Exploration of truss metamaterials with graph based generative modeling

In the expanding landscape of metamaterial design, Zheng and colleagues introduces a framework that bridges design and properties, using machine learning to enhance truss metamaterials. A neural network creates an interpretable, low-dimensional space, empowering designers to tailor mechanical proper...

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Autor principal: Shaikeea, Angkur Jyoti Dipanka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Comment
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10663501/
https://www.ncbi.nlm.nih.gov/pubmed/37990017
http://dx.doi.org/10.1038/s41467-023-43217-y
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author Shaikeea, Angkur Jyoti Dipanka
author_facet Shaikeea, Angkur Jyoti Dipanka
author_sort Shaikeea, Angkur Jyoti Dipanka
collection PubMed
description In the expanding landscape of metamaterial design, Zheng and colleagues introduces a framework that bridges design and properties, using machine learning to enhance truss metamaterials. A neural network creates an interpretable, low-dimensional space, empowering designers to tailor mechanical properties.
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spelling pubmed-106635012023-11-21 Exploration of truss metamaterials with graph based generative modeling Shaikeea, Angkur Jyoti Dipanka Nat Commun Comment In the expanding landscape of metamaterial design, Zheng and colleagues introduces a framework that bridges design and properties, using machine learning to enhance truss metamaterials. A neural network creates an interpretable, low-dimensional space, empowering designers to tailor mechanical properties. Nature Publishing Group UK 2023-11-21 /pmc/articles/PMC10663501/ /pubmed/37990017 http://dx.doi.org/10.1038/s41467-023-43217-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Comment
Shaikeea, Angkur Jyoti Dipanka
Exploration of truss metamaterials with graph based generative modeling
title Exploration of truss metamaterials with graph based generative modeling
title_full Exploration of truss metamaterials with graph based generative modeling
title_fullStr Exploration of truss metamaterials with graph based generative modeling
title_full_unstemmed Exploration of truss metamaterials with graph based generative modeling
title_short Exploration of truss metamaterials with graph based generative modeling
title_sort exploration of truss metamaterials with graph based generative modeling
topic Comment
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10663501/
https://www.ncbi.nlm.nih.gov/pubmed/37990017
http://dx.doi.org/10.1038/s41467-023-43217-y
work_keys_str_mv AT shaikeeaangkurjyotidipanka explorationoftrussmetamaterialswithgraphbasedgenerativemodeling

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