Transcript Slide 1

Imaging and modeling diffusion to defects in GaAs
Mac Read and Tim Gfroerer, Davidson College, Davidson, NC
Mark Wanlass, National Renewable Energy Lab, Golden, CO
Abstract
Motivation
Defect-related Recombination
Radiative Recombination
Conduction Band
Conduction Band
ENERGY
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Defect Level
HEAT
HEAT
Defect-related electron-hole recombination impairs the performance of many semiconductor devices.
At high excitation, the density of electrons and holes is higher, so they encounter each other more
frequently. Early encounters reduce the average lifetime and diffusion distance so the carriers are less
likely to reach defects. We observe native defects in a GaAs epilayer where the area of the defectdominated region depends strongly on excitation intensity. We model the behavior with a simulation
that allows for lifetime-limited diffusion of carriers, and we report good qualitative agreement
between the experimental and simulated images.
LIGHT
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Valence Band
Valence Band
Electrons can recombine with holes in semiconductors by hopping
through localized defect states and releasing heat. This defect-related
trapping and recombination process is a loss mechanism that reduces
the efficiency of many semiconductor devices.
Experimental Images
Diffusion to Defect Model
The radiative efficiency is the ratio of the radiative and total
recombination rates:
radiative_ rate
Bn2
efficiency 

total _ recom bination _ rate An  Bn2
The defect-related recombination rate scales linearly with the carrier
density n, while the radiative rate is proportional to n2. A and B are
coefficients that set the magnitude of the defect and radiative rates,
respectively.
Modeling Results
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Diffusion
Low-excitation
y
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High-excitation
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d
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D
y
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-
+
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D
Defect
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+
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d
x
D
Carrier density is reduced
by diffusion to the defect
Low density
A=4.2*107 cm3/s
x
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Electron
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Hole
The carrier lifetime is determined by how long it takes an electron to
find a suitable hole for recombination. At low excitation density,
electrons are more likely to encounter a defect before a hole, allowing
for defect-related trapping and recombination. At high excitation, the
electrons and holes don’t live as long, reducing the diffusion length d
and the probability of reaching a defect before radiative
recombination occurs.
High density
Photoluminescence images are obtained from an undoped
GaAs/GaInP heterosturcture. The excitation intensitydependent images shown above center on a native defect in
the thin, passivated GaAs layer.
Using the model and algorithm shown to the right, we
obtain the theoretical images above. These images, with
A=4.2*107 cm3/s (defect pixel) and A=8.2*104 cm3/s
(non-defect pixels), produced the lowest error.
A=8.2*104 cm3/s
We model the defect as an isolated pixel with an augmented defect (A)
coefficient. Diffusion to this pixel reduces the carrier density n near the
defect, and since the brightness is proportional to the radiative rate Bn2,
the adjacent region appears darker.
The Algorithm
Experimental Setup
Conclusions
• Even for high-quality semiconductor materials with few defects, diffusion can lead to significant
defect recombination at low excitation intensity.
• At low density, carriers diffuse more readily to defective regions rather than recombining
radiatively, producing larger effective “dead” areas.
•If the defect constant A is non-uniform throughout the sample, diffusion will contribute to a
reduction in net efficiency.
• The behavior can be modeled by assigning a larger A coefficient to the defect and allowing
diffusion to control the density of carriers.
• Although not shown here, our model also appears to be qualitatively consistent with preliminary
temperature-dependent measurements.
Acknowledgment
We thank Jeff Carapella for growing the test structures and the Donors of the
American Chemical Society – Petroleum Research Fund for supporting this work.
The algorithm to find steady state carrier densities (n) follows a simple rate
equation including generation, recombination, and Laplacian diffusion:
2
 Iex
d
(n) 
2
n(t )  
 ( Bn  An)  Dn 
 (t )
2 
dx 
 Eex  d
Where Eex is the photon energy, d is the layer thickness, and Dn is the
diffusion coefficient for electrons in GaAs.
•The different A coefficients produce different recombination rates in the
defect and non-defect pixels, which yield different carrier densities.
•We use Laplacian diffusion to determine the flux between adjacent pixels
during each time step and then calculate new carrier densities.
•We allow the diffusion process to continue until the average lifetime of
the generated carriers is reached.
•Then we adjust the defect and non-defect A coefficients to minimize the
error between model and experiment.