Comments (6)
by the way, Do you calculate the qm9 standard Gibbs yourself or get from other place?
thanks
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I guess the gibbs energy here is the molecule atomization energy, right?
from megnet.
@liuxiaotong15 qm9_pretrained.ipynb shows the prediction results for a specific molecule compared to the DFT results. Those are not errors for each model. Please read the context of the notebook. The units are eV.
The QM9 data are from literature, please check the paper for its origin.
Yes the gibbs energy is computed by subtracting atomic references.
from megnet.
thank you very much. and my result have a fixed 3-5 ev difference with you, so I guess maybe my atomic references is different with you? I use
'H': -13.90, 'C': -1030.26, 'N': -1485.71, 'O': -2043.02, 'F': -2713.89
what about yours?
from megnet.
We used data processed by "Journal of chemical theory and computation 13.11 (2017): 5255-5264"
The data was shared by the authors at https://drive.google.com/open?id=0Bzn36Iqm8hZscHFJcVh5aC1mZFU
from megnet.
thanks
from megnet.
Related Issues (20)
- Can MEGNet be made end-to-end differentiable wrt atomic positions of atoms? HOT 8
- import pybel error HOT 1
- Multi-output Regression HOT 4
- could you please provide an example to predict disordered structure? HOT 12
- Multi classification task HOT 5
- installation issue (RDKit and openbabel must be installed) HOT 3
- Might be nice to see MEGNet on matbench HOT 7
- unlockNN module for uncertainty quantification of MEGNet HOT 5
- code in pytorch? HOT 3
- Problem with load molecule data from ase HOT 4
- how does megnet paper address possible data leakage HOT 1
- Return history of the model using .train_from_graphs HOT 1
- Using megnet for systems having atoms apart from "H", "C", "N", "O", "F" HOT 4
- Breaking up a big molecule into two parts; making predictions from graphs of the two separate "molecular" parts
- Unable to understand the shape of the target/output tensor for example in "Customized Graph Network Models"
- List index out of range while training the NN
- Web App HOT 2
- Web App Access HOT 1
- Review request for disordered structure example HOT 2
- ImportError: cannot import name 'ReduceLRUponNan' from 'megnet.callbacks' in multifidelity/train.py
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