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1 to 10 of 198 Results
DoubleDecoupling.tar.gz
Nov 25, 2021 - Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B'
Gzip Archive - 291.5 MB - MD5: 8d02b26f3e61997c947c6fecbae2a403
Contains simulation data (in-/output, scripts) from alchemical double decoupling
UmbrellaSampling.tar.gz
Nov 25, 2021 - Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B'
Gzip Archive - 3.4 MB - MD5: c700659d5c6c890fdac4b1d9dff636ce
Contains simulation data (in-/output, scripts) from Umbrella Sampling
example_usage.m
Nov 24, 2021 - Code for relative permeabilities for two-phase flow between parallel plates with slip conditions
Objective-C Source Code - 771 B - MD5: 4023c6b9ebbe56673b683e3e6cc127b5
Example script on how to use relativePermeabilities.m
overview_relativepermeabilities.pdf
overview_relativepermeabilities.pdf
Nov 24, 2021 - Code for relative permeabilities for two-phase flow between parallel plates with slip conditions
Adobe PDF - 160.5 KB - MD5: 295831a59379d0f398f7dbe168a59b65
Underlying assumptions behind the relative permeabilities
relativePermeabilities.m
Nov 24, 2021 - Code for relative permeabilities for two-phase flow between parallel plates with slip conditions
Objective-C Source Code - 4.3 KB - MD5: f05cb34f371fe59b9208e7b5ea9f42a4
Calculation of relative permeabilities
adam.py
Oct 15, 2021 - Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments
Python Source Code - 2.8 KB - MD5: 43201d1bd5e849ffc4b7794c6ab8e87c
adam.rst
Oct 15, 2021 - Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments
Unknown - 89 B - MD5: 8250c6756d6506ffa4b66dd979abe8eb
calculators.py
Oct 15, 2021 - Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments
Python Source Code - 19.4 KB - MD5: e29400ad67a376583c46cbf02660672d
calculators.rst
Oct 15, 2021 - Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments
Unknown - 127 B - MD5: 6897ce0afd3ef2996882b9b277e51e72
conf.py
Oct 15, 2021 - Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments
Python Source Code - 2.1 KB - MD5: ab53e5b08ee9fee9026c45a93398dab5
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