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91
Hello,

We have looked into the vibrational correction issues in your charged point defect simulations.

- In the Charged Point Defect Analyzer – if you unclick “Include vibrations”, you will be able to see trap levels without vibrational corrections.
- The error is related to the fact that you have negative frequencies (for B reference/elemental material, look for this warning: “There are 973 non-positive eigenmodes”). And if you do have negative frequencies, you can't calculate the vibrational DOS, and therefore you can't work out vibrationally corrected formation energies and trap levels.
-Now the question is why you have got negative frequencies. The geometry optimization of reference material with your MTP didn’t converge, and doing phonon calculations on an under-optimized structure is not a good idea.

- How to solve this? There are two options
1.  When training an MTP, you need to include elemental B material and some displacements into the training data set. Did you use the PBE functional for generating training dataset?
2. Try using a universal MACE NN potential for vibrational corrections and pre-relaxation instead of the MTP and evaluate the results.

Another thing we have noticed, that your NEB was not converged in many cases within 200 steps and these NEB calculations for diffusion take long time (formation energies/trap levels were done within a couple of hours), explaining long simulation time that you mentioned. We will think about this problematic NEB convergence in your case.

Hope, this helps.

Best regards, Vaida

92
Hello,

Thanks a lot for reporting this.
The issue is probably in the custom block "Filter migration pairs based on Pre-relaxation Calculator barrier heights".
If you convert it to a CustomBlock (right click on the block to do this), and then look at the script, the append function is expecting different values, but it gets a list. If you change it to:

for index, _ in indices_and_barriers:
    filtered_defect_migration_pairs_table.append(*defect_pair_table[index])

(note the additional *) then it should work.

We will further investigate this in the QuantumATK team.

We will also look into errors in the vibrational correction and your calculation timings and come back to you.

Best regards, Vaida
93
Hello,
I am trying to follow a procedure similar to the one outlined here (https://docs.quantumatk.com/tutorials/work_function_ag_100/work_function_ag_100.html) to calculate the electron affinity of oxides (like HfO2). However, I am unable to obtain a value that matches the experimental quantity. I generated the slab and set up the boundary conditions as described in the tutorial. I am using hybrid functionals and the LCAO calculator to obtain realistic band gaps. However, the value I am obtaining diverges significantly from the experimental value. I tried increasing the number of k-points and the basis set size but saw no significant difference in the answer. Is there anything that I should be particularly careful with when following this process with a material like HfO2? Are there any best practices for cleaving the surface and setting up ghost atoms? Are there any calculator settings that I should be particularly careful with?

I would appreciate any suggestions. Thanks!
94
Hello ,

I re-ran the calculation with the corrections previously suggested:

Added the chemical potential calculation for the boron atom

Tightened the convergence criteria in the calculator

Linked the calculators as described in the PDF

Despite these changes, the job crashed near the end with the following error:

Code
1_Defect_Diffusion_Workflow/1_Trial_1/250921_003210_4ibppi7p.hdf5' no longer exists.This means no task results will be saved to the new file.
Traceback (most recent call last):
  File "/home/synopsys/quantumatk/X-2025.06/bin/../atkpython/bin/atkpython", line 8, in <module>
    sys.exit(__run_atkpython())
             ^^^^^^^^^^^^^^^^^
  File "zipdir/ATKExecutables/atkwrappers/__init__.py", line 912, in __run_atkpython
  File "./defect_diffusion_MTP_results.py", line 901, in <module>
    filter_migration_pairs_based_on_prerelaxation_calculator_barrier_heights(
  File "./defect_diffusion_MTP_results.py", line 895, in filter_migration_pairs_based_on_prerelaxation_calculator_barrier_heights
    filtered_defect_migration_pairs_table.append(defect_pair_table[index])
  File "zipdir/sergio/HDF5/Table.py", line 2476, in append
  File "zipdir/sergio/HDF5/Table.py", line 1633, in validate
ValueError: The initial_defect column can only contain instances of NamedPointDefect, was list
Abort(1) on node 20 (rank 20 in comm 0): application called MPI_Abort(MPI_COMM_WORLD, 1) - process 20

I’ve attached the link to the relevant output files for your review through message, please alert me if the message was not sent because I have sent the message twice but it didn't show up in the sent box.

Could you please check where my setup or workflow may be incorrect, particularly around the initial_defect field expected to be a NamedPointDefect? Any guidance on resolving this would be appreciated.

Also, this run took a little over three days on 5 nodes (48 cores per node; tasks per node: 6; CPUs per task:; 8 ) before failing. Is this runtime typical for the Defect Diffusion workflow with these settings, or does it suggest a misconfiguration or inefficiency?

Thank you in advance for your help.
95
Especially when processing an I-V curve calculation with bias.

Also, can we Do the analysis of electric field , Current density , EF, Mobility variations for FET Device ?

If then how, Like what will be the efficient / suitable calculator and analysis block

Thanks
96
General Questions and Answers / How to get carrier density in a device?
« Last post by DDLDLL on September 24, 2025, 18:26 »
Especially when processing an I-V curve calculation with bias.
97
General Questions and Answers / Re: HartreeDifferencePotential caculation 2
« Last post by Anders Blom on September 24, 2025, 00:21 »
This is a perfectly normal graph. Those "fluctuations" are the actual variations of the potential with atomic resolution.
98
Quick check, do you really need Ge-Se-Te or Ge-Sn-Te (commonly, GST)? If it's the latter, we already have such a potential provided in the package.

Otherwise, you are in for a ride, but a potentially very rewarding one!

Your methodology is sort of correct, but you don't fit separately for 1-3, you combine those steps into one. That is, you include a bunch of basic crystal structures for all combinations in one training set (which you can test against the crystal experimental data). Then, instead of your step 4, you use active learning on a set of random alloys (and/or amorphous structures) of Ge-Se-Te to refine the potential for the full system. Ideally, for different stoichiometries! This is similar to the workflow we used for TiSi2 in the tutorial below, just a bit more complex for your case since you have 3 elements.

https://docs.quantumatk.com/tutorials/mtp-training-c-am-TiSi/mtp-training-c-am-TiSi.html

99
Dear experts,


 can we Do the analysis of electric fireld , Current density , EF, Mobility variations for FET Device ?

If then how, Like what will be the efficient / suitable calculator and analysis block

Thanks
100
Hi Anders, I see. Thank you for your help!
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