Outdoor Organic Photovoltaic module characteristics; benchmarking against other PV technologies for performance, calculation of Ross coefficient and outdoor stability monitoring

A comparison of performance parameters for first, second and third generation PV technologies has been conducted. Organic photovoltaic (OPV) modules displayed markedly different outdoor performance characteristics to other PV technologies owing to the positive temperature coefficient, lower thermal mass and response under low light conditions. The linear relationship between irradiance and module temperature rise above ambient is studied, leading to calculation of values for the Ross coefficient for OPV modules. OPVs are shown to possess a lower Ross coefficient than poly-Si, due to the lower absorption of infrared radiation. The effect of wind speed on the Ross coefficient is also investigated, showing the effect that module structure has upon outdoor PV performance, with the OPV module cooling quicker under windy conditions than the poly-Si due to a lower thermal mass. A long term stability study on OPV modules with a silver nanowire-zinc oxide (AgNW-ZnO) composite front electrode has showed two phases of degradation: a short initial burn-in with significant drops in performance; followed by stabilisation and degradation progressing at a much slower rate. During the burn-in period the modules showed diurnal reversible degradation in the short circuit current (ISC), whereas open circuit voltage (VOC) and fill factor (FF) show a steady decline. The reversible degradation is assumed to be related to the desorption of oxygen from the ZnO layer during the day due to UV excitation, leading to an increase in trap formation and a drop in current generation capacity, followed by re-adsorption of the oxygen overnight

Multi stress testing of OPV modules for accurate predictive ageing and reliability predictions

Organic photovoltaic (OPV) degradation remains a complex challenge and previous studies have shown the degradation to be a function of multiple stresses, so it can be inaccurate to predict failure rates using single stress tests. In this paper, a new testing methodology whereby multiple stresses are applied simultaneously using a “design of experiment (DOE) approach” is reported and used for predictive aging of modules. Multistress data are used for predictive aging of OPV modules under different stress levels; a general log-linear life model has been adapted and applied in order to predict the life of OPV modules and this is compared to experimental data, which show that a close estimation of simulated lifetime is obtained (within 18% accuracy). The life test models can be used for predicting aging of OPV modules in different geographic locations and could be used to account for different degradation rates due to seasonal climatic variations. Furthermore, by using the DOE data, we show how the major stress factors can be screened and their statistical significance upon degradation quantified using analysis of variance. One of the potential benefits of using this approach for OPV degradation studies is that additional factors could be added to study the impact on degradation to provide a more comprehensive study

Multivariate Approach for Studying the Degradation of Perovskite Solar Cells.

Despite the progress in the performance of perovskite solar cells (PSCs), the absorber layer degradation during prolonged exposure to multiple environmental conditions is still a major issue. As the degradation depends upon many intrinsic and extrinsic factors, the need to adopt a multivariate testing protocol, which provides rapid assessment of device stability, is required. To do this, a Plackett Burman (PB) screening design has been used to analyze 9 different factors that affect the PSC stability; including four extrinsic factors (oxygen, moisture, UV exposure and temperature) and five intrinsic factors (selection of hole transport layer and electron transport layer, absorber layer thickness, halide type and perovskite deposition process). This approach allows us to rank the relative severity of these factors and can be used to narrow the scope of materials and device architectures to be modified, by identifying materials and configurations, which are the most stable. The least and most stable device configurations have been identified and the success of the screening approach has been demonstrated by testing the optimized configurations under ISOS-D1 and –L2 protocols. Importantly, only 12 experiments are needed to establish the most stable combination from the 9 factors thus providing a rapid assessment. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) measurements of perovskite absorber films have been performed in order to understand the degradation pathways and to support the conclusion of PB screening technique

Understanding UV Sensor Performance in ZnO TFTs Through the Application of Multivariate Analysis

Zinc oxide (ZnO) thin film transistors are well suited to UV sensing application because they absorb predominantly in the UV region due to the wide bandgap (Eg = 3.37 eV) and possess a large exciton binding energy (60 meV) with high radiation hardness. When operated as a transistor, many device performance parameters alter such as threshold Voltage, on-off current and channel mobility. As a result, it is to distinguish between changes in electrical performance induced by UV light and environmental effects that add noise to the sensor performance. In this work, the UV response of zinc oxide thin film transistors (ZnO TFTs) is examined using Taguchi Design of Experiment (DOE) method. By using this multivariate analysis approach, it is possible to reduce the number of calibration tests required for the sensor to accurately assess UV irradiation It is observed that different input conditions (UV power, exposure time, temperature, bias conditions) affect different TFT performance parameters more or less significantly. From the perspective of UV sensing, ON current in the saturation region appears to be the best performance parameter in a ZnO TFT for examining differences in UV exposure

Spray coated silver nanowires as transparent electrodes in OPVs for Building Integrated Photovoltaics applications

The application of spray coated silver nanowires (AgNWs) onto OPVs for building Integrated Photovoltaics (BIPVs) is demonstrated. By using AgNWs with PEDOT:PSS, a transparent conductive layer was demonstrated on top of an P3HT:PCBM active layer with a sheet resistance of 30 Ω/⎕ for 90% transparency. This has been applied to two separate configurations; semi-transparent OPVs for solar glazing applications and OPVs onto an opaque substrate, namely steel. For the latter, a novel technique to planarise the steel substrate with an intermediate layer is also presented, with a substantial decrease in surface roughness reported to ensure that the substrate is smooth enough to use for OPV fabrication. The use of SU-8 as an intermediate layer reduced the surface roughness to RA=10 nm, which is one of the lowest values reported to date, and was achieved on a low cost substrate (DC01 low carbon steel) using solution processing

Optimization of the Anodization Processing for Aluminum Oxide Gate Dielectrics in ZnO Thin Film Transistors by Multivariate Analysis

The present study reports a two-level multivariate analysis to optimize the production of anodized aluminum oxide (Al₂O₃) dielectric films for zinc oxide thin-film transistors (TFTs). Fourteen performance parameters were measured and analysis of variance (ANOVA) of the combined responses has been applied to identify how the Al₂O₃ dielectric fabrication process influences the electrical properties of the TFTs. Using this approach, the levels for the manufacturing factors to achieve optimal overall device performance have been identified and ranked. The cross-checked analysis of the TFT performance parameters demonstrated that the appropriate control of the anodization process can have a higher impact on TFT performance than the use of traditional methods of surface treatment of the dielectric layer. Flexible electronics applications are expected to grow substantially over the next 10 years. Given the complexity and challenges of new flexible electronics components, this “multivariate” approach could be adopted more widely by the industry to improve the reliability and performance of such devices

Using ISOS consensus test protocols for development of quantitative life test models in ageing of organic solar cells

As Organic Photovoltaic (OPV) development matures, the demand grows for rapid characterisation of degradation and application of Quantitative Accelerated Life Tests (QALT) models to predict and improve reliability. To date, most accelerated testing on OPVs has been conducted using ISOS consensus standards. This paper identifies some of the problems in using and interpreting the results for predicting ageing based upon ISOS consensus standard test data. Design of Experiments (DOE) in conjunction with data from ISOS consensus standards are used as the basis for developing life test models for OPV modules. This is used to study their temperature-humidity and light-induced degradation, which enables failure rates during accelerated testing to be assessed against the typical outdoor operational conditions. The life test models are used to assess the relative severity of the ISOS standards and the impact of geographic and seasonal climatic changes on OPV degradation

Using Large Datasets of Organic Photovoltaic Performance Data to Elucidate Trends in Reliability Between 2009 and 2019

The application of data analytical approaches to understand long-term stability trends of organic photovoltaics (OPVs) is presented. Nearly 1900 OPV data points have been catalogued, and multivariate analysis has been applied in order to identify patterns, produce models that quantitatively compare different internal and external stress factors, and subsequently enable predictions of OPV stability to be achieved. Analysis of the weights associated with the acquired predictive model shows that for light stability (ISOS-L) testing, the most significant factor for increasing the time taken to reach 80% of the initial performance (T80) is the substrate and top electrode selection, and the best light stability is achieved with a small molecule active layer. The weights for damp-heat (ISOS-D) testing shows that the type of encapsulation is the primary factor affecting the degradation to T80. The use of data analytics and potentially machine learning can provide researchers in this area new insights into degradation patterns and emerging trends