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At least 127 records · Page 7

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high‐resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED‐2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED‐2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

Marcos Longo↗

The "PVLib" of Degradation: PVDeg

The Photovoltaic (PV) industry constantly aims for lower costs through higher-efficiency cells, improved module designs, and improvements in durability. This leads to the use of new materials, designs, and manufacturing processes, and not always with a sufficient amount of durability testing. To help drive down costs there is a desire to create modules that will last for up to 50 years of service life. To accomplish this, every degradation mode and mechanism must be identified and either eliminated or otherwise mitigated. This involves the extrapolation of laboratory results to the field conditions. There is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. While the basic equations used to model degradation are sometimes very simple, the full analysis involves calculations are cumbersome but ubiquitous for many degradation processes. A simplified, modeling framework to accomplish these repetitive processes will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this talk, we will describe our progress creating the open-source tool PVDeg. This tool can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. PVDeg simplifies many of the common foundational computational operations for obtaining meteorological data and using it to generate a model of the PV deployment. This prediction tool repository also contains various degradation models as well as a library of material parameters suitable for estimating the durability assessment of materials and components. We use an integration pipeline approach that allows us to leverage weather data from the National Solar Radiation Database, and other weather sources, to perform geospatial degradation analysis in the US and worldwide. We hope to become a repository that can be used for weathering and degradation analysis for various applications beyond the PV industry. During the talk, we will provide the PVPMC attendees the opportunity to interact with the tool via a Google Collab tutorial they can run on their phones or laptops.

durability↗

Spent-fuel recycling molecule degradation product standards can be produced with preparative liquid chromatography

Solvent systems used for spent nuclear fuel separation schemes are subject to intense radiation fields from the spent fuel, resulting in a degradation of separation performance over time from both the radiolytic destruction of active compounds (extractants, holdback agents, etc.) and the production of degradation compounds (compounds produced from the destruction of the active compounds). Development of a quantitative understanding of the effects of radiolysis on separations is impeded by a near-complete lack of availability of degradation products from chemical manufacturers. Synthesis of these degradation products through traditional means is both cost and time prohibitive, inhibiting advancement of new fuel separation processes. We hypothesize that comprehensive sets of degradation products can be synthesized using preparative radiolysis, and purified using high performance liquid chromatography in quantities sufficient for unequivocal identification and subsequent use as quantitative analytical studies. Achieving this objective will facilitate development of a much more accurate understanding of radiolysis reactions and their effects on solvent extraction processes, positioning Idaho National Laboratory (INL) in a leadership role in the science of fuel cycle separations. We propose producing these degradation compounds by irradiating concentrated samples of solvent ligands in the INL gamma irradiator, separating the resulting mixture with preparative chromatography, and removing the mobile phase in the separated fractions with a vacuum concentrator. This will yield milligram to gram quantities of purified degradation products, sufficient for fundamental research, at a fraction of the time and cost of synthesis. Facile production of separation molecule degradation products at minimal cost will enable the fundamental research that will accelerate the development of fuel cycles that will ensure the competitiveness of nuclear energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lifetime and Degradation Study of Poly(Methyl Methacrylate) via a Data-Driven Study Protocol Approach

We report to optimize and extend the service life of polymeric materials in outdoor environments, a domain knowledge-based and data-driven approach was utilized to quantitatively investigate the temporal evolution of degradation modes, mechanisms, and rates under various stepwise accelerated exposure conditions. Six formulations of poly(methyl methacrylate) (PMMA) with different combinations of stabilizing additives, including one unstabilized formulation, were exposed in three accelerated weathering conditions. Degradation was dependent on wavelength as samples in UV light at 340 nm (UVA) exposure showed the most yellowing. The unstabilized PMMA formulation showed much higher yellowness index values (59.5) than stabilized PMMA formulations (2–12). Urbach edge analysis shows a shift toward longer wavelength from 285 to 500 nm with increasing exposure time and an increased absorbance around 400 nm of visible region as the unstabilized samples increase in yellowing. The degradation mechanisms of PMMA were tracked using induced absorbance to dose at specific wavelengths that correspond to known degradation mechanisms. The degradation pathway of PMMA was modeled in a framework using network structural equation modeling (netSEM). netSEM showed changes in degradation pathway as PMMA transition stages of degradation.

36 MATERIALS SCIENCE↗

Electrochemical Degradation Modes in Bifacial Silicon Photovoltaic Modules

Motivated by the rapidly rising deployment of bifacial monocrystalline-silicon photovoltaics (PV), we investigate the durability of various PV module packaging configurations with transparent coverings on both the front and rear sides of the module. We use a series of bifacial passivated emitter and rear cell (p-PERC) mini-modules with systematically varying outer cover materials (glass/glass, G/G, or glass/transparent backsheet, G/TB) and encapsulant chemistries (poly [ethylene-co-vinyl acetate], EVA; or polyolefin, POE). We study degradation modes over 1,000 hours of combined damp heat (DH) exposure and high system voltages that can cause potential-induced degradation (PID) under positive, zero, or negative 1,000 V cell-to-frame bias. We analyze the degradation modes using a combination of current-voltage measurements, impedance spectroscopy, external quantum efficiency, and spatially resolved luminescence and thermal imaging. Our results highlight various types of degradation including shunting, enhanced recombination, and series resistance increases, and we use spatially resolved characterization to separately identify the localized effects. We show that multiple PID and moisture-ingress degradation modes severely affect EVA-containing modules, with previously reported PID processes under negative-bias DH and a unique observation of rear-side surface recombination in G/EVA/G modules under positive-bias DH. We observe significantly less degradation in POE-containing modules, where the G/POE/G configuration exhibits minimal degradation under all stress conditions that we employ.

14 SOLAR ENERGY↗

Belowground cross-trophic networks impact CH4 and CO2 emissions in degraded alpine peatlands

Belowground organisms forming complex cross-trophic ecological networks are essential for maintaining peatland carbon stability and energy flow. However, how peatland degradation affects the biodiversity and cross-trophic ecological networks of soil communities remains poorly understood. Here, we examined the degradation effects on soil prokaryotes (i.e., bacteria, archaea), fungi and nematodes in alpine peatlands on the eastern Tibetan Plateau, characterized by varying water table depths (indicating degradation levels). We found that peatland degradation, accompanied by significant shifts in soil moisture and pH (P < 0.05), reduced the taxonomic richness and phylogenetic diversity of prokaryotes, fungi, and nematodes, particularly in deeper soil layers (20–50 cm). Crucially, peatland degradation weakened potential cross-trophic interactions within bipartite networks of prokaryotes-nematodes and fungi-nematodes, resulting in less than 6.5 %–28.8 % of unchanged modules. Degradation-induced changes in soil moisture and pH were identified as primary drivers of biodiversity loss and network restructuring. Furthermore, such changes of belowground cross-trophic networks (particularly prokaryote-nematode) were significantly correlated with greenhouse gas emissions, such as decreased CO2 emissions, maintained CH4 emissions (leading to a higher CH4/CO2 ratio in deep layers), and reduced temperature sensitivity (Q10) of soil respiration. These findings underscore the critical need to protect soil biodiversity and cross-trophic networks in peatlands, particularly under the threat of climate change, to preserve peatland carbon stocks and maintain ecosystem stability. Our findings highlight that belowground cross-trophic networks are pivotal to decipher soil carbon dynamics of degraded peatlands and project the fate of peatland carbon stocks under future climate change scenarios.

Cross-trophic networks↗

Conclusions from 3 years of continuous capture plant operation without exchange of the AMP/PZ-based solvent at Niederaussem – insights into solvent degradation management

A many times heard mantra of solvent degradation management in amine-based post combustion capture is “keep the solvent clean” to minimize solvent consumption. It is assumed that the amine losses would decrease by the removal of metals, degradation products, and reactive trace components which are captured from the flue gas, like NO 2 (as potentially driving components of the amine degradation besides dissolved O 2 ). However, this theoretical hypothesis – based on results from laboratory experiments typically generated with fresh amines – disregards the complexity of the solvent matrix, interaction of potential metal catalysts with degradation products and oxidizing agents, and specific chemical requirements which must be fulfilled before a degradation mechanism can proceed. Degradation of the solvent CESAR1 (aqueous solution of 3.0 molar 2-amino-2-methylpropan-1-ol (AMP) and 1.5 molar piperazine (PZ)) is investigated in a unique long-time test campaign (testing time up to now 40 months; 24/7 operation) without replacement of the solvent inventory at the capture pilot plant at the lignite-fired power plant in Niederaussem. Three solvent management strategies with different effect mechanisms are investigated and evaluated: (a) removal of only anionic compounds and trace elements (within 75 days solvent inventory treated two times) and anionic as well as cationic compounds and trace elements (114 days, inventory treated four times) from the solvent by ion exchange, (b) adsorptive removal of trace elements from the solvent by active carbon in 35% of the operating time, and (c) removal of >80% NO 2 by flue gas pretreatment with thiosulfate/sulfite solution (dosing for 2,000 h). The results of the testing program clearly show that “solvent cleanliness” is not a well-defined parameter and that results from laboratory tests, tests without fully representative industrial flue gasses, and short-term testing of monoethanolamine cannot be generalized for other solvents and industrial application. Furthermore, these results showcase that specific degradation management considering solvent, capture plant and flue gas quality is reasonable. Overshooting efforts for solvent management are contra-productive and produce unnecessary waste streams, efficiency losses and costs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mn(III)-mediated bisphenol a degradation: Mechanisms and products

Bisphenol A (BPA) is a high production volume chemical with potential estrogenic effects susceptible to abiotic degradation by MnO 2 . BPA transformation products and reaction mechanisms with MnO 2 have been investigated, but detailed process understanding of Mn(III)-mediated degradation has not been attained. Rapid consumption of BPA occurred in batch reaction vessels with 1 mM Mn(III) and 63.9 ± 0.7% of 1.76 ± 0.02 μmol BPA was degraded in 1 hour at circumneutral pH. BPA was consumed at 1.86 ± 0.09-fold higher rates in vessels with synthetic MnO 2 comprising approximately 13 mol% surface-associated Mn(III) versus surface-Mn(III)-free MnO 2 , and 10–35% of BPA transformation could be attributed to Mn(III) during the initial 10-min reaction phase. High-resolution tandem mass spectrometry (HRMS/MS) analysis detected eight transformation intermediates in reactions with Mn(III), and quantum calculations proposed 14 BPA degradation products, nine of which had not been observed during MnO 2 -mediated BPA degradation, suggesting mechanistic differences between Mn(III)- versus MnO 2 -mediated BPA degradation. Finally, the findings demonstrate that both Mn(III) and Mn(IV) can effectively degrade BPA and indicate that surface-associated Mn(III) increases the reactivity of synthetic MnO 2 , offering opportunities for engineering more reactive oxidized Mn species for BPA removal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Targeted protein degradation: from small molecules to complex organelles—a Keystone Symposia report

Targeted protein degradation is critical for proper cellular function and development. Protein degradation pathways, such as the ubiquitin proteasomes system, autophagy, and endosome–lysosome pathway, must be tightly regulated to ensure proper elimination of misfolded and aggregated proteins and regulate changing protein levels during cellular differentiation, while ensuring that normal proteins remain unscathed. Protein degradation pathways have also garnered interest as a means to selectively eliminate target proteins that may be difficult to inhibit via other mechanisms. Additionally, on June 7 and 8, 2021, several experts in protein degradation pathways met virtually for the Keystone eSymposium “Targeting protein degradation: from small molecules to complex organelles.” The event brought together researchers working in different protein degradation pathways in an effort to begin to develop a holistic, integrated vision of protein degradation that incorporates all the major pathways to understand how changes in them can lead to disease pathology and, alternatively, how they can be leveraged for novel therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring novel alkane-degradation pathways in uncultured bacteria from the North Atlantic Ocean

Microbes play a significant role in the degradation of petroleum hydrocarbons in the oceans, yet little is known about the native bacteria that metabolize hydrocarbons before an oil spill. The Faroe-Shetland Channel (FSC) is a deepwater subarctic region of the North Atlantic with prominent oil production and a diverse microbial community associated with the degradation of petroleum. Here, we combine DNA-based stable-isotope probing (DNA-SIP) with metagenomics to elucidate the metabolic underpinnings of native alkane-degrading bacteria from the FSC. From two 13C n-hexadecane SIP experiments using seawater from 5 and 700 m depths in the FSC, we obtained 42 metagenome-assembled genomes (MAGs) belonging to 19 genera, including two previously overlooked hydrocarbon-degrading bacteria, Lentibacter (Alphaproteobacteria) and Dokdonia (Bacteroidetes). Diversity surveys indicated Lentibacter were dominant members of the FSC, constituting up to 17% of these communities. Many of the SIP-enriched MAGs (20/42) encoded a complete alkane oxidation pathway, including alkane monooxygenase (AlkB), rubredoxin reductase (AlkT), and rubredoxin-2 (AlkG). Fourteen Aphaproteobacteria MAGs lacked AlkG for electron transfer. Instead, they encoded novel disulfide isomerases with iron-binding cysteine motifs conserved across rubredoxins. Dokdonia lacked AlkT and AlkG, however, their central alkane-degradation catabolic pathways were complete. We describe previously unrecognized bacteria capable of hydrocarbon degradation, including the dominant genera Lentibacter, which may continuously purge hydrocarbons released from oil exploration activities in the FSC. This advances the understanding of the diversity and physiologies of alkane degradation in the North Atlantic and provides evidence of new mechanisms used to metabolize alkanes.

59 BASIC BIOLOGICAL SCIENCES↗

Effects of forest degradation classification on the uncertainty of aboveground carbon estimates in the Amazon

Tropical forests are critical for the global carbon budget, yet they have been threatened by deforestation and forest degradation by fire, selective logging, and fragmentation. Existing uncertainties on land cover classification and in biomass estimates hinder accurate attribution of carbon emissions to specific forest classes. In this study, we used textural metrics derived from PlanetScope images to implement a probabilistic classification framework to identify intact, logged and burned forests in three Amazonian sites. We also estimated biomass for these forest classes using airborne lidar and compared biomass uncertainties using the lidar-derived estimates only to biomass uncertainties considering the forest degradation classification as well. Our classification approach reached overall accuracy of 0.86, with accuracy at individual sites varying from 0.69 to 0.93. Logged forests showed variable biomass changes, while burned forests showed an average carbon loss of 35%. We found that including uncertainty in forest degradation classification significantly increased uncertainty and decreased estimates of mean carbon density in two of the three test sites. Our findings indicate that the attribution of biomass changes to forest degradation classes needs to account for the uncertainty in forest degradation classification. By combining very high-resolution images with lidar data, we could attribute carbon stock changes to specific pathways of forest degradation. This approach also allows quantifying uncertainties of carbon emissions associated with forest degradation through logging and fire. Both the attribution and uncertainty quantification provide critical information for national greenhouse gas inventories.

54 ENVIRONMENTAL SCIENCES↗

Degradation and Accelerated Recovery of Surface Passivation in n+ Poly-Si/SiOx Passivating Contacts for TOPCon Solar Cells

We studied the surface degradation and recovery of fired poly-Si/SiOx passivating contacts during subsequent dark and illuminated annealing. We report on an industrially-viable path for accelerated recovery of surface passivation. The degradation is influenced by the type of doping in the poly-Si. Phosphorus doped n+ poly-Si/SiOx contacts show degradation followed by recovery, undoped poly-Si/SiOx contacts only show recovery during annealing. Boron doped p+ poly-Si/SiOx contacts show neither degradation nor improvement with annealing. Both degradation and recovery are thermally-activated processes and are completely reversible and cyclic in nature. The activation energy of degradation and recovery in dark for n+ poly-Si/SiOx contacts are 1.27 and 1.33 eV respectively. Dark annealing at elevated temperatures is effective for complete recovery but takes a long time (~30 min at 350 degrees C) due to higher activation energies. Annealing under 7.5 Suns of illumination lowers the activation energy for degradation and recovery to 0.88 and 0.90 eV, respectively. Using this data, we have developed an industrially viable post-firing treatment for accelerated recovery of TOPCon cells by annealing them at elevated temperatures and under intense illumination for a few minutes.

14 SOLAR ENERGY↗

Insulation Resistance Degradation in Ni-BaTiO3 Multilayer Ceramic Capacitors

Insulation resistance (IR) degradation in NiBaTiO3 multilayer ceramic capacitors has been characterized by the measurement of both time to failure (TTF) and direct current leakage current as a function of stress time under highly accelerated life test conditions. The measured leakage current time dependence data fit well to an exponential form, and a characteristic growth time tau (sub SD) can be determined. A greater value of tau (sub SD) represents a slower IR degradation process. Oxygen vacancy migration and localization at the grain boundary region results in the reduction of the Schottky barrier height and has been found to be the main reason for IR degradation in NiBaTiO3 capacitors. The reduction of barrier height as a function oftime follows an exponential relation of phi (t ) = phi (0) e (exp -2Kt), where 13 the degradation rate constant K Koe (Ek/kT) is inversely proportional to the mean TTF (MTTF) and can be determined using an Arrhenius plot. For oxygen vacancy electromigration, a lower barrier height phi (0) will favor a slow IR degradation process, but a lower phi (0) will also promote electronic carrier conduction across the barrier and decrease the IR. As a result, a moderate barrier height phi (0) (and therefore a moderate IR value) with a longer MTTF (smaller degradation rate constant K) will result in a minimized IR degradation process and the most improved reliability in NiBaTiO3 multilayer ceramic capacitors.

reliability↗

Insulation Resistance Degradation in Ni-BaTiO3 Multilayer Ceramic Capacitors

Insulation resistance (IR) degradation in Ni-BaTiO3 multilayer ceramic capacitors has been characterized by the measurement of both time to failure and direct-current (DC) leakage current as a function of stress time under highly accelerated life test conditions. The measured leakage current-time dependence data fit well to an exponential form, and a characteristic growth time SD can be determined. A greater value of tau(sub SD) represents a slower IR degradation process. Oxygen vacancy migration and localization at the grain boundary region results in the reduction of the Schottky barrier height and has been found to be the main reason for IR degradation in Ni-BaTiO3 capacitors. The reduction of barrier height as a function of time follows an exponential relation of phi (𝑡)=phi (0)e(exp -2Κt), where the degradation rate constant 𝐾=𝐾o𝑒(𝐸𝑘/𝑘𝑇) is inversely proportional to the mean time to failure (MTTF) and can be determined using an Arrhenius plot. For oxygen vacancy electromigration, a lower barrier height phi(0) will favor a slow IR degradation process, but a lower phi(0) will also promote electronic carrier conduction across the barrier and decrease the insulation resistance. As a result, a moderate barrier height phi(0) (and therefore a moderate IR value) with a longer MTTF (smaller degradation rate constant 𝐾) will result in a minimized IR degradation process and the most improved reliability in Ni-BaTiO3 multilayer ceramic capacitors.

dielectric degradation↗

Using Degradation Modeling to Identify Fragile Operational Conditions in Human- and Component-driven Resilience Assessment

Studying failure events shows that many high-impact events result from the complex interactions between precipitating failure events and degraded operational conditions. Often, when a system is put in operations, unforeseen practical realities (e.g., maintenance and/or workforce availability) lead the system to be operated in configurations outside its envisioned nominal range. However, design-time failure models often assume that the failure events are initiated in an idealized, nominal state of system operation, resulting in an incomplete assessment of future risk. To solve this, this paper develops a framework to consider degraded operational performance in scenario-based resilience models which uses a corresponding model of performance degradation to determine the values of deteriorated model parameters in the resilience model. This framework is demonstrated on a remotely-piloted rover to determine the (individual and combined) effect of drive-train wear and operator fatigue on the resilience of the rover to drive-train faults. This demonstration showed the substantial impact that degradation has on resilience, highlighting the need to account for degradation in resilience models–specifically, unconsidered degradation can lead to overestimates of resilience (and thus underestimates of safety margin) and because resilience can degrade prior to visible unreliability, which can lead to an operational environment with a high propensity for high-impact unforeseen failure events.

resilience↗

Deciphering Degradation: Machine Learning on Real-World Performance Data (Final Report)

This project addresses a fundamental flaw in solar PV research and solar project financing; the assumed rate of degradation for solar plants. The solar industry currently relies on an out-dated report that observed a 0.5% degradation rate based on a small sample size of systems (~100). While the research conducted at the time was new and innovative, the solar community has not updated this research and universally applies this 0.5% degradation assumption in financial models. Our project updates this assumption by analyzing observed degradation from the industry’s largest dataset of operating solar assets (>10,000 systems) and creating the first machine-learning model based on these observed results to quantify and identify features that drive degradation. There are two strategic goals for this award: reduce the cost of capital (enable solar to attract more capital) and improve the reliability of solar itself. These dual goals are achieved by leveraging an industry dataset to observe system degradation on a large scale, deploying advanced data analysis and machine learning methods to quantify and predict system reliability, and engaging with industry stakeholders to help them accurately price degradation in financial models.

14 SOLAR ENERGY↗

PVDeg: Development of a Streamlined Tool for PV Degradation Modeling

The photovoltaic (PV) industry constantly aims for lower costs, higher-efficiency cells, and improved module designs. These trends lead to using new materials, designs, and manufacturing processes, resulting in a continually changing technological landscape. These changes can potentially introduce new, unknown degradation mechanisms and failure modes that are difficult to diagnose, analyze, test, and model. This introduces uncertainty into the expected lifetime of PV modules of 25 to 50 years. research efforts aim to achieve this while keeping performance degradation at a minimum for decades. This puts considerable pressure on improving the accuracy of long-term durability and reliability assessments. There is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. Because the core of this type of analysis involves calculations that are complicated but ubiquitous for many degradation processes, an enhanced predictive modeling framework will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this work, we present an online tool that can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. The tool will simplify many of the routine computational operations that are common to many degradation studies. The prediction tool will be built modular and published as open source, enabling users to expand on the existing framework. This repository will contain various degradation models and material parameters suitable for the reliability and durability assessment of materials and components deployed outdoors.

degradation↗

Multiscale Characterization of Photovoltaic Modules—Case Studies of Contact and Interconnect Degradation

The current popularity of photovoltaic (PV) systems is due in large part to their exceptional reliability and significantly lower cost than other energy sources. Studying cell and module degradation is key to promote further development in the state of the art. Fielded or accelerated aged modules exhibit different failure modes, of which metallization degradation (contacts and interconnections) is prevalent. In this work, we discuss how multiscale characterization methods can be applied to a variety of module technologies that have been field exposed and have undergone accelerated age testing. These methods include performing characterization on the module level, cell level, and finally the materials level. The observed performance losses from the module- and cell-level characterization can be correlated with materials properties to find out the root cause of degradation. We recommend an initial nondestructive characterization suite, including module- and cell-level current-voltage ( I--V ), Suns-V OC , photoluminescence and electroluminescence imaging, quantum efficiency, ultraviolet fluorescence imaging, and thermal infrared imaging. Samples are then extracted from particularly degraded regions of the module and prepared for materials characterization techniques, such as top-down and cross-sectional scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, secondary ion mass spectrometry, Raman spectroscopy, and transmission electron microscopy, allowing a deeper look into the mechanism behind the metallization degradation. This article serves as an instructional review to introduce the different multiscale characterization methods and how they can be effectively applied to perform PV degradation studies. Furthermore, we also share some of our examples and discuss the strengths, limitations, and best practices for each of the characterization techniques.

14 SOLAR ENERGY↗