Recent Posts

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31
I want to reproduce my senior's design, but he used the 2021 version while I'm using the 2025 version. After copying his components over, we saw a 4-5 order of magnitude difference in the off-state current. Then I directly ran his Python file, but got the same result. Can someone tell me why this is happening? Would reverting to the 2021 version solve this problem? If so, could you provide me with a PBS file that works for the 2021 version?
32
Dear developers and users,
May I know how do I define NRLTightBindingParameters instead of parsing from the file?

Thank you for your attention.
33
General Questions and Answers / Re: changing display format in builder
« Last post by Chaoning on March 19, 2026, 03:38 »
sorry, v2023
34
General Questions and Answers / Re: changing display format in builder
« Last post by Chaoning on March 19, 2026, 03:36 »
my version is 2013, "graphics" is at the right of the window of "builder"
35
Scripts, Tutorials and Applications / Re: Tutorials from the past
« Last post by filipr on March 16, 2026, 10:43 »
All documentation and tutorials are available online: https://docs.quantumatk.com/index.html

The online documentation is living: pages are changed, created and deleted with every release as the program undergoes changes as well. It is therefore almost impossible to keep links alive. If a link is dead you can maybe find the up-to-date equivalent page by searching the documentation using the search field or using Google or another search engine with "<query> site: docs.quantumatk.com"
36
Can you share the script for the calculation that causes this problem?
37
Scripts, Tutorials and Applications / Tutorials from the past
« Last post by KHipps on March 16, 2026, 06:32 »
Looking through the message boards, I see a number of questions that were answered by a link to a tutorial or example.  Links like http://quantumwise.com/publications/tutorials/item/114-i-v-curve-and-voltage-drop.

Unfortunately, none of these links work.  It would be great to have a list of available tutorials, examples, and discussions that actually are available.  Something like a FAQ for program usage.

Yes, there are some youtube videos, but they are not particularly easy to find and are on a limited range of subjects. 
While on this topic, it seems to me that Quantum ATK is a bit of a stepchild for synopsis since finding anything about it is a bit of a chore within https://solvnetplus.synopsys.com/.  Can you provide a link that would get a user more directly to support for ATK?

After all that whining, I should say that it is straight forward to submit a case and that responses are usually fast and very helpful.  I just wish that self-help was easier.

Best wishes
38
General Questions and Answers / Update on: Finetuning MACE
« Last post by AsifShah on March 13, 2026, 02:37 »
Dear Admin,
I am fine-tuning (multi-head) a MACE model "mace-mp-0b3-medium.model" with interface  ~3000 configurations obtained from optimization of various interface structures between two materials. The caculator used to generate the data was LCAO-PAW. However, I observe that the training loss is more than validation loss and it does not converge easily below 2. I am using latest version of QuantumATK Y-2026.03

Code
# %% MACEFittingParameters

model_parameters = MACEModelParameters(
    foundation_model_path='/home/MHeadFineTune/AB_PAW/Model2/mace-mp-0b3-medium.model'
)

replay_finetuning_settings = MACEReplayFinetuningSettings(
    replay_data_filepath='/home/MHeadFineTune/AB_PAW/Model2/mp_traj_combined.xyz',
    number_of_samples=10000,
    replay_subselect_method=MLParameterOptions.REPLAY_SUBSELECT.RANDOM,
    replay_filtering_type=MLParameterOptions.REPLAY_FILTERING.COMBINATIONS,
)

dataset_parameters = ForceFieldDatasetParameters(
    dataset_name=None,
    validation_fraction=0.2,
    isolated_atom_energies=None,
    energy_key='REF_energy',
    forces_key='REF_forces',
    stress_key='REF_stress',
    energy_weight=1,
    forces_weight=100.0,
    stress_weight=1,
    compute_stress=True,
    forces_cap=None,
    replay_finetuning_settings=replay_finetuning_settings,
)

training_parameters = TrainingParameters(
    experiment_name='AB_replay_finetuning',
    batch_size=5,
    max_number_of_epochs=200,
    patience=50,
    device=Automatic,
    random_seed=123,
    number_of_workers=0,
    default_dtype=MLParameterOptions.DTYPE.FLOAT64,
    learning_rate=0.005,
    weight_decay=5e-07,
    restart_from_last_checkpoint=True,
    scheduler_patience=5,
    gradient_clipping_threshold=100,
    save_all_available_model_formats=True,
    additional_parameters=None,
)

mace_fitting_parameters = MACEFittingParameters(
    model_parameters=model_parameters,
    dataset_parameters=dataset_parameters,
    training_parameters=training_parameters,
)
nlsave('GSiO2hBN_Train_model_with_MultiHFine.hdf5', mace_fitting_parameters)


# %% MachineLearnedForceFieldTrainer

machine_learned_force_field_trainer = MachineLearnedForceFieldTrainer(
    fitting_parameters=mace_fitting_parameters,
    training_sets=combined_training_set_training_set_0,
    calculator=cam_AB_training_set_lcao_calculator_0,
    train_test_split=0.9,
    random_seed=None,
    save_model_evaluator=True,
)
machine_learned_force_field_trainer.train()

Log file
Code
Epoch |   Train loss | dataset val. loss | foundation_replay val. loss |
Combined val. loss
    1 |      18.9857 |       9.0502 |       9.6832 |       9.5235
    2 |      16.2392 |       9.5699 |       9.8213 |       9.7579
    3 |      15.9793 |       8.4948 |      14.1380 |      12.7140
    4 |      15.7344 |       7.0205 |       9.3637 |       8.7724
    5 |      15.2174 |       7.4290 |       9.1267 |       8.6983
    6 |      15.1447 |       7.6615 |       9.5313 |       9.0595
    7 |      13.9269 |       7.7902 |       9.3499 |       8.9563
    8 |      14.3858 |       6.9831 |       8.4594 |       8.0869
    9 |      14.6542 |       6.1258 |       9.1843 |       8.4125
   10 |      67.0137 |       7.2914 |       9.0968 |       8.6412
   11 |      14.6468 |       7.3211 |       9.6342 |       9.0505
   12 |      13.7790 |       6.7579 |      72.1496 |      55.6489
   13 |    3348.1013 |       6.4292 |       9.5679 |       8.7759
   14 |      13.6505 |       6.6999 |      13.4243 |      11.7275
   15 |      18.6541 |       4.8157 |       8.1373 |       7.2992
   16 |      10.8260 |       4.5590 |       9.3064 |       8.1084
   17 |      10.2169 |       5.3469 |       8.0607 |       7.3759
   18 |      10.8128 |       4.8280 |       7.9056 |       7.1290
   19 |      44.6345 |       4.8770 |       8.8867 |       7.8749
   20 |      13.1652 |       6.0382 |       8.0510 |       7.5431
   21 |       9.9637 |       5.0135 |       8.2736 |       7.4510
   22 |       9.9831 |       5.1497 |       7.8262 |       7.1508
   23 |       9.9076 |       5.5356 |       8.3363 |       7.6296
   24 |       9.4363 |       5.0831 |       8.0683 |       7.3150
   25 |       9.2744 |       4.0919 |       8.0174 |       7.0269
   26 |       8.5802 |       4.0783 |       7.9753 |       6.9919
   27 |       8.5956 |       3.7595 |       7.9519 |       6.8940
   28 |       7.9154 |       4.1679 |       8.0973 |       7.1057
   29 |       7.9012 |       4.1561 |       8.0263 |       7.0497
   30 |       7.8318 |       3.7461 |       7.9410 |       6.8825
   31 |       7.6374 |       3.7943 |       8.1701 |       7.0659
   32 |       8.1747 |       3.6043 |       8.1010 |       6.9663
   33 |       8.0958 |       3.6114 |       8.4863 |       7.2561
   34 |       7.4335 |       3.9294 |       8.1361 |       7.0746
   35 |       7.4023 |       4.0456 |       8.1316 |       7.1006
   36 |       7.2933 |       3.7167 |       8.4425 |       7.2500
   37 |       7.0873 |       3.3984 |       8.2840 |       7.0512
   38 |       6.3931 |       3.4524 |       8.4852 |       7.2152
   39 |       6.6867 |       3.2221 |       8.5646 |       7.2165
   40 |       6.4043 |       3.3317 |       8.5464 |       7.2305
   41 |       6.6129 |       3.1848 |       8.6768 |       7.2910
   42 |       6.4041 |       3.3490 |       8.6733 |       7.3298
   43 |       6.3622 |       3.0963 |       8.7256 |       7.3051
   44 |       6.0477 |       3.0227 |       8.8481 |       7.3782
   45 |       5.9473 |       3.0272 |       8.8475 |       7.3789
   46 |       5.9198 |       3.0129 |       8.8019 |       7.3411
39
General Questions and Answers / Re: changing display format in builder
« Last post by KHipps on March 12, 2026, 20:37 »
Thanks for the reply.  Where do i find the "Graphics" option?
40
General Questions and Answers / WSe2 bilayer energies with sliding
« Last post by gayani2025 on March 12, 2026, 05:28 »
Dear All,

I have been trying to obtain the energy profile for WSe2 bilayer. One layer is sliding over the other.
I do not get a smooth E plot. I have checked my inputs with lammps MD simulations and the results are attached.
So far I tried with ATK
1. Planewaves and
2. LCAO

exchange_correlation = GGA.PBE

correction_extension = GrimmeDFTD3(exchange_correlation=exchange_correlation)

k_point_sampling = MonkhorstPackGrid(na=9, nb=9)

numerical_accuracy_parameters = NumericalAccuracyParameters(
    density_mesh_cutoff=125.0 * Hartree, k_point_sampling=k_point_sampling
)

iteration_control_parameters = IterationControlParameters(max_steps=500)

calculator = LCAOCalculator(
    exchange_correlation=exchange_correlation,
    numerical_accuracy_parameters=numerical_accuracy_parameters,
    iteration_control_parameters=iteration_control_parameters,
    checkpoint_handler=NoCheckpointHandler,
    correction_extension=correction_extension,
)

This study is without any optimization. Just need the energy.

I have systematically generated the sliding along long diagonal

I would appreciate any guidance on this

Thank you


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