Toward a 1D Device Model Part 1: Device Fundamentals

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Toward a 1D Device Model Part 1: Device Fundamentals Lecture 7 9/29/2011 MIT Fundamentals of Photovoltaics 2.626/2.627 Fall 2011 Prof. Tonio Buonassisi 1

Learning Objectives: Toward a 1D Device Model 1. Describe the difference between Energy Conversion Efficiency and Quantum Efficiency. 2. Describe common factors that cause solar cell IV curves to deviate from an ideal diode model: shunt & series resistance, recombination currents, and current crowding. 3. Calculate series resistance for a solar cell. 4. Calculate the Fermi Energy of a solar cell as a function of dopant concentration, illumination condition, and temperature. 5. Calculate carrier generation as a function of depth in a solar cell. 6. Calculate how material quality (minority carrier diffusion length) affects QE and solar cell performance. 7. Create a 1D model for solar cell performance based on diffusion length, optical absorption coefficient, surface reflectivity, and series & shunt resistances. 2

Key Concept: Energy conversion efficiency is not the same thing as quantum efficiency. Quantum efficiency (QE) is defined as the number of electrons out per incident photon. Note that QE is simply a census: it does not take into consideration the energy of the electron or photon. QE is generally reported as a function of wavelength. QE is a useful troubleshooting tool to identify why a device is underperforming. QE values can be quite high (between 60 and 99% for certain wavelengths), and thus can be used by devious individuals to misrepresent the conversion efficiency of their solar cell device. 3

A Note about Efficiency Courtesy of Edward H. Sargent. Used with permission. Technical Terms: - Solar Conversion Efficiency - External Quantum Efficiency - Internal Quantum Efficiency What does this really mean? 4

Solar Conversion Efficiency: Defined in Previous Slides Power Out Power In I mp V mp FF I sc V oc Typical values are 12 20% for established technologies, <10% for most emerging technologies. and F : Vary with illumination intensity (e.g., 1 Sun) 5

External Quantum Efficiency EQE Electrons Out Photons In Typical peak values are 60 90%, depending on reflectivity, for moderate-efficiency devices. EQE highly wavelength- and illumination-dependent! 6

External Quantum Efficiency Here s an example of a QE spectrum for a solar cell. Note the near-unity (i.e., 100%) QE in the visible wavelengths. Courtesy of PVCDROM. Used with permission. from PVCDROM 7

Internal Quantum Efficiency IQE = EQE 1 R = Electrons Out Photons In 1 R where R = Reflectivity Typical peak values between 80 98% for moderate-efficiency devices. IQE highly wavelength- and illumination-dependent! 8

Internal Quantum Efficiency Reflectivity and IQE (measured with different bias illumination) Examples of illumination-dependent IQE measurements for a defect-rich multicrystalline silicon solar cell. Minority carrier trapping results in low IQE with low bias illumination. 9

Approach efficiency with a grain of salt: When an efficiency is quoted, think about: - What efficiency is being measured? - What is the nature of the light being used? - What spectrometer to simulate solar spectrum? - If monochromatic, what wavelength? - What intensity (photon flux)? 10

An example of honest efficiency reporting Please see the abstract from Huynh, W., J. Dittmer et al. Hybrid Nanorod- Polymer Solar Cells. Science 295, no. 5564 (2002): 2425-7. 11

Learning Objectives: Toward a 1D Device Model 1. Describe the difference between Energy Conversion Efficiency and Quantum Efficiency. 2. Describe common factors that cause solar cell IV curves to deviate from an ideal diode model: shunt & series resistance, recombination currents, and current crowding. 3. Calculate series resistance for a solar cell. 4. Calculate the Fermi Energy of a solar cell as a function of dopant concentration, illumination condition, and temperature. 5. Calculate carrier generation as a function of depth in a solar cell. 6. Calculate how material quality (minority carrier diffusion length) affects QE and solar cell performance. 7. Create a 1D model for solar cell performance based on diffusion length, optical absorption coefficient, surface reflectivity, and series & shunt resistances. 12

Equivalent Circuit: Simple Case Lin Scale V ja J 0 V Current Density (ma/cm2) 1.E+00 8.E-01 6.E-01 4.E-01 2.E-01 0.E+00 I-V Curve 0 0.2 0.4 0.6 0.8 Voltage (V) J J 0 exp qv 1 J kt L Current Density (ma/cm2) 1.E+00 1.E-02 1.E-04 1.E-06 1.E-08 1.E-10 Log Scale I-V Curve 0 0.2 0.4 0.6 0.8 Voltage (V) 13

Equivalent Circuit: Simple Case V ja J 0 R s V Current Density (ma/cm2) 5.E-02 4.E-02 3.E-02 2.E-02 1.E-02 0.E+00 I-V Curve 0 0.2 0.4 0.6 0.8 Voltage (V) J J 0 exp q V JR s kt 1 J L Current Density (ma/cm2) 1.E+00 1.E-02 1.E-04 1.E-06 1.E-08 1.E-10 I-V Curve 0 0.2 0.4 0.6 0.8 Voltage (V) 14

Equivalent Circuit: Simple Case V ja J 0 R s R sh V Current Density (ma/cm2) 5.E-02 4.E-02 3.E-02 2.E-02 1.E-02 0.E+00 I-V Curve 0 0.5 1 Voltage (V) J J 0 exp q V JR s kt 1 V JR s R sh J L Current Density (ma/cm2) 1.E+00 1.E-02 1.E-04 1.E-06 1.E-08 1.E-10 I-V Curve 0 0.5 1 Voltage (V) 15

Key Concepts: The ideal diode equation can be enhanced in two key ways: 1) We can add the effects of parallel resistance and series resistance. 2) Advanced Concept: Instead of one saturation current I o, there are usually two saturation currents contributing to most solar cell devices: (a) one resulting from carrier recombination in the space-charge region (dominant at lower forward bias voltages) and (b) one resulting from carrier recombination in the bulk (dominant at higher forward bias voltages). The two-diode model takes both saturation currents into account. J J 01 exp q V JR s n 1 kt J exp q V JR s 02 n 2 kt V JR s J R L sh Further Reading: Green, Chapter 5 PVCDROM, Chapter 4: Solar Cell Operationhttp://www.pveducation.org/pvcdrom/solar-cell-operation/solar-cell-structure K. McIntosh: Lumps, Humps and Bumps: Three Detrimental Effects in the Current-Voltage Curve of Silicon Solar Cells, Ph.D. Thesis, UNSW, Sydney, 2001 16

IV Curve Measurements Several IV curves for real solar cells, illustrating a variety of IV responses! #14 #100 #124 FZ, e.s.r. 79-87 /sq. #9 #14 #100 FZ, e.s.r. 85-101 /sq. 17

Fill Factor 18

Why Fill Factor (FF) Matters: This is a sample IV curve for a high-efficiency solar cell: High FF. Courtesy of PVCDROM. Used with permission. 19

Why Fill Factor (FF) Matters: This is a sample IV curve for a low-efficiency solar cell (same I sc and V oc, but lower FF). Courtesy of PVCDROM. Used with permission. 20

Effect of Low Shunt Resistance (R sh ) J J L J 0 exp q(v JR s) V JR s nkt R shunt Source : http://www.pveducation.org/pvcdrom/solar-cell-operation/shunt-resistance 21 Courtesy of PVCDROM. Used with permission.

Physical Causes of Shunt Resistance (R sh ) Paths for electrons to flow from the emitter into the base. Can be caused by physical defects (scratches), improper emitter formation, metallization over-firing, or material defects (esp. those that traverse the space-charge region). Courtesy of Elsevier, Inc., http://www.sciencedirect.com. Used with permission. For more information: See publications by Dr. Otwin Breitenstein (Max-Planck Institute in Halle, Germany) on use of lock-in thermography for shunt detection and classification in solar cells. 22

Effect of High Series Resistance (R s ) J J L J 0 exp q(v JR s) V JR s nkt R shunt NB: IV curve flipped! Source: http://www.pveducation.org/pvcdrom/solar-cell-operation/series-resistance 23 Courtesy of PVCDROM. Used with permission.

Learning Objectives: Toward a 1D Device Model 1. Describe the difference between Energy Conversion Efficiency and Quantum Efficiency. 2. Describe common factors that cause solar cell IV curves to deviate from an ideal diode model: shunt & series resistance, recombination currents, and current crowding. 3. Calculate series resistance for a solar cell. 4. Calculate the Fermi Energy of a solar cell as a function of dopant concentration, illumination condition, and temperature. 5. Calculate carrier generation as a function of depth in a solar cell. 6. Calculate how material quality (minority carrier diffusion length) affects QE and solar cell performance. 7. Create a 1D model for solar cell performance based on diffusion length, optical absorption coefficient, surface reflectivity, and series & shunt resistances. 24

Components of Series Resistance Front Contact Grid Lateral Current Front Contact Grid Emitter (front surface) Bulk Current Base (bulk) Back Contact 25

Components of Series Resistance Line Losses Front Contact Grid Lateral Current Front Contact Grid Contact Resistance Emitter Sheet Resistance Bulk Resistance Bulk Current Emitter (front surface) Base (bulk) Back Contact 26

Components of R s : Bulk Resistance (i.e., How to choose absorber thickness) 27

Components of Series Resistance Line Losses Front Contact Grid Lateral Current Front Contact Grid Contact Resistance Emitter Sheet Resistance Bulk Resistance Bulk Current Emitter (front surface) Base (bulk) Back Contact 28

Bulk (Base) Resistance Resistivity: Base Resistance: 1 qn R b l A q = charge n = carrier density = carrier mobility l = length of conductive path A = Area of current flow = base resistivity NB: Beware of non-linearities! (e.g., dependence of µ on n). 29

Components of R s : Emitter Sheet Resistance (i.e., How to design front contact metallization) 30

Components of Series Resistance Line Losses Front Contact Grid Lateral Current Front Contact Grid Contact Resistance Emitter Sheet Resistance Bulk Resistance Bulk Current Emitter (front surface) Base (bulk) Back Contact 31

Emitter Sheet Resistance Bulk Resistivity is defined according to the following expression: 1 q N = resistivity µ = carrier mobility N = Carrier concentration (dopant concentration) Units of : Ω-cm For a thin layer, a sheet resistance can be described: s q t 0 s 1 e (x) N D (x)dx 1 q N t For uniform layers, a simplification: x = layer thickness Units of s : Ω, or Ω/ 32

Sheet Resistance Losses bird s eye view of solar cell device Contact Grid dy b Contact Grid S/2 The total power loss is thus: P loss I 2 dr J 2 b 2 y 2 s dy J 2 b s S 3 b 24 S / 2 0 33

Sheet Resistance Losses bird s eye view of solar cell device Contact Grid dy b Contact Grid S/2 At the maximum power point, the generated power in the emitter ROI is: V mp J mp b S 2 Hence, the fractional power loss at the maximum power point (MPP) is: p P loss P mpp s S 2 J mp 12V mp 34

Sheet Resistance Losses bird s eye view of solar cell device Contact Grid dy b Contact Grid S/2 Consider a solar cell with s = 40 Ω/, J mp = 30 ma/cm 2, and V mp = 450 mv. If we want less than a 4% power loss (i.e., p < 0.04) through the emitter, then S 12pV mp s J mp 4 mm Agrees with finger spacing in commercial solar cells! 35

Components of R s : Contact Resistance 36

Components of Series Resistance Line Losses Front Contact Grid Lateral Current Front Contact Grid Contact Resistance Emitter Sheet Resistance Bulk Resistance Bulk Current Emitter (front surface) Base (bulk) Back Contact 37

Method to Measure Contact Resistance (TLM Method) Sequential measurements of resistance between reference finger and measured finger. Textbox rechts (Bild links) nicht verschieben Frutiger 55 Roman 18 pt R c = contact resistance Figures courtesy of Stefan Kontermann Courtesy of Stefan Kontermann. Used with permission. 38

Components of R s : Line Losses 39

Components of Series Resistance Line Losses Front Contact Grid Lateral Current Front Contact Grid Contact Resistance Emitter Sheet Resistance Bulk Resistance Bulk Current Emitter (front surface) Base (bulk) Back Contact 40

Line Losses Line Resistance: R b l A l = length of conductive path A = Area of current flow = metal resistivity 1.E-06 Resistivities of Common Materials Resistivity (Ohm-cm) 1.E-07 1.E-08 1.E-09 1.E-10 Silver Copper Aluminum Tungsten Iron Platinum Lead Manganin Constantan Mercury Nichrome Graphite 41

Learning Objectives: Toward a 1D Device Model 1. Describe the difference between Energy Conversion Efficiency and Quantum Efficiency. 2. Describe common factors that cause solar cell IV curves to deviate from an ideal diode model: shunt & series resistance, recombination currents, and current crowding. 3. Calculate series resistance for a solar cell. 4. Calculate the Fermi Energy of a solar cell as a function of dopant concentration, illumination condition, and temperature. 5. Calculate carrier generation as a function of depth in a solar cell. 6. Calculate how material quality (minority carrier diffusion length) affects QE and solar cell performance. 7. Create a 1D model for solar cell performance based on diffusion length, optical absorption coefficient, surface reflectivity, and series & shunt resistances. 42

Question: When I illuminate my device, do I perturb the band structure or Fermi energy? 43

Calculate Fermi Energy (function of dopant + illumination + temperature) 44

Conductivity Band Diagram (E vs. x) Density of States Energy 45 Courtesy Christiana Honsberg and Stuart Bowden. Used with permission. http://pvcdrom.pveducation.org/ Density of States

Conductivity: Dependence on Temperature At absolute zero, no conductivity (perfect insulator). Band Diagram (E vs. x) Density of States Covalentlybonded electrons Energy 46 Courtesy Christiana Honsberg and Stuart Bowden. Used with permission. Density of States

Conductivity: Dependence on Temperature At T > 0 K, some carriers are thermally excited across the bandgap. Band Diagram (E vs. x) Density of States Energy 47 Courtesy Christiana Honsberg and Stuart Bowden. Used with permission. Density of States

Conductivity: Dependence on Temperature At T > 0 K, some carriers are thermally excited across the bandgap. Band Diagram (E vs. x) Covalentlybonded excited Thermally electrons Density of States Energy 48 Courtesy Christiana Honsberg and Stuart Bowden. Used with permission. Density of States

Conductivity: Dependence on Temperature At T > 0 K, some carriers are thermally excited across the bandgap. Band Diagram (E vs. x) Covalentlybonded Intrinsic Carriers electrons Density of States Energy 49 Courtesy Christiana Honsberg and Stuart Bowden. Used with permission. Density of States

Temperature Dependence of Intrinsic Carrier Concentration 50 source unknown. All rights reserved. This content is excluded from our Creative Commons license. For more information, see http://ocw.mit.edu/fairuse. Arrhenius Equation, generic form: N N o exp E A /k b T

Temperature Dependence of Intrinsic Carrier Concentration 51 source unknown. All rights reserved. This content is excluded from our Creative Commons license. For more information, see http://ocw.mit.edu/fairuse. Arrhenius Equation, generic form: N N o exp E A /k b T

Conductivity: Dependence on Temperature At absolute zero, no conductivity (perfect insulator). Probability Distribution Function Density of States Conduction Band Energy T = 0 Energy Valence Band 52 Probability of Occupancy Density of States

Conductivity: Dependence on Temperature At a finite temperature, finite conductivity (current can flow). Probability Distribution Function Density of States Conduction Band Occupied Density of States Conduction Band T > 0 Energy x Energy = Energy Valence Band Valence Band 53 Probability of Occupancy Density of States Density of States

Conductivity: Dependence on Temperature At a finite temperature, finite conductivity (current can flow). Probability Distribution Function Fermi-Dirac Distribution Occupied Density of States Conduction Band Energy T > 0 n e E E F 1 / k b T 1 Energy Valence Band 54 Probability of Occupancy Density of States

To reduce noise in a Si CCD camera, should you increase or decrease temperature? 55

Lower Temperature = Lower Intrinsic Carrier Concentration CCD inside a LN dewar http://msowww.anu.edu.au/observing/detectors/wfi.php Courtesy of The Australian National University. Used with permission. 56 Public domain image (Source: Wikimedia Commons). http://www.answers.com/topic/semiconductor

Question: Transistors made from which semiconductor material experience greater electronic noise at room temperature: Germanium or Silicon? 57

Intrinsic Conductivity: Dependence on Bandgap At a finite temperature, finite conductivity (current can flow). Probability Distribution Function Density of States Energy T > 0 Energy Silicon Bandgap ~ 1.12 ev 58 Probability of Occupancy Density of States

Intrinsic Conductivity: Dependence on Bandgap At a finite temperature, finite conductivity (current can flow). Probability Distribution Function Density of States Energy T > 0 Energy Germanium Bandgap ~ 0.67eV 59 Probability of Occupancy Density of States

Intrinsic Conductivity: Dependence on Bandgap Please see table at https://web.archive.org/web/20130818190346/ http://www.siliconfareast.com/sigegaas.htm 60

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