Tag Archives: Optoelectronics

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

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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):

pnjunctionbandenergies

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:

pinjunction

PIN Junction Unbiased:

pinjunction_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:

pinconc

Energy Bandgaps

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Previously, a PN Junction Simulator in ATLAS program was posted. Now, we will use and modify this program to explore more theory in respect to semiconductor materials, high speed electronics and optoelectronics.

The bandgap, as mentioned previously is the difference between the conduction band energy and valence band energy. The materials GaAs, InP, AlGaAs, InGaAs and InGaAsP are simulated and the bandgap values for each are estimated (just don’t use these values for anything important).

  • GaAs: ~ 1.2 eV
  • InP: ~ 1.35 eV
  • AlGaAs: ~ 1.8 eV
  • InGaAs: ~0.75 eV
  • InGaAsP: 1.1 eV

bandgaps

Here the conduction band and valence band are shown.

bandgaps2

The structure used in the PN Junction Simulator is found below:

#TOP TO BOTTOM – Structure Specification
region num=1 bottom thick = 0.5 material = GaAs NY = 20 acceptor = 1e17
region num=3 bottom thick = 0.001 material = InP NY = 10
region num=4 bottom thick = 0.001 material = GaAs NY = 10
region num=5 bottom thick = 0.001 material = AlGaAs NY = 10 x.composition=0.3 grad.3=0.002
region num=6 bottom thick = 0.001 material = GaAs NY = 10
region num=7 bottom thick = 0.001 material = InGaAs NY = 10 x.comp=0.468
region num=8 bottom thick = 0.001 material = GaAs NY = 10
region num=9 bottom thick = 0.001 material = InGaAsP NY = 10 x.comp=0.145 y.comp = 0.317
region num=2 bottom thick = 0.5 material = GaAs NY = 20 donor = 1e17

Is the bandgap affected by doping the concentration level?

A quick simulation (below) will tell us that the answer is no. What might influence the bandgap however? And what could the concentration level change?

bandgap4

This (above) is a simulation of GaAs with layers at different doping concentration levels. The top is a contour of the bandgap, which is constant, as expected. The top right is a cross section of this GaAs structure (technically still a pn junction diode); the bandgap is still constant. The bottom two images are the donor and acceptor concentrations.

The bandgap energy E_g is the amount of energy needed for a valence electron to move to the conduction band. The short answer to the question of how the bandgap may be altered is that the bandgap energy is mostly fixed for a single material. In praxis however, Bandgap Engineering employs thin epitaxial layers, quantum dots and blends of materials to form a different bandgap. Bandgap smoothing is employed, as are concentrations of specific elements in ternary and quarternary compounds. However, the bandgap cannot be altered by changing the doping level of the material.

PN Junction Simulator in ATLAS

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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

Title PN JUNCTION SIMULATOR

#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 AND PLOT
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
quit

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.

pnjunction_biased

Here is the pn junction with no biasing.

pnjunction_unbiased

The beam profile can also be obtained:

beamprof

ATLAS TCAD: Simulation of Frequency Response from Light Impulse

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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.

METHOD HALFIMPL

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
SOLVE B1=1.0 RAMPTIME=1E-9 TSTOP=1E-9 TSTEP=1E-12
SOLVE B1=0.0 RAMPTIME=1E-9 TSTOP=20E-9 TSTEP=1E-12

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

quit

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.

trr

 

High Speed UTC Photodetector Simulation with Frequency Response in TCAD

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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.

Structure:

121

I-V Curve

1211

Beam Simulation Entering Photodetector:

12111

 

Light Impulse:

121111

Frequency Response in ATLAS:

1211111

The full project (pdf) is here: ece530_final_mbenker

 

LED Simulation in Atlas

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This post features an LED structure simulated in ATLAS. The goal will be to demonstrate why this structure may be considered an LED. Light Emitting Diodes and Laser Diodes both serve as electronic-to-photonic transducers. Of importance to the operation of LEDs is the radiative recombination rate.

The following LED structure is built using the following layers (top-down):

  • GaAs: 0.5 microns, p-type: 1e15
  • AlGaAs: 0.5 microns, p-type: 1e15, x=0.35
  • GaAs: 0.1 microns, p-type: 1e15, LED
  • AlGaAs: 0.5 microns, n-type: 1e18, x=0.35
  • GaAs: 2.4 microns, n-type: 1e18

This structure uses alternating GaAs and AlGaAs layers.

 

06_0106_02

Bragg Gratings

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Bragg gratings are commonly used in optical fibers. Generally, an optical fiber has a relatively constant refractive index throughout. With a FBG (Fiber Bragg Grading) the refractive index is varied periodically within the core of the fiber. This can allow certain wavelengths to be reflected while all others are transmitted.

spec

The typical spectral response is shown above. It is clear that only a specific wavelength is reflected, while all others are transmitted. Bragg Gratings are typically only used in short lengths of the optical fiber to create a sort of optical filter. The only wavelength to be reflected is the one that is in phase with the Bragg grating distribution.

A typical usage of a Bragg Grating is for optical communications as a “notch filter”, which is essentially a band stop filter with a very high Quality factor, giving it a very narrow range of attenuated frequencies. These fibers are generally single mode, which features a very narrow core that can only support one mode as opposed to a wider multimode fiber, which can suffer from greater modal distortion.

The “Bragg Wavelength” can be calculated by the equation:

λ = 2n∧

where n is the refractive index and ∧ is the period of the bragg grating. This wavelength can also be shifted by stretching the fiber or exposing it to varying temperature.

These fibers are typically made by exposing the core to a periodic pattern of intense laser light which permanently increases the refractive index periodically. This phenomenon is known as “self focusing” which is when refractive index can be permanently changed by extreme electromagnetic radiation.