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81
Hi Anders,

Great! I will try this. Thank you so much for your help!
82
Hello QuantumATK team,

Thank you for your guidance; the process is now clear to me. I go through the reference image attached showing a temperature profile analysis for SiO₂ quartz (MTP pretrained, RNEMD) using the Molecular Dynamics Analyzer in QuantumATK.
Could you please share the official documentation or example workflow/script that explains how to set up and perform the RNEMD (Reverse Non-Equilibrium Molecular Dynamics) simulation for SiO₂ using the MTP potential and generate and fit the temperature profile as shown in this plot?

Any references or sample Python scripts for automating this process in the QuantumATK Script Generator would be very helpful.

Thank you in advance for your guidance!
83
Hi kaihuang,

Can you check with these quick fixes for the file D0_BulkDevice.py

1. Increase electrode extension.
2. Use k_point_sampling = MonkhorstPackGrid(na=12, nc=300).
3. Use medium basis set.


84
Dear QuantumATK team,

My research strongly relies on ATK for calculating transport properties, and the LCAO framework in ATK has been extremely helpful and valuable for my studies.

Recently, I calculated the transmission spectrum of monolayer graphene. Since graphene is a well-studied material with a simple structure, it is often used as a benchmark system. However, I encountered a strange problem.


(Web image here. If it's not shown, find in the attachment.)

As shown in the figures:
- Fig.(a) presents the graphene band structure calculated using VASP along a chosen direction c. b direction has vacuum layer. The lattice has been orthogonalized, showing the well-known two Dirac cones, with the Fermi energy set to zero. ATK band-structure calculation matches this result.
- Fig.(b) and (c) show the bulk (unit cell) non-bias transmission spectrum calculated using ATK 2024. In (b), the x-axis is k-parallel and the y-axis is energy; in (c), the x-axis is energy and the y-axis is transmission. Overall, (b) looks very similar to the band structure in (a) which right, but there is one abnormal transmission channel (green line). This green channel causes the transmission at the Fermi level in (c) to be 1 instead of 0, which is clearly incorrect. The calculation was done using DFT with Dojo pseudopotentials.

To identify the issue, I tried several approaches: Using ATK 2022 instead of 2024; Rewriting the structure with cleaner fractional coordinates (Fig.(d)); Increasing the k-grid to up to 18×1×96 (Fig.(e)). None of these changes fixed the problem.

I also tried using SG15 pseudopotentials (Fig.(f)), it’s even worse that two fake conduction channels appeared (green lines).

I also tried building a bulk-like device by repeating the unit cell several times (Fig.(g)). In that case, the fake channel disappeared, but the transmission became non-integer, and the non-zero region below the Fermi level appeared as discrete lines rather than continuous bands.

Finally, I tested the Slater–Koster (method following the official tutorial (https://docs.quantumatk.com/tutorials/transmission_gr_mos2/transmission_gr_mos2.html). The result was correct and free of fake channels. However, since my main workflow is based on DFT, the S-K method is not suitable for my project. The fact that the S-K method works correctly suggests that my structure setup is fine and the problem might come from the DFT implementation in ATK.

I have attached the calculation files for both the bulk (unit cell) case (corresponds to Fig.(e)) and the bulk-like device case (corresponds to Fig.(g)).

I sincerely hope to receive your advice.

Thank you very much!
Kai
85
I suppose you are mainly looking at how the electron density changes with bias, so you can just subtract the zero-bias electron density and that's your bias-induced charge transfer.

Dear experts,

Good afternoon, how to compute cgg, cgd, cgs  of a fet using quantum atk?
86
Dear experts,

Good afternoon, how to compute cgg, cgd, cgs  of a fet using quantum atk?
87
Dear experts,

Good morning, Hope you are doing well. Whenever trying to open the Current density .hdf5 file after execution is not opening.. Opening editor instead. How to open the executed result file? Thank you.

88
General Questions and Answers / Connection to Cluster
« Last post by Ruhani on October 5, 2025, 01:11 »
Hi All,
I have tried since last weeks to makea  connection to the cluster to make my simulations faster. Of course, there are a lot of steps that maybe one of them is the main reason to fail of running. But in the attachment, you can see the error I have made in the last step. Have you ever met such an error?
Regards
Ruhani Dadashov
89
Correct, the Builder tools are for crystalline, well-behaved cases where the coincident lattice model makes sense.

There is not really a simple algorithm to create an interface between two random materials. At heart it's a global optimization problem, hard in itself, and any starting point (the configurations you happen to have of the left and right material, respectively) it's just a representative case, and can never be said to be universal, since each time you generate the amorphous sample you will get a new random configuration, and how you choose the surface termination is equally random.

Now, that may have been obvious to you already, but I just wanted to ensure we share the same picture.

As for the approaches you mention, I would definitely try the universal NN-based potentials for this case. They may not be perfect, and often not accurate enough for a reaction barrier or other very detailed calculations, but the time you save from not having to create a new MTP from scratch or even a fine-tuned MACE demo model from compensates for this. And, you can (and probably should) always do a final DFT relaxation - that is, the MLP-generated structure should just be seen as a starting guess for the interface configuration. And, thanks to their speed and readiness, you can try generate dozens or hundred of candidates in very short time.
90
Hello,
Hi,

I would like to know what the recommended approach is with the most recent update to build an interface between two arbitrary amorphous materials. Is the best approach still to train an MTP that can handle both amorphous materials as well as the interface? Is it better to use a newer neural-network-based universal potential instead of training an MTP? If neural-network-based potentials are recommended, then should they be fined tuned to the specific interfaces we are considering? Also, once the specific potential has been chosen or trained, how do we go about building the interface that will be then be analyzed? Is there a builder tool that is recommended? The builder tool seems to be mostly oriented to creating interfaces between crystals.

I would appreciate any recommendations. Thank you!
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