High‐Throughput Generation of 3D Graphene Metamaterials and Property Quantification Using Machine Learning
3D graphene assemblies are proposed as solutions to meet the goal toward efficient utilization of 2D graphene sheets, showing excellent performances in applications such as mechanical support, energy storage, and electrochemical catalysis. However, given the diversity and complexity of possible grap...
Main Authors: | Yang, Zhenze, Buehler, Markus J |
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Other Authors: | Massachusetts Institute of Technology. Department of Materials Science and Engineering |
Format: | Article |
Language: | English |
Published: |
Wiley
2022
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Online Access: | https://hdl.handle.net/1721.1/145464 |
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