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In this work the dependence of the slow boron-oxygen defect formation rate on excess carrier density is examined in p-type Cz silicon. In order to examine behavior at elevated temperatures simple models are developed to simulate the injection-level dependent lifetime of samples at a range of temperatures and active defect concentrations. These models are then verified against experimental data. Based on these models it is possible to clearly observe a quadratic dependence of defect formation rate upon total hole concentration over a range of temperatures. The implications of a hole (and hence excess carrier (Δ n )) dependent defect formation rate, combined with the temperature dependence of defect activity are then discussed. It is demonstrated how a dependence of formation rate upon hole concentration increases the rate of defect formation and mitigation of carrier-induced degradation in samples with reduced saturation current density during anneals at elevated temperatures and illumination intensities. [ABSTRACT FROM AUTHOR]

Photovoltaic devices operate under a wide range of temperature and illumination conditions. While the temperature coefficients (TC) of crystalline silicon solar cells have been well-studied, there have been only a few investigations regarding the effect of illumination on TCs. In this study, the TCs of the main electrical parameters of various silicon solar cell technologies are first determined. The illumination spectrum dependence of the TC of the short-circuit current and the illumination intensity dependence of the TC of the open-circuit voltage are then investigated. For the latter investigation, a custom-designed temperature-dependent Suns-V OC system is used. It is found that: (1) the TC of the short-circuit current measured using an A-rated spectrum may differ from the TC measured using the AM1.5G spectrum by up to 30%, (2) the TC of the open-circuit voltage of all technologies at 0.001 suns approximately doubles compared to at one-sun, and (3) silicon heterojunction cells seem to have the overall best TC performance at medium to high intensities. [Display omitted] • A-rated I-V testers may still produce inaccurate current temperature coefficients. • Silicon solar cell voltages are more temperature-sensitive at lower illuminations. • Heterojunction cells suffer the least from higher temperatures above 0.2 suns. • Diode saturation currents reflect recombination reduction at higher temperatures. • Impacts for yield estimation in the field and tandem current matching outlined. [ABSTRACT FROM AUTHOR]

The emitter sheet resistance is an essential parameter impacting the efficiency of silicon solar cells with diffused layers. Conventional measurement methods of this parameter either require electrical contacts or are impacted by the bulk resistivity of the measured samples. In this study, a novel method based on the combination of eddy-current conductance and photoluminescence imaging is developed for a contactless determination of the emitter sheet resistance. Numerical simulation is used to establish the correlation between the photoluminescence profile and the sum of the emitter and bulk resistance. Together with eddy-current conductance measurements, the emitter sheet resistance and bulk resistance can be separated. The accuracy of the method is validated experimentally, and its uncertainty is investigated. The contactless nature of the developed method makes it attractive for inline inspection of diffused layers in solar cell manufacturing. • A fully contactless method for determining emitter sheet resistance is developed. • Good agreement between the proposed method and four point probe is achieved over a wide range of emitter sheet resistance. • After given solar cell processing steps, the developed method is resilient to the variation of other sample properties. [ABSTRACT FROM AUTHOR]

Recently, it has been shown that the investigation of minority carrier traps (traps) is a useful method to study defects in silicon wafers. In this paper, we report the presence of traps in p-type multicrystalline silicon with a photoconductance decay time constant of 1.9 ± 0.4 s (at 30 °C). It is shown that the density of traps is significantly reduced after firing. However, this reduction in trap density is metastable, and it recovers by short dark annealing at 100 °C or after several days of storage at room temperature. In contrast, laser annealing is shown to eliminate the traps in fired wafers, while no change in the trap density is observed for wafers that have not been fired. Further dark annealing of those wafers does not recover the traps, suggesting that this trap annihilation is not reversible. • Minority carrier trap with a very long PCD time constant is detected in mc-Si wafers. • Firing temporarily reduces the trap density. • Firing generates metastable hydrogen-related complex in the bulk. • Light soaking reduces the trap density permanently. • Traps do not seem to be connected with LeTID. [ABSTRACT FROM AUTHOR]

The performance of high-efficiency silicon solar cells is limited by the presence of bulk defects. Identification of these defects has the potential to improve cell performance and reliability. The impact of bulk defects on minority carrier lifetime is commonly measured using temperature- and injection-dependent lifetime spectroscopy and the defect parameters, such as its energy level and capture cross-section ratio, are usually extracted by fitting the Shockley-Read-Hall equation. We propose an alternative extraction approach by using machine learning trained on more than a million simulated lifetime curves, achieving coefficient of determinations between the true and predicted values of the defect parameters above 99%. In particular, random forest regressors, show that defect energy levels can be predicted with a high precision of ±0.02 eV, 87% of the time. The traditional approach of fitting to the Shockley-Read-Hall equation usually yields two sets of defect parameters, one in each half bandgap. The machine learning model is trained to predict the half bandgap location of the energy level, and successfully overcome the traditional approach's limitation. The proposed approach is validated using experimental measurements, where the machine learning predicts defect energy level and capture cross-section ratio within the uncertainty range of the traditional fitting method. The successful application of machine learning in the context of bulk defect parameter extraction paves the way to more complex data-driven physical models which have the potential to overcome the limitation of traditional approaches and can be applied to other materials such as perovskite and thin film. [ABSTRACT FROM AUTHOR]

To address the growing demand for photovoltaic inspection, an increasing volume of photoluminescence, electroluminescence, and infrared image datasets is being produced for research and analysis. Most of these images exhibit perspective distortions, which introduce challenges in subsequent analysis, such as defect detection and classification. Hence, distortion correction is required during the preprocessing stage. However, manually correcting each dataset to eliminate distortions is labour-intensive. This paper addresses this issue by developing a convolutional neural network model to estimate the camera parameters of yaw, pitch, and roll. A heuristic method was referenced as a comparative benchmark, demonstrating that the developed deep learning-based approach is equally accurate and significantly faster. The findings underscore the potential of deep learning techniques in automating and refining image analysis in photovoltaic diagnostics, offering substantial improvements over traditional methods in terms of speed and scalability. • Trained a deep learning model to correct module images for better defect detection. • The model predicts the camera angles and then applies suitable corrections. • It demonstrates effective correction of severe distortions in real-world images. • The model outperforms current methods in both accuracy and speed. [ABSTRACT FROM AUTHOR]

C60 is a widely used electron selective material for p–i–n perovskite cells, however, its energy level does not match well with that of a wide‐bandgap perovskite, resulting in low open‐circuit voltage (VOC) and fill factor (FF). To overcome this issue, ultra‐thin LiF has been widely used as an interlayer between C60 and perovskite layers facilitating efficient electron extraction but resulting in instability. In this work, the use of a piperidinium bromide (PpBr) is reported as an interlayer between C60 and perovskite, and the interlayer further is optimized by introducing an additional oxygen atom on the opposite side of the NH2+. This results in morpholinium bromide (MLBr) with increased dipole moment. Because of this, MLBr is highly effective in minimizing the energy band mismatch between perovskite and C60 layer for electron extraction while at the same time passivating defects. The champion single junction 1.67 eV MLBr solar cell produced a PCE of 21.9% and the champion monolithic MLBr perovskite‐Si tandem cell produced a PCE of 28.8%. Most importantly, both encapsulated MLBr and PpBr devices retain over 97% of their initial efficiency after 400 thermal cycles (between −40 and 85 °C), twice the number of cycles specified by the International Electrotechnical Commission (IEC) 61215 photovoltaic module standard. [ABSTRACT FROM AUTHOR]

While interfacial and grain‐boundary passivation presently attract enormous research interest for perovskite solar cells (PSCs), the improvement of Cs‐(FAPbI3)X(MAPbBr3)Y bulk quality still lacks systematical study, especially for constructing polycrystalline layers in planar configurations. Here, a DMSO‐molecule‐process for improving the quality of Cs‐(FAPbI3)0.85(MAPbBr3)0.15 is developed, where the molar ratio of precursors, the kind of anti‐solvents, and speed‐time profiles are found critical. The optimized treatment significantly enhanced the crystal orientation, grain size, surface roughness, photo‐response, carrier lifetime, and contact potential difference of absorbers. Cs‐(FAPbI3)0.85(MAPbBr3)0.15 absorbers also present superior charge transport, as well as reduced carrier recombination and decreased trap densities via DMSO‐molecule‐control, enabling performance improvement on both long‐term stability and photovoltaic parameters of 1 cm2 PSCs. Champion planar cells demonstrated a power conversion efficiency (PCE) of 21.07% (0.159 cm2) and PCE of 19.4% (1 cm2) with negligible hysteresis. Moreover, 1 cm2 devices retained 90% of initial PCE after aging 50 days in ambient air. DMSO‐molecule‐control is demonstrated to enhance the morphological and electronic qualities of Cs‐(FAPbI3)0.85(MAPbBr3)0.15 absorbers, thus increasing the efficiency (reaching 19.4%) and boosting the long‐term stability (retaining 90% of the initial efficiency after 50 days in ambient air) of 1 cm2 sized planar perovskite solar cells. [ABSTRACT FROM AUTHOR]

Over the past five years, there has been a significant increase in both the intensity of research and the performance of crystalline silicon devices which utilize metal compounds to form carrier‐selective heterocontacts. Such heterocontacts are less fundamentally limited and have the potential for lower costs compared to the current industry dominating heavily doped, directly metalized contacts. A low temperature (≤230 °C), TiOx/LiFx/Al electron heterocontact is presented here, which achieves mΩcm2 scale contact resistivities ρc on lowly doped n‐type substrates. As an extreme demonstration of the potential of this heterocontact, it is trialed in a newly developed, high efficiency n‐type solar cell architecture as a partial rear contact (PRC). Despite only contacting ≈1% of the rear surface area, an efficiency of greater than 23% is achieved, setting a new benchmark for n‐type solar cells featuring undoped PRCs and confirming the unusually low ρc of the TiOx/LiFx/Al contact. Finally, in contrast to previous versions of the n‐type undoped PRC cell, the performance of this cell is maintained after annealing at 350–400 °C, suggesting its compatibility with conventional surface passivation activation and sintering steps. An electron‐selective TiOx based heterocontact is developed and trialed as a dopant‐free partial rear contact in high efficiency silicon solar cells. This cell not only reaches an efficiency of above 23% but also maintains its performance after a short anneal at 400 °C—setting new benchmarks of performance and thermal stability for this cell architecture. [ABSTRACT FROM AUTHOR]

Charge carrier lifetime is an important parameter for semiconductor materials. This study proposes a dynamic calibration method for injection‐dependent carrier lifetime measurements. This method is based on the comparison between lifetime measurements under quasi‐steady‐state and non‐quasi‐steady‐state conditions. The proposed method is first demonstrated by numerical simulation. Experimental data are subsequently used to compare the proposed method with conventional calibration methods, demonstrating good agreement between the methods. Furthermore, the calibration method is found to be much less sensitive to measurement noise. When applied to photoluminescence‐based carrier lifetime measurements, the proposed method also provides the net bulk doping concentration. [ABSTRACT FROM AUTHOR]

Plasma enhanced chemical vapor deposition (PECVD) is ubiquitously used in the crystalline silicon photovoltaics industry to deposit surface passivation and anti-reflection coatings. Aluminum oxide deposited by PECVD is becoming an increasingly common rear surface passivation layer, due to the growing market share of solar cells with partial rear contacts, such as the passivated emitter and rear solar cell. In this study, we use in - situ monitoring to investigate the correlation between the PECVD plasma properties and the resulting aluminum oxide film properties. Although no linear correlation between the density of the constituent radicals (aluminum, oxygen, and hydrogen) in the plasma and the surface passivation quality was observed, we did identify optimum processing conditions for a high quality surface passivation layer using in - situ plasma monitoring. This study also highlights the limited knowledge that currently exists within the photovoltaic community regarding plasma characterization and its impact on device performance. [ABSTRACT FROM AUTHOR]

It is compelling to eliminate inactive phosphorus in industrial POCl 3 diffused emitters for high efficiency silicon solar cells. Several approaches were reported to significantly reduce inactive phosphorus in the literature. However, the underlying physical mechanisms are not fully understood. In this work, we conduct a systematic investigation and fabricate eight emitters involving two POCl 3 :O 2 ratios at pre-deposition and both inert and oxidising scenarios at drive-in. Characterization techniques such as secondary ion mass spectrometry and X-ray photoelectron spectroscopy are carried out with an emphasis on the phosphosilicate glass. To provide a consistent interpretation of our results and those in the literature, we suggest a probable reaction, “free phosphorus oxidation”, as the dominant mechanism to unveil the role and impact of oxygen during POCl 3 diffusion. We further propose that various industrial POCl 3 emitters can be fabricated inactive phosphorus free without drive-in or a pre-grown oxide. Among the eight emitters, three emitters are free from inactive phosphorus with a sheet resistance range from 65 to 140 Ω/□, featuring a surface doping from 1 × 10 20 to 3 × 10 20 cm −3 and a remarkably low emitter saturation current density down to 51 fA/cm 2 . [ABSTRACT FROM AUTHOR]

Luminescence imaging is widely used to identify spatial defects and extract key electrical parameters of photovoltaic devices. To reliably identify defects, high‐quality images are desirable; however, acquiring such images implies a higher cost or lower throughput as they require better imaging systems or longer exposure times. This study proposes a deep learning‐based method to effectively diminish the noise in luminescence images, thereby enhancing their quality for inspection and analysis. The proposed method eliminates the requirement for extra hardware expenses or longer exposure times, making it a cost‐effective solution for image enhancement. This approach significantly improves image quality by >30% and >39% in terms of the peak signal‐to‐noise ratio and the structural similarity index, respectively, outperforming state‐of‐the‐art classical denoising algorithms. [ABSTRACT FROM AUTHOR]

We investigate the limitations of two-photon absorption time-resolved photoluminescence to measure the low-injection bulk lifetime of different semiconductor materials under varying surface recombination. The excitation source is assumed to be a sub-bandgap pulsed laser and the localized absorption and carrier generation was modeled using a focused TEM00 Gaussian beam under the assumption of diffraction-limited performance. The subsequent carrier kinetics were simulated by applying the finite-difference time-domain method to the continuity equation. Three typical semiconductor materials were modeled: direct bandgap low-mobility material (such as CZTS), direct bandgap high mobility (such as GaAs), and indirect bandgap high mobility (such as float-zone silicon). The extracted effective lifetime as a function of surface recombination velocity was compared to the bulk lifetime and the effective lifetime calculated using an analytical 1D approximation. For the direct bandgap materials, focusing inside the material yields an effective lifetime within a few percent of the bulk lifetime, regardless of the surface recombination velocity, while for excitation close to the surface it is up to 30% lower than the bulk lifetime at high surface recombination velocities (>104 cm/s). For the indirect bandgap material, the effective lifetime is dominated by the surface, making the bulk lifetime inaccessible, even at surface recombination velocities of 100 cm/s. Finally, we use the 1D approximation to find under what conditions the bulk lifetime can be extracted by this method and determine that both the bulk diffusion length and the product of the bulk lifetime and surface recombination velocity must be much less than twice the device thickness. [ABSTRACT FROM AUTHOR]

Light-induced degradation (LID) in boron (B)-doped Czochralski (Cz) silicon wafers has impacted commercial p -type silicon solar cells for decades. Substitution of boron with gallium (Ga) or (to a lesser extent) indium (In) has been suggested as a method to tackle this problem since Ga- and In-doped Cz wafers were shown to be less prone to LID. Although less prone to LID, several studies have reported some LID in these materials. In this study, LID in Ga- and In-doped Cz wafers is investigated. First, it is shown that LID is present in both materials. The degradation has two stages (fast and slow) for Ga-doped wafers and one stage for In-doped wafers. By performing the degradation at different temperatures, the activation energy of the defect formation is determined to be 0.74 ± 0.10 eV for the slow step in Ga-doped and 0.91 ± 0.15 eV for In-doped wafers. We then investigate defect deactivation with dark annealing. Both Ga- and In-doped wafers demonstrate a two-stage defect deactivation. Similar to defect formation, the defect deactivation activation energies are determined and reported. Finally, the focus is shifted to investigating the degradation mechanism in Ga-doped wafers, since they are currently the dominating wafer substrate for photovoltaic applications. It is shown that a three-state mechanism ("annealed", "degraded", and "stabilised"), similar to boron-oxygen (BO)-related defects, can explain their degradation. It seems the four-state model, suggested for the light- and elevated temperature-induced degradation, is not suitable for describing the degradation in Ga-doped Cz wafers. • Ga-doped Cz wafers have a two-stage LID process. • A two-stage defect deactivation is observed for both Ga- and In-doped wafers. • The activation energy of defect formation and deactivation for Ga- and In-doped wafers is measured. • A three-state model is presented to describe LID in Ga-doped wafers. [ABSTRACT FROM AUTHOR]

A novel, camera‐based method for direct implied open‐circuit voltage (iVOC) 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's 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 iVOC 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. [ABSTRACT FROM AUTHOR]

Photovoltaic module performance in the field is strongly dependent on the optical properties of its component layers and the temperature dependencies of these properties. However, despite their importance, the temperature dependencies of the optical properties of many photovoltaic module components appear to have not been characterised. Hence, the assumptions regarding their optical stabilities at various temperatures have not been verified. In this study, a temperature-dependent spectrophotometry method is developed to enable this verification. The temperature dependencies of the optical properties of silicon nitride, ethylene vinyl acetate (EVA), and backsheets are characterised, and their impacts on module operations are quantified via ray-tracing simulations. It is concluded that (1) silicon nitride anti-reflection coatings are optically stable between room temperature and 85 °C, and (2) several temperature dependencies exist at different wavelengths in both EVA and backsheets, however, they do not have a significant impact on the module operation. • Temperature-dependent spectrophotometry system developed and presented. • Silicon nitride anti-reflection coating optically stable up to at least 84 °C. • EVA refractive index reduces by ∼0.02 at 64 °C; no changes to module performance. • Backsheets reflect <1 % more at 70 °C; no impact on module operation. [ABSTRACT FROM AUTHOR]

This study introduces a pioneering machine learning (ML)-based methodology to characterise two-level defects in the bulk of silicon wafers. Bulk defects have a critical impact on the efficiency of silicon solar cells. By identifying the specific parameters of these defects, namely, their energy levels and capture cross-sections, researchers can devise strategies to mitigate their effects. It is often assumed that bulk defects are single-level defects following the Shockley-Read-Hall recombination statistics. However, two-level defects or even multi-level defects are common as well. At present, it is challenging to distinguish between single-level defects and two-level defects, and to extract the parameters of a two-level defect. This study proposes an ML-based approach to distinguish between one- and two-level defects based on temperature- and injection-dependent lifetime spectroscopy with an accuracy above 90 %. Furthermore, if the defect is identified as a two-level defect, this study presents another ML method to extract its defect parameters, with a correlation coefficient above 0.9 for the energy levels. • TIDLS reveals critical insights into defects that limit performance in photovoltaic (PV) devices. • Two-level defects are common in silicon (Si) wafers, but traditional methods often treat them as single-level defects • We propose using ML to classify single- and two-level defects and extract two-level defect parameters from TIDLS measurements. • The ML models were validated against both simulations and experimental data. [ABSTRACT FROM AUTHOR]

Accurate and efficient characterisation techniques are essential to ensure the optimal performance and reliability of photovoltaic devices, especially given the large number of silicon solar cells produced each day. To unlock valuable insights from the amount of data generated during the characterisation process, researchers have increasingly turned to different machine learning (ML) techniques. In this review, advances in ML applications for silicon photovoltaic (PV) characterisation from 2018 to 2023, including device investigation, process optimisation, and manufacturing line assessment are examined. Additionally, studies on deep learning techniques for luminescence-based measurements, such as defect classification, detection, and segmentation, which can help manufacturers identify potential reliability issues are explored. Despite the abundance of ML applications, it is emphasised that the lack of both publicly available datasets and the uniform use of ML metrics poses a significant challenge for researchers to benchmark their frameworks and achieve consistent and accurate results. In advancing ML applications in PV, future research should focus on improving model interpretability, balancing speed and accuracy, understanding computational demands, and integrating niche applications into a unified framework. Lastly, industry involvement and interdisciplinary collaboration among experts in solar energy, data science, and engineering are vital in tailoring ML solutions and enhancing innovation in addressing various challenges in the PV field. • Recent ML applications in Si PV characterisation from 2018 to 2023 are presented. • Key challenges include scarce public datasets and inconsistent evaluation metrics. • Future research should focus on improving model interpretability. • Crucial considerations are speed vs accuracy trade-off and integration to a unified framework. • Interdisciplinary collaboration and industry involvement will enhance ML applications in PV. [ABSTRACT FROM AUTHOR]

The dissociation of FeB pairs in p‐type silicon under injection is often explained by the charge state change of interstitial Fe (Fei) from positive to neutral. It is also sometimes interpreted as a recombination‐enhanced defect reaction (REDR) mechanism. The charge effect and the REDR have fundamentally different impacts on the dissociation/association reactions: the former changes the concentration of Fei+, whereas the latter changes the reaction rate constants. Herein, the two effects are investigated and compared through measuring and analyzing the dynamics of the reactions. The results confirm that the dissociation of FeB under carrier injection cannot be purely attributed to the change of charge states. The extracted dissociation/association rate constant ratio shows an approximately linear dependence on the recombination rate on each FeB pair, indicating the REDR effect. The results allow the two effects to be directly compared, highlighting the dominant role of the REDR effect in dissociating the pairs. [ABSTRACT FROM AUTHOR]

Efficient monitoring of solar cell performance in high-volume production lines is crucial to ensure consistency and stability. However, this task faces challenges as many manufacturing processes introduce efficiency variations. This study proposes a method, based on lag sequential analysis, to monitor and evaluate these variations. The proposed method is based on the analysis of time-series electrical measurements (such as open-circuit voltage, short-circuit current, fill factor, and efficiency) to identify the degree of randomness, trace process-induced batch variations, and assess line stability. Real-time application of the method can flag anomalies. Furthermore, the suggested method can be extended to image analysis by extracting relevant features from time-series luminescence images, enabling the study of whether cell defects in manufacturing exhibit a random pattern or possess distinguishable characteristics. With its various possible applications, the proposed method has significant potential in enhancing solar cell production line monitoring systems, enabling early identification of production issues and process improvement by manufacturers. • An alternative method to monitor variations in solar cell production lines has been developed. • Random variations can be identified and line stability can be assessed with the approach. • Real-time application can detect anomalies. • The extension of the method to image analysis allows for the temporal analysis of cell defects. • The proposed technique is also applicable to other types of production lines. [ABSTRACT FROM AUTHOR]

The sub-bandgap photoluminescence (PL) arising from dislocations in crystalline silicon (known as "D-lines") has been studied for over half a century. However, many properties of the D-lines such as the defect parameters and the underlying recombination mechanism are poorly understood. In this study, we perform both temperature-dependent and injection-dependent hyperspectral mapping and apply this to a cast-mono silicon sample held at room-temperature and above. We parameterize the energy levels and defect densities of the D-lines in this sample. We also demonstrate for the first time that the D1 line in silicon wafers originates from the donor–acceptor pair recombination mechanism. • Show for the first time that the D1 dislocation luminescence peak in silicon originates from donor–acceptor pair recombination. • Development of a unique method to determine spatially-resolved defect parameters of radiative defects. • Parameterization of the defect energy of the D1 line. [ABSTRACT FROM AUTHOR]

Silicon dioxide (SiO 2) has played a critical role in the development of high-efficiency silicon (Si)-based photovoltaic devices. Recently, it has experienced a renaissance as an interlayer in many of the new contact passivating structures. Studies have extensively investigated the recombination process at the Si–SiO 2 interface, however, only little is known about the impact of temperature on the surface recombination. In this study, we investigate the recombination at the Si–SiO 2 interface by varying the temperature, excess carrier density, and dielectric fixed charge. An improved lifetime is observed with increasing temperature. A forming gas anneal is used to improve the passivation quality, however, at higher temperatures, the hydrogenated interface passivation degrades due to increased surface state density. The degradation is stronger for corona-charged SiO 2 , due to the instability of the corona charge within the dielectric. Using the extended Shockley-Read Hall recombination model, the Si–SiO 2 interface defects' parameters are extracted. Most importantly, we determine the value and the temperature-dependence of the capture cross-sections at this interface. Silicon dioxide (SiO 2) continues to play an important role in the development of current photovoltaic devices, like passivating contact cells. This study investigates the recombination at this interface by varying temperature, injection-level, and dielectric charge. An improved lifetime is observed with increasing temperature, indicating possible benefits under high temperatures, therefore providing advantages when operating in the field. Using the extended Shockley-Read-Hall recombination model, we determine this interface defects' parameters, and most importantly the temperature-dependency of its capture cross-sections. Image 1 • Temperature and injection dependent lifetime measurements are used to study Si–SiO 2 interface. • SiO 2 layer is expected to benefit from high operational temperatures. • A modelling method is developed to extract the interface defects parameters. • The temperature-dependency of the capture cross-sections at Si–SiO 2 interface are determined. [ABSTRACT FROM AUTHOR]

Halide perovskite‐based photovoltaic (PV) devices have recently emerged for low energy consumption electronic devices such as Internet of Things (IoT). In this work, an effective strategy to form a hole‐selective layer using phenethylammonium iodide (PEAI) salt is presented that demonstrates unprecedently high open‐circuit voltage of 0.9 V with 18 µW cm−2 under 200 lux (cool white light‐emitting diodes). An appropriate post‐deposited amount of PEAI (2 mg) strongly interacts with the perovskite surface forming a conformal coating of PEAI on the perovskite film surface, which improves the crystallinity and absorption of the film. Here, Kelvin probe force microscopy results indicate the diminished potential difference across the grain boundaries and grain interiors after the PEAI deposition, constructing an electrically and chemically homogeneous surface. Also, the surface becomes more p‐type with a downshift of a valence band maximum, confirmed by ultraviolet photoelectron spectroscopy measurement, facilitating the transport of holes to the hole transport layer (HTL). The hole‐selective layer‐deposited devices exhibit reduced hysteresis in light current density–voltage curves and maintain steadily high fill factor across the different light intensities (200–1000 lux). This work highlights the importance of the HTL/perovskite interface that prepares the indoor halide perovskite PV devices for powering IoT device. [ABSTRACT FROM AUTHOR]

• The most critical factors for thermally stable AlO x layer are discovered. • The most significant factor for high quality surface passivation is discovered. • Stoichiometry of the PECVD aluminum oxide layer is firstly reported. • Depth profile and the behaviour of a hydrogen in AlO x is firstly reported. • STEM reveals the c-Si/AlO x interface which affects surface passivation. Plasma-enhanced chemical-vapor deposition systems are commonly used to deposit aluminum oxide (AlO x) on silicon wafers in the production of silicon solar cells. This study investigates the impact of the deposition conditions on the obtained surface passivation quality of p -type wafers. It is the first to investigate the impact of all the five main process parameters. The ratio between the microwave power and the total gas flow rate is identified as a critical condition to form thermally stable layers. We find that the most significant parameter for high quality surface passivation is the flow rate ratio of nitrous oxide (N 2 O) to tri-methyl-aluminum (TMA). Higher flow rate ratio ([N 2 O]/[TMA]) is required to achieve better passivation for fired wafers, whereas lower ratio is preferred when the firing process is not permissible. Elastic-recoil detection analysis reveals that the gas flow rate ratio has a significant impact on the likely direction of hydrogen released from the layer during firing (either to the interface with the silicon wafer or to the environment). Surprisingly, the atomic concentration of aluminum and oxygen is found to be almost stoichiometric regardless of the wide range of the gas flow rate ratios studied in this paper. [ABSTRACT FROM AUTHOR]

Abstract In this work, we investigate the use of advanced hydrogenation and low-temperature diffusion processes (a 3 h 700 °C process after emitter diffusion) for the electrical neutralization of laser-induced defects for laser doped and grooved solar cells. Despite the laser doping and grooving (LDG) process being performed before silicon nitride passivation to avoid thermal expansion mismatch between the silicon and the silicon nitride layer, some crystallographic defects are still formed during the process. The application of a low-temperature diffusion process increases implied open circuit voltages by 14 mV, potentially due to phosphorus diffusion of dislocated regions induced during laser processing. Laser hydrogenation is shown to be capable of passivating the majority of the remaining laser-induced defects. Over 1% absolute improvement in efficiency is achieved on cells with a full area aluminum back surface field. Preliminary results with minimal optimization demonstrate efficiencies of over 19% with a full area Al back contact cell. The potential to achieve much higher voltages when used with a passivated rear is also demonstrated. Highlights • A new laser grooving process that simultaneously dopes the groove walls has been developed. • The novel process has demonstrated the ability to form narrow grooves of only 3–5 µm width in preparation for metal contact formation. • The application of a low-temperature diffusion process significantly increases the implied open circuit voltages by 14 mV. • Laser hydrogenation is shown capable of passivating the majority of the remaining laser-induced defects. • Over 1% absolute improvement in efficiency is achieved. • Preliminary results demonstrate efficiencies of over 19% on industrial full area aluminum back surface field solar cells. [ABSTRACT FROM AUTHOR]

Abstract In the past few years, carrier-induced degradation (CID) in p- type multicrystalline silicon (mc-Si) has been receiving significant attention. Recently, it has been reported that this material is also susceptible to degradation under dark anneal at moderate temperatures. In the first part of this study, we investigate the impact of the dark anneal temperature on mc-Si wafers. We identify both degradation and regeneration of the effective lifetime, where higher temperatures lead to faster rates and lower degradation extent. A fitting model is developed to describe the kinetics of these processes, where the degradation and regeneration process are assumed to happen simultaneously. An Arrhenius analysis of the degradation and regeneration rates, extracted from the proposed model, determines activation energies of 1.08 ± 0.05 eV for the degradation process and 1.11 ± 0.04 eV for the regeneration one. An improvement of the minority carrier effective lifetime of up to 40% is observed after a long dark anneal process. This improvement is associated with enhancement of both the bulk and surface passivation. Temperature- and injection-dependent lifetime spectroscopy measurements indicate that the recombination parameters of the associated defect causing the degradation in the dark are similar to those determined for the CID-related defect; therefore, it seems both defects have a similar nature. In the second part of the study, the effect of the illumination intensity at room temperature on the degradation/regeneration is studied. Surprisingly, an improvement in the effective lifetime is found, followed by a very slow degradation. The proposed model is found to be suitable to fit these measurements. The extracted rates suggest that the observed behavior is due to a regeneration that is much faster than the degradation. The reported findings provide new insights into CID in p -type mc-Si that will help improve understanding and assist in developing mitigation solutions. Highlights • The temperature dependence of the degradation of p- type mc-Si anneal in the dark. • A new model to describe the degradation and regeneration of mc-Si due to CID. • The activation energies of the degradation and regeneration processes are extracted. • TIDLS was used to identify the SRH parameters of the dark anneal related defect. • The effect of illumination at room temperature on mc-Si wafers is studied. [ABSTRACT FROM AUTHOR]

Both buried contact solar cells (BCSC) and laser doped selective emitter (LDSE) solar cells have achieved considerable success in large-scale manufacturing. Both technologies are based on plated contacts. High metal aspect ratios achieved by BCSC allow low shading loss while the buried metal contacts in the grooves provide good contact adhesion strength. In comparison, although the LDSE cell achieves significantly higher efficiencies and is a much simpler approach for forming the selective emitter region and self-aligned metal plating, the metal adhesion strength falls well short of that achieved by the BCSC. Recent studies show that plated contacts based on the latter can be more durable than screen-printed contacts. This work introduces a new concept of laser doping with grooving to form narrow grooves with heavily doped walls in a simultaneous step, with the self-aligned metal contact subsequently formed by plating. This process capitalizes on the benefits of both BCSC and LDSE cells. The laser-doped grooves are only 3–5 µm wide and 10–15 µm deep; the very steep walls of these grooves remain exposed even after the subsequent deposition of the antireflection coating (ARC). This unique feature significantly reduces the formation of laser-induced defects since the stress due to the thermal expansion mismatch between the ARC and silicon is avoided. Furthermore, the exposed walls allow nucleation of the subsequent metal plating. This novel structure also benefits from greatly enhanced adhesion of the plated contact due to it being buried underneath the silicon surface in the same way as the BCSC. Cell efficiencies over 19% are achieved by using this technology on p -type Czochralski (Cz) wafers with a full area aluminum (Al) back surface field (BSF) rear contact. It is expected that much higher voltages and consequently higher efficiencies could be achieved if this technology is combined with a passivated rear approach. [ABSTRACT FROM AUTHOR]

Luminescence imaging is a fast and non-destructive method to spatially resolve non-uniform electrical properties of solar cells. The spatial resolution of these images determines the smallest identifiable features. The higher the spatial resolution of an image, the better the capability to detect small defects. However, high-resolution cameras with high near-infrared light sensitivity that are suited to luminescence imaging of crystalline silicon are often expensive. In this study, we present a method, based on deep learning, that enhances the spatial resolution of luminescence images computationally with minimal cost. We also demonstrate the ability to overcome noise which is inevitable in any imaging system. This approach provides a simple and promising path toward reducing the cost of luminescence imaging systems and enhancing the capability of existing systems. • A neural-network based approach (ESRGAN) was used to solve the issue of poor spatial resolution in luminescence imaging. • ESRGAN outperforms the traditional bicubic interpolation algorithm, for enhancing the spatial resolution of EL images. • New image features, which are not present in the training dataset, were successfully enhanced and image noise was supressed. [ABSTRACT FROM AUTHOR]

This study assesses and improves the accuracy of commonly used expressions for the fill factor (FF). Parameters that could affect the accuracy of the revised expressions are investigated. Empirical coefficients of the commonly used analytical expressions are first recalculated using a modified fitting approach. Although the predictions of the revised expressions perfectly match the results of theoretical one-diode model simulations, gaps are observed when compared with actual measurements. The different impacts of unaccounted factors in the expressions are then explored. It is shown that adjusting the ideality factor or considering edge recombination improves the accuracy of the predictions. Moreover, the expressions can slightly overestimate the FF of cells with non-uniform implied open-circuit voltage distribution. As methods to extract electrical parameters from luminescence images continuously improve, the findings of this study can aid in developing techniques for extracting FF from luminescence images of industrial solar cells. • The fill factor (FF) of solar cells can be derived from empirical expressions. • The expressions are improved for modern industrial solar cells. • With ideality factor or edge recombination, FF predictions are more accurate. • Non-uniform implied open-circuit voltage tends to overestimate FF. [ABSTRACT FROM AUTHOR]

Extracting the parameters, energy level and electron-to-hole capture cross-section ratio, of efficiency-limiting bulk defects in silicon solar cells is a critical step in identifying those defects and potentially eliminating their impact. Typically, this is achieved on specially prepared test structures. However, in some cases, this is not possible, especially in mass production lines when only completed solar cells are available. In this study, a method that is based on temperature-dependent Suns-V oc measurements is introduced to extract the defect parameters in metalized solar cells. The method is validated by comparing the parameters of the boron-oxygen-related defect extracted from cells and those extracted from wafers using the commonly used temperature- and injection-dependent lifetime spectroscopy. It is shown that this method has the benefit of a more accurate lifetime at low injection levels compared with photoconductance-based lifetime measurement since it is not impacted by minority carrier traps. The proposed technique is then applied to determine the parameters of the defect causing light-induced degradation in gallium-doped silicon solar cells. We determined an energy level, with respect to the intrinsic level, of −0.26 ± 0.04 eV and a capture cross-section ratio of 34 ± 2 for this defect. Finally, a sensitivity analysis is performed by considering the system's limited measurement temperature range. The findings demonstrate the potential of the temperature-dependent Suns-V oc method as a fast and easy-to-apply method for defect characterization in metalized cells. • Parameters of bulk defects in cells can be extracted using Sun-V oc (T) method. • The method is validated by extracting the parameters of BO-related defects. • The parameters of LID-related defects in Ga-doped cells are extracted with the method. • Sensitivity analysis is performed to assess the limitations of the method. [ABSTRACT FROM AUTHOR]

The temperature coefficient (TC) is a critical figure of merit to accurately evaluate the performance of solar cells at various operating temperatures, and hence, enabling the comparison between different cell technologies. Recently, tunnel oxide passivated contact (TOPCon) solar cells have shown outstanding cell performance. They are likely to be adopted in production lines and deployed in the field in the near future. Therefore, knowledge of their TCs and insights into their performance at realistic operating temperatures are of significant interest. In this study, we investigate the temperature dependence of the performance of TOPCon solar cells and quantify their TCs. To gain better understanding regarding the temperature-dependent behavior of their performance, the passivation quality and the contact resistivity of polysilicon (poly-Si) passivating contacts as a function of temperature are investigated. Although an improvement of the passivation quality of these contacts with increasing temperature has been observed, it seems that this improvement weakly impacts on the open-circuit voltage TC. The cell performance at elevated temperatures is dominated by the drop in the open-circuit voltage, associated with the intrinsic carrier concentration related to band gap narrowing. The fill factor TC (TC FF) is superior to those of other cell structures reported in the literature. We attribute this favorable TC FF to the fact that some of the fill factor losses are compensated by the decrease of contact resistivity of the poly-Si passivating contacts at elevated temperatures. The relative TC of the cell efficiency of the investigated TOPCon cells is comparable to the TC of silicon heterojunction cells and it is superior to those of cell structures without passivating contacts. Moreover, we found that the investigated solar cell is more sensitive to temperature variation at lower illumination intensities. • TC FF of TOPCon cells is superior to those of other cell structures. • Part of FF losses is compensated by the decrease of ρ c of the polysilicon passivating contacts at elevated temperatures. • TC η of TOPCon cells is better than those of cell structures without passivating contacts. • The investigated cell is more sensitive to temperature variation at lower illumination intensities. [ABSTRACT FROM AUTHOR]