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Computational Photonics
Jena, 15 April 2015 Thomas Pertsch Institut für angewandte Physik & Abbe School of Photonics Friedrich-Schiller-Universität Jena
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Com
puta
tiona
l Pho
toni
cs, A
SP, J
ena Photolithography
2 source: www.jcmwave.com
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Com
puta
tiona
l Pho
toni
cs, A
SP, J
ena Nanostructures for photon management in solar cells
3
milling with focused ion beam
slice recording with SEM
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Solar Cell Reconstruction
1 µm
Protective layer for FIB slicing
a-Si:H pin (~475nm)
Asahi U-type, ~625nm
ZnO (~80nm) Aluminum (~100nm)
ion beam
protective Pt layer
y x
Z
q
Commercial a-Si:H module 𝜂 ≈ 7%
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Reconstructed Interfaces: TCO
FIB Slicing Parameters: Step size (y) = 25 nm Pixel size (x, z) = 4.47 nm
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Reconstructed Interfaces: Metal Back Contact
FIB Slicing Parameters: Step size (y) = 25 nm Pixel size (x, z) = 4.47 nm
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Surface Statistics
Height Distribution Metal Height Distribution TCO
𝜎RMS = 37.7 nm 𝜎RMS = 34.7 nm
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Surface Statistics
Autocorrelation
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Electro-Optical Properties
Absorption back contact?
EQE / Reflectance
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Simulation of light trapping properties
Silicon (µc-Si, no abs.) 66 nm
Silicon (µc-Si) 133 nm
ZnO - 80nm
Aluminum / Silver 100 nm
Glass (no abs.)
Glass (no abs.)
PML
PML
Periodic
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Symmetries
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Com
puta
tiona
l Pho
toni
cs, A
SP, J
ena Quantify surface roughness effects
12
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Com
puta
tiona
l Pho
toni
cs, A
SP, J
ena Integrated optical ADD/DROP multiplexer
SOI ring resonator
13 source: www.jcmwave.com
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Com
puta
tiona
l Pho
toni
cs, A
SP, J
ena Coupled microresonators
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Com
puta
tiona
l Pho
toni
cs, A
SP, J
ena Coupled microresonators
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Com
puta
tiona
l Pho
toni
cs, A
SP, J
ena Coupled microresonators
mapped intensity distribution (reflection signal)
•10 µm •1
0 µm
symmetric mode anti-symmetric mode
calculated intensity distribution
simul
ated
in
tens
ity
expe
rimen
tal
refle
ctio
n
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Com
puta
tiona
l Pho
toni
cs, A
SP, J
ena Photonic crystal
17 source: www.jcmwave.com
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Com
puta
tiona
l Pho
toni
cs, A
SP, J
ena Photonic crystal fibers
18 source: www.jcmwave.com
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Com
puta
tiona
l Pho
toni
cs, A
SP, J
ena Necessary to overcome experimental restrictions
rigorous solution of Maxwell’s equations including complex material models
150 nm
700 nm
Au spirals
Poyn
ting
vect
or
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Photonics Computing Cluster PhoClus
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• 282 nodes with 2388 CPU cores (up to 2.7 GHz clock rate) • nodes with up to 512 GB main memory à S 12 TB main memory • nodes connected by InfiniBand QDR with 40 GB/s • RAID-5 lustre file system • Green IT system = energy-saving low-voltage processors (~50 W)
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High Performance Computing ≠ High Availability Data Systems
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Blue Gene/P supercomputer at Argonne National Lab with >250,000 processors
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General-purpose computing on graphics processing units – GP-GPU
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NVIDIA Tesla K80 (not a GeForce) • up to 4992 cores (clock 1.33GHz) • up to 24 GB memory • 512-bit memory bus • peak memory bandwidth of 480 GB/s • X00 W
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GRID Computing = slow communication
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Supercomputing power [kW] •24
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Computing efficiency •25
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High performance computing @ faculty of physics & astronomy in Jena
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Research Institute of Condensed Matter Theory and Solid State Optics
• Prof. Peschel – nonlinear optics, nonlinear dynamics, nano optics • Prof. Botti – condensed matter theory
Institute of Material Science and Material Technology
• Prof. Sierka – computational material science Institute of Theoretical Physics
• Prof. Brügmann – numerical relativity • Prof. Ansorg – conformal methods in theoretical physics
Helmholtz Institute Jena
• Dr. Rykovanov – laser plasma generation and particle acceleration Institute of Applied Physics
• Prof. Pertsch – experimental and computational nano optics