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Type: (files OR datasets)

141 to 150 of 151 Results

POSCAR_i May 11, 2026 - Dopant-vacancy synergy effects on ferroelectric La doped ZrO2 Plain Text - 6.2 KB - MD5: 6c80815f8c3372b158d6438b74c0f6fc
POSCAR_i May 11, 2026 - Dopant-vacancy synergy effects on ferroelectric La doped ZrO2 Plain Text - 6.2 KB - MD5: fc7ee929780d5e0d2cc2a1a4850ba5d8
POSCAR_i May 11, 2026 - Dopant-vacancy synergy effects on ferroelectric La doped ZrO2 Plain Text - 12.5 KB - MD5: a1a14aee57c5ade570e0cc6e7039eef8
POSCAR_i May 11, 2026 - Dopant-vacancy synergy effects on ferroelectric La doped ZrO2 Plain Text - 6.2 KB - MD5: 96395ec35112522f14ed37f4260f0b9d
Machine Learning Texture Optimization Mar 3, 2023 - Lab Física Computacional Marques, Luis, 2023, "Machine Learning Texture Optimization", https://doi.org/10.34622/datarepositorium/MUVOJD, Repositório de Dados da Universidade do Minho, V1, UNF:6:PYIYvLMs2mywboc9nuNvdw== [fileUNF] This data set contains the data used for training, validation and test the deep neural network used for solving a texture optimization problem for the lubricated contacts between surfaces.
00_README.txt Mar 3, 2023 - Machine Learning Texture Optimization Plain Text - 1.0 KB - MD5: 389bfc2f1a11e6e5d5229657a35eafb9
inputs.tab Mar 3, 2023 - Machine Learning Texture Optimization Tab-Delimited - 14.1 MB - MD5: ba4bc1b2c58220469b88aa09f1397912
inputs_test_set.csv Mar 3, 2023 - Machine Learning Texture Optimization Comma Separated Values - 403.7 KB - MD5: 4d27879770d10ce970acac13c54f02ff
script_DNN_training.ipynb Mar 3, 2023 - Machine Learning Texture Optimization Jupyter Notebook - 10.0 KB - MD5: 780a3e6bdf582afd7db34856f5d00922
targets.tab Mar 3, 2023 - Machine Learning Texture Optimization Tab-Delimited - 15.9 MB - MD5: 554f247895d7f564102182f9d752d2f0

POSCAR_i

May 11, 2026 - Dopant-vacancy synergy effects on ferroelectric La doped ZrO2

Plain Text - 6.2 KB - MD5: 6c80815f8c3372b158d6438b74c0f6fc

POSCAR_i

May 11, 2026 - Dopant-vacancy synergy effects on ferroelectric La doped ZrO2

Plain Text - 6.2 KB - MD5: fc7ee929780d5e0d2cc2a1a4850ba5d8

POSCAR_i

May 11, 2026 - Dopant-vacancy synergy effects on ferroelectric La doped ZrO2

Plain Text - 12.5 KB - MD5: a1a14aee57c5ade570e0cc6e7039eef8

POSCAR_i

May 11, 2026 - Dopant-vacancy synergy effects on ferroelectric La doped ZrO2

Plain Text - 6.2 KB - MD5: 96395ec35112522f14ed37f4260f0b9d

Machine Learning Texture Optimization

Mar 3, 2023 - Lab Física Computacional

Marques, Luis, 2023, "Machine Learning Texture Optimization", https://doi.org/10.34622/datarepositorium/MUVOJD, Repositório de Dados da Universidade do Minho, V1, UNF:6:PYIYvLMs2mywboc9nuNvdw== [fileUNF]

This data set contains the data used for training, validation and test the deep neural network used for solving a texture optimization problem for the lubricated contacts between surfaces.

00_README.txt

Mar 3, 2023 - Machine Learning Texture Optimization

Plain Text - 1.0 KB - MD5: 389bfc2f1a11e6e5d5229657a35eafb9

inputs.tab

Mar 3, 2023 - Machine Learning Texture Optimization

Tab-Delimited - 14.1 MB - MD5: ba4bc1b2c58220469b88aa09f1397912

inputs_test_set.csv

Mar 3, 2023 - Machine Learning Texture Optimization

Comma Separated Values - 403.7 KB - MD5: 4d27879770d10ce970acac13c54f02ff

script_DNN_training.ipynb

Mar 3, 2023 - Machine Learning Texture Optimization

Jupyter Notebook - 10.0 KB - MD5: 780a3e6bdf582afd7db34856f5d00922

targets.tab

Mar 3, 2023 - Machine Learning Texture Optimization

Tab-Delimited - 15.9 MB - MD5: 554f247895d7f564102182f9d752d2f0

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