Table of Contents
Quantum Efficiency | Definition, Equations, Applications, Computations
Quantum efficiency is a parameter used to characterize the performance of optoelectronic devices. We describe the definitions and information of these photonic-electronic devices in different applications, including solar cells, photosensors (photodiodes, PDs), avalanche photodiodes (APDs), charge-coupled element (CCD) sensors, CMOS image sensors (CIS), light-emitting diodes (LEDs).
What is Quantum Efficiency?
Quantum efficiency is a parameter that describes the ability of a system to convert between “input” and “output”. It is often used in modern optoelectronic components or light-emitting materials related to the photoelectric effect. Photonics – Electronic components can be solar cells, photosensors (photodiodes, PDs), avalanche photodiodes (APDs), charge-coupled element (CCD) sensors, CMOS image sensors (CIS), light-emitting diodes (LEDs). Below, we’ll cover the definitions, equations, applications, and how quantum efficiency is calculated in these devices or applications.
The quantum efficiency of different photon-electronic components is defined as follows:
Quantum efficiency of solar cells
What is the quantum efficiency of a solar cell? Incident photon-electron conversion efficiency is also known as Incident Photon-Electron Conversion Efficiency (IPCE). Defined as how many electrons are produced by an incident photon. It helps researchers judge the quality of each or specific wavelength of solar cells. For more details, please read “Quantum Efficiency and Spectral Responsivity of Solar Cells“.
The quantum efficiency of LEDs
What is the quantum efficiency of LEDs (light-emitting diodes)? LED is an active lighting photoelectric component with a solar cell reverse process. The quantum efficiency of LEDs describes how many injected electrons are converted into photons, a phenomenon known as electroluminescence. There are two types of quantum efficiency in LEDs. One is the outer quantum efficiency (EQE) and the other is the inner quantum efficiency (IQE). The IQE of an LED is defined as the number of electrons injected per unit time that becomes the number of photons per unit time (inside the LED device). The IQE formula for LEDs is:
The EQE of an LED is defined as the number of electrons injected per unit time that is converted into the number of “luminous photons” per unit time (outside of the LED device).
The EQE formula for LEDs is:
The difference between IQE and EQE of LEDs is the Light Extraction Efficiency (LEE). The relationship is:
Therefore, the formula for LEE is:
IQE characterizes the ability of the LED active layer to convert injected electrons into photons. LEE stands for the light extraction capability of the LED component structure design, including the layer structure and the layer refractive index n matching. EQE is the ability of LED electrical energy to be converted into light energy outside of the entire device.
Quantum yield of luminescent materials
What is the quantum yield of the material? Quantum yield (QY) is common in materials science and chemistry. It is defined as the number of events per unit time produced by absorbed photons per unit time. In a system of luminescent materials, an “event” is an emitted photon. In simple terms, it is consistent with the previous description of quantum efficiency: the ability to convert between input and output.
In photochemistry and materials science, it is important to study the energy levels and electronic structure of systems. Photoluminescence spectroscopy is a common and essential technique for characterizing luminescence quality parameters, including center wavelength, half-height width, and efficiency. Therefore, photoluminescence efficiency is also known as photoluminescence quantum efficiency or photoluminescence quantum yield.
The notation for quantum yield QY is usually expressed in Latin or η. Therefore, the quantum yield QY of a light-emitting material is defined as:
Quantum yield (QY) is also known as PLQY (photoluminescence quantum yield). In some fields, such as physics, the term quantum efficiency (QE) or external quantum efficiency (EQE) is used to denote the photoluminescent ability of luminescent materials. So, in a more common way,
Quantum Yield (QY) = Quantum Efficiency (QE) = External Quantum Efficiency (EQE) = Photoluminescence Quantum Yield (PLQY)
Technical instructions on how to measure quantum yield can be found on the website PLQY
Fig. 1 Quantum yield process.
Quantum yield is the quantity that describes a material’s ability to convert incident photons into photons. Quantum yield calculates how many emitted photons per second divided by absorbed photons.
Quantum yield of luminescent materials
What is the quantum efficiency of fluorescence? Fluorescence is a type of photoluminescence. When an electron is excited from the ground state to the excited state, the spin is singlet. If the excited singlet state decays to the ground state by direct radiation, there is no spin change. The phenomenon of emitted light is called fluorescence.
Fluorescence: Excited Singlet State (S1) => Ground State (S0)
Therefore, the quantum efficiency of fluorescence is the quantum yield of fluorescence. It characterizes the photoluminescence capacity of materials through fluorescence processes without spin changes.
Quantum Efficiency of Fluorescence = Quantum Yield of Fluorescence
In contrast to fluorescence, phosphorescence is another luminescence phenomenon. From the famous Jablonski-Diagram it is easy to identify the difference between fluorescence and phosphorescence. After the spin state of the excited singlet state (S1) is transformed into an excited triplet state by system-to-system crossing (ISC), the radiative decay to the ground state is called phosphorescence.
Phosphorescence: Excited Triplet State (T1) => Ground State (S0)
Figure 2 Jablonski diagram. The photoluminescence process is described below.
The first step is absorption or excitation. The electrons or carriers are excited to the excited singlet state (S2 or S3) and relax to the first excited singlet state (S1). This relaxation process is performed on a femtosecond time scale (10-14 seconds).
S1 has two ways to release energy:
1. The radiation decays to the ground state and emits photons.
2. Non-radiative decay to the ground state and emission of phonons through vibrational energy relaxation.
3. Change its spin state to a triplet state through the intersystem crossing (ISC) process. From the Jablonski-Diagram we can see these processes.
Apparent Quantum Efficiency (AQE)
What is Apparent Quantum Efficiency (AQE)? Apparent quantum efficiency is commonly used in the field of photocatalysts or photochemistry. It can be defined as follows:
“In heterogeneous photocatalysis, quantum efficiency has begun to define the number of reactive electrons relative to the total number of photons incident in the reactive system, and for undefined reactor geometries and multicolor radiation, rather than the number of photons absorbed at a given wavelength, satisfies the photochemical definition in homogeneous photochemistry.” (Photocatalytic water splitting from semiconductor-based photocatalysts).
The AQE formula for a photocatalyst can be calculated as follows:
Apparent quantum efficiency AQE is also known as AQY (apparent quantum yield). It characterizes the efficiency of hydrogen production in photocatalytic reactions. AQE (%) = 2*H2 number of reactions/number of incident photons.
Detection Quantum Efficiency (DQE) of X-ray Imagers
What is Detection Quantum Efficiency (DQE)? DQE is often used to describe the performance of X-ray imaging equipment. It is crucial in X-ray medical imaging, it can tell the user what the radiation dose is to the patient. The formula for DQE is expressed in terms of Fourier-based spatial frequency:
DQE values can be used to quantify and judge the quality of an X-ray image sensor. However, since the X-ray image sensor is an integral part of the image system, DQE does not fully represent the quality of the X-ray image. There are other components and factors that can affect the final X-ray image quality.
For more information, please refer to the external links:
Quantum efficiency of image sensors
What is the quantum efficiency of an image sensor? An image sensor is an optical component that consists of photodiodes clustered in a two-dimensional fashion. A quantum efficiency image sensor is the efficiency of the incident photon-electron conversion, similar to a photodiode. One can realize that the quantum efficiency of an image sensor is the “average quantum efficiency” of all photodiodes in the sensor.
Image sensors can be divided into CCD and CMOS image sensors according to component design. In recent years, CMOS image sensors (CIS) have dominated the image sensor market due to their low cost and high performance.
Figure 3 Schematic diagram of CCD and CMOS image sensors.
The incident photons enter the photodiode unit of the image sensor, generating photoelectrons based on the quantum efficiency capabilities of the image sensor. Due to the inherent component structure of CCD and CMOS image sensors, the charge is transmitted outward in different ways and converted into a voltage signal.
The structure of an image sensor affects quantum efficiency performance. For example, the absolute quantum efficiency of BSI (back-illumination) CIS is about 30% higher than that of conventional FSI (front-side illumination) CIS due to the increased photosensitive area.
The quantum efficiency curve of CIS is usually performed using non-destructive testing methods. By using a special beam modulation technique and measuring the change in the image produced by CIS, the digital image variance can be converted into an analog quantum efficiency curve. The biggest benefit is that you don’t need to break the CIS and use the probe tip to test the photodiode assembly of the CIS. If you are interested in testing the system, please read the SG-A.
Figure 4 Quantum efficiency curves of CIS with R, G, and B Bayer filters.
The black curve is the sum of the RGB curves, which are often summed to represent the overall quantum efficiency capability of the CIS. These curves are measured by the SG-A system.
Quantum efficiency of CCD
What is the quantum efficiency of CCD? A CCD is a type of image sensor that consists of an array of photodiodes. The quantum efficiency of a CCD is an ability to characterize the photon-to-electron conversion capability. The quantum efficiency of the CCD describes the performance of the entire component; Therefore, it is also called EQE (External Quantum Efficiency) of CCD.
Fig. 5 Quantum efficiency of CCDs and light sensitivity of human vision.
The quantum efficiency curves of CCDs vary greatly depending on the device structure and different processing conditions. The highest quantum efficiency of CCDs is the black thin CCD, which can reach or even exceed 90%. (Source: Hamamatsu)
How to measure the quantum efficiency of a CCD? The CCD quantum efficiency is measured in a similar way to the CIS quantum efficiency measurement. Images under different beams are measured and analyzed using non-destructively modulated beams. The digital image signal is reconvoluted into an analog quantum efficiency curve.
Figure 6: QE comparison chart of the most popular CCDs.
The manufacturers of these CCDs are from Kodak (KAF-3200, KAF-1603ME, KA11002, KAF-8300, KAF-6303, KAI-4022, KAF-16803) and Sony (ICX285, ICX694). (Source)
Quantum efficiency of PMT
What is the quantum efficiency of PMT? Before that, we should understand what PMT is:
“A photomultiplier tube is a vacuum tube consisting of an input window, a photocathode, a focusing electrode, an electron multiplier, and an anode usually sealed in a vacuum glass tube.” From the Hamamatsu PMT Manual:
Figure 7: Schematic diagram of the structure of the photomultiplier tube.
The light is incident on the panel of the PMT and then passes through the photocathode, focusing electrode, electron multiplier, and anode. Based on the quantum efficiency capability of the photocathode, the incident photons are converted into electrons. The resulting electrons are multiplied in the Tona pole by high pressure, allowing very low photon conditions to be detected even in the case of single photons.
A PMT is a photoelectric element that converts incident photons into electrical signals. Thus, the quantum efficiency of PMT is a parameter that characterizes the ability of how many incident photons are converted into photoelectrons.
Figure 8 Quantum efficiency of PMTs with different photocathodes.
The curve code and the photocathode material are matched in the table below, and the theoretical quantum efficiency curve of the photocathode is plotted. Photocathode materials dominate PMT. It can vary the spectral response wavelength range and response intensity. (Source: Hamamatsu)
| Curve Code | Photocathode Material | Window Material |
|---|---|---|
| 150M | Cs-I | MgF2 |
| 250S | Cs-Te | Quartz |
| 250M | Cs-Te | Borosilicate |
| 350K | Sb-Cs | UV |
| 351U | Sb-Cs | UV |
| 452U | Bialkali | UV |
| 456U | Low dark bialkali | UV |
| 552U | Multialkali | UV |
| 555U | Multialkali | UV |
| 650U | GaAs(Cs) | UV |
| 650S | GaAs(Cs) | Quartz |
| 851K | InGaAs(Cs) | Borosilicate |
The quantum efficiency of photodiodes (PDs).
What is the quantum efficiency of a photodiode (PD)? Photodiodes, also known as photodetectors, convert incident photons into electrons. Therefore, the quantum efficiency of photodiodes is a feature that describes the photon-electron conversion efficiency.
Quantum Efficiency Formula for PD:
SR(λ) is the spectral responsivity in amps/watts. In the field of photodiode or photodetector characterization, spectral responsivity (SR) is more commonly used than quantum efficiency to describe the performance of photodiode components. The quantum efficiency of a photodiode is the same as that of an external quantum efficiency (EQE).
Fig.9. Quantum efficiency of different photodiodes with different wavelength response ranges.
Silicon photodiodes have a response wavelength range of 300nm to 1100nm. The quantum efficiency curve of GE photodiodes ranges from 900 nm to 1800 nm. The green line is the quantum efficiency curve of the silicon solar cell, with an external quantum efficiency of more than 95%. Unlike solar cells, the quantum efficiency curve design of photodiodes is not designed on extremely high EQEs, but rather balances quantum efficiency with the wavelength range (e.g., UV or NIR range) for dark noise current or light sensing applications. Therefore, the quantum efficiency curve is important for photodiode components, but it is not the most important parameter for photodiodes. (Source: Enlitech)
In many applications, photodiodes operate at a certain bias voltage, which can reduce the PN junction band pattern and improve the response speed of photon detection. Therefore, the quantum efficiency curve of a photodiode is also common at a certain bias voltage.
Figure 11 Encapsulated germanium photodiode.
The Ge photodiode is a TO package that covers an anodized aluminum body. Photons pass through the Ge PN junction and are converted into electron and current signals according to their quantum efficiency capabilities. The current signal is connected to an external circuit via a BNC connector.
Quantum efficiency of APD
What is the quantum efficiency of an avalanche photodiode (APD)? APD is a type of photodetector that operates at a high bias voltage. It can create an “avalanche effect” to increase the gain of the APD. The quantum efficiency of APD is:
Fig. 12 Quantum efficiency curves of APD and PMT.
In general, APDs have higher quantum efficiency performance than PMTs. The spectral response wavelength range in the quantum efficiency curve of the APD is much wider than that of any photocathode type PMT, especially in the NIR wavelength range. From the perspective of the quantum efficiency curve, they are the main advantages of APD. (Source: Wiley.com)
To learn more about how to measure the quantum efficiency of a photovoltaic module, we will explain the information about quantum efficiency using the example of a solar cell.
Quantum efficiency and spectral responsivity of solar cells
Before we explain what quantum efficiency is, let’s look at spectral response.
Spectral responsivity (SR) is an index that evaluates the photoelectric conversion ability of optical radiation detection components (such as light detectors, photometers, solar cells, etc.), that is, the incident photon-electron conversion efficiency (IPCE). For example, a solar cell is also a kind of photovoltaic component that converts light into electrical energy, so the spectral response is also an important indicator to evaluate its conversion efficiency.
The spectral response SR(λ) can be written as:
where P(λ) is the incident light energy of each wavelength, measured in Watt; I(λ) is the current converted by the solar cell after receiving the incident light, measured in amps (Amp). The meaning is: the ability of a solar cell to receive one watt of light energy and how many amperes of current can be generated.
The spectral response can also be referred to as Quantum Efficiency (QE) or IPCE (Incident Photon-Electron Conversion Efficiency). The spectral response can represent the ability of each incident photon to be converted into electrons transmitted to the external circuit, which is called quantum efficiency (QE), expressed in percentages. This can also be referred to as incident photon-electron conversion efficiency (IPCE).
Figure 13. Schematic diagram of solar cell quantum efficiency/spectral response/IPCE principle.
How is quantum efficiency calculated?
The conversion of the spectral response SR(λ) to the quantum efficiency QE(λ) can be written as follows:
where q is the amount of electron, h is Planck’s constant, v is the frequency of photons, and λ is the wavelength of incident light (in nm). Rewrite the above equation to obtain the external quantum efficiency formula:
Figure 14. Conversion of spectral response to quantum efficiency.
Figure 15. Definition and description of External Quantum Efficiency (EQE) and Internal Quantum Efficiency (IQE).
What is External Quantum Efficiency?
The quantum efficiency obtained by converting Amp/Watt units of spectral response to electron/sec and Watt to Photons/sec is called EQE.
Generally speaking, quantum efficiency QE refers to external quantum efficiency EQE, also known as incident photon-electron conversion efficinecy (IPCE).
QE=EQE=IPCE
The external quantum efficiency EQE calculates the number of electrons produced by the total number of incident photons. Using Figure 15 as an example, suppose a total of 10 photons are incident on a solar cell, and 2 photons are reflected on the surface of the solar cell, resulting in 6 charges. Then according to the definition, the external quantum efficiency of this solar cell
EQE = Number of Generated Charges / Total Number of Incident Photons = 6 / 10 = 60%
What is Internal Quantum Efficiency?
Internal Quantum Efficiency (IQE) is also the calculation of photon-electron conversion efficiency. Unlike the external quantum efficiency EQE, it calculates the number of photons actually incident inside the solar cell, as well as the number of electrons it produces. Using Figure 2-1 as an example, suppose that a total of 10 photons are incident on a solar cell, and 2 photons are reflected on the surface of the solar cell. Then the number of photons that actually enter the battery material is (10 – 2) = 8 photons to produce 6 electrons. Then the internal quantum efficiency of this battery
IQE = number of charges generated / number of photons incident inside the material = 6 / (10-2) = 75%.
The relationship between the internal quantum efficiency IQE and the external quantum efficiency EQE
The internal quantum efficiency is only calculated as incident on the inside of the material. The external quantum efficiency, on the other hand, calculates the total number of incident photons regardless of the reflection or penetration of the interface. If the reflectivity of the interface is R, then the relationship between the two is:
Figure 16. Spectra of the external quantum efficiency EQE, internal quantum efficiency IQE, and reflectance R of a Si solar cell.
Why is quantum efficiency the best tool for creating high-efficiency solar cells?
The quantum efficiency/spectral response reflects the photoelectric conversion efficiency of solar cells to different wavelengths, and the conversion efficiency of solar cells is affected by the material, process, structure and other factors of the battery itself, so that different wavelengths have different conversion efficiency. The use of spectral response technology to detect and analyze the changes in the conversion efficiency of the battery under different conditions can analyze the advantages and disadvantages of the manufacturing process and find out the key factors related to improving efficiency.
Fig. 17 shows the spectral responses A and B measured by two silicon crystal cells A and B after two processes, from which it can be seen that the efficiency of cell A is higher, mainly because the conversion efficiency in the 700~1100 nm band is higher than that of cell B, and the short-circuit current contributed is 0.897 mA/cm2 higher than that of cell B. However, at 300~500 nm, the efficiency of A is slightly lower than that of B battery, and the short-circuit current density is 0.675 mA/cm2 lower than that of B battery. Therefore, the overall short-circuit current density of battery A is still higher than that of battery B (0.897-0.675)=0.222 mA/cm2.
The structure and process of different bands representing different layers of the battery will be described in more detail in the next section. Therefore, the process of A cell in the short wavelength range can be improved according to the results reflected in different wavelength bands, so as to improve the efficiency of A cell. From the results of the spectral response, it is fairly easy to analyze the advantages and disadvantages of solar cells, which can be used as a guideline for improving efficiency.
Figure 17. Schematic diagram of the spectral response of solar cells and AM1.5G under different process conditions.
Quantum efficiency/spectral response/IPCE application in silicon crystalline solar cell process improvement
Quantum efficiency/spectral response/IPCE spectra react to the characteristics of each layer of the solar cell in different bands. Taking silicon crystalline solar cells as an example, at the incident interface, the interface reflection is generated, and the degree of reflection at different wavelengths is different, usually the loss caused by the reflection in the UV and infrared bands is higher, and the loss in the visible light band is the lowest.
In the 350 nm ~ 500 nm band, the spectral response curve increases with the increase of wavelength, and the conversion efficiency is improved because the penetration depth of long-wavelength photons is deeper, close to the PN interface. Generally, the part with the highest efficiency is in the band of the PN junction, because the electric field inside the pn junction can efficiently disassemble the electron hole pair after absorbing photons, so the highest efficiency is in the 500 ~ 800 nm band, which reflects the characteristics of the pn junction layer. The 800 ~1100 nm band penetrates to the lowest p-layer, and the spectrum decreases rapidly with the increase of wavelength. The reaction characteristics of each layer can be observed from the external quantum efficiency of the monocrystalline silicon solar cell in Figure 4.
Figure 18. Schematic diagram of the quantum efficiency spectra of silicon crystalline solar cells and the reaction of each wavelength. The illustration shows the structure of a silicon crystalline solar cell element.
Figure 19. Quantum efficiency spectra of two cells with different processes.
For example, in Figure 17, the conversion of the spectral response to the quantum efficiency yields Figure 19 below. The efficiency of A cell is lower than that of B cell at 300 nm ~ 500 nm, so in order to improve the efficiency of A cell, we should focus on the process of anti-reflection layer (300 nm ~ 350 nm) and n layer (350 nm ~ 500 nm).
How is quantum efficiency calculated? (Quantum Efficiency Formula)
The conversion between spectral response and quantum efficiency can be written as follows:
q is the number of electrons, h is Planck’s constant, v is the frequency of the photon, and λ is the wavelength of the incident photon (nm).
According to the above equation, the external quantum efficiency formula can be rewritten as:
What is the Quantum Efficiency Formula?
As mentioned above, the quantum efficiency of a solar cell is the electrons produced by incident photons, also known as the outer quantum efficiency (EQE). Therefore, the formula for quantum efficiency is:
Measuring instrument for the quantum efficiency of solar cells
The quantum efficiency of a solar cell/photovoltaic device is defined as the output current per input irradiance or radiated power at a given wavelength. A device that measures the external quantum efficiency of a solar cell typically has the following main components:
Monochromatic light generation system
The quantum efficiency of a solar cell/photovoltaic device is defined as the output current per input irradiance or radiated power at a given wavelength. A device that measures the external quantum efficiency of a solar cell typically has the following main components:
- Continuous wavelength bulbs
- Light collection system
- Monophotometer
- Auto filter wheel
1. Continuous wavelength bulb/light source
What kind of bulb/light source is suitable for a quantum efficiency test system? In solar cell quantum efficiency testing applications, xenon bulbs are most commonly used as a continuous wavelength white light source. The luminous wavelength of xenon lamp covers from 250nm to 2700nm, which is very suitable for the application of quantum efficiency system, not only covering the current mainstream and new solar cells, including Si solar cells (300nm ~ 1200nm), CIGS solar cells (300~1300nm), organic solar cells OPV (300nm ~ 1000nm), perovskite solar cells (300nm ~ 800nm), etc. Although the luminescence radiation spectrum of halogen bulb QTH is relatively smooth, its radiation intensity at short wavelength (< 400 nm) is insufficient, and it cannot be used to detect the quantum efficiency of solar cells 300nm ~ 400nm. Therefore, most of the light sources used in quantum efficiency measurement systems are xenon light sources.
2. Light collection system
The photons emitted by the bulb require optics to collect and introduce them into the monophotometer. The optical elements used can be lenses or mirrors, etc. Different optical designs of the light collector system affect the radiant intensity of the final monochromatic light. The light-emitting structure of a short-arc xenon lamp (how a xenon lamp works you haven’t thought about?) ) is the closest to the point light source, and with the paraxial optics, it can put more photons into the monophotometer than a halogen bulb to produce monochromatic light with higher light intensity. During the quantum efficiency test, more incident photons can produce more electrons. This results in a better signal/noise ratio and a significant reduction in the uncertainty of quantum efficiency test results (Uncertainty Analysis of Certified Photovoltaic Measurements at the National Renewable Energy Laboratory). Therefore, the design of the photocollection system plays an important role in the accurate quantum efficiency test system.
3. Monophotometer
What is a monophotometer? The monophotometer is an indispensable and important part in the quantum efficiency test system. A monophotometer is an optical device that can separate different wavelengths of color light in space by refraction (Prism) or diffraction (grating) of continuous wavelengths of white light, filter and output specific wavelengths. At present, monophotometers are mainly in the form of grating Czerny-Turner, which can provide good resolution filtering and photosensitive intensity. In the optical arrangement, light is reflected onto the grating plane by a curved collimator through an inlet slit. Grating diffraction disperses the light into a series of bands, and then a mirror passes the diffracted monochromatic light through the exit slit at a specific angle.
4. Auto filter wheel
The function of the filter wheel is to fix the filter and filter out the higher-order stray light of the diffraction grating. Each diffraction grating has a higher-order term for monochromatic rays. This is the essence of gratings. The wavelength detection range of quantum efficiency measurements typically covers a few hundred nanometers, as well as the diffraction higher-order terms of each grating. These higher-order diffracted rays are often wavelength rays that are not needed for quantum efficiency measurements. Therefore, it is common and necessary to remove this stray light with bandpass filters. The automatic filter wheel can be controlled to change different filters in different wavelength ranges of the monochromator, automating quantum efficiency measurements across the entire wavelength range of interest.
Where should the automatic filter wheel be placed in the quantum efficiency measurement system? In quantum efficiency measurements, white light is collected at the entrance of the monochromator and becomes the monochromatic beam output at the exit slit. The automatic filter wheel is usually placed behind the slit at the exit of the monochromator. It filters out as much monochromator stray light as possible.
Monochromatic light modulation system
What is a monochromatic light modulation system?
The monochromatic light modulation system is to modulate the monochromatic light of DC into an AC AC beam of a specific frequency f. In the quantum efficiency inspection system of solar cells, mechanical optical choppers are the most commonly used to modulate monochromatic light.
What is an Optical Chopper?
An optical chopper is a fan-type blade that uses electronic feedback control to modulate continuous light into periodic intermittent light of a specific frequency at a certain speed. Its composition includes a control unit, a chopping device, a chopping blade, etc.
Why are there optical choppers to modulate monochromatic light?
Optical choppers are usually used in conjunction with lock-in amplifiers. The optical chopper controls the chopping blades and the chopping device through the control unit, and modulates the continuous DC monochromatic light into an AC beam with a fixed frequency f. The control unit also sends a TTL reference signal with a modulated frequency f, which is connected to the received reference frequency signal channel of the lock-in amplifier. The lock-in amplifier filters out the various frequencies received at the signal input, leaving only the signal at the same frequency as the reference frequency f.
Where should I place the optical chopper in the quantum efficiency measurement system in the EQE measurement system?
The optimal position of the optical chopper is in front of the light entry slit of the monophotometer. This position can best chop the incident light, and can avoid the multiple reflections of monochromatic light being modulated by the chopper and incident on the measured sample, generating interference signals. In quantum efficiency measurement systems, the position of the chopper and the shielding of the diffuse light are very important. If the optical path design of the two is poor, it will cause a large error in the quantum efficiency test results.
Figure 20. The position of the chopper within the system
What kind of optical chopper should I choose?
Optical chopper multi-concomitant lock-in amplifiers are used for precision spectroscopy measurements. The SR540 optical chopper from Stanford Research System, a well-known lock-in amplifier manufacturer, has been well-known in the field of optical choppers since its introduction in 1986. However, with the great progress of electronic component technology in the past three decades, the SR540 has not undergone major design changes and improvements. As a result, there are a number of optical choppers that significantly outperform the SR540 optical chopper. In particular, the frequency stability and frequency drift of the optical chopper are 2%, but the frequency drift of the SR540 is 0.1% if the repetition of the quantum efficiency measurement is more than 99%. The frequency feedback control capability of the Phase-lock-loop, which represents the optical chopper, is very important.
| SRS SR540 Chopper | Newport 3502 chopper | Enli chopper | |
|---|---|---|---|
| 適用EQE測量的葉片 | 6/5 slot | 2 slot | 3 slot |
| 適用EQE的葉片頻率 | 4 Hz ~ 400 Hz | 4 Hz ~ 213 Hz | 4 Hz ~ 450 Hz |
| 頻率解析度 | 1 Hz | 0.1 Hz | 0.01 Hz |
| 頻率穩定度 | 2% | > 0.12% | > 0.05% |
In a quantum efficiency system, the light source is not a homotonic laser light source. As a result, the spot and divergence angle are quite large compared to ordinary cohomology laser beams. The slot density of the chopper should not be too high, that is, the number of slots is generally not more than 5 slots.
It is more appropriate to use 2 or 3 slot blades in quantum efficiency testing, as the slots have a larger area and are more capable of completely “chopping” incoherent monochromatic beams. If the monochromatic beam is not “completely chopped” by the blade slot, the beam will not be modulated to a single frequency. The signal read by the lock-in amplifier can be unstable, resulting in incorrect EQE curves for quantum efficiency measurements.
The role of photocurrent amplification and signal demodulation in EQE systems
When a monochromatic beam of light is incident on a solar cell or device under test, a photocurrent is generated due to the photoelectric effect.
The incident beam is modulated by a chopper with frequency f, therefore, the resulting photocurrent will also be a modulated AC current signal. The AC current is usually connected to a preamplifier, which can convert the current signal to a voltage signal and amplify the intensity via OP or JFET. The amplified signal is sent to a lock-in amplifier, which demodulates it at a modulated frequency f.
It is important to note that the photocurrents generated in quantum efficiency measurement systems are typically between a few nA and several hundred nA, which is in the cable noise range. Therefore, the noise generated by the cable and the electromagnetic noise caused by other instruments should be shielded and avoided. If the noise current cannot be effectively suppressed, the quantum efficiency curve will not be smooth. The repeatability and reproducibility of the EQE will not be very high, which will result in measurement uncertainty as described above.
In quantum efficiency measurement systems, chopper frequency modulation and lock-in amplifier demodulation are commonly used. One of the advantages is the high signal-to-noise ratio when using a lock-in amplifier. The second benefit of using modulation and locking techniques is that a DC voltage bias or DC light bias can be applied to the solar cell or DUT. Below we will describe the main reasons for applying optical bias and voltage bias.
Bias light system
What is a polarizing system in a quantum efficiency measurement system? It is a light source system in which a continuous wavelength light source can produce a stable light intensity over time.
In general, there are two cases where it may be necessary to apply DC bias light to a solar cell or DUT.
The first use of DC-biased light systems is to fill in the defects and carrier traps inside the solar cell. In the 1980s, scientists discovered that quantum efficiency curves depend on bias light intensity. When the bias light intensity is increased, the quantum efficiency intensity and spectral shape also change. At that time, the Si purification technology was not as good as it is now (99.9999%), so there were many pitfalls and defects inside the silicon wafer. In general, the intensity of the AC monochromatic beam in quantum efficiency measurements is less than uW, much less than the intensity of one solar (1000 W/m2). Solar cells work at one solar intensity. To obtain reasonable quantum efficiency, DC polarized illumination should be used to “create” a single-solar condition for quantum efficiency measurements. The DC bias photon will fill the trap, thus avoiding the alternating current generated by the monochromatic beam.
However, DC bias light is also a kind of “noise” for AC photocurrent signals. While a lock-in amplifier can “lock” a photocurrent signal with a modulated frequency f and electrically filter out the DC signal. If the DC photocurrent generated by the DC bias light is too high, it can still cause the lock-up amplifier to “overload” and not work.
The second use of polarized light is when measuring tandem or multi-junction solar cells. A “color” bias illumination is required to “saturate” the subcells/cells to obtain the quantum efficiency curve for each subcell. Details on how to measure the quantum efficiency of solar cells are described in IEC 60904-8-1:2017.
Bias voltage system
Sample clamp fixture
Reference Photodiode
What is a reference photodetector in quantum efficiency measurements?
In general, there are 3 types of detectors that can be accepted in the calibration of monochromatic light sources in quantum efficiency testing.
- Spectrally calibrated photodiodes, photodiode irradiance detectors, or solar cells, calibrated in power or irradiance mode.
- Cryogenic radiometer.
- Pyroelectric radiometer.
It should be noted that a spectrally calibrated photodiode should have calibration data that includes the entire spectral response range of the component before performing quantum efficiency testing. If a portion of the range is missing, the spectral measurement range is limited.
External quantum efficiency measurement software
Why is calibration important for quantum efficiency measurements?
The reference photodetector must have a known ratio of linear current to incident light intensity in the intensity and wavelength range of the monochromatic light source. The calibration of the reference photodetector must be traceable to SI units by NIST, PTB, or any ISO 17025 accredited laboratory (spectral responsivity scales or other radiometric scales are available).
What are the "Power Mode" and "Irradiance Mode" in EQE measurements?
The types of measurements that can be performed depend on the calibration mode of the reference photodetector and the relationship between the size of the reference photodetector, the DUT, and the monochromatic beam. “Smaller” means that the entire beam reaches the light-sensitive surface of the reference detector or DUT. “Bigger” means that the entire detector or device is illuminated. “Homogeneous” means that the portion of the beam that intersects the reference detector or DUT is homogeneous. “Defined” means that the beam power is known because the irradiance is uniform within the aperture region between the light source and the DUT. Where the ability to measure “absolutely” is indicated, it is implied that a “relative” measurement can also be performed.
A photodetector calibrated in power mode must have spatially uniform spectral responsivity over its photosensitive region. Photodetectors calibrated in irradiance mode may have spatially non-uniform spectral response characteristics and should only be used with uniform monochromatic beams larger than their surface area.
How to Calculate External Quantum Efficiency?
The formula for calculating the external quantum efficiency using experimental data is as follows:
After obtaining EQEDUT(λ), multiply to
correct the perturbation error of light intensity at each wavelength to EQE’DUT(λ).
Quantum Efficiency/Spectral Response/IPCE in Copper Indium Gallium Senillide CIGS) solar cell applications
Copper Indium Gallium Selenium (CIGS) is a quaternary compound semiconductor that is classified as a single-junction solar cell, and Figure 22 is a common module structure.
Figure 22. CIGS copper indium gallium selenide solar cell element structure. [2]
The energy gap of CIGS varies with the indium gallium content, making its light absorption range from 1.02 EV to 1.68 EV. Quantum efficiency/spectral response/IPCE can be tested for different solar cells. As shown in Figure 23, when the gallium content of copper indium gallium selenide increases, the energy gap increases as it is found by the results of quantum efficiency/spectral response/IPCE spectroscopy, so it can be used as a tool for the detection of gallium content in the manufacturing process.
Figure 23. Changing the quantum efficiency spectra of different gallium components under the same component structure shows that the energy gap of CIG increases from 1 eV to 1.67 eV with the increase of gallium composition. [3]
At present, the focus of technology development is to reduce costs and improve photoelectric conversion efficiency, as shown in Figure 24, the characteristics of each part of the component structure corresponding to the quantum efficiency/spectral response/IPCE spectra of different bands are plotted. For example, the quantum efficiency of the Window layer (ZnO) can be observed at the wavelength of 300 nm~400 nm, the quantum efficiency of the Buffer layer (CdS) can be observed at the wavelength of 400 nm~540 nm, and the quantum efficiency of the Absorber layer (CIGS) can be observed at the wavelength of 540 nm~1200 nm.
Figure 24. Schematic diagram of the quantum efficiency spectrum of copper indium gallium selenide solar cells and the characteristics of each layer of the reaction cell at different wavelengths. [3]
The quantum efficiency spectrum of Fig. 25 shows that the efficiency of the 400-500 nm band changes with the thickness of CdS (15 nm ~ 80 nm), and in the wavelength> 500 nm band, it shows that there is no significant difference in the efficiency of CIS, indicating that the process conditions are stable, and finally the optimal film thickness condition for CdS is 15 nm. If the> 500 nm band spectrum changes under the same CIS process conditions, it means that there are other factors affecting the experimental results of different CdS film thickness changes, and the influence of the related manufacturing process can be re-analyzed to achieve the effect of obtaining the most effective information in a single process experiment. Through the detection of quantum efficiency/spectral response/IPCE, the detailed effects of process changes can be observed, and a database can be established as a convenient tool to find problems and improve conditions when the yield changes on the production line.
Figure 25. Adjusting the thickness of different CdS layers can see the effect of the 400~500nm band on the cell efficiency from the quantum efficiency/spectral response/IPCE spectra. [2]
Figure 26. The current-voltage efficiency diagram of the battery module made by using different buffer layer materials shows that the short-circuit current of the new material ZnS(O,OH) increases by about 1%, and the open-circuit voltage decreases by 25 mV. [2]
Figure 27. Quantum efficiency/spectral response/IPCE spectra of different buffer layer materials.
It shows that the conversion efficiency of the ZnS(O,OH) layer itself is better than that of CdS, but it also has an impact on CIGS, and if the ZnS(O,OH)/CIGS interface problem can be overcome, ZnS(O,OH) has the potential to be applied. [2]
From the above description, the quantum efficiency/spectral response/IPCE spectroscopy can be understood, and the CIGS message is provided as follows:
- Photoelectric conversion efficiency of each layer such as Window/Buffer/Absorber
- Identification of the gallium concentration in Absorber copper indium gallium selenide for the identification of material bandgaps
- The degree to which the efficiency of each layer changes due to changes in process conditions
Quantum efficiency/spectral response/IPCE application in Thin-film Si tandem solar cells
Silicon crystal materials are expensive, while silicon thin film materials use few materials (silicon chip ~ 200 um; The silicon film < is 5 um, and the material is less than 5% of the silicon chip). As a result, silicon thin-film solar cells have attracted a lot of research and investment since 2006. In terms of conversion efficiency, the limit of commercial amorphous silicon thin-film modules is about 7%, which can exceed 10% compared with stacked silicon thin-film solar modules, making stacked silicon thin-film solar cells have become the mainstream of the market. Figure 28 shows the module structure of a double-stacked solar cell.
Figure 28. Structural diagram of stacked silicon thin-film solar cells; An amorphous silicon film is fabricated on a TCO glass substrate, followed by an intermediate layer with a high doping concentration, and then a microcrystalline silicon film and electrode are fabricated.
圖29是利用量子效率/光譜響應/IPCE光譜技術檢查非晶矽-微晶矽堆疊型矽薄膜太陽能電池各層的量子效率/光譜響應/IPCE光譜，此光譜對AM1.5G標準太陽光譜做計算可以得到各層的短路電流密度。若是利用太陽光模擬器與電流-電壓曲線儀，僅能得到一個輸出電流密度，無法知道各層電池的好壞，更無法訂定明確的製程改善方向與目標[4]。以圖13的結果為例，利用量子效率/光譜響應/IPCE光譜技術測出是由下層微晶矽電池限制了整體電池的輸出電流，因此可以將製程改善的方向放在下層微晶矽電池的製程，藉由提高微晶矽電池的轉換效率，使得上、下層電流密度匹配，即可提高整體效率，無需再設計更多的實驗條件來驗證是何層電池限制了整體電池效率，可大幅提升製程開發、效率改進的時程與成本。
Figure 29. Quantum efficiency/spectral response/IPCE spectra of amorphous silicon-microcrystalline silicon stacked silicon thin-film solar cells.
For example, in order to increase the current density of the upper cell, an intermediate reflective layer such as ZnO can be added between the upper and lower cells, and the light that would otherwise penetrate the upper amorphous silicon cell can be reflected back into the upper cell to form a light trapping function and increase the current density of the upper cell. Figure 30 shows whether or not an intermediate layer ZnO is added as a light capture structure in a standard bilayer amorphous-microcrystalline silicon stacked solar cell. Figure 15 shows the results of quantum efficiency/spectral response/IPCE spectroscopy of the two structures. We can understand that quantum efficiency/spectral response/IPCE spectroscopy can easily detect changes in the microstructure of stacked silicon thin-film cells, which can be used as a strong basis for process improvement. [5]
Figure 30. The standard double-layer stacked cell structure and the addition of an intermediate layer ZnO as a light capture structure.
Figure 31. Increase the spectral response/quantum efficiency spectra before and after the ZnO mesolayer process.
In today’s fiercely competitive solar energy industry, it is necessary for solar energy manufacturers to continuously reduce costs and improve photoelectric conversion efficiency! The key to improving the conversion efficiency of solar cells lies in the improvement of manufacturing processes and materials. Measuring the quantum efficiency/spectral response/IPCE of solar cells can understand the photoelectric conversion efficiency of solar cells at different light wavelengths, and users can quickly find process problems and improve them based on the results of spectral response, which is more conducive to improving efficiency.
References
[1] https://enlitechnology.com/
[2] A. Pudov “IMPACT OF SECONDARY BARRIERS ON CuIn1-xGaxSe2 SOLAR‐CELL OPERATION” Dissertation, Dep. Of Physics, Colorado State University, 2005
[3] Markus Gloeckler “DEVICE PHYSICS OF CuIn1-xGaxSe2 SOLAR‐CELL” Dissertation, Dep. Of Physics, Colorado State University, 2005
[4] A.V. Shah et al./Solar Energy Materials & Solar Cells 78 （2003） 469-491
[5] Oerlikon Solar – Constantine, 24 Sep 08