研究目的
To determine the spatial distribution of charge collection in colloidal quantum dot (CQD) solar cells and identify the chief losses within the active layer.
研究成果
The study provides a quantitative tool to analyze the spatial distribution of charge collection in CQD solar cells, revealing that the region near the thiol-treated hole-transport layer suffers from low collection efficiency due to bad band alignment. The method is applicable to a wide range of thin-film solar cell architectures and offers insights into the physical origins of losses in these devices.
研究不足
The method requires precise optical modeling and measurement of EQE spectra, which may be challenging for very thin or highly absorbing layers. The accuracy of the spatial collection efficiency profiles depends on the quality of the input data and the assumptions made in the optical model.
1：Experimental Design and Method Selection:
A systematic computational method was implemented to ascertain the spatial distribution of charge collection in CQD solar cells, relying on measured optical parameters and bias-dependent external quantum efficiency spectra.
2：Sample Selection and Data Sources:
CQD solar cells were fabricated and characterized under simulated AM1.5G solar illumination. Spectroscopic ellipsometry was used to measure the complex refractive index spectrum of each layer.
3：5G solar illumination. Spectroscopic ellipsometry was used to measure the complex refractive index spectrum of each layer.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Instruments included a Horiba UVISEL Plus Extended Range ellipsometer, a Newport QUANTX-300 system for EQE measurements, and a Keithley 2400 source measure unit for current-voltage characteristics.
4：Experimental Procedures and Operational Workflow:
Devices were fabricated with ITO substrates, ZnO nanoparticles as the electron-transport layer, halide-treated CQDs as the active layer, and gold as the reflective back contact. EQE spectra were measured at different bias voltages.
5：Data Analysis Methods:
A Gaussian-noise regularized least-squares approach was used to solve the inverse problem of determining the spatial collection efficiency from the experimental data.
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