DeepFlames: Neural network-driven self-assembly of flame particles into hierarchical structures
Abstract The spontaneous assembly of materials from elementary building blocks is one of the most intriguing natural phenomena. Conventional modeling relies physical approaches to examine such processes. In this paper, a framework is proposed to offer an alternative paradigm, via the...
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| Format: | Article |
| Language: | English |
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Springer Science and Business Media LLC
2022
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| Online Access: | https://hdl.handle.net/1721.1/141916.2 |