 EB014976, NIH U01 EB014976, EB014976
- MUMultidisciplinary University Research InitiativeAward: FA9550-15-1-0514
- QFQuest for Intelligence, Massachusetts Institute of Technology
- OOOffice of Naval ResearchAwards: N000141612333, FA9550
- AFAir Force Office of Scientific ResearchAwards: FA9550-, FA9550-15-1-0514, FA9550
- ARArmy Research OfficeAward: W911NF1920098