Predicting solar cell efficiencies from bulk lifetime images of multicrystalline silicon bricks

We present a model for predicting the solar cell efficiency potential of multicrystalline silicon bricks prior to sawing. Three model inputs are required: bulk lifetime images from the side faces of the bricks, the cell manufacturing process, and its gettering action. The model is set up with numerical device and circuit simulations, but may afterwards be parameterized for inline application. In the example shown here, we chose literature data to quantify the increase in bulk lifetime caused by phosphorus gettering of impurities during cell manufacturing. Our proposed model enables manufacturers to (i) assess initial brick quality in relation to their specific cell production line, (ii) to exclude certain parts of the bricks from cell manufacturing, and (iii) to adjust cell manufacturing to initial material quality. The specific gettering efficiency and cell process can be fed into the model dynamically and need to be calibrated ideally for each material manufacturer and each cell production line. The model presented here can be extended to cast mono and dendritically grown bricks.Australian Renewable Energy Agency (ARENA

On the method of photoluminescence spectral intensity ratio imaging of silicon bricks: Advances and limitations

Spectralphotoluminescenceimaging is able to provide quantitative bulk lifetime and doping images if applied on silicon bricks or thick silicon wafers. A comprehensive study of this new method addresses previously reported artefacts in low lifetime regions and provides a more complete understanding of the technique. Spectrally resolved photoluminescence measurements show that luminescence originating from sub band gap defects does not cause those artefacts. Rather, we find that optical light spreading within the siliconCCD is responsible for most of the distortion in image contrast and introduce a method to measure and remove this spreading via imagedeconvolution. Alternatively, image blur can be reduced systematically by using an InGaAscamera. Results of modelling this alternative camera type and experiments are shown and discussed in comparison. In addition to eliminating the blur effects, we find a superior accuracy for lifetimes above 100 μs with significantly shorter, but dark noise limited exposure times

Using machine learning to predict the complete degradation of accelerated damp heat testing in just 10% of the time

The ability to accurately predict the long-term performance of photovoltaic modules would have substantial benefits for the photovoltaic market. If we can precisely determine how new modules will perform after 25–30 years in the field, the reliability and bankability of photovoltaic systems will significantly increase. Keeping this target in mind, this study presents the first step towards achieving more cost-effective degradation monitoring. We develop machine learning models to predict the performance of photovoltaic modules at the end of 1,000 hours of damp heat tests after modules have only spent less than 10% of that time in damp heat conditions. Hence, we investigate the ability of unsupervised neural ordinary differential networks to model the entire dynamics of the degradation during a damp heat test using only the data that is collected in the first 10% of the process. The developed algorithms can significantly reduce the required time for damp heat tests and pave the way to transform the photovoltaic market

Contactless Series Resistance Imaging of Perovskite Solar Cells via Inhomogeneous Illumination

A contactless effective series resistance imaging method for large area perovskite solar cells that is based on photoluminescence imaging with non-uniform illumination is introduced and demonstrated experimentally. The proposed technique is applicable to partially and fully processed perovskite solar cells if laterally conductive layers are present. The capability of the proposed contactless method to detect features with high effective series resistance is validated by comparison with various contacted mode luminescence imaging techniques. The method can reliably provide information regarding the severeness of the detected series resistance through photo-excitation pattern manipulation. Application of the method to sub-cells in monolithic tandem devices, without the need for electrical contacting the terminals, appears feasible.Comment: 17 pages, 5 figure

Automated analysis of internal quantum efficiency using chain order regression

Spectral analysis of internal quantum efficiency (IQE) measurements of solar cells is a powerful method to identify performance-limiting mechanisms in photovoltaic devices. This analysis is usually performed using complex curve-fitting methods to extract various electrical and optical performance parameters. As these traditional fitting methods are not easy to use and are often sensitive to measurement noise, many users do not utilize the full potential of the IQE measurements to provide the key properties of their solar cells. In this study, we propose a simplified approach to analyze IQE curves of silicon solar cells using machine learning models that are trained to extract valuable information regarding the cell's performance and decoupling the parasitic absorption of the anti-reflection coating. The proposed approach is demonstrated to be a powerful characterization tool for solar cells as machine learning unlocks the full potential of IQE measurements

Surface Saturation Current Densities of Perovskite Thin Films from Suns-Photoluminescence Quantum Yield Measurements

We present a simple, yet powerful analysis of Suns-photoluminescence quantum yield measurements that can be used to determine the surface saturation current densities of thin film semiconductors. We apply the method to state-of-the-art polycrystalline perovskite thin films of varying absorber thickness. We show that the non-radiative bimolecular recombination in these samples originates from the surfaces. To the best of our knowledge, this is the first study to demonstrate and quantify non-linear (bimolecular) surface recombination in perovskite thin films

Decoupling Bimolecular Recombination Mechanisms in Perovskite Thin Films Using Photoluminescence Quantum Yield

We present a novel analytical model for analysing the spectral photoluminescence quantum yield of non-planar semiconductor thin films. This model considers the escape probability of luminescence and is applied to triple-cation perovskite thin films with a 1-Sun photoluminescence quantum yield approaching 25%. By using our model, we can decouple the internal radiative, external radiative, and non-radiative bi-molecular recombination coefficients. Unlike other techniques that measure these coefficients separately, our proposed method circumvents experimental uncertainties by avoiding the need for multiple photoluminescence measurement techniques. We validate our model by comparing the extracted implied open-circuit voltage, effective luminescence escape probabilities, absorptivity, and absorption coefficient with values obtained using established methods and found that our results are consistent with previous findings. Next, we compare the implied 1-Sun radiative open-circuit voltage and radiative recombination current obtained from our method with literature values. We then convert the implied open-circuit voltage and implied radiative open-circuit voltage to the injection-dependent apparent-effective and apparent-radiative carrier lifetimes, which allow us to decouple the different recombination coefficients. Using this lifetime analysis, we predict the efficiency losses due to each recombination mechanism. Our proposed analytical model provides a reliable method for analysing the spectral photoluminescence quantum yield of semiconductor thin films, which will facilitate further research into the photovoltaic properties of these materials

Decoupling Bimolecular Recombination Mechanisms in Perovskite Thin Films Using Photoluminescence Quantum Yield

We present a novel analytical model for analysing the spectral photoluminescence quantum yield of non-planar semiconductor thin films. This model considers the escape probability of luminescence and is applied to triple-cation perovskite thin films with a 1-Sun photoluminescence quantum yield approaching 25%. By using our model, we can decouple the internal radiative, external radiative, and non-radiative bi-molecular recombination coefficients. Unlike other techniques that measure these coefficients separately, our proposed method circumvents experimental uncertainties by avoiding the need for multiple photoluminescence measurement techniques. We validate our model by comparing the extracted implied open-circuit voltage, effective luminescence escape probabilities, absorptivity, and absorption coefficient with values obtained using established methods and found that our results are consistent with previous findings. Next, we compare the implied 1-Sun radiative open-circuit voltage and radiative recombination current obtained from our method with literature values. We then convert the implied open-circuit voltage and implied radiative open-circuit voltage to the injection-dependent apparent-effective and apparent-radiative carrier lifetimes, which allow us to decouple the different recombination coefficients. Using this lifetime analysis, we predict the efficiency losses due to each recombination mechanism. Finally, by comparing several different thicknesses, we conclude that the non-radiative bimolecular recombination is likely caused by surface recombination. Our proposed analytical model provides a reliable method for analysing the spectral photoluminescence quantum yield of semiconductor thin films, which will facilitate further research into the photovoltaic properties of these materials.Comment: Main text: 11 figures, 7 tables Supplemental Material: 42 figures, 7 table

Implied Open‐circuit Voltage Imaging via a Single Bandpass Filter Method—Its First Application in Perovskite Solar Cells

A direct, camera-based implied open-circuit voltage (iVOC) imaging method via the novel use of a single bandpass filter (s-BPF) is developed for large-area photovoltaic solar cells and solar cell precursors. This method images the photoluminescence (PL) emission using a narrow BPF with centre energy in the high-energy tail of the PL emission taking advantage of the close-to-unity absorptivity of typical photovoltaic devices with low variability in this energy range. As a result, the exact value of the sample\u27s absorptivity within the BPF transmission band is not required. The use of a s-BPF enables the adaptation of a fully contactless approach to calibrate the absolute PL photon flux for camera-based spectrally-integrated imaging tools. The method eliminates the need for knowledge of the imaging system spectral response and the use of the emission and excitation spectral shapes. Through an appropriate choice of the BPF centre energy, a range of absorber compositions or a single absorber with different surface morphologies (e.g., planar vs textured) can be imaged, all without the need for additional detection optics. The feasibility of this s-BPF method is first assessed using a high-quality Cs$_{0.05}$FA$_{0.79}$MA$_{0.16}$Pb(I$_{0.83}$Br$_{0.17}$)$_3$ perovskite neat film. The error in iVOC is determined to be less than 1.5%. The efficacy of the method is then demonstrated on device stacks with two different perovskite compositions commonly used in single-junction and monolithic tandem solar cells

Implied Open‐circuit Voltage Imaging via a Single Bandpass Filter Method—Its First Application in Perovskite Solar Cells

A novel, camera-based method for direct implied open-circuit voltage (iV$_{OC}$) imaging via the use of a single bandpass filter (s-BPF) is developed for large-area photovoltaic solar cells and precursors. The photoluminescence (PL) emission is imaged using a narrow BPF with centre energy inside the high-energy tail of the PL emission, utilising the close-to-unity and nearly constant absorptivity of typical photovoltaic devices in this energy range. As a result, the exact value of the sample\u27s absorptivity within the BPF transmission band is not required. The use of an s-BPF enables a fully contactless approach to calibrate the absolute PL photon flux for spectrally integrated detectors, including cameras. The method eliminates the need for knowledge of the imaging system spectral response. Through an appropriate choice of the BPF centre energy, a range of absorber compositions or a single absorber with different surface morphologies, such as planar and textured, can be imaged, all without the need for additional detection optics. The feasibility of this s-BPF method is first validated. The relative error in iV$_{OC}$ is determined to be ≤1.5%. The method is then demonstrated on device stacks with two different perovskite compositions commonly used in single-junction and monolithic tandem solar cells