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Automated workflow from the FHI-aims output, generate ML-IP training data

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MAOA

Contributors: Dr. Woongkyu Jee (collect data from DFT optimisation output), Dong-Gi Kang, PhD candidate (the vibration, ML-IP workflow)


This repository contains scripts that can take essential data from atomic simulation calculations

Software that can work with: FHI-aims, GULP

It has functions to take data from output file:
✅ SCF converged atomic coordination
✅ Forces
✅ Energies
✅ Eigenvector of vibrational mode
✅ Vibration calculation
✅ Single point calculation of the frames of vibrational modes
✅ Single point calculation of breathing mode frames
✅ Preparing extended xyz file format (total energy, geometry, atomic forces)
✅ Train, Test, Valid split
✅ MACE (ML-IP): training
✅ MACE (ML-IP): optimisation/single point calculation using the trained model
✅ MACE (ML-IP): vibration calculation using the trained model
✅ MACE (ML-IP): nudge elastic band calculation using the trained model
✅ MACE (ML-IP): Plot dimer interaction energy with the interatomic distances of trained data in .html format (plotly)

☉ Upcoming function:
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Automated workflow from the FHI-aims output, generate ML-IP training data

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