Coupons (mini-modules) experimental data
Adhesion testing results on mini-module coupons (cell/encapsulant/glass laminates) that were aged under the different accelerated aging conditions (outlined more in the DataHub URL).
accelerated aging↗
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Results for “sequential aging”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water‐Tagging Enabled Hydrologic Models
Determining the age distribution of water exiting a catchment is important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages, yet forward modeling of individual events may not systematically capture the full transit time distribution (TTD). Here, we present a “sequential precipitation input tagging” (SPIT) framework to tag all input precipitation at regular intervals during extended model simulations. Monthly tags over 7 years were applied at six National Ecological Observatory Network sites to calculate TTDs and derive mean virtual tracer age, $\overline{T_{V}}$, fractions of young water, F yw , and hydrologic tracer concentrations (water isotopes δ 18 O and δ 2 H) within a tagging enabled version of the Weather Research and Forecast hydrologic model (WRF-Hydro). Throughout seven simulation years, the fraction of simulated discharge derived from tagged events, F tag , increased each year, with the final year's F tag ranging from 66% to 100% and highlights the need to apply SPIT over many years to understand TTDs. When the F tag was >75%, simulated $\overline{T_{V}}$ ranged 179–923 days and F yw 0.6%–23.9%, with daily values exhibiting a power-law relationship with precipitation, discharge, and groundwater. Through implementation of SPIT, we find this hydrologic model configuration performs poorly in estimation of $\overline{T_{V}}$ and F yw (root mean squared error of 469 days and 14.4% respectively), suggesting it misrepresents subsurface mixing. Thus, the SPIT framework provides a reproducible approach to calculate watershed transit times within tagging enabled models and thereby assess and improve representation of hydrologic processes.
fraction of young water↗
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↗
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 (Al-BSF) 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 60deg C/60% relative humidity (RH) for 96 h, as in International Electrotechnical Commission (IEC) Technical Specification 62804-1; 70 deg C/70% RH for 200 h; and 85 deg C/85% RH for 200 h. Characterizations at each step included visual camera and electroluminescence (EL) imaging, colorimetry, and current-voltage (I-V) curve tracing. Final characterizations included: Suns-Voc; spatial mapping of external quantum efficiency (EQE); high-resolution photoluminescence (PL), EL, and dark lock-in thermography (DLIT) imaging. Forensics were performed on extracted cores, including scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), 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 +1500V (HV+) stressed MiMos and modules. Appearance, color, and reflectance were the most distinguishing characteristics relative to glass corrosion, gridline-corrosion and -delamination as well as other concurrent degradation modes. SEM/EDS and SAM identified 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↗
Effect of CO on alcohol oxidation over commercial oxidation catalysts for control of emissions from lean-burn engines
For commercialization, alcohol-based net-zero carbon fuels in diesel-driven internal combustion engines must meet emissions standards set by the U.S. Environmental Protection Agency. Here, a series of aged commercial oxidation catalysts, Pt diesel oxidation catalyst (DOC), Pd+Pt DOC, and Pt oxidation catalyst (Pt OC), were studied using an automated flow reactor and in situ DRIFTS techniques to investigate the impact of CO on alcohol oxidation. Surface formate and acetate intermediates were formed due to partial oxidation of methanol and ethanol, respectively. Sequential introduction of alcohol and CO experiments using in situ DRIFTS on all three catalysts showed that CO inhibited low temperature methanol oxidation. Mutual inhibition effects between CO and ethanol were observed during co-oxidation. Acetate species shifted CO oxidation to higher temperatures on Pt DOC and Pt OC, whereas CO pre-exposure inhibited acetate formation. CO oxidation occurred at lower temperatures during ethanol and CO co-oxidation on Pd+Pt DOC.
33 ADVANCED PROPULSION SYSTEMS↗
Understanding Solvent-Induced Glass Transition in Polymer Thin Films Using Absorption–Desorption Isotherms
The fundamental thermodynamic and mechanical underpinnings of polymer thin films exposed to solvent vapor are critical for the development of advanced nanolithography and high-performance coatings. This work investigates the solvent− polymer interactions of glassy thin films by using the solvent absorption−desorption isotherms. An analogous relationship to the Flory−Fox equation was observed between solvent−induced glass transition, swelling, Flory−Huggins interaction parameter, and molecular weight. Isothermal swelling measurements revealed that the glass transition trends are more robust in the absorption curve compared to desorption, contrary to previous reports. Excess osmotic pressure analysis of the isotherm provides a measure of the degree of physical aging in thin films annealed below the glass transition. This is further validated in the ordering of block copolymer (BCP) films annealed at low solvent activity. In agreement with the thermal analysis, free-surface plasticization effects become the most prominent below 100 nm. However, solvent annealing is largely dependent on solvent mass transport, as made evident by the strong dependence on solvent viscosity. From these observations, four general types of isotherms are identified that graphically capture distinct solvent−polymer interaction regimes. More broadly, these results inform solvent vapor annealing-induced self-assembly, sequential infiltration synthesis, membrane-based separations, adsorptive processes, and swelling-based responsive materials design.
Hendeniya, Nayanathara [Iowa State Univ., Ames, IA↗
Laser Powder Directed Energy Deposition of Steels for Nuclear Applications
This comprehensive investigation examines the structure–property relationships in two nuclear alloy systems—Alloy 709 (A709) austenitic stainless steel and Grade 92 (G-92) ferritic/martensitic (F/M) steel—manufactured via directed energy deposition (DED) for sodium-cooled fast reactor applications. This study establishes the fundamental mechanisms for controlling microstructures for optimizing the mechanical performance of additively manufactured nuclear materials through systematic heat treatment optimization and multiscale characterization. As-deposited A709 steel develops a complex multiscale strengthening architecture consisting of a fine cellular solidification structure with diameter of 2-3 µm within10–50 µm grains, elevated dislocation densities from rapid thermal cycling, and grain boundary precipitates that activate concurrent Hall–Petch, dislocation, and precipitation hardening mechanisms to achieve exceptional properties [yield strength (YS): 603 MPa, ultimate tensile strength (UTS): 844 MPa, Vickers hardness: 220 HV] that achieve a 44% superior strength compared to that of the wrought material. Heat treatments produce different results. Solution annealing (SA) dissolves the cellular structure and reduces the hardness to 190 HV. Precipitation treatment (PT) keeps the cellular structure but adds carbides, allowing the hardness to reach 205 HV. The best approach combines both treatments (SA+PT) and creates uniform precipitate distributions with M 23 C 6 carbides at the grain boundaries and MX carbonitrides in the matrix, achieving a hardness of 195 HV. However, directional differences persist, with a 12%–15% strength variation between orientations due to the inherited layered microstructural architecture that survives aggressive heat treatment. While tensile testing at 550°C demonstrates 40%–50% thermal softening with dynamic strain aging, DED A709 steel still maintains a 71% higher YS than that of the wrought material. Ion irradiation studies (100–400 dpa) of DED A709 steel reveal progressive radiation damage with increasing void density and radiation-induced segregation causing nickel enrichment and chromium depletion, which will ultimately compromise mechanical properties. As-deposited G-92 exhibits exceptional strength (UTS: 1650–1700 MPa, 430 HV) through a complex microstructure containing both ferrite and martensite phases, a high geometrically necessary dislocation (GND) density (17.04×10 14 /m 2 ), and fine carbides. Heat treatments create distinct changes. Normalizing produces fresh martensite with the highest hardness (460 HV) and an increased GND density (20.23×10 14 /m 2 ). Tempering develops dual precipitation systems and reduces the hardness to 290 HV. The optimal approach uses sequential normalizing plus tempering, achieving balanced properties with the lowest hardness (250 HV) and a reduced GND density (11.01×10 14 /m 2 ). A processing-dependent anisotropy is observed: horizontal specimens achieve superior ductile behavior, while vertical specimens exhibit brittle failure. A tempering heat treatment successfully mitigates this anisotropic behavior by transforming the hard martensitic as-deposited structure into tempered martensite enabling both horizontal and vertical specimens to exhibit similar stress–strain characteristics with visible necking behavior. Remarkably, testing at 550°C reveals a reversal in the anisotropy, where as-deposited specimens achieve near isotropy with superior thermal stability (a 15%–20% strength reduction), while tempered specimens develop an orientation dependence with a 25%–30% strength reduction. Both alloy systems demonstrate that DED processing creates specimens with a superior strength through refined microstructural features, though with distinct strengthening mechanisms—austenitic through cellular structures and precipitates versus F/M through phase transformations and precipitates. Heat treatment optimization requires alloy-specific approaches, with A709 benefiting from controlled precipitation while G-92 requires careful phase transformation control. The results show that DED manufacturing can produce nuclear materials with exceptional performance, but directional effects and temperature-dependent behavior must be carefully considered for reactor component design and qualification.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Fuel Property Effects on Stochastic Preignition Events During Engine Load Transitions
Stochastic preignition (SPI) is an abnormal combustion phenomenon that can cause catastrophic engine damage. There have been several proposed mechanisms of SPI, where a uniform source is still not certain, however, SPI tendencies have been shown to be influenced by engine operating conditions, oil composition, engine age, and fuel chemical and physical properties. Laboratory research and testing for SPI propensity is challenging given the stochastic nature of events, as well as the potential for significant degradation of the engine platform and measuring equipment over time. Thus, SPI specific experiments are generally conducted under either sustained or cyclic patterning of steady-state operating conditions to avoid the influence of transient engine boundary conditions on test parameters of interest (e.g. oil additive package, fuel properties, engine speed/load, etc.). In this work a cyclically varying SPI test sequence involves a 5 min engine warmup period at a low engine load of around 4 bar gross indicated mean effective pressure (IMEPg), followed by a transition to high load (~20 bar IMEPg) at a constant 2000 rev/min engine speed for a total of 25 min. This individual test sequence load schedule is then sequentially repeated 10 times to generate significant statistical data for analysis. This work examines the influence of fuel chemical and physical properties on SPI tendency during the unsteady portion of the 10-cycle sequence (the first 5 min of the high load operation in each sequence of the loading cycle) which has been discarded from previous analyses due to the uncertainty in engine operating and thermal boundary conditions. Results from this analysis suggest an increasing trend in the ratio of SPI events during the unsteady test period relative to the steady test period with increasing fuel Reid Vapor Pressure (RVP), implying differences in uncontrolled ignition source terms, possibly from, fuel wall interactions and retention during the load transition phase of the test.
Splitter, Derek [ORNL] (ORCID:0000000174044047)↗
Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)
Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.
14 SOLAR ENERGY↗
Data and script associated with “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest”
This data package contains the data and code to use and run the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model (WT-WRF-Hydro) with the Sequential Precipitation Input Tagging (SPIT) framework. It is associated with the publication “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest” published in Scientific Reports (Butler et al., 2026; https://doi.org/10.1038/s41598-026-46539-1). We use the Continental U.S. (CONUSII; Rasmussen et al., 2021) dataset to force the model with an historical climate (2006–2013) and a future climate (2086–2093) with a representative carbon pathway (RCP) 8.5 scenario. We use the model to calculate water transit times in five headwater catchments within the U.S. Pacific Northwest. We also show key hydrologic and environmental variables that affect water transit times and changes in the future. Finally, we use observed data to validate the model such as stream water isotopes, snowpack characteristics, and stream discharge. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. The data package consists of 11 folders: (1) "Figures" contains the exported figures used in the manuscript; (2) "Model_Isotope_Date" contains the WT-WRF-Hydro isotope date used in model validation; (3) “Model_Outputs_Future” contains the WT-WRF-Hydro future climate outputs; (4) “Model_Outputs_Historical” contains the WT-WRF-Hydro historical climate outputs; (5) “Model_Outputs_Weights_Areas” contains the WT-WRF-Hydro weights per catchment used to calculate water transit times and isotopes in stream water; (6) “MODIS_data_scripts” contains data used to validate snow conditions in the study area; (7) “Observed_Flow_Data” contains the observed streamflow data used in model validation; (8) “Observed_Isotope_Data” contains the observed stream water isotope data used in model validation; (9) “Scripts” contains the Python scripts used to general results and the figures; (10) “Statistic_Outputs” contains the water transit time statistical outputs reported in this manuscript; (11) “Validation_SNOTEL” contains the SNOTEL data used in model validation. The files in this data package have the following file extensions: .tif, .txt, .csv, .pdf, .py, .jpg, and .png.
American River↗