Measuring the Spectral Response of Solar Cells

By Rebecca Ingle, Ph.DMar 28 2024Reviewed by Megan Craig, M.Sc.

There is now a wealth of different solar cell technologies available, with the solar photovoltaics market showing no signs of slowing down.¹ Solar radiation is the most abundant energy source on Earth, and the challenge for researchers and engineers in solar cell development is to find how to capture and convert that energy into usable electricity efficiently.

Image Credit: Mr.Teerapong Kunkaeo/Shutterstock.com

Some current research strategies involve thinning the cells to try and compensate for the poorer penetration depth of certain wavelengths of radiation and improve the overall energy capture.² Other approaches that make use of chemical compounds, such as dyes, to absorb the solar radiation are trying to ‘green’ the molecules used to make them both more sustainable and cost effective.³

Characterization of solar cell performance and the interaction of solar cell materials with electromagnetic radiation is crucial in profiling cell efficiencies and understanding what design aspects need to be improved to help develop better solar technologies. One key approach for doing this is the measurement of the spectral response.  

Importance of Spectral Response

An object’s spectral response describes its interaction with electromagnetic radiation. The most common spectral response measurements involve measuring the amount of radiation absorbed or reflected as a function of the wavelength of the incident radiation.

Spectral response measurements are commonly used in remote sensing applications, particularly in combination with hyperspectral imaging approaches that make it possible to view images constructed in different regions of the electromagnetic spectrum.^4,5

For photovoltaics, the spectral response is often defined as the ratio of the current generated to the incident power on the solar cell as a function of wavelength, which is similar in many ways to quantum efficiency measurements.

For solar cells, the absorption and reflection profiles are critical as they will ultimately determine how much energy can be absorbed from the sun. The solar spectrum largely covers the visible region of the electromagnetic spectrum, though there are variations in the exact emission profile depending on the time of day and the weather.⁶

Ideally, a solar cell needs a high absorption coefficient across all wavelengths that fall into the solar spectrum range and a low reflectance across the same region, as any reflected radiation is not being used by the cell. Some solar cells use light trapping as a way of effectively increasing the absorption path length and the amount of light that can be absorbed, as the absorption coefficients are dependent on the material or molecular properties.⁷

Measuring Spectral Response

A common approach to measuring the spectral response to solar cells is to use a ‘solar simulator’ – a light source with a spectrum designed to mimic the sun – with a filter control system, a reference and sample cell, and an analyzer to measure the cell current.⁸

A full monochromator may be used instead of a filter set-up depending on the wavelength range to be covered and whether the response measurements need to be performed with more narrowband light, which may be necessary for compliance with performing reference and standardized measurements.

The spectral response can then be used to understand how well a cell will perform and learn about the band gaps of the materials used for semiconductor-based cells. Solar cells cannot utilize any energy absorbed above the band gap of the semiconductor material, so this acts as a means of heating the cell rather than providing useful energy that can be converted into current.

Testing Methodologies and Standards

Standardization of solar cell measurements is critical for meaningfully comparing efficiencies measured in different settings. A variety of standard standards, such as IEC60904-8:2014, cover the complete differential spectral responsivity approaches.⁹

The approach specified by IEC60904-8:2014 necessitates a two-beam approach with a bias irradiance and a quasi-monochromatic irradiance, though there can be limitations under certain conditions ⁹

Other standards include EC 60904-1 for I-V testing, IEC 60904-3 for determination of module efficiency and IEC 60904-8 for the single junction device spectral response.¹⁰

Analyzing Spectral Response Data

Normally, spectral response data for photovoltaics is analyzed by considering the measured cell's response to the ideal cell, which should give a linear spectral response as a function of wavelength. Then, if parameters such as the material collection efficiency are known, the measured response can be analyzed to extract the solar cell parameters.¹¹

Modeling the solar cell behavior and spectral response can also be a powerful tool for understanding how the solar cell works and how certain design parameters, like the material band gap, influence the measured spectral response.¹²

Applications in Device Characterization

Spectral response measurements are now a key part of solar cell device performance evaluations and are useful as a research tool into device functionality and a means of quality control testing. Many commercial platforms are available now for spectral response testing for solar cells, which has also helped improve the standardization of these measurements and make them a routine tool for evaluating potential device efficiency.

Improving Photovoltaic Efficiency with Sensors

References and Further Reading

1. Ukpanah, I. (2024) Global Solar Energy Trends in 2024, https://www.greenmatch.co.uk/solar-energy/solar-pv-statistics, accessed March 2024
2. Massiot, I., Cattoni, A., & Collin, S. (2020). Progress and prospects for ultrathin solar cells. Nature Energy, 5, 959 - 972. https://doi.org/10.1038/s41560-020-00714-4
3. Mariotti, N., Bonomo, M., Fagiolari, L., Barbero, N., Gerbaldi, C., Bella, F., & Barolo, C. (2020). Recent advances in eco-friendly and cost-effective materials towards sustainable dye-sensitized solar cells. Green Chemistry, 22(21), 7168–7218. https://doi.org/10.1039/d0gc01148g
4. Yao, H., & Qin, R. (2019). Unmanned Aerial Vehicle for Remote Sensing Applications — A Review. Remote Sensing, 1121443. https://doi.org/10.3390/rs11121443
5. Wan, L., Li, H., Li, C., Wang, A., & Yang, Y. (2022). Hyperspectral Sensing of Plant Diseases : Principle and Methods. Agronomy, 12, 1451. https://doi.org/10.3390/agronomy12061451
6.  Gottschalg, R., Infield, D. G., & Kearney, M. J. (2003). Experimental study of variations of the solar spectrum of relevance to thin film solar cells. Solar Energy Materials and Solar Cells, 79(4), 527–537. https://doi.org/10.1016/S0927-0248(03)00106-5
7. Ferry, V. E., Polman, A., & Atwater, H. A. (2011). Modeling light trapping in nanostructured solar cells. ACS Nano, 5(12), 10055–10064. https://doi.org/10.1021/nn203906t
8. Silvestre, S., Sentís, L., & Castañer, L. (1999). A fast low-cost solar cell spectral response measurement system with accuracy indicator. IEEE Transactions on Instrumentation and Measurement, 48(5), 944–948. https://doi.org/10.1109/19.799652
9. Hinken, D., Kröger, I., Winter, S., Brendel, R., & Bothe, K. (2019). Determining the spectral responsivity of solar cells under standard test conditions. Measurement Science and Technology, 30(12). https://doi.org/10.1088/1361-6501/ab34ef
10. Bentham (2024) Spectral Characterisation of Photovolatic Devices, https://www.bentham.co.uk/fileadmin/uploads/bentham/Systems/Detector_Evaluation/PVE300/PVE300_Technical_Note.pdf, accessed March 2024
11. Sinkkonen, J., Hovinen, A., Siirtola, T., Tuominen, E., & Acerbis, M. (1996). Interpretation of the spectral response of a solar cell in terms of the spatial collection efficiency. Conference Record of the IEEE Photovoltaic Specialists Conference, 561–564. https://doi.org/10.1109/pvsc.1996.564068
12. Farah Khaleda, M. Z., Vengadaesvaran, B., & Rahim, N. A. (2021). Spectral response and quantum efficiency evaluation of solar cells: A review. Energy Materials: Fundamentals to Applications. Elsevier Ltd. https://doi.org/10.1016/B978-0-12-823710-6.00014-5

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