Show Posts

This section allows you to view all posts made by this member. Note that you can only see posts made in areas you currently have access to.


Messages - chp

Pages: [1] 2 3
1
Thanks a lot.

I also notice that there is only one choice in the list of built-in Slter-Koster Basis sets (i.e. “DFTB (CP2K, non-selfconsistent)”) to use when I perform DFTB calculations for BN system. According to your reply 1, can this set give good results for relaxations or properties if I don’t choose the “No SCF iteration” below?

2
Dear QuantumWise Staff,

I am trying to use the ATK-SE package, but there are two questions which are not clear to me. Would you please give me some advice?

1.   I am going to perform structural optimization within the framework of ATK-SE: Slater-Koster, however, there is a choice of “No SCF iteration” in the settings of Slter-Koster Basis set. What’s the difference of optimization with and without “No SCF iteration”?

2.   In general, the ATK-SE method can run for a larger system than DFT method. Taking an example, if I run a two-dimensional system consisting of Boron Nitride and graphene in parallel (for example, with 8 CPUs), what’s the upper limit of the numbers of atoms in the system?

Thanks for the help.

3
Thank you very much!

4
Thank you for your reply!

Can we calculate the PDOS of the left/right electrode under a finite bias voltage in ATK 2008.10 using a function like the following example or other methods?

http://quantumwise.com/forum/index.php?topic=69.msg338#msg338

5
Thanks.

I also calculated the projected density of states (PDOS) of C atoms in the central region. (please see the attached figure.) Figure (a) shows the transmission spectrum and the PDOS of a graphene nanoribbon. It can be seen that there is a region of zero transmission located around the Fermi level, the width of which coincides with the energy gap in the plot of PDOS. However, at the bias voltage of 1.5 V (figure (b)), there are nonzero transmission values near the Fermi level in the original band gap, while the gap in the plot of PDOS disappears and there is a continuous distribution of DOS in the whole range of energies. I want to know whether the finite DOS near the Fermi level is only due to the band-to-band tunneling from a valence band to a conduction band. Why is the PDOS continuous in the whole energy scale? Furthermore, figures (c) and (d) show the cases of a locally deformed graphene nanoribbon. It is noteworthy that there are obvious electron states near the Fermi level in the plot of PDOS under a bias voltage of 1.5 V. Why is the shape of the PDOS near the Fermi level fluctuant? How to analyses and understand this phenomenon?

Thanks in advance!

6
    Recently, I performed some test calculations bout the effects of the applied bias on the transport properties of graphenen nanoribbons. The attached figure shows the results of two kinds of armchair nanoribbons. It can be seen that in both of cases, with the increase of bias, the transport spectra move further away from the Fermi level as well as the suppressed amplitude for a wide range of energies. At higher bias voltage, there are nonzero transmission values near the Fermi level in the original band gap, the transmission values of which are dependent on the bias voltage. Where do the nonzero transmission values in the original band gap come from? How to understand these phenomena?

    Thanks in advance!

7
Thank you for your reply!

As Anders Blom indicates that at finite bias, electrostatic effects increase the effective band gap. But we also can observe that there are nonzero transmission values near the Fermi level in transmission spectrum when the bias voltage is larger than 3.6 V. I want to know where it comes from?

Thanks again!

8
Hi:

Recently, I have performed some test calculations on the I-V characteristics of semiconductor SiC nanobube. It is shown that the SiC nanotube has a band gap of 1.55 eV. However, it need about 3.5 V bias to inject a current in the nanotube? (Please see the attached python script and the pictures) Why? Is there any mistake?

Thanks in advance!

10
However, I also want to know why the energy gap in the transmission spectrum under bias cannot coincide with the corresponding results of DOS and PDOS, where a high peak lies in the energy range.

12
Hi:

     I performed some test calculations on zigzag graphene nanoribbon. The transmission spectrum, density of states (DOS), and projected density of states (PDOS) of the nanoribbon without bias can give a reasonable result. However, the transmission spectrum obtained under bias has an energy gap, conflicting with the corresponding results of DOS and PDOS (please see the attached picture, which gives the examples of zero bias and at the bias voltage of 0.5V, respectively). I cannot understand it. I doubt if I set any inappropriately parameter (please see the attached file). 

Thanks in advance.

13
Thank you very much !

14
Hi:

    I performed some test calculations on pristine (4,4) carbon nanotube. It is recognized that the (4,4) tube is metallic, but in the obtained transmission spectrum there is a deep trench at the Fermi level (please see the attach picture), which is different from other theoretical results. Moreover, the transmission coefficients (0.00815129) is not consistent with the transmission eigenvalues (1.00005082 , 0.99371959) at the energy of 0.0*electronVolt. I doubt if I set any inappropriately parameters (please see the attached file).
 
    Thanks in advance.

15
Thank you for your nice advice!

Now it can work. But I have another question. The main aim of my script is to optimize any randomly generated molecular roughly and quickly, however, the optimization steps are often very long due to the randomly initial geometry. Is there any “tricks” to improve this situation? I have tried to adjust some parameters such as the “optimizer” of “geometricOptimizationParameters”, But no clear hints are obtained. For the optimization of molecular, which of the “optimizer algorithms” (QuasiNewton and SteepestDescent) is better? In the case of “SteepestDescent”, how to set the best value of the “time_step” parameter to finish quickly the optimization?

Thanks a lot !

Pages: [1] 2 3