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At least 379 records · Page 21

Organic Carbon Concentrations in 3-Billion-Year-Old Lacustrine Mudstones of Mars

Understanding the inventory of carbon on Mars is relevant to the question of whether Mars was ever habitable. While the Mars atmosphere represents a large reservoir of carbon, in situ pyrolysis performed on Mars and meteorite analyses indicate that another significant reservoir of carbon is the rocks themselves. Complex organic carbon was discovered in 3.5 Ga mudstones sampled at Cumberland (CB) in the Yellowknife Bay Formation in Gale Crater by the Sample Analysis at Mars (SAM) instrument suite on the Mars Science Laboratory (MSL) using a thermal decomposition technique called evolved gas analysis (EGA). Other simple organics have also been detected in these same CB materials. Low temperature co-evolution of CO and CO2 (~200°C – 500°C) has been detected in many samples from Gale Crater where SAM EGA has been performed, and potential sources include combustion of terrestrial organics from SAM, as well as combustion and/or decarboxylation of either indigenous martian or exogenous organic carbon.

J. C. Stern↗

Redesigning large-scale multimodal transit networks with shared autonomous mobility services

Here, this study addresses a large-scale multimodal transit network design problem, with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an origin-to-destination mode. The framework captures spatial demand and modal characteristics, considers intermodal transfers and express services, determines transit infrastructure investment and path flows, and generates transit routes. A system-optimal multimodal transit network is designed with minimum total door-to-door generalized costs of users and operators, satisfying transit origin-destination demand within a pre-set infrastructure budget. Firstly, the geography, demand, and modes in each zone are characterized with continuous approximation. The decisions of network link investment and multimodal path flows in zonal connection optimization are formulated as a minimum-cost multi-commodity network flow (MCNF) problem and solved efficiently with a mixed-integer linear programming (MILP) solver. Subsequently, the route generation problem is solved by expanding the MCNF formulation to minimize intramodal transfers. The model is illustrated through a set of experiments with the Chicago network comprised of 50 zones and seven modes, under three scenarios. The computational results present savings in traveler journey time and operator cost demonstrating the potential benefits of collaboration between multimodal transit systems and SAMS.

Autonomous vehicles↗

A New 1D Model for Thermal Mixing and Stratification in Advanced Reactor Transients

Thermal mixing and stratification in large pools and enclosures play a critical role in the safety and performance of pool-type nuclear reactors, particularly during transient scenarios involving significant temperature differences between incoming and bulk coolant. Accurate modeling of these phenomena is essential for predicting system behavior and supporting passive safety features such as natural circulation. Here, this paper presents a new 1D model for thermal mixing and stratification, developed and implemented in the SAM code. The model represents a large pool as 1D coolant jet channels and zero-dimensional bulk pool volumes, enabling the simulation of a wide range of flow configurations, including hot and cold jet interactions, stratified layers, and the influence of complex geometries such as ceilings, free surfaces, and internal obstacles. Heat exchange between jet and pool regions is governed by closure relations calibrated against 3D computational fluid dynamics (CFD) simulations. The model improves upon earlier approaches by incorporating time-dependent jet characteristics and capturing the associated delay effects more accurately. Code-to-code comparisons and validation against experimental data from the Thermal Stratification Test Facility demonstrate the model’s accuracy and flexibility. This work offers two key contributions: (1) an efficient and robust method for simulating thermal mixing and stratification at the system level, eliminating the need for external coupling between system analysis codes and CFD, and (2) a significant enhancement of SAM’s capabilities to analyze thermal stratification phenomena in advanced reactor systems.

SAM↗

High-Temperature Gas-Cooled Pebble-Bed Reactors Running In And Transient Modeling Capabilities Demonstration

This study presents a comprehensive benchmarking and verification effort of several thermal-hydraulic and multiphysics capabilities for high-temperature gas-cooled reactor (HTGR) applications. The first part of this effort focuses on the running-in verification of Griffin's multiphysics capabilities, specifically for simulating the evolution of Pebble Bed reactor cores from startup to equilibrium. In the absence of validation data, code-to-code comparisons are conducted with Kugelpy, showing good agreement for key quantities like maximum power density and fresh core k-eigenvalue predictions. However, discrepancies in equilibrium core predictions suggest potential issues with cross sections, underscoring the need for further refinement and evaluation. The HTTF system analysis code benchmark involves RELAP5-3D, SAM, and GAMMA+ to assess their predictive capabilities for HTTF behavior under both normal operation and pressurized conduction cooldown (PCC) transient conditions. While there is good agreement in predicting major parameters such as coolant temperature, solid temperature, and flow distribution, discrepancies in transient behavior highlight differences in modeling approaches, nodalizations, and heat transfer models. The HTTF lower plenum CFD benchmark employs nekRS to simulate flow mixing phenomena, successfully capturing relevant flow physics and demonstrating mesh independence in complex geometries. Preliminary results suggest a relatively uniform temperature field but significant unsteadiness in the flow, requiring time-averaging analyses. The GPBR200 system analysis code benchmark uses SAM's core channel and porous media models, incorporating an RCCS loop for decay heat removal. During steady-state and transient conditions, including protected de-pressurized and pressurized loss of forced cooling (DLOFC and PLOFC), both models show good agreement in predicting temperature profiles and key parameters. Notably, while the core channel model underpredicts convective heat transfer effects, both models maintain temperatures well below the TRISO fuel safety limit. These benchmarking efforts collectively enhance the predictive capabilities of the tools used in HTGR design and safety analysis, guiding developments to improve their accuracy and applicability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Perchlorate and Volatiles of the Brine of Lake Vida (Antarctica): Implication for the in Situ Analysis of Mars Sediments

The cold (-13.4 C), cryoencapsulated, anoxic, interstitial brine of the 27 m-thick ice of Lake Vida (Victoria Valley, Antarctica) contains 49 microgram L-1 of perchlorate and 11 microgram L-1 of chlorate. Lake Vida brine (LVBr) may provide an analog for potential oxychlorine-rich subsurface brine on Mars. LVBr volatiles were analyzed by solid-phase microextraction (SPME) gas chromatography-mass spectrometry (GC-MS) with two different SPME fibers. With the exception of volatile organic sulfur compounds, most other volatiles observed were artifacts produced in the GC injector when the thermal decomposition products of oxychlorines reacted with reduced carbon derived from LVBr and the SPME fiber phases. Analysis of MilliQ water with perchlorate (40 microgram L-1) showed low level of organic artifacts, reflecting carbon limitation. In order to observe sample-derived organic compounds, both in analog samples and on Mars, the molar abundance of reduced carbon in a sample must exceed those of O2 and Cl2 produced during decomposition of oxychlorines. This suggests that the abundance of compounds observed by the Sample Analysis at Mars (SAM) instruments in Sheepbed samples (CB-3, CB5, and CB6) may be controlled by an increase in the reduced-carbon/oxychlorine ratio of these samples. To increase chances of in situ detection of Martian organics during pyrolysis-GC-MS, we propose that the derivatization agents stored on SAM may be used as an external source of reduced carbon, increasing artificially the reduced-carbon to perchlorate ratio during pyrolysis, allowing the expression of more abundant and perhaps more diverse Martian organic matter.

Mars analog experiment↗

Mapping Rare Earths and Toxics in E-Waste via Hyperspectral Imaging and Machine Learning

Electronic waste (e-waste) presents a mounting challenge to environmental sustainability due to its complex composition, which includes high-value rare earth elements, hazardous organic compounds, and non-recyclable plastics. Accurate and scalable material classification is essential for enabling efficient resource recovery and safe recycling practices. This study introduces a confidence-aware classification pipeline that combines mid-infrared hyperspectral imaging (HSI), spectral angle mapping (SAM), and iterative machine learning to perform pixel-level material identification across e-waste devices. A curated spectral library encompassing artificial materials (e.g., plastic iron oxide, galvanized metals), minerals (e.g., allanite, hematite), and organic compounds (e.g., benzanthracene, toluene) was used to generate pseudo-labels, each assigned a confidence score based on SAM-derived spectral similarity. High-confidence samples from seven consumer electronics—digital cameras, keyboards, laptop fans, modems, motherboards, TV remotes, and speakers—were iteratively expanded and classified using models such as Support Vector Machine (SVM), Random Forest, Gradient Boosting Classifier, Partial Least Squares Discriminant Analysis (PLSDA) and Logistic Regression. The best-performing classifiers achieved macro F1 scores approaching 1.0. Results revealed widespread plastic content (dominated by plastic iron oxide), the presence of rare earth-bearing minerals like cerium-containing allanite, and pervasive detection of hazardous organics such as benzanthracene. Principal Component Analysis (PCA) visualizations and confusion matrices confirmed high separability and robust classification performance. This methodology enables precise, non-destructive, and scalable classification of heterogeneous e-waste streams. It supports automated, hazard-aware sorting in recycling workflows, facilitating selective recovery of critical materials and compliance with circular economy goals. The confidence-aware framework provides a foundation for real-time deployment in industrial settings, offering significant implications for smart e-recycling infrastructure and policy-driven material stewardship.

Circular economy↗

A methodology for domain overlapping coupling of thermal-hydraulic systems

Multi-scale coupling has increasingly drawn attention as a promising approach for modeling thermal systems. Traditional system codes provide fast and robust predictions at the plant scale, while high-fidelity computational fluid dynamics (CFD)-based tools resolve localized flow and heat transfer phenomena with greater accuracy. By combining these complementary strengths, co-simulations enable multi-scale analysis that would otherwise be computationally prohibitive for a standalone CFD code. Here, this work introduces a robust and problem-agnostic domain overlapping (DO) coupling between the system thermal-hydraulic (STH) code System Analysis Module (SAM) and the coarse-mesh CFD code Pronghorn. Both applications belong to the Comprehensive Reactor Analysis Bundle (BlueCRAB) code suite, a code suite in active development at the Idaho National Laboratory (INL), tailored for multi-physics analysis of advanced reactors. Unlike previous approaches, BlueCRAB supports an agnostic interface between codes based on different fidelity, while its coupling formulation can address arbitrary flow geometries with multiple inlets and outlets in coupled components. The implemented method leads to consistent pressure drops, enthalpies, and scalar concentrations between coupled SAM and Pronghorn simulations. The methodology is demonstrated through two verification tests, which ensure the numerical consistency and conservation across the codes, and through one validation test against experimental data. The proposed problems explore different physical aspects inherent to thermal systems, with particular attention given to nuclear reactor analysis. These include buoyancy-driven flows, complex flow patterns, and setups with multiple inlets and outlets, representing challenges in advanced reactor applications.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Toward Lithium Recovery Using Modular (and Membraneless) Phase Separation and Extraction (MPSE) Technology with Ionic Liquid (IL) Solvents: Effect of Coatings

In this work, a single-channel slope-plate Modular and Membrane-less Phase Separation and Extraction (MPSE) device was fabricated using 3D printing. The slope-plate was designed with an insertable glass slide to enable surface modification with coatings. Self-assembled monolayers (SAMs) and perfluoropolyether (Zdol) coatings were applied to tailor surface wettability and enhance phase separation. Using a model biphasic system of water and hexadecane, both coatings significantly improved the separation efficiency compared to the uncoated device by promoting selective wetting. Building on these results, lithium extraction from a simulated saline solution was investigated using 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][NTf₂]) as the ionic liquid (IL) extractant. The IL effectively extracted Li⁺ from the aqueous phase in bulk extraction, demonstrating its potential for lithium recovery. However, the low interfacial tension between the IL and aqueous phases posed challenges for phase separation. The application of SAM and Zdol coatings effectively mitigated this issue. Overall, integrating tailored surface chemistry with the slope-plate MPSE design shows great promise as an efficient and scalable platform for studying liquid–liquid separation and optimizing ionic liquid–based extraction processes for lithium recovery from saline sources.

3D printing↗

Amino Acid Sequence Controls Enhanced Electron Transport in Heme-Binding Peptide Monolayers

Metal-binding proteins have the exceptional ability to facilitate long-range electron transport in nature. Despite recent progress, the sequence-structure–function relationships governing electron transport in heme-binding peptides and protein assemblies are not yet fully understood. In this work, the electronic properties of a series of heme-binding peptides inspired by cytochrome bc1 are studied using a combination of molecular electronics experiments, molecular modeling, and simulation. Self-assembled monolayers (SAMs) are prepared using sequence-defined heme-binding peptides capable of forming helical secondary structures. Following monolayer formation, the structural properties and chemical composition of assembled peptides are determined using atomic force microscopy and X-ray photoelectron spectroscopy, and the electronic properties (current density–voltage response) are characterized using a soft contact liquid metal electrode method based on eutectic gallium–indium alloys (EGaIn). Our results show a substantial 1000-fold increase in current density across SAM junctions upon addition of heme compared to identical peptide sequences in the absence of heme, while maintaining a constant junction thickness. These findings show that amino acid composition and sequence directly control enhancements in electron transport in heme-binding peptides. Overall, this study demonstrates the potential of using sequence-defined synthetic peptides inspired by nature as functional bioelectronic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Connecting Interfacial Mechanical Adhesion, Efficiency, and Operational Stability in High Performance Inverted Perovskite Solar Cells

Carbazole-based self-assembled monolayers (SAMs) at the interface between the metal-halide perovskite (MHP) and the transparent conducting oxide (TCO) serve the function of hole-transport layers in p-i-n "inverted" perovskite solar cells (PSCs). In this report we show that the use of an iodine-terminated carbazole-based SAM increases the interfacial mechanical adhesion dramatically (2.6-fold) and that this is responsible for substantial improvements in the interfacial morphology, photocarrier transport, and operational stability. While the improved morphology and optoelectronic properties impart high efficiency (up to 25.39%) to the PSCs, the enhanced adhesion suppresses nucleation and propagation of pores/cracks during PSC operation, resulting in the retention of 96% of the initial efficiency after 1000 h of continuous-illumination testing at the maximum power-point. This demonstrates the strong connection between judicious interfacial adhesion toughening and simultaneous enhancement in the efficiency and operational stability of p-i-n PSCs, with broader implications for the reliability and durability of perovskite photovoltaics before they can be commercialized.

14 SOLAR ENERGY↗

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗

Phonon-mediated ultrafast dynamics in self-assembled monolayers of 4-mercaptobenzoic acid on gold

Non-equilibrium interactions between plasmonic metals and adsorbed molecules lie at the heart of emerging applications such as plasmonic photocatalysis and sensing, though the ultrafast charge and energy transfer mechanisms arising from these interactions are not well understood. Herein, we investigate the ultrafast dynamics of Au nano-islands tethered with a self-assembled monolayer (SAM) of electron-withdrawing 4-mercaptobenzoic acid (4MBA) molecules. Ultrafast UV-visible transient absorption spectroscopy following excitation of the interband transition in Au reveals three well-known, characteristic time constants that quantify electron–electron (el–el), electron–phonon (el–ph) and phonon–phonon (ph–ph) scattering lifetimes. When comparing the dynamics of bare Au and 4MBA-Au, we find that the el–ph and ph–ph scattering lifetimes are notably longer in 4MBA-Au. Density functional perturbation theory calculations ascribe the elongation in el–ph lifetimes in 4MBA-Au to the significant coupling of acoustic phonon modes of Au with certain molecular vibrations of 4MBA, leading to decreased spatial overlap between carrier electronic states and the acoustic modes. We speculate that the elongation of ph–ph scattering lifetimes in 4MBA-Au arises due to poor thermal conductivity of the SAM which disrupts efficient energy dissipation from Au to the environment, thus slowing down the thermalization of phonons. This work provides a glimpse into how molecular adsorbates modify the charge carrier and phonon dynamics of Au and sets the stage for further systematic exploration of plasmonic metal–molecule interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

S-adenosyl-L-methionine is the unexpected methyl donor for the methylation of mercury by the membrane-associated HgcAB complex

Mercury (Hg) is a heavy metal that exhibits high biological toxicity. Monomethylmercury and dimethylmercury are neurotoxins and a significant environmental concern as they bioaccumulate and biomagnify within the aquatic food web. Microbial Hg methylation involves two proteins, HgcA and HgcB. Here, we show that HgcA and HgcB can be heterologously coexpressed, and the HgcAB complex can be purified. We demonstrated that HgcA is a membrane-associated cobalamin-dependent methyltransferase and HgcB is a ferredoxin-like protein containing two [4Fe-4S] clusters. Further, spectroscopic and kinetic results demonstrate that S-adenosyl-L-methionine (SAM) donates the methyl group to Hg in a two-step reaction involving a methylcob(III)alamin intermediate including Co-thiolate ligation from a conserved Cys residue. Our findings uncover a biological role for SAM in microbial Hg methylation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Numerical Simulation and Experimental Comparison of System Analysis Module 1D Mixing Model for Cold Shock Transients in the Gallium Thermal-Hydraulic Mixing Facility

Abstract Liquid metals are being investigated as coolants in many advanced reactor designs because of their high thermal conductivity and effectiveness at high temperatures. However, they often pose challenges to reactor operation and safety because of the complex thermal mixing and stratification in the plenum of pool-type reactor designs. The advanced system analysis code System Analysis Module (SAM) currently under development at Argonne National Laboratory aims to develop and implement thermal mixing models to accurately capture these complex thermal fluid behaviors. In this study, the SAM thermal mixing model was compared against experimental data from the Gallium Thermal-Hydraulic Experiment facility, a scaled liquid metal test facility that uses gallium as a surrogate fluid to investigate the stratification and thermal mixing of low-Prandtl-number fluids in the upper plenum of a liquid metal-cooled reactor. Two cold shock transient cases were used: one with stable stratified flow (Ri = 32) and one with stronger thermal mixing (Ri = 0.5). The resultant temperatures were then compared with the experimental temperatures over the entire plenum to assess the ability of the mixing models to capture the thermal behavior and to better correspond mixing parameters to various flow scenarios. Generally, the zero-dimensional mixing model was more capable of capturing the bulk temperature of the component modeled assuming that an accurate mass flow rate was provided, but it was inherently unable to capture thermal gradients in space. The one-dimensional mixing model was capable of capturing that the thermal gradients provided accurate selection of the mixing coefficients. Further, the temperature at the outlet junction was compared over time for each of the mixing models with the recorded experimental temperature. The implemented mixing models demonstrated the ability to effectively capture the overall thermal behavior for stronger mixing scenarios but struggled with more stably stratified flows. It was found that a system analysis code's covering of the entire range of different operating conditions still remains a challenging task, and it is suggested that further model and closure improvements are necessary to accurately capture complex thermal mixing and stratification phenomena.

stratification↗

Development and Experimental Validation of a Heat Transfer Model for Spilled Molten Salt Pools

A spill of radionuclide-bearing molten salt is one of the major postulated events that needs to be analyzed for liquid fluorine salt-cooled high-temperature reactor (FHR) or molten salt reactor licensing purposes. In this postulated event, radioactive source term materials (RSTMs) in the molten salt are discharged from the reactor vessel to the reactor building. The release of RSTMs from the spilled salt pool to the gas space in the reactor building is expected to be controlled by the cooling behavior of the spilled salt, including the growth and shrinkage of the solid crust on the surface of the spilled salt pool. This paper presents a simulation model for spilled salt pool heat transfer and validation efforts. The validation data come from two molten salt spill tests that were performed recently: the PELE2 test by the Rapid Experimental Laboratory of Kairos Power LLC (KP) and the Argonne salt cooling test conducted by Argonne National Laboratory. The former was a large-scale test involving kilograms of molten spilled FLiNaK salt, and the latter was a relatively smaller-scale test targeting various processes associated with a salt spill event. Both tests generated valuable data sets that can be used to assess salt cooling and validate evaluation models. This paper provides a new one-dimensional model that can simulate the cooling process of a spilled salt pool as well as the thermal responses of heat structures, such as the stainless steel liner and the concrete below the salt. The model has been implemented as part of KP-SAM code, which is a branch of the systems code SAM specific to KP FHR. In conclusion, the simulation results of the model are compared with the data of the PELE2 and Argonne tests, and reasonable agreements are observed between the model and test data.

heat transfer model↗

Multiphase Species Transport Modeling for Molten Salt Reactors in the System Analysis Module: Generation, Decay, Deposition, and Extraction of Insoluble Fission Products

With the increase of interests in the design and deployment of advanced reactor systems, a desire for simulation tools supporting system analysis of reactor operation and safety is rising. Molten salt reactors (MSRs), one of the advanced reactor systems, utilize liquid fused salt fuel as both coolant and fuel. During operation, MSR generates insoluble fission products, including noble metals and gases. The buildup of these species in fuel salt presents safety concerns as they may deposit on surfaces of critical components and produce excessive decay heat, causing the failure of system components. Timely removal of these noble metals and gases would ensure the safe operation of the reactor system. The dynamic nature of salt fuel system, involving the generation, decay, deposition, and extraction of noble metals and gases, calls for robust species transport models to facilitate system analysis and monitoring, and design of efficient species removal components. This paper concentrates on the development of a computational framework for species transport, consisting of multiphase transport model formulation, mass transfer between phases, numerical implementation in MOOSE environment, verification through Method of Manufacture Solutions (MMS) and validation against experimental data from the Molten Salt Reactor Experiment (MSRE). Integrating this framework into the System Analysis Module (SAM) code further enhances SAM’s capabilities for advanced reactor analysis in the future.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Thermomechanical Degradation of Sintered Copper Under High-Temperature Thermal Shock

The need for reliable bonded interface materials is critical to realize the performance benefits of wide-bandgap devices in power electronics modules, especially in operating temperatures greater than 150 degrees C. In this paper, we investigate the thermomechanical performance of sintered copper (Cu) as a large-area attachment, bonded between Cu baseplates and active-metal-bonded substrates, under accelerated thermal shock (-40 degrees C to 200 degrees C) conditions. In the fabrication phase of the samples, we used different stencil patterns and found that the grid and stripe patterns resulted in a better outgassing of the residual organics during the sintering process, thereby ensuring a substantially improved bond quality compared to a full-area print. The paste consisted of Cu microflakes, and we performed sintering using a Budatec SP300 sintering press at 275 degrees C with 15 MPa of bonding pressure for 5 minutes in a nitrogen atmosphere. Under accelerated experiments, we monitored the degradation of the sintered Cu bond in the samples through C-mode scanning acoustic microscope (C-SAM) images. To quantify the defect percentage in C-SAM images, we investigated image denoising techniques to exclude the pattern prints. Finally, we cross-sectioned a sample and obtained scanning electron microscope images, which revealed adhesive fracture as the dominant failure mechanism.

ADVANCED PROPULSION SYSTEMS,INORGANIC, ORGANIC, PH↗

Diagnosis of PV Cell Antireflective Coating Degradation Resulting From Hot-Humid High-Voltage Potential Aging

Corrosion of the antireflective coating on a photovoltaic cell ("ARc corrosion") has previously been observed in studies using hot-humid test conditions with external high-voltage (HV) bias. This study primarily focuses on known vulnerable legacy aluminum back surface field cells in mini-modules (MiMos) put through comparative stepped stress tests. Each cell type had MiMos at +1500 V, -1500 V, or unbiased ("Voc") potential, which were sequentially subjected to test conditions of 60 degrees C/60% relative humidity (RH) for 96 h, as in International Electrotechnical Commission Technical Specification 62804-1; 70 degrees C/70% RH for 200 h; and 85 degrees C/85% RH for 200 h. Characterizations at each step included visual camera and electroluminescence (EL) imaging, colorimetry, and current-voltage curve tracing. Final characterizations included: Suns-Voc, spatial mapping of external quantum efficiency, high-resolution photoluminescence, EL, and dark lock-in thermography imaging. Forensics were performed on extracted cores, including scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy, and scanning Auger microscopy (SAM). Forensics were also conducted on MiMos from previous studies that underwent stepped HV aging and separate outdoor aged full-sized modules. ARc corrosion was specifically seen for the glass/encapsulant/cell side of the +1500 V (HV+) stressed MiMos and modules. Appearance, color, and reflectance were the most distinguishing characteristics relative to glass corrosion, gridline corrosion and delamination, and other concurrent degradation modes. SEM/EDS and SAM identified the conversion of silicon nitride to hydrated silica, hydrous silica, or hydrated amorphous silica, which preferentially occurred at the edges and tips of the pyramidal textured cell surface.

14 SOLAR ENERGY↗