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At least 199 records · Page 11

Light and Elevated Temperature Induced Degradation (LeTID) in a Utility-Scale Photovoltaic System

Here, we present a detailed case study of degradation in monocrystalline silicon photovoltaic modules operating in a utility-scale power plant over the course of approximately three years. We present the results of degradation analysis on arrays within the site, and find that five of the six arrays degraded faster than the best performing array, even though the arrays consist of modules of the same manufacturer and model. We also describe the results of extensive laboratory characterization of modules returned from the field, including module- and cell-level current–voltage characterization, luminescence imaging, and accelerated testing. The laboratory test results and the field performance are consistent with light and elevated temperature induced degradation (LeTID). Notably, we observe differences in back contact technology between affected and unaffected modules. This article also demonstrates a method to identify possible LeTID degradation in the field and confirm the result with laboratory testing of a small number of modules.

14 SOLAR ENERGY↗

Prediction of Climate-Specific Degradation Rate for Photovoltaic Encapsulant Discoloration

Encapsulant discoloration is a well-known field degradation mode of crystalline-silicon photovoltaic modules, particularly in the hot climate zones. The discoloration rate is influenced by several weathering factors, such as UV light, module temperature, and humidity, as well as the permeability of oxygen into the module. Here, a rate dependence model employing the modified Arrhenius equations to predict the degradation rate for encapsulant discoloration in different climates is presented. Two modeling approaches are introduced, which utilize the field and accelerated UV testing degradation data in conjunction with the field meteorological data to determine the acceleration factor for encapsulant browning. A novel method of accelerated UV stress testing at three simultaneous module temperatures in a single environmental chamber test run is implemented to estimate the activation energy for browning. The test was performed on three field-retrieved modules to capture the wear-out failure mechanism. The degradation in short-circuit current Isc rather than maximum power is used as a decisive parameter for the discoloration analysis. Furthermore, the developed model has been used to predict the Isc degradation rate for the Arizona field characterized by a hot and dry climate and is validated against the field-measured value. It has also been applied to other climate types, e.g., the cold and dry climate of New York.

14 SOLAR ENERGY↗

Nanometer-Scale Measurement of Grid Finger Electrical Conduction Pathways to Detect Series Resistance Degradation of Utility-Scale Silicon Solar Cells

Here, we report on an electrical conduction mechanism for series resistance (Rs) degradation observed in a utility-scale photovoltaic power plant by imaging the local resistance at the Ag/Si interface of the c-Si front metallization. Scanning spreading resistance microscopy imaging with nanometer (nm) scale spatial resolution revealed that the number of point or small-area electrical contacts decreased substantially in a degraded cell compared to an unaffected cell, demonstrating the root cause of Rs degradation. The decrease in electrical contacts is likely caused by a structural change - the Ag particles in contact with the Si cell (or via a nm-thickness tunneling glass layer) aggregate into bulk Ag, and a highly resistive glass frit forms a belt shape at the Ag/Si interface. This resistive belt, with a thickness of ~1 um, blocks the current conduction from the cell emitter to the Ag grid. Our microscopy results help to unravel unambiguously the degradation mechanism and demonstrate an example of the multiscale characterization approach for understanding degradation in field-weathered PV module.

14 SOLAR ENERGY↗

Different Damp-Heat-Induced Series Resistance Degradation Behaviors in Fielded Crystalline Silicon Photovoltaic Modules Due to Difference in Bill of Materials

This case study investigates mono-crystalline silicon modules from underperforming portions of a utility-scale photovoltaic power plant. Field-collected I-V curves and electroluminescence imaging suggested that increased series resistance was a primary factor driving module degradation. Selected modules were removed from the field for further analysis, including incremental damp heat accelerated testing, which confirmed a progression in series resistance degradation. Two distinct cell degradation behaviors became apparent during the investigation. Cross-sectional scanning electron microscopy (with elemental analysis) and scanning spreading resistance microscopy identified key differences between the two degradation mechanisms, primarily grid finger width and contact resistance. Additionally, the study highlights the reliability implications of retest requirements in International Electrotechnical Commission 61215 for material changes and how they may have mitigated the degradation observed at this site.

14 SOLAR ENERGY↗

Spectroscopic Investigation of Light-Induced Degradation Paramagnetic Defect in Czochralski Silicon

We report on the electron paramagnetic resonance (EPR) spectra of Cz and FZ Si in different stages of light-induced degradation. Firstly, we show that the paramagnetic signal at low temperature (10K) is dependent on the state of light-induced degradation performed at room temperature and on the sample doping. The light-degraded state in p-Cz Si shows strong, sharp paramagnetic defect signatures compared to samples in the annealed state. When an excitation light is applied during the EPR measurement, additional structures appear in the spectra. In contrast, the wide EPR active signature related to boron interaction with lattice, is present in the annealed state but diminishes after light exposure. Finally, we show that the degraded paramagnetic signal returns when annealed samples are exposed to ambient light. We suggest that these changes in the electron paramagnetic resonance spectra is related to the boron-oxygen defect that causes light-induced degradation.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Preliminary Nuclear Containment Vessel Modeling for Multi-Hazard Probabilistic Risk Assessment under Seismic Hazards and Concrete Degradation

The current practice for natural phenomena hazards (NPH) risk assessment of nuclear facilities is to compute the risk for each hazard independently and then compound the total risk as a combination of single hazard risks. This state of practice does not consider correlations between hazards and the cascading impacts to structures, systems, and components (SSCs), and could thus underestimate the NPH risk or overestimate the nuclear facility safety. Events such as the Fukushima Daiichi accident have highlighted the importance of multi-hazard risk considerations to nuclear power plants (NPPs) that quantify the cascading damage effects to SSCs in the risk models. Moreover, the current fleet of NPPs in the United States is aging; these NPPs are now expected to operate well beyond their initially planned design life. Aging-related deterioration can potentially decrease the capacity of critical structures such as containment vessels to withstand NPH. Such aging considerations may not be adequately accounted for by the current NPH risk assessment guidelines. This paper presents a preliminary modeling and simulation of a representative reinforced concrete containment vessel subjected to seismic mainshock and aftershock considering concrete degradation due to alkali silica reaction. The broader aim is to develop multi-hazard time-dependent fragility functions that could be subsequently used in the probabilistic risk assessment (PRA) model. The multi-hazard component comes into play due to the consideration of damage to the containment vessel under seismic loads and concrete degradation. Consideration of concrete degradation also brings into play the time-dependent nature of the containment vessel response. The response of the containment vessel under varying degrees of concrete degradation to seismic loads is investigated. The results presented are simulated using the Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) software for seismic analysis and the Blackbear software for concrete degradation and damage modeling. Both software are open source and developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE).

42 ENGINEERING↗

Effect of Alkali-Silica Reaction Expansion Rate and Confinement on Concrete Degradation

Alkali-silica reaction (ASR) is a major deterioration mechanism that affects the durability of concrete structures. As the slow rate of ASR development and the restrained expansion in field concrete might affect the development of ASR damage, an experimental program was performed to investigate the effects of the rate of ASR expansion and confinement on the degradation of mechanical properties of concretes. Literature data on the degradation of mechanical properties of concretes with ASR expansion were collected and analyzed to investigate the influence of the rate of ASR expansion and confinement on the degradation trends. Degradation of mechanical properties was found to be significantly influenced by the rate of ASR expansion and slightly affected by confinements. The slow rate of ASR expansion seems to be beneficial in limiting concrete degradation. The effects of confinement seem to be related to the direction of restraint and crack orientations.

36 MATERIALS SCIENCE↗

Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost of energy (LCOE), which is crucial to rationalizing PV investment and installation. However, SLP is challeging since PV reliability in the field is affected by many combined factors, including various environmental stresses and module quality. In order to map out the active degradation mechanisms and pathways that best resemble real world conditions, we introduce the framework of a study protocol and use network models fitted to data, to enable analysis and SLP of complex PV systems with multiple active degradation mechanisms. The study protocol is the experimental design, including module variants and different exposure conditions, selection of evaluation methods, time-series data acquisition and training of network models to these data. We present SLP of minimodules in the lab and PV systems in the field. For lab SLP, minimodules with 8 variants based on manufacturer, architecture, and encapsulation were prepared and aged in modified damp heat with or without full spectrum light exposure. Stepwise I-V and Suns-Voc data acquisition tracks changes in electrical properties including Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss of minimodules. Network structural equation modeling (netSEM) was utilized to construct degradation pathway models that identify active degradation mechanisms and predict power loss over time. For field SLP, datastreams of Pmp values and I-V curve datastreams of two types of modules installed in three distinctly different Köppen-Geiger climate zones for 9 years were acquired. With power loss modes corresponding to uniform current loss (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), and current mismatch (ΔPImis) determined, the performance loss rates (PLR) were determined using PVplr. We show how to establish a study protocol framework to ensure appropriate parametric variations and valid data collection from the variants of your complex systems. Then the data-driven netSEM model fitting provides a comprehensive mapping of multiple active degradation mechanisms, and accurate service life prediction.

network model, degradation, photovoltaic, solar↗

Desulfatiglans anilini Initiates Degradation of Aniline With the Production of Phenylphosphoamidate and 4-Aminobenzoate as Intermediates Through Synthases and Carboxylases From Different Gene Clusters

The anaerobic degradation of aniline was studied in the sulfate-reducing bacterium Desulfatiglans anilini. Our aim was to identify the genes and their proteins that are required for the initial activation of aniline as well as to characterize intermediates of this reaction. Aniline-induced genes were revealed by comparison of the proteomes of D. anilini grown with different substrates (aniline, 4- aminobenzoate, phenol, and benzoate). Most genes encoding proteins that were highly abundant in aniline- or 4-aminobenzoate-grown D. anilini cells but not in phenol- or benzoate-grown cells were located in the putative gene clusters ani (aniline degradation), hcr (4-hydroxybenzoyl-CoA reductase) and phe (phenol degradation). Of these putative gene clusters, only the phe gene cluster has been studied previously. Based on the differential proteome analysis, four candidate genes coding for kinase subunits and carboxylase subunits were suspected to be responsible for the initial conversion of aniline to 4-aminobenzoate. These genes were cloned and overproduced in E. coli. The recombinant proteins were obtained in inclusion bodies but could be refolded successfully. Two subunits of phenylphosphoamidate synthase and two carboxylase subunits converted aniline to 4-aminobenzoate with phenylphosphoamidate as intermediate under consumption of ATP. Only when both carboxylase subunits, one from gene cluster ani and the other from gene cluster phe, were combined, phenylphosphoamidate was converted to 4-aminobenzoate in vitro, with Mn 2+ , K + , and FMN as co-factors. Thus, aniline is degraded by the anaerobic bacterium D. anilini only by recruiting genes for the enzymatic machinery from different gene clusters. We conclude, that D. anilini carboxylates aniline to 4-aminobenzoate via phenylphosphoamidate as an energy rich intermediate analogous to the degradation of phenol to 4-hydroxybenzoate via phenylphosphate.

59 BASIC BIOLOGICAL SCIENCES↗

Restoring Soil Fertility on Degraded Lands to Meet Food, Fuel, and Climate Security Needs via Perennialization

A continuously growing pressure to increase food, fiber, and fuel production to meet worldwide demand and achieve zero hunger has put severe pressure on soil resources. Abandoned, degraded, and marginal lands with significant agricultural constraints—many still used for agricultural production—result from inappropriately intensive management, insufficient attention to soil conservation, and climate change. Continued use for agricultural production will often require ever more external inputs such as fertilizers and herbicides, further exacerbating soil degradation and impeding nutrient recycling and retention. Growing evidence suggests that degraded lands have a large potential for restoration, perhaps most effectively via perennial cropping systems that can simultaneously provide additional ecosystem services. Here we synthesize the advantages of and potentials for using perennial vegetation to restore soil fertility on degraded croplands, by summarizing the principal mechanisms underpinning soil carbon stabilization and nitrogen and phosphorus availability and retention. We illustrate restoration potentials with example systems that deliver climate mitigation (cellulosic bioenergy), animal production (intensive rotational grazing), and biodiversity conservation (natural ecological succession). Perennialization has substantial promise for restoring fertility to degraded croplands, helping to meet future food security needs.

54 ENVIRONMENTAL SCIENCES↗

Degradation of Insulating Glass Units: Thermal Performance, Measurements and Energy Impacts

Insulating glass unit (IGU) degradation has been studied extensively. However, there is limited understanding of how present durability evaluation standards relate to product lifetime. Furthermore, there is debate on how to quantify performance of installed windows over time to better understand degradation processes. More knowledge on these topics is required to link durability evaluation to product lifetime projections based on energy performance. Energy models provide helpful estimations of total annual building energy consumption. However, most models are based on “as installed” performance of envelope components and fail to account for performance degradation. This can lead to an underestimation of building lifetime energy consumption. A better understanding of the relationship between durability and energy performance can inform integration of degradation dynamics into energy modeling software. This will improve lifetime building energy consumption estimations as well as inform appropriate retrofit strategies and timing. This paper reviews current durability literature, various standards for window performance ratings and weathering methods, existing in situ IGU energy performance measurement techniques, and whole-building energy effects. The challenges and disparities among various studies are analyzed and discussed. The authors hope that further work in this area will lead to the development of improved in situ test methods to assess IGU degradation in the field and link this knowledge to improved energy performance modeling approaches.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Bifacial Photovoltaic Module Degradation Dynamics

In a comprehensive study conducted at NREL's 75 kW bifacial single-axis-tracked field, accelerated degradation was observed in four out of five bifacial silicon photovoltaic (PV) module technologies when compared to their monofacial counterparts. Root cause analysis of accelerated bifacial degradation involved various analytical tools and techniques. This included employing RdTools to identify rates of power loss, conducting measurements on fielded and control modules using infrared imaging, electroluminescence (EL) and photoluminescence (PL), quantum efficiency (QE) analysis, IV-curves assessment, as well as utilizing handheld Raman and reflectance measurement targeted at anti-reflective coating. Most cases pointed to carrier lifetime degradation causing Voc loss and simultaneous Isc loss. In some cases, Isc further decreases likely due to optical effects from encapsulant degradation. The outcomes and methodologies employed in this investigation are documented in this publication. This study's significance is further emphasized by placing the findings within the broader context of the performance and degradation of various bifacial systems, as identified in the PV Fleets data.

bifacial↗

Elucidating and Mitigating High-Voltage Degradation Cascades in Cobalt-Free LiNiO 2 Lithium-Ion Battery Cathodes

LiNiO 2 (LNO) is a promising cathode material for next-generation Li-ion batteries due to its exceptionally high capacity and cobalt-free composition that enables more sustainable and ethical large-scale manufacturing. However, its poor cycle life at high operating voltages over 4.1 V impedes its practical use, thus motivating efforts to elucidate and mitigate LiNiO 2 degradation mechanisms at high states of charge. Here, a multiscale exploration of high-voltage degradation cascades associated with oxygen stacking chemistry in cobalt-free LiNiO 2 , is presented. In this work, lattice oxygen loss is found to play a critical role in the local O3–O1 stacking transition at high states of charge, which subsequently leads to Ni-ion migration and irreversible stacking faults during cycling. This undesirable atomic-scale structural evolution accelerates microscale electrochemical creep, cracking, and even bending of layers, ultimately resulting in macroscopic mechanical degradation of LNO particles. By employing a graphene-based hermetic surface coating, oxygen loss is attenuated in LNO at high states of charge, which suppresses the initiation of the degradation cascade and thus substantially improves the high-voltage capacity retention of LNO. Overall, this study provides mechanistic insight into the high-voltage degradation of LNO, which will inform ongoing efforts to employ cobalt-free cathodes in Li-ion battery technology.

25 ENERGY STORAGE↗

Unifying themes and distinct features of carbon and nitrogen assimilation by polysaccharide-degrading bacteria: a summary of four model systems

Our current understanding of enzymatic polysaccharide degradation has come from a huge number of in vitro studies with purified enzymes. While this vast body of work has been invaluable in identifying and characterizing novel mechanisms of action and engineering desirable traits into these enzymes, a comprehensive picture of how these enzymes work as part of a native in vivo system is less clear. Recently, several model bacteria have emerged with genetic systems that allow for a more nuanced study of carbohydrate active enzymes (CAZymes) and how their activity affects bacterial carbon metabolism. With these bacterial model systems it is now possible to not only study a single nutrient system in isolation (i.e. carbohydrate degradation and carbon metabolism), but also how multiple systems are integrated. Given that most environmental polysaccharides are carbon rich but nitrogen poor (e.g. lignocellulose), the interplay between carbon and nitrogen metabolism in polysaccharide-degrading bacteria can now be studied in a physiologically relevant manner. Therefore, in this review we have summarized what has been experimentally determined for CAZyme regulation, production, and export in relation to nitrogen metabolism for two Gram-positive (Caldicellulosiruptor bescii and Clostridium thermocellum) and two Gram-negative (Bacteroides thetaiotaomicron and Cellvibrio japonicus) polysaccharide-degrading bacteria. By comparing and contrasting these four bacteria we have highlighted the shared and unique features of each, with a focus on in vivo studies, in regard to carbon and nitrogen assimilation. Finally, we conclude with what we believe are two important questions that can act as guideposts for future work to better understand the integration of carbon and nitrogen metabolism in polysaccharide-degrading bacteria.

Cellvibrio japonicus↗

Structure-dependent mechanisms for plastic degradation in the marine environment

The visible and invisible accumulation of waste plastic in our oceans is a consequence of rapidly increasing inputs and very slow degradation rates. In general, this combination of effects results in long residence times. Nevertheless, the abiological degradation rate of a specific synthetic plastic varies widely, depending on its structural characteristics at the molecular, mesoscopic, and macroscopic levels. This chapter summarizes factors that determine these rates of degradation, and describes their principal mechanisms, for several of the major types of waste plastic found in the oceans. Mechanical forces cause cracking and flaking that break macroplastics into microplastics and even smaller fragments with increasing surface-to-volume ratios. Chemical degradation rates increase with surface area, influenced by intrinsic variations in crystallinity and the presence of additives, as well as extrinsic factors such as temperature, pH, and UV light intensity. Since polyolefin-based plastics are less dense than seawater and lack hydrolysable bonds in their polymer backbones, they accumulate close to the surface of the ocean where photo-oxidation is the principal cause of C–C bond cleavage in the polymer backbone. In contrast, polyesters and polyamides are denser than seawater and they sink, experiencing less exposure to solar irradiation. However, they can also degrade by slow hydrolysis of the C–O or C–N bonds intrinsic to the polymer structures.

Maciulis, Nicholas A.↗

Synergistically combining peracetic acid and reduced graphene oxide membranes to degrade trace organic contaminants

The removal of trace organic contaminants is a critical step for the reuse of municipal and industrial wastewater. Herein, we demonstrate a catalytic membrane platform synergistically integrating reduced graphene oxide (rGO) membranes and peracetic acid (PAA) oxidation, using a dye of methylene blue (MB) and a pesticide of 2,4-dichlorophenoxyacetic acid (2,4-D) as model contaminants. In a crossflow system with rGO membrane and 25 ppm PAA, the degradation rates of MB and 2,4-D were 22 and 0.12 g h −1 per g rGO, with an initial concentration of 10 and 1.1 ppm, respectively. The degradation time profile of MB and 2,4-D follows a pseudo-first-order model, and the degradation rate constant increases with increasing initial PAA doses. Here, the rGO membranes also exhibited good stability over a 1-month test for 2,4-D degradation. In addition to the nanofiltration performance of the rGO membrane, the integrated PAA-rGO membrane process shows great potential to degrade various organic contaminants without the need to separate and recover the metal-free catalyst in downstream treatment.

2,4-D↗

Anisotropic thermal-conductivity degradation in the phase-field method accounting for crack directionality

Dynamic loads applied to metals may lead to brittle or ductile fracture depending on the imposed strain rates, material properties, and specimen geometry. With an increase in the applied velocity, brittle to ductile failure mode transition may also be observed. Furthermore, at high strain rates, ductile fracture may be preceded by shear bands, which are narrow bands of intense plastic deformation, typically accompanied by a significant rise in temperature. Reliable models are needed to predict the response of metals subject to dynamic loads. In particular, capturing the interplay between heat conduction and crack propagation using the phase-field fracture method is still an open research field. To accurately capture the heat transfer physics across crack surfaces, damage models degrading thermal-conductivity are necessary. While isotropic thermal-conductivity degradation models were proposed, they may lead to errors as they are indifferent to crack directionality. In our current work, a new anisotropic approach is proposed in which thermal-conductivity, which depends on the phase-field gradient, is degraded solely across the crack. Here, it is shown that this approach improves the near-field approximation of temperature and heat flux compared with isotropic degradation, when taking the discontinuous crack solutions as reference. Additionally, the anisotropic degradation approach is implemented in a unified dynamic fracture model and a couple of examples demonstrate the viability of this approach.

42 ENGINEERING↗

Reinforcement learning for adaptive maintenance policy optimization under imperfect knowledge of the system degradation model and partial observability of system states

Maintenance policy optimization usually is faced with challenges that arise from an imperfect knowledge of system degradation models and from the partial observability of system degradation states. Here, this paper proposes a reinforcement learning method to address these two challenges for a class of maintenance problems with Markov degradation processes. The reinforcement learning approach consists of a learning component and a planning component. Using sequentially collected observations, at each step of decision-making the learning component improves the knowledge of system degradation in terms of the probability distributions of the transition rates based on sequential Bayesian inference. Using the updated transition rates, at each step of decision-making the maintenance policy optimization problem is then formulated as a partially observable Markov decision problem, and the planning component computes the optimal maintenance policy that maximizes the expected cumulative reward. The proposed method is illustrated using a numerical example with repair and inspection maintenance actions. The result shows that as more observations are collected, the learning component progressively learns the true system degradation process, and the planning component adjusts the optimal maintenance policy accordingly as well, which leads to increased reward.

42 ENGINEERING↗