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Messages - Anders Blom

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106
1. Yes
2. Definitely use Active Learning because you dopant needs to move to many different locations in the crystal not captured by the simple "shake and twist" protocol in Batch (move atoms around a bit, change unit cell szie and shape a bit). You need to explore regions of the PES far from equilibrium for the NEBs to be accurate. Notably, in the newest version you can actually do active learning on the NEB itself though, that might save a lot of time!
3. Eh, not yet...
4. Really? Maybe share some data with us, so we can check. You could try to use a smaller basis_size of  course. But don't try to include all dopants at once, that will be too many elements.

107
There is a rather old explanation on how to at least project the transmission onto the MPSH states here:
https://docs.quantumatk.com/tutorials/low_level_entities/low_level_entities.html
I hope it still works, but perhaps some small changes in the code lately will require the utility script at least to be updated...

You will have to loop over the energy and record the contribution to the transmission from each MPSH state to make the plot.

The phase is defined the paper through the ratio of the real and imaginary parts of the projected transmission eigenvalues, as I understand it. By default, the transmission eigenvalues computed by QuantumATK are expressed in the basis of the original basis set orbitals (https://docs.quantumatk.com/manual/Types/TransmissionEigenvalues/TransmissionEigenvalues.html), so again one would need to perform a unitary transformation to the space spanned by the MPSH states. I'll check on the best way to do that.

Also see https://docs.quantumatk.com/tutorials/molecular_device/molecular_device.html#the-molecular-projected-self-consistent-hamiltonian-mpsh regarding how to obtain the MPSH spectrum.

108
Yes, I suppose you have to do this manually, and the procedure you indicated is correct. Probably the boundary conditions are not too critical for the geometry optimization, so it might be easier to use FFT anyway, provided you have enough vacuum above the surface.

109
Because spin up and down are no longer meaningful concepts in the noncollinear regime, to which spin-orbit belongs. Or put differently, s-o interaction couples the up and down spins so you no longer can have pure spin states, only spinors. You will therefore need to consider up/up and down/down currents, but also note there is up/down and down/up contributions.

110
Which version of the code are you using? Ideally, if you can share the Python input file, we can look at this, as it seems like a bug, but it could already have been fixed in newer versions. If you don't want to share the script publicly, you can email it.

111
General Questions and Answers / Re: optimize_cell flag Error
« on: December 1, 2023, 20:56 »
Correct

112
Yes, HTST is part of the calculation for the transition rates.

113
This functionality is today included in the GUI, so I would recommend you use that instead. Anyway, it would not be possible to just port this script from such an old version, the API is completely different today.

114
It appears to be a bug. It will be fixed in the December release V-2023.12.

115
Thanks, we will investigate! Unfortunately a lot of our tutorials were written for older versions and we have not had time to update them. If you have a chance to try the V-2023.09 version it will be even more helpful, because if the error is isolated to the U-version but it works in V, then there is no point in fixing it since we cannot release updates to U anymore.

116
You will need to explain more in detail what you do before the error appears. It seems to be related to the GUI, not running the calculation?

117
The short answer is don't use the DensityOfStates class, it's outdated and very slow and cumbersome to work with. We have a much more powerful ProjectedDensityOfStates class that hopefully takes care of all your needs!

It still takes the same amount of time to calculate the DOS (which btw parallelizes really well, so use as many MPI processes as possible), and you do have to decide on the projections beforehand. But as long as you only need e.g. site and angular momentum projection, it will later be instantaneous to get the projection plots, and you can do it right in the GUI analyzer.

118
See https://docs.quantumatk.com/tutorials/inelastic_electron_spectrometry_au_h2_au/inelastic_electron_spectrometry_au_h2_au.html#introduction for the difference between the two in terms of how the GUI analyzer shows it. That is, IETS=(d2I/d2V) / (dI/dV).

The two versions where you divide with dI/dV or not do however seem to vary a bit in the literature and the term IETS can be used for both.

The method inelasticElectronTunnelingSpectroscopy() returns d2I/d2V as the manual states https://docs.quantumatk.com/manual/Types/InelasticTransmissionSpectrum/InelasticTransmissionSpectrum.html.

119
I looked back at your original post. You need to separate two cases, which I think now are a bit mixed up. If you are looking for the Schottky barrier between two materials, then you would follow the approach as in our Ag/Si paper of the NiSi2 tutorial https://docs.quantumatk.com/tutorials/nisi2-si/nisi2-si.html. In both cases it is very helpful to introduce doping to screen the interface potential, but of course as we show in the paper, the barrier itself depends on this doping.

On the other hand, if you want to simulate a specific channel length, you just make the system the size you want, and add both left and right electrodes. In this case you still need to worry about the potential going flat but in metallic electrodes this happens very quickly. And again, if you use semiconducting electrodes, they need to be doped, how else would you get a current?

120
It's the length of the entire device. With low doping this can be very long.

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