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This Assessment Update by the Environmental Effects Assessment Panel (EEAP) of the United Nations Environment Programme (UNEP) considers the interactive effects of solar UV radiation, global warming, and other weathering factors on plastics. The Assessment illustrates the significance of solar UV radiation in decreasing the durability of plastic materials, degradation of plastic debris, formation of micro- and nanoplastic particles and accompanying leaching of potential toxic compounds. Micro- and nanoplastics have been found in all ecosystems, the atmosphere, and in humans. While the potential biological risks are not yet well-established, the widespread and increasing occurrence of plastic pollution is reason for continuing research and monitoring. Plastic debris persists after its intended life in soils, water bodies and the atmosphere as well as in living organisms. To counteract accumulation of plastics in the environment, the lifetime of novel plastics or plastic alternatives should better match the functional life of products, with eventual breakdown releasing harmless substances to the environment. [ABSTRACT FROM AUTHOR]

This article explores the relationship between solar UV radiation, climate change, and plastic pollution. It highlights the role of UV-driven weathering in the degradation of plastics and the formation of harmful micro- and nanoplastic particles. The article emphasizes the need for global assessments of plastic dispersal, persistence, and weathering to consider these linkages. It also discusses the impact of the Montreal Protocol on plastic degradation and the potential effects of UV radiation and climate change on plastic pollution in the future. The article concludes by calling for further research and the development of new plastics with durability matching the functional life of products. [Extracted from the article]

Accurate estimation of photovoltaic (PV) system performance is crucial for determining its feasibility as a power generation technology and financial asset. PV-based energy solutions offer a viable alternative to traditional energy resources due to their superior Levelized Cost of Energy (LCOE). A significant challenge in assessing the LCOE of PV systems lies in understanding the Performance Loss Rate (PLR) for large fleets of PV systems. Estimating the PLR of PV systems becomes increasingly important in the rapidly growing PV industry. Precise PLR estimation benefits PV users by providing real-time monitoring of PV module performance, while explainable PLR estimation assists PV manufacturers in studying and enhancing the performance of their products. However, traditional PLR estimation methods based on statistical models have notable drawbacks. Firstly, they require user knowledge and decision-making. Secondly, they fail to leverage spatial coherence for fleet-level analysis. Additionally, these methods inherently assume the linearity of degradation, which is not representative of real world degradation. To overcome these challenges, we propose a novel graph deep learning-based decomposition method called the Spatio-Temporal Graph Neural Network for fleet-level PLR estimation (PV-stGNN-PLR). PV-stGNN-PLR decomposes the power timeseries data into aging and fluctuation components, utilizing the aging component to estimate PLR. PV-stGNN-PLR exploits spatial and temporal coherence to derive PLR estimation for all systems in a fleet and imposes flatness and smoothness regularization in loss function to ensure the successful disentanglement between aging and fluctuation. We have evaluated PV-stGNN-PLR on three simulated PV datasets consisting of 100 inverters from 5 sites. Experimental results show that PV-stGNN-PLR obtains a reduction of 33.9% and 35.1% on average in Mean Absolute Percent Error (MAPE) and Euclidean Distance (ED) in PLR degradation pattern estimation compared to the state-of-the-art PLR estimation methods. [ABSTRACT FROM AUTHOR]

Abstract Poly(ethylene-terephthalate) (PET) film is widely used in photovoltaic module backsheets, for its dielectric breakdown strength, and in applications requiring high optical clarity. PET degrades under exposure to ultraviolet (UV) irradiance, heat, and moisture, which leads to loss of optical clarity and performance properties. To study the weathering driven degradation of PET films, three grades of PET, including unstabilized and stabilized grades, were exposed to three types of accelerated weathering exposure. Fluorescence excitation-emission matrix (EEM) spectra were collected after predetermined exposure intervals. Parallel factor analysis (PARAFAC) was applied to the resulting spectra to decompose the fluorescence data into individual fluorophore components and monitor their relative concentrations over time. EEM-PARAFAC was used to identify and distinguish between the formation of monohydroxy-terephthalate and dihydroxy-terephthalate units in PET over time under the UV-light bearing accelerated exposures. The relative concentrations of these fluorophores were found to increase, while the relative concentration of the PARAFAC component assigned to PET was found to generally decrease. ATR-FTIR was used to support findings from EEM-PARAFAC. Results were also used to assess the impact of additives (UV stabilizer and TiO 2) on degradation. Highlights • PET forms hydroxy-substituted terephthalate units under UV exposure. • A three component parallel factor analysis model can capture degradation phenomena. • Model interpretation reveals impact of composition and weathering parameters. • Parallel factor analysis results build upon previous PET degradation studies. [ABSTRACT FROM AUTHOR]

Understanding the impact of climate stressors on photovoltaic (PV) backsheet degradation in real-use conditions is critical to improve the accelerated testing exposures, extend the backsheet lifetime, and increase the confidence in PV reliability. In this work, a total of 33 PV module backsheets were retrieved from six climatic zones worldwide with 2 - 28 years of exposure. These modules included five types of backsheet air-side materials (or outer layer): poly(vinylidene fluoride) (PVDF), poly(tetrafluoroethylene-co-hexafluoropropylene-co-vinylidene fluoride) (THV), poly(vinyl fluoride) (PVF), poly(ethylene terephthalate) (PET), and polyamide (PA). Attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) was used to identify air-side materials. The degradation induced color change, gloss loss, and chemical material changes analyzed using optical microscopy, differential scanning calorimetry (DSC), scanning electron microscopy (SEM), colorimetry (yellowness index (YI)), and gloss measurements. PVDF, THV, and PVF air-side layer backsheets, in particular PVF, had minimal degradation in the air-side layer appearance and chemical structures after exposure in different climatic zones. The PET air-side backsheets exhibited obvious color increase (22.55 YI units after about 9 years exposure) and the PA/PA/PA backsheets showed large gloss loss (up to 76.4 %) relative to the unexposed backsheets. Severe cracks between cells that penetrated through the entire thickness of backsheets are observed on PA/PA/PA backsheets after 4-6 years of exposure in 6 climatic zones. The current indoor exposure standards were not sufficient to identify this degradation type. However, fluoropolymer based PV backsheets showed lower levels of degradation predictors and increased climatic resistance. Specific samples (PVF) showed little change from baseline after 28 years of outdoor exposure. • Retrieved module backsheet characterization. • Diverse climatic exposure. • Inhomogeneous backsheet degradation. [ABSTRACT FROM AUTHOR]

The width tapered beam method for measuring fracture toughness has been contemplated for use in measuring the adhesion of photovoltaic materials, is promoted by it being a viable method for use directly on modules rather than to engineered test specimens. However, precise determination of crack length is often difficult as failure often involves tendril formation, cavitation voids, and other plastic deformation at the crack front in addition to obfuscation by opaque materials. Because fracture energy varies as the square of crack length, imprecise crack tip length results in large measurement uncertainties. In this work, we develop a method to estimate the crack tip length using the relationship between the applied force and the displacement of the load frame. The crack tip is determined for every data point and can be defined from a calibration curve related to the amount of energy put into the beam, or from a theoretically idealized estimation. Once a calibration curve is set up and the equations programmed, the fracture energy as a function of position on the newly formed crack interface can be accurately estimated. The test additionally provides much easier analysis and insight into the joint failure through more precise knowledge of fracture toughness at each de-bonded area. [ABSTRACT FROM AUTHOR]

The open circuit voltage (VOC) is a critical and common indicator of solar cell performance as well as degradation, for panel down to lab-scale photovoltaics. Detecting VOC at the nanoscale is much more challenging, however, due to experimental limitations on spatial resolution, voltage resolution, and/or measurement times. Accordingly, an approach based on Conductive Atomic Force Microscopy is implemented to directly detect the local VOC, notably for monocrystalline Passivated Emitter Rear Contact (PERC) cells which are the most common industrial-scale solar panel technology in production worldwide. This is demonstrated with cross-sectioned monocrystalline PERC cells around the entire circumference of a poly-aluminum-silicide via through the rear emitter. The VOC maps reveal a local back surface field extending ~ 2 μm into the underlying p-type Si absorber due to Al in-diffusion as designed. Such high spatial resolution methods for photovoltaic performance mapping are especially promising for directly visualizing the effects of processing parameters, as well as identifying signatures of degradation for silicon and other solar cell technologies. [ABSTRACT FROM AUTHOR]

Materials and devices age with time. Material aging and degradation has important implications for lifetime performance of materials and systems. While consensus exists that materials should be studied and designed for degradation, materials inspection during operation is typically performed manually by technicians. The manual inspection makes studies prone to errors and uncertainties due to human subjectivity. In this work, we focus on automating the process of degradation mechanism detection through the use of a fully convolutional deep neural network architecture (F-CNN). We demonstrate that F-CNN architecture allows for automated inspection of cracks in polymer backsheets from photovoltaic (PV) modules. The developed F-CNN architecture enabled an end-to-end semantic inspection of the PV module backsheets by applying a contracting path of convolutional blocks (encoders) followed by an expansive path of decoding blocks (decoders). First, the hierarchy of contextual features is learned from the input images by encoders. Next, these features are reconstructed to the pixel-level prediction of the input by decoders. The structure of the encoder and the decoder networks are thoroughly investigated for the multi-class pixel-level degradation type prediction for PV module backsheets. The developed F-CNN framework is validated by reporting degradation type prediction accuracy for the pixel level prediction at the level of 92.8%. [ABSTRACT FROM AUTHOR]

A materials data analytics (MDA) methodology was developed in this study to evaluate publicly available information on 9% Cr family steel and to handle nonlinear relationships and the sparsity in materials data for this alloy class. The overarching goal is to accelerate the design process as well as to reduce the time and expense associated with qualification testing of new alloys for fossil energy applications. Data entries in the analyzed data set for 82 iron‐base alloy compositions, several processing parameters, and results of tensile mechanical tests selected for this study were arranged in 34 columns by 915 rows. While detailed microstructural information was not available, it is assumed that the compositional space for the 9 to 12% Cr steels is limited such that all data entries have a tempered martensitic microstructure during service. Establishing a hierarchy of first‐order trends in the publicly available data requires the MDA to filter out the biases. Complexity of the phase transformations and microstructure evolution in the multicomponent alloys (using 21 chemical elements) with major influence on mechanical properties, leads to inefficiency in direct application of unbiased linear regression across the entire data space. To address the nonlinearity, analyses of tensile data were performed in composition‐based clusters. Clusters corresponding to moderately frequent patterns and maximized information gain were further refined by using p‐norm distance measures, matching the alloy classification groups adopted by industry. The evolutionary method of propagating an ensemble of competing cluster‐based models proved to be a viable option in dealing with scarce, multidimensional data. [ABSTRACT FROM AUTHOR]

Photolytic and hydrolytic degradation of poly(ethylene-terephthalate) (PET) polymers with different stabilizers were performed under multiple accelerated weathering exposures and changes in the polymers were monitored by various evaluation techniques. Yellowing was caused by photolytic degradation and haze formation was induced by combined effects of photolytic and hydrolytic degradation. The formation of light absorbing chromophores and bleaching of the UV stabilizer additive were recorded through optical spectroscopy. Chain scission and crystallization were found to be common mechanisms under both photolytic and hydrolytic conditions, based on the infrared absorption of the carbonyl (C = O) band and the trans ethylene glycol unit, respectively. The degradation mechanisms determined from these evaluations were then used to construct a set of degradation pathway network models using the network structural equation modeling (netSEM) approach. This method captured the temporal evolution of degradation by assessing statistically significant relationships between applied stressors, mechanistic variables, and performance level responses. Quantitative pathway equations provided the contributions from mechanistic variables to the response changes. [ABSTRACT FROM AUTHOR]

Developing materials for use in photovoltaic (PV) systems requires knowledge of their performance over the warranted lifetime of the PV system. Poly(ethylene-terephthalate) (PET) is a critical component of PV module backsheets due to its dielectric properties and low cost. However, PET is susceptible to environmental stressors and degrades over time. Changes in the physical properties of nine PET grades were modeled after outdoor and accelerated weathering exposures to characterize the degradation process of PET and assess the influence of stabilizing additives and weathering factors. Multivariate multiple regression (MMR) models were developed to quantify changes in color, gloss, and haze of the materials. Natural splines were used to capture the non-linear relationship between predictors and responses. Model performance was evaluated via adjusted-R2 and root mean squared error values from leave-one-out cross validation analysis. All models described over 85% of the variation in the data with low relative error. Model coefficients were used to assess the influence of weathering stressors and material additives on the property changes of films. Photodose was found to be the primary degradation stressor and moisture was found to increase the degradation rate of PET. Direct moisture contact was found to impose more stress on the material than airbone moisture (humidity). Increasing the concentration of TiO2 was found to generally decrease the degradation rate of PET and mitigate hydrolytic degradation. MMR models were compared to physics-based models and agreement was found between the two modeling approaches. Cross-correlation of accelerated exposures to outdoor exposures was achieved via determination of cross-correlation scale factors. Cross-correlation revealed that direct moisture contact is a key factor for reliable accelerated weathering testing and provided a quantitative method to determine when accelerated exposure results can be made more aggressive to better approximate outdoor exposure conditions. [ABSTRACT FROM AUTHOR]

The long-term durability of photovoltaic modules is paramount for the continued growth of the industry. Polymer backsheets are of particular concern since they provide electrical insulation and an environmental barrier. In this study, 23 freestanding, multilayer backsheets with nine unique material combinations underwent four different weathering exposures under accelerated and real-world conditions. Besides changes in color and gloss, the induced degradation included parallel or mudflat cracks on 11 backsheets, sometimes in combination with delamination or blistering. Similar degradation has been observed in previous studies and is concerning since cracks compromise the mechanical integrity and electrical safety of backsheets. Quantitative parameters are desirable to reliably classify categories of cracks and supply unbiased features for statistical analysis in predictive lifetime models. We developed an analysis technique that utilizes surface profilometry data to quantify the depth, width, area, spacing, and number of cracks. Parameters are automatically extracted from the raw data by an algorithm running on a high performance distributed computing cluster. Our algorithm excelled at characterizing parallel cracks with minimal de-adhesion, and only an estimated 4% of crack detections were false positives. The addition of humidity and temperature variation formed up to three times as many cracks on a photodose basis compared to dry, constant temperature exposures. Cracks in real-world and accelerated exposures propagated to similar depths with equivalent photodoses; however, the number of cracks formed in accelerated exposures was far greater on a photodose basis. Of samples that cracked, the best performing backsheet configuration was polyvinyl fluoride/poly (ethylene-terephthalate)/polyethylene (PVF/PET/PE) while the least durable was PET/PET/ethylene-vinyl acetate. None of the six PVF/PET/PVF backsheets cracked in any of the exposures. [ABSTRACT FROM AUTHOR]

Accelerated weathering exposures were performed on poly(ethylene-terephthalate) (PET) films. Longitudinal multi-level predictive models as a function of PET grades and exposure types were developed for the change in yellowness index (YI) and haze (%). Exposures with similar change in YI were modeled using a linear fixed-effects modeling approach. Due to the complex nature of haze formation, measurement uncertainty, and the differences in the samples’ responses, the change in haze (%) depended on individual samples’ responses and a linear mixed-effects modeling approach was used. When compared to fixed-effects models, the addition of random effects in the haze formation models significantly increased the variance explained. For both modeling approaches, diagnostic plots confirmed independence and homogeneity with normally distributed residual errors. Predictive R2 values for true prediction error and predictive power of the models demonstrated that the models were not subject to over-fitting. These models enable prediction under pre-defined exposure conditions for a given exposure time (or photo-dosage in case of UV light exposure). PET degradation under cyclic exposures combining UV light and condensing humidity is caused by photolytic and hydrolytic mechanisms causing yellowing and haze formation. Quantitative knowledge of these degradation pathways enable cross-correlation of these lab-based exposures with real-world conditions for service life prediction. [ABSTRACT FROM AUTHOR]

A laboratory method to simulate natural exposure of roofing materials has been reported in a companion article. In the current article, we describe the results of an international, nine-participant interlaboratory study (ILS) conducted in accordance with ASTM Standard E691-09 to establish the precision and reproducibility of this protocol. The accelerated soiling and weathering method was applied four times by each laboratory to replicate coupons of 12 products representing a wide variety of roofing categories (single-ply membrane, factory-applied coating (on metal), bare metal, field-applied coating, asphalt shingle, modified-bitumen cap sheet, clay tile, and concrete tile). Participants reported initial and laboratory-aged values of solar reflectance and thermal emittance. Measured solar reflectances were consistent within and across eight of the nine participating laboratories. Measured thermal emittances reported by six participants exhibited comparable consistency. For solar reflectance, the accelerated aging method is both repeatable and reproducible within an acceptable range of standard deviations: the repeatability standard deviation s r ranged from 0.008 to 0.015 (relative standard deviation of 1.2–2.1%) and the reproducibility standard deviation s R ranged from 0.022 to 0.036 (relative standard deviation of 3.2–5.8%). The ILS confirmed that the accelerated aging method can be reproduced by multiple independent laboratories with acceptable precision. This study supports the adoption of the accelerated aging practice to speed the evaluation and performance rating of new cool roofing materials. [ABSTRACT FROM AUTHOR]

Based on recent advances in nanoscience, data science and the availability of massive real-world datastreams, the mesoscopic evolution of mesoscopic energy materials can now be more fully studied. The temporal evolution is vastly complex in time and length scales and is fundamentally challenging to scientific understanding of degradation mechanisms and pathways responsible for energy materials evolution over lifetime. We propose a paradigm shift towards mesoscopic evolution modeling, based on physical and statistical models, that would integrate laboratory studies and real-world massive datastreams into a stress/mechanism/response framework with predictive capabilities. These epidemiological studies encompass the variability in properties that affect performance of material ensembles. Mesoscopic evolution modeling is shown to encompass the heterogeneity of these materials and systems, and enables the discrimination of the fast dynamics of their functional use and the slow and/or rare events of their degradation. We delineate paths forward for degradation science. [ABSTRACT FROM AUTHOR]

Photovoltaic backsheets are exposed to harsh outdoor weathering conditions throughout their service lives that can compromise their protective function, through adhesive debonding between their constituent layers and between the backsheet and the module. A large-scale study on adhesive degradation was conducted on 37 field-exposed modules, that spanned 19 different module manufacturers, that were deployed among six Köppen–Geiger climatic zones, and that were fielded between 0 and 28 years. Six outer layer polymer classes were identified among the backsheets: polyamide (PA), polyethylene terephthalate (PET), polyvinyl fluoride (PVF), polyvinylidene fluoride (PVDF), fluoroethylene vinyl ether copolymer (FEVE), and tetrafluoroethylene hexafluoropropylene vinylidene fluoride copolymer (THV). Two adhesion tests were used to measure the adhesive strength: the wedge test and the width-tapered single-cantilever beam (SCB) test. Adhesion energies were compared across exposure time and Köppen–Geiger climatic zone. Many of the PET-, PVF-, and PVDF-based backsheets experienced degradation of the adhesive layer between the backsheet outer and core layers. A consistent trend of decreasing adhesion energy with exposure time was observed in five out of the six backsheet types. Trends among adhesion energy and climatic zone, while expected, were not observed, possibly due to broad ranges in temperature, humidity, and precipitation defining Köppen–Geiger climatic zones. The cantilever beam measurements produced an upper cutoff of approximately 100 J/m2, above which no modules exhibited field delamination. The results are part of a two-part study quantifying adhesion in both field-weathered and indoor-exposed PV backsheets. • Thirty-seven (37) PV modules were retrieved from various regions around the world • Two adhesion tests were used to characterize backsheet adhesion • Adhesion energy decreased with number of years of field exposure • Backsheets with adhesive tie layers often showed failure in an adhesive layer • Modules with adhesion energies greater than 100 J/m2 showed no field delamination [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) backsheets provide critical moisture, mechanical, and electrical insulation to the backside of PV modules, but their continued functionality depends upon their ability to remain well adhered over years of harsh environmental exposure. A study of adhesive strength was conducted on several PV backsheet types exposed to indoor accelerated weathering. Two adhesion tests – the wedge test and single cantilever beam test – were used to measure adhesion energy in four backsheets: two with fluoropolymer-based outer (airside) layers – polyvinyl fluoride (PVF), polyvinylidene fluoride (PVDF) – and two with non-fluoropolymer-based outer layers–polyamide (PA) and polyethylene terephthalate (PET). The effects of changes in temperature, ultraviolet (UV) irradiance, relative humidity, and a periodic water spray were studied. The PET-, PVF- and PVDF-based backsheets all showed instances of debonding in an adhesive layer, which is commonly reported. For the PA-, PET-, and PVDF-based backsheets, adhesion energy dropped fairly rapidly with exposure, reaching very low levels by 4000 h. The PVF-based backsheet was relatively robust to weathering. Pull-off of an outer chalking layer in the PA- and PET-based backsheets suggested a sensitivity to UV. Adhesion in these two backsheets was also highly sensitive to changes in moisture level. Changes in UV irradiance and temperature did not show a statistically significant effect on adhesion loss for the exposure levels used. The present work is part of a two-part adhesion study on both field-weathered and indoor-exposed backsheets, and forms a basis for understanding adhesion degradation across a variety of backsheet types and degradation factors. • Four indoor-exposed backsheet types were adhesion-tested using two different methods. • Adhesion in the PVF-based backsheet was relatively stable. • The PA-, PET- and PVDF-based backsheets exhibited substantial decrease after 4000 hours. • The PA- and PET-based backsheets exhibited sensitivity to changes in moisture level. • The PET-, PVF-, and PVDF-based backsheets all exhibited debonding in an adhesive layer. [ABSTRACT FROM AUTHOR]

Data science techniques were used to quantify the effect of alloying additions on the tensile behavior of martensitic steels. The effort was undertaken to exploit the heritage data to establish the next experimental design space for the class of 9–12 wt% Cr steels for the application of turbine rotors with an operating temperature of 650 ∘C and above. Linear, lasso, and multivariate multiple regression models were utilized to identify which alloying elements contribute towards strength and ductility. Visualization techniques such as t-distributed stochastic neighbor embedding and pair-wire element specific comparisons were utilized to explore information gaps that exist within the data. The study found that tantalum, recently added to improve the creep rupture lifetime, does not show any effect on tensile properties. All combined, the results suggest that the low tempering temperature has compensated for the low alloying additions in the past, therefore, new experiments are needed to isolate the effects of tempering temperature from those of individual elements. [ABSTRACT FROM AUTHOR]