Dear everyone,
I want to use machine learning to train a potential function for SiC at 2000K. First, I turned off machine learning for AIMD testing, but the temperature fluctuations in my OSZICAR file are very severe. I would like to know how to solve this problem. The following is the setup of my INCAR file.
SYSTEM = Si C
ISMEAR = 0
SIGMA = 0.1
ISYM = 0
NELM = 100
EDIFF = 1E-06
LWAVE = .FALSE.
LCHARG = .FALSE.
EDIFFG = -0.01
#MD
IBRION = 0
MDALGO = 3
ISIF = 3
PSTRESS = 0
SMASS = 3
APACO = 16
TEBEG = 2000
TEEND = 2000
NSW = 200
POTIM = 0.5
RANDOM_SEED = 88951986 0 0
#Machine-learned
#ML_LMLFF = .TRUE.
#ML_MODE = train
#ML_ISTART = 0
#Parallelization of ab initio calculations
NCORE = 2
#For long MD-runs use Nwrite = 0 or 1
Nwrite = 0
How to modify the INCAR in AIMD
Moderators: Global Moderator, Moderator
-
- Newbie
- Posts: 2
- Joined: Wed Dec 18, 2024 9:39 am
How to modify the INCAR in AIMD
-
- Global Moderator
- Posts: 538
- Joined: Mon Nov 04, 2019 12:44 pm
Re: How to modify the INCAR in AIMD
Are you starting from an equilibrated liquid? If not you need to equilibrate otherwise you will see massive fluctuations.
If you haven't and you start from a solid, you can either wait long with AIMD to equilibrate or use MLFF with on-the-fly learning to speed up.
For the liquid you may also need an ICONST file otherwise the liquid cell may irreversibly deform.
-
- Newbie
- Posts: 2
- Joined: Wed Dec 18, 2024 9:39 am
Re: How to modify the INCAR in AIMD
Dear ferenc_karsai,
Thank you very much for your answer! I have been simulating SiC-beta crystals. When conducting AIMD tests, I found that the calculation speed is extremely slow, and the temperature fluctuates drastically in the early stage, which is very time-consuming. Then I tested the case with machine learning enabled. At around 5000 steps, the temperature fluctuates around 2000 K. Can I continue the training in this situation?
-
- Global Moderator
- Posts: 538
- Joined: Mon Nov 04, 2019 12:44 pm
Re: How to modify the INCAR in AIMD
You should also visualize your cell/trajectory at that temperature, does it look like a proper melt? Ovito is great for visualizing trajectories. Check also if the volume fluctuates strongly or the cell deforms. As I wrote before an ICONST file is very likely neccessary to keep the melt from collapsing.
You have a step size of 0.5 fs which would result only in 2.5 ps, that might not be long enough.