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Mar 25, 2024 -
Additional Material: Viscosities of Inhomogeneous Systems from Generalized Entropy Scaling
Fixed Field Text Data - 41.6 KB -
MD5: 350df6ff6dec2c86a206dbb6aa372e6b
Velocity profile from NEMD simulations. |
Mar 25, 2024 -
Additional Material: Viscosities of Inhomogeneous Systems from Generalized Entropy Scaling
Fixed Field Text Data - 41.8 KB -
MD5: e0615d5080d2bcf36e79478a8df6d792
Velocity profile from NEMD simulations. |
Mar 25, 2024 -
Additional Material: Viscosities of Inhomogeneous Systems from Generalized Entropy Scaling
Fixed Field Text Data - 41.6 KB -
MD5: 7f2bcd9b9d448dbc0c6bc970dfb9cd20
Velocity profile from NEMD simulations. |
Mar 25, 2024 -
Additional Material: Viscosities of Inhomogeneous Systems from Generalized Entropy Scaling
Fixed Field Text Data - 41.6 KB -
MD5: 98c945709352a47fd47ffabeb5aaf8ae
Velocity profile from NEMD simulations. |
Mar 25, 2024 -
Additional Material: Viscosities of Inhomogeneous Systems from Generalized Entropy Scaling
Fixed Field Text Data - 41.6 KB -
MD5: ad513dfe239c54cff62356c5981c0b9a
Velocity profile from NEMD simulations. |
Mar 25, 2024 -
Additional Material: Viscosities of Inhomogeneous Systems from Generalized Entropy Scaling
Fixed Field Text Data - 41.8 KB -
MD5: cca9f394cf7ae67e0da5bf833f8d6195
Velocity profile from NEMD simulations. |
Feb 16, 2024 - PN3-5
Sriram, Siddharth, 2024, "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes", https://doi.org/10.18419/DARUS-3881, DaRUS, V1
The datasets and codes provided here are associated with our article entitled "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle". The main idea of the work is to develop surrogate models using the concepts of machine learning (ML) to predict the onset of wrinkling insta... |
Jupyter Notebook - 13.7 KB -
MD5: dacad485cece6350acf08afa30461e19
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application/x-yaml - 8.5 KB -
MD5: 86f5d2848b4668165c8e936214efed7f
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Jupyter Notebook - 17.6 KB -
MD5: 060c1d1f671f506010836b1ef8333a41
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