Dear Sir,

I am studying the the inelastic current of a graphene nanoribbon Based TFET device using the STD method.

I have read through the case study

https://docs.quantumwise.com/casestudies/std_transport/std_transport.html on Si device and trying to do the same thing on a GNR based device. So basically I first computed the dynamic matrix of my device (

**GNR_PN_dynmat.py**), then I computed the corresponding std configuration of my device (

**std-300k.py**), next I started a loop to calculate the DeviceConfiguration at different bias voltage(

**300K_iv_scf.py**), finally I calculated the transmission spectrum at these bias voltage (

**300K_transmission.py**). The procedure is same as shown in the case study. The only difference is that I used a different forcefield potential Tersoff_CH_2010, since the materials is carbon rather than Silicon. And I used the Extended Huckel calculator rather than the DFT-LCAO calculator to calculated the DeviceConfiguration and transmission spectrum.

But the hard part is that the DeviceConfiguration calculation is very difficult to get converged. Actually most of them did not converged at the max step. As a result the calculated current is oscillating wildly, making it hard to interpret:

The result is very unreasonable to me, and I don't know if it is solely due to the unconverged calculation.

So, can any one help me with:

(1) why is the STD calculation so hard to get converged, and is there any specific advice for increase the convergence chance for my device calculation?

(2) If the calculation converged at all bias points will the oscillation diminishes, and the current curve looks more reasonable?