2D-PNjuction's capacitance

senzhao · August 13, 2023, 10:26am

Dear Juan,
I’m sorry to bother you. This problem occurs when the simulated 2D-PNjuction’s capacitance varies with the external voltage. When I changed the voltage, the capacitance didn’t change.Here is my code.

and this is my doping:

I used the ssac_cap.py analog capacitor in devsim-main.
Its results remain at a constant without change.I wonder where such a question might come from.
I guess if I have a wrong concept in simulating capacitance.Do we use fc =\frac {1}{2πRC} to calculate capacitance?
Sorry to bother you again.Thank you very much!
P.S.If I get a 2Delectric field.How can I find the change of electricFiled_x(/y) in the X-axis(/Y-axis) components with respect to the corresponding coordinates.

Juan · August 13, 2023, 10:21pm

The ssac_cap.py example does not consider doping, it is only an insulator so its capacitance will be constant.

Please look at:

examples/diode/ssac_diode.py

It is located in:

$CONDA_PREFIX/devsim_data/examples/diode

on Linux if you are using Anaconda python. The edge model values are not useful to get x and y components, or for visualization. Even in 1d each position can sometimes point in the wrong direction.

To generate the x and y components from 2d simulation, us something like:

element_from_edge_model(edge_model="ElectricField",   device=device, region=region)

and the plot the components in the visualizer as ElectricField_x and ElectricField_y

senzhao · August 14, 2023, 2:26am

Thank you for your reply:
Now x and EField_x have different dimensions and it seems it can’t plot by python.How can I change to get a picture like it in Tecplot?

Juan · August 14, 2023, 3:39am

Hello,

I suggest first starting with creating some kind of “cut line” or “slice line” in VisIt or Tecplot.

If you want to do this in Python, it is more difficult. The electric field on each triangular element can be getting from the element_model_values as every 3rd value:

z=Z[::3]

since each triangle has 3 edges and the length of the element model values is 3 times the number of triangles.

It looks like @SinglePhotonGuy has done something similar by plotting the magnitude of the electric field in 2d.
Basic questions from a new user - Visualization of Resuls and Mesh for 1D and 2D Sims

senzhao · August 15, 2023, 1:37am

Hi!
Thank you for your reply.I will test this way.
Aa for electric field,I want to export as csv file.I will try if that way works.
Thank you!

senzhao · August 15, 2023, 3:42am

Hi,
Sorry for bothering you again.
I have another question.

Can I change v=151 to do next loop?Like this:

Do we need to manually save the results of previous iterations and import them into later loops?
Thank you!

Juan · August 16, 2023, 5:46am

The solve command will use the previous solution as an initial guess for the next bias point. If you want to start a sweep from an origin point, you would need to save Electrons, Holes, Potential using get_node_model_values.

You can then set them using set_node_values

senzhao · August 17, 2023, 7:24am

Thank you for your reply!

Now I save the values into txt file,can it read from txt files?

I tried this way,it seems like I can’t load data from these txt files.

Juan · August 18, 2023, 12:39am

Please see hear for an example of doing this in memory:

loop

github.com

devsim/devsim_3dmos/blob/main/ieee/sweeps.py#L109


      
          vgstep  = (vgstart-gatebias)/4.
          vdstart = vdrange[0]
          
          rampbias(device, "gate", vgstart, vgstep, 0.001, 25, 1e-8, 1e30, mos90.printAllCurrents)
          
          vgstep  = (vgrange[1]-vgrange[0])/(vgrange[2] - 1)/4.
          vgmax = vgrange[1]
          
          backup = None
          
          for vd in np.linspace(*vdrange):
              vd = float(vd)
              if backup:
                  mos90.restore_backup(backup)
                  ds.solve(type="dc", absolute_error=1.0e30, relative_error=1e-4, maximum_iterations=100)
                  backup = None
          
              gatebias = ds.get_parameter(device=device, name=GetContactBiasName("gate"))
              if gatebias != vgstart:
                  raise RuntimeError("Unexpected backup gate bias %g != %g" % (gatebias, vgstart))

save_backup

github.com

devsim/devsim_3dmos/blob/main/ieee/mos90.py#L357


      
                  CreateSolution(device, r, "sizing")
                  ds.set_node_values(device=device, region=r, name="sizing", values=node_refinements[r])
                  for i, v in zip(coordinate_indexes[r], node_refinements[r]):
                      cr = min(coordinate_refinement[i], v)
                      #cr = math.pow(10., math.floor(math.log10(min(coordinate_refinement[i], v))))
                      coordinate_refinement[i] = cr
          
              data = np.array(coordinate_refinement)*scale
              return data
          
          def save_backup():
              # we are now at the initial bias
              biases = ('drain', 'gate', 'source', 'body')
              backup = {'regions' : {},
                        'contacts' : {},
                }
              for i in oxide_regions:
                  backup['regions'][i] = {}
                  for j in ("Potential",):
                      backup['regions'][i][j] = ds.get_node_model_values(device=device, region=i, name=j)
              for i in silicon_regions:

restore_backup

github.com

devsim/devsim_3dmos/blob/main/ieee/mos90.py#L376


      
                      backup['regions'][i][j] = ds.get_node_model_values(device=device, region=i, name=j)
              for i in silicon_regions:
                  backup['regions'][i] = {}
                  for j in ("Potential", "Electrons", "Holes"):
                      backup['regions'][i][j] = ds.get_node_model_values(device=device, region=i, name=j)
              backup['biases'] = {}
              for i in biases:
                  backup['biases'][GetContactBiasName(i)] = ds.get_parameter(device=device, name=GetContactBiasName(i))
              return backup
          
          def restore_backup(backup):
              for region, solution_data in backup['regions'].items():
                  for name, values in solution_data.items():
                      ds.set_node_values(device=device, region=region, name=name, values=values)
              for contact_bias, value in backup['biases'].items():
                  print("RESTORE %s %g" % (contact_bias, value))
                  ds.set_parameter(device=device, name=contact_bias, value=value)

senzhao · August 18, 2023, 12:46pm

Thank you!
The problem has been solved!
Thank you very much.