Tag Archives: ATLAS

Heterostructures & Carrier Recombination

Heterojunction is the term for a region where two different materials interact. A Heterostructure is a combination of two or more materials. Here, we will explore several interesting cases.


The AlGaAs-InGaAs interaction is interesting due to the difference in energy bandgap levels. It was found that AlGaAs has a higher bandgap level, while InGaAs has a lower bandgap. By layering these two materials together with a stark difference in bandgap levels, the two materials make for an interesting demonstration of a heterostructure.

The layering of a smaller bandgap material between a wider bandgap material has an effect of trapping both electrons and holes. As shown on the right side of the below picture, the center region, made of AlGaAs exibits high concentrations of both electrons and holes. This leads to a higher rate of carrier recombination, which can generate photons.


Here, the lasing profile of the material under bias:






A commonly used group of materials is InGaAsP, InGaAs and InP. Unlike the above arrangements, these materials may be lattice-matched. Lattice-matching may be explored in depth later on.Simulations suggest low or non-existent recombination rates. Although this is a heterostructure, one can see that there are no jagged or sudden drastic movements in the conduction and valence band layers with respect to each other to create a discontinuity that may result in a high recombination rate.



Conduction & Valence Band Energies under Biasing (PN & PIN Junctions)

Previously, we discussed the effect of doping concentrations on the energy band gap. The conclusion of this process was that the doping concentration alone does not alter the band gap. The band gap is the difference between the conduction band and valence bands. Under biasing, the conduction and valence bands are in fact affected by doping concentration.

One method to explain how the doping level will influence the conduction band and valence band under bias is by demonstrating the difference between the energy bands of a PN Junction versus that of a PIN Junction. Simulations of both are presented below. The intermediate section found between the p-doped and n-doped regions of the PIN junction diode offer a more gradual transition between the two levels. A PN junction offers a sharper transition at the conduction and valence band levels simulatenously. A heterostructure, which is made of more than one material (which will have different band gaps) may produce even greater discontinuities. Depending on the application, a discontinuity may be sought (think, Quantum well), while in other situations, it may be necessary to smooth the transition between band levels for a desired result.

The conduction and valence bands are of great importance for determining the carrier concentrations and carrier mobilities in a semiconductor structure. These will be discussed soon.

PN Junction under biasing (conduction and valence band energies):


Code Used (PN Junction):

#TOP TO BOTTOM – Structure Specification
region num=1 bottom thick = 0.5 material = GaAs NY = 20 acceptor = 1e18
region num=2 bottom thick = 0.5 material = GaAs NY = 20 donor = 1e18


PIN Junction Biased:


PIN Junction Unbiased:


Code Used (PIN Junction):

#TOP TO BOTTOM – Structure Specification
region num=1 bottom thick = 0.5 material = GaAs NY = 20 acceptor = 1e18
region num=3 bottom thick = 0.2 material = GaAs NY = 10
region num=2 bottom thick = 0.5 material = GaAs NY = 20 donor = 1e18

Here, the carrier concentrations are plotted:


PN Junction Simulator in ATLAS

This post will outline a program for ATLAS that can simulate a pn junction. The mesh definition and structure between the anode and cathode will be defined by the user. The simulator plots both an unbiased and biased pn junction.

go atlas


#Define the mesh

mesh auto
x.m l = -2 Spac=0.1
x.m l = -1 Spac=0.05
x.m l = 1 Spac=0.05
x.m l = 2 Spac =0.1

#TOP TO BOTTOM – Structure Specification
region num=1 bottom thick = 0.5 material = GaAs NY = 20 acceptor = 1e17
region num=2 bottom thick = 0.5 material = GaAs NY = 20 donor = 1e17

#Electrode specification
elec num=1 name=anode x.min=-1.0 x.max=1.0 top
elec num=2 name=cathode x.min=-1.0 x.max=1.0 bottom
#Gate Metal Work Function
contact num=2 work=4.77
models region=1 print conmob fldmob srh optr
models region=2 srh optr
material region=2

solve init outf=diode_mb1.str master
output con.band val.band
tonyplot diode_mb1.str

method newton autonr trap maxtrap=6 climit=1e-6
solve vanode = 2.5 name=anode
save outfile=diode_mb2.str
tonyplot diode_mb2.str

This program may also be useful for understanding how different materials interact between a PN junction. This simulation below is for a simple GaAs pn junction.

The first image shows four contour plots for the pn junction with an applied 2.5 volts. With an applied voltage of 2.5, the recombination rate is high at the PN junction, while there is low recombination throughout the unbiased pn junction. The hole and electron currents are plotted on the bottom left and right respectively.


Here is the pn junction with no biasing.


The beam profile can also be obtained:


ATLAS TCAD: Simulation of Frequency Response from Light Impulse

Recently a project was posted for a high speed photodetector. Part of that project was to develop a program that takes the frequency response of a light impulse. My thought is to create a program that can perform these tasks, including an impulse response for any structure.

Generic Light Frequency Response Simulator Program in ATLAS TCAD

The first part of the program should include all the particulars of the structure that is being simulated:

go atlas

[define mesh]

[define structure]

[define electrodes]

[define materials]

Then, the beam is defined. x.origin and y.origin describes from where the beam is originating on the 2D x-y plane. The angle shown of 270 degrees means that the beam will be facing upwards. One may think of this angle as starting on the right hand sixe of the x-y coordinate plane and moves clockwise. The wavelength is the optical wavelength of the beam and the window defines how wide the beam will be.

beam num=1 x.origin=0 y.origin=5 angle=270 wavelength=1550 min.window=-15 max.window=15

The program now should run an initial solution and set the conditions (such as if a voltage is applied to a contact) for the frequency response.


solve init
outf = lightpulse_frequencyresponse.str
LOG lightpulse_frequencyresponse.log

[simulation conditions such as applied voltage]

LOG off

Now the optical pulse is is simulated as follows:

LOG outf=transient.log

tonyplot transient.log

outf=lightpulse_frequencyresponse.str master onefile
log off

The optical pulse “transient.log” is simulated using Tonyplot at the end of the program. It is a good idea to separate transient plots from frequency plots to ensure that these parameters may be chosen in Tonyplot. Tonyplot does not give the option to use a parameter if it is not the object that is being solved before saving the .log file.

log outf=frequencyplot.log
FOURIER INFILE=transient.log OUTFILE=frequencyplot.log T.START=0 T.STOP=20E-9 INTERPOLATE
tonyplot frequencyplot.log
log off

output band.param ramptime TRANS.ANALY photogen opt.intens con.band val.band e.mobility h.mobility band.param photogen opt.intens recomb u.srh u.aug u.rad flowlines

save outf=lightpulse_frequencyresponse.str
tonyplot lightpulse_frequencyresponse.str


Now you can focus on the structure and mesh for a light impulse frequency response. Note that adjustments may be warranted on the light impulse and beam.

And so, here is a structure simulation that could be done easily using the process above.



High Speed UTC Photodetector Simulation with Frequency Response in TCAD

The following is a TCAD simulation of a high speed UTC photodetector. An I-V curve is simulated for the photodetector, forward and reverse. A light beam is simulated to enter the photodetector. The photo-current response to a light impulse is simulated, followed by a frequency response in TCAD.



I-V Curve


Beam Simulation Entering Photodetector:



Light Impulse:


Frequency Response in ATLAS:


The full project (pdf) is here: ece530_final_mbenker


AlGaAs/GaAs Strip Laser

This project features a heterostructure semiconductor strip laser, comprised of a GaAs layer sandwiched between p-doped and n-doped AlGaAs. The model parameters are outlined below. The structure is presented, followed by output optical power as a function of injection current. Thereafter, contour plots are made of the laser to depict the electron and hole densities, recombination rate, light intensity and the conduction and valence band energies.




GaAs MESFET Designs

A GaAs MESFET structure was built using Silvaco TCAD:

• Channel Donor Electrons: 2e17
• Channel thicknes s : 0.1 microns
• Bottom layer: p doped GaAs (5 micron thick, 1e15p doping)
• Gate length: 0.3 micron
• Gate metal work function: 4.77eV
•Separation between the source and drain electrode: 1 micron


The IV curve is as follows. Of primary importance are the two bottom curves, which are for a gate voltage of -0.2V and -0.5V. The top curve is 0V, over which would be undesirable for the MESFET operation.


Now, in terms of designing a MESFET, there is a large amount of theory that one may need to grasp to build one from scratch – you would probably first start by building one similar to a more common iteration. That said, there are a number of parameters that one may wish to tweak and to achieve, to name a few: saturation current, threshold voltage, transit frequency, maximum frequency, pinch-off voltage.

The iteration above does not show a highly doped region under the source and drain contacts. The separation between source and drain may also be increased and the size of the gate decreased.


Channel doping level was found to make a significant difference in overall function. The channel must be doped to a certain level, otherwise the structure may not behave properly as a transistor.

go atlas


# Define the mesh

mesh auto
x.m loc = 0 Spac=0.1
x.m loc = 1 Spac=0.05
x.m loc = 3 Spac=0.05
x.m loc = 4 Spac =0.1

# n region

region num=1 bottom thick = 0.1 material = GaAs NY = 10 donor = 2e17

# p region

region num=2 bottom thick = 5 material = GaAs NY = 4 acceptor = 1e15

# Electrode specification
elec num=1 name=source x.min=0.0 x.max=1.0 top
elec num=2 name=gate x.min=1.95 x.max=2.05 top
elec num=3 name=drain x.min=3.0 x.max=4 top

doping uniform conc=5.e18 n.type x.left=0. x.right=1 y.min=0 y.max=0.05
doping uniform conc=5.e18 n.type x.left=3 x.right=4 y.min=0 y.max=0.05

#Gate Metal Work Function
models fldmob srh optr fermidirac conmob print EVSATMOD=1
contact num=2 work=4.77

# specify lifetimes in GaAs and models
material material=GaAS taun0=1.e-8 taup0=1.e-8
method newton

solve vdrain=0.5
LOG outf=proj2mesfet500mVm.log
solve vgate=-2 vstep=0.25 vfinal=0 name=gate
save outf=proj2mesft.str
output band.param photogen opt.intens con.band val.band

tonyplot proj2mesft.str
tonyplot proj2mesfet500mVm.log

High Speed Waveguide UTC Photodetector I-V Curve (ATLAS Simulation)

The following project uses Silvaco TCAD semiconductor software to build and plot the I-V curve of a waveguide UTC photodetector. The design specifications including material layers are outlined below.


Simulation results

The structure is shown below:



Forward Bias Curve:



Negative Bias Curve:



Current Density Plot:



Acceptor and Donor Concentration Plot:



Bandgap, Conduction Band and Valence Band Plots:




Construct an Atlas model for a waveguide UTC photodetector. The P contact is on top of layer R5, and N contact is on layer 16. The PIN diode’s ridge width is 3 microns. Please find: The IV curve of the photodetector (both reverse biased and forward bias).

The material layers and ATLAS code is shown in the following PDF: ece530proj1_mbenker



P-I-N Junction Simulation in ATLAS

Introduction to ATLAS

ATLAS by Silvaco is a powerful tool for modeling for simulating a great number of electronic and optoelectronic components, particularly related to semiconductors. Electrical structures are developed using scripts, which are simulated to display a wide range of parameters, including solutions to equations otherwise requiring extensive calculation.


P-I-N Diode

The function of the PN junction diode typically fall off at higher frequencies (~3GHz), where the depletion layer begins to be very small. Beyond that point, an intrinsic semiconductor is typically added between the p-doped and n-doped semiconductors to extend the depletion layer, allowing for a working PN junction structure in the RF domain and to the optical domain. The following file, a P-I-N junction diode is an example provided with ATLAS by Silvaco. The net doping regions are, as expected at either end of the PIN diode. This structure is 10 microns by 10 microns.


The code used to create this structure is depicted below.



The cutline tool is used through the center of the PIN diode after simulating the code. The Tonyplot tool allows for the plotting of a variety of parameters, such as electric field, electron fermi level, net doping, voltage potential, electron and hole concentration and more.


Semiconductor Distribution of Electrons and Holes

Charge Flow in Semiconductors

Charge flow in a semiconductor is characterized by the movement of electrons and holes. Considering that the density and availability of electrons and holes in a material is determined by the valence and conduction bands of that material, it follows that for different materials, there will be different densities of electrons and holes. The electron and hole density will determine the current throughput in the semiconductor, which makes it useful to map out the density of holes and electrons in a semiconductor.


Density of States

The density of electrons and holes is related to the density of states function and the Fermi distribution function. States are the formations of electrons and holes that can be formed in a semiconductor. A density of states is the amount of possible formations that can exist in a semiconductor. The Fermi-Dirac probability function is used for determining the the density of quantum states. The following formula determines the most probable formation distribution or state. By varying Ni (number of particles) along energy levels, the most probable state can be found, while gi refers to remaining particle positions in the distribution.


Density of States Calculation using ATLAS

By integration of Fermi-Dirac statistics for the density of states in the conduction and valence bands arises the formulae for electron and hole concentration in a semiconductor:


where Nc and Nv are the effective density of states for the conduction bands and valence bands, which are characteristics of a chosen material. If using a program such as ATLAS, the material selection will contain parameters NC300 and NV300.



Charge Carrier Density

Charge carriers simply refer to electrons and holes, which both contribute to the flow of charge in a semiconductor. The electron distribution in the conduction band is given by the density of quantum states multiplied by the probability (Fermi-Dirac probability function) that a state is occupied by an electron.

Conduction Band Electron Distribution:


The distribution of holes in the valence band is the density of quantum states in the valence band multiplied by the probability that a state is not occupied by an electron:



Intrinsic Semiconductor

An intrinsic semiconductor maintains the same concentration of electrons in the conduction band as holes in the valence band. Where n is the electron concentration and p is the hole concentration, the following formulae apply:


The overall intrinsic carrier concentration is:


Eg is the band gap energy, which is equal to the difference of the energy is the conduction band and the energy in the valence band. Eg = Ec – Ev.

Electron and Hole concentrations expressed in terms of the intrinsic carrier concentration, where Ψ is the intrinsic potential and φ is the potential corresponding to the Fermi level (Ef = qφ):



Donor Atoms Effect on Distribution of Electrons and Holes (Extrinsic Semiconductor)

Adding donor or acceptor impurity atoms to a semiconductor will change the distribution of electrons and holes in the material. The Fermi energy will change as dopant atoms are added. If the density of holes is greater than the density of electrons, the semiconductor is a p-type and when the density of electrons is greater than the density of holes, the semiconductor is n-type (see Density of States formulas above).

[8], [10]