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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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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Long-Term Aging in Miscible Polymer Nanocomposites

Here we find that the initial, solvent-cast state of nanoparticles (NPs) in a polymer matrix temporally evolves during thermal annealing such that, at steady state, NPs maximize their distance from each other subject to mass balance constraints. The observed timescales for this unexpected structural reorganization, as probed by small-angle X-ray scattering, are temperature-dependent and can be prohibitively large, especially at temperatures around and below 1.2Tg. X-ray photon correlation spectroscopy measurements during reorganization reveal that the collective NP dynamics slow down with annealing at constant temperature; this is accompanied by changes in the low-frequency regime in macroscopic viscoelastic measurements in equilibrated materials. By ruling out other potential sources for these effects (i.e., electrostatic interactions, adsorbed layers), we attribute these results to a long-ranged repulsive force between the NPs caused by fluctuations in the polymer phase, i.e., the "anti-Casimir" effect proposed by Obhukhov and Semenov [Long-range interactions in polymer melts: The anti-Casimir effect. Phys Rev Lett 2005, 95 (3), 038305]. Thus, our results highlight the important role of long-term, slow NP reorganization on the structure and, subsequently, the properties of polymer nanocomposites (PNCs), even in the case of nominally miscible polymer nanoparticle hybrids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Long-Term Structural and Chemical Stability of Carbon Electrodes in Vanadium Redox Flow Battery

Predicting the performance decay in carbon electrodes is critical to maximizing the longevity of redox flow battery (RFB) systems. This study investigates the effect of long-term cycling (over 8000 cycles) on the structural and chemical evolution of carbon electrodes. We find that the microstructural aspects such as graphitic stacking order and interlayer spacing along with overall morphological construct remains largely unchanged even after the prolonged cycling process. Conversely, significant changes in surface chemistry such as evolution of functional groups and point defects are evident from our combined multimodal spectroscopic and computational analysis. The XPS and FTIR analysis reveals chemical absorption of chloride counter anions at point defects within graphitic surface. Additionally, our results suggest that vanadium cation plays an important role in counter anion-carbon surface interaction and subsequently the surface chemistry evolutions. Our findings provide insights about surface chemical evolution that is critical for predicting electrode performance and longevity of RFB.

Modachur Sivakumar, Bhuvaneswari↗
DOE OSTI2026

Confinement Reconstruction Unlocks Stable Ru Single Atom-Doped IrO x Anodes for Long-Term High-Rate CO 2 Electrolysis

IrO 2 is a commonly employed anode catalyst for CO 2 electrolysis in membrane electrode assembly (MEA) systems. However, under high current densities, its structural reconstruction leads to activity loss and stability degradation, limiting the industrial viability of CO 2 electrolysis. In this work, we demonstrated a confinement reconstruction strategy to precisely regulate the structural evolution during electrolysis. Ethylene glycol serves as a structural modulator, protecting the catalyst surface, suppressing soluble species formation, and promoting ordered structural evolution. Single-atom Ru acts as a stability enhancer, forming robust Ir–O–Ru bridging structures that facilitate an ordered transformation from a 4-fold [RuO 4 ]/[IrO 4 ] to a 6-fold symmetry [RuO 6 ]/[IrO 6 ] octahedral framework, thereby enhancing structural rigidity and long-term stability. As a result, in MEA-based CO 2 electrolysis, the catalyst achieves a stable operation at 200 mA cm –2 for 480 h, maintaining a CO selectivity above 80%. Theoretical calculations further elucidate that the enhanced stability originates from the suppression of oxygen vacancy formation, making the lattice-oxygen-mediated mechanism (LOM) potentially less favorable. This work provides insights into the structural evolution of the OER catalysts under high-current-density conditions, paving the way for large-scale CO 2 electrolysis commercialization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Decadal-Scale Hydrothermal Alteration of Basalt: Implications for Long-Term Reactivity in Subsurface Technologies

Global demands to secure critical mineral supply chains and managing water resources require innovative resource management strategies. Subsurface basalt reservoirs offer a dual-purpose application, where CO2 enhanced critical metal recovery can be coupled with water remediation strategies for the extraction of economically important and environmentally relevant elements. This study utilizes static batch experiments conducted on Columbia River Basalt Group samples to evaluate long-term fluid–rock interactions relevant to coupled subsurface applications. Samples were reacted under elevated temperature and pressure conditions, for 296 and 4,061 days, providing a unique dataset to assess geochemical evolution, element partitioning, and aqueous chemistry over decadal timescales. The alteration was dominated by silicate, aluminosilicate, and oxide phases. Progressive hydrothermal alteration increased the cation exchange capacity through the formation of secondary minerals (e.g. clays and zeolites), influencing solute retention, ion exchange behavior, and aqueous chemistry. Grain-scale and bulk analyses revealed selective cation release and retention patterns, establishing a mechanistic baseline for predicting element mobility. These geochemical constraints inform the prospective use of CO2-enhanced metal recovery for critical resources (e.g. Co, Ni, Mn, Mg, Ti, Fe) and associated water-quality impacts, providing a foundation for the design and management of engineered fluid–rock systems in basalt reservoirs.

Gibson, Marie N.↗
DOE OSTI2024

Atomically Precise Graphene Nanoribbon Transistors with Long-Term Stability and Reliability

Atomically precise graphene nanoribbons (GNRs) synthesized from the bottom-up exhibit promising electronic properties for high-performance field-effect transistors (FETs). The feasibility of fabricating FETs with GNRs (GNRFETs) has been demonstrated, with ongoing efforts aimed at further improving their performance. However, their long-term stability and reliability remain unexplored, which is as important as their performance for practical applications. In this work, we fabricated short-channel FETs with nine-atom-wide armchair GNRs (9-AGNRFETs). We revealed that the on-state (/ ON ) current performance of the 9-AGNRFETs deteriorates significantly over consecutive full transistor on and off logic cycles, which has neither been demonstrated nor previously considered. To address this issue, we deposited a thin ~10 nm thick atomic layer deposition (ALD) layer of aluminum oxide (Al 2 O 3 ) directly on these devices. The integrity, compatibility, electrical performance, stability, and reliability, of the GNRFETs before and/or after Al 2 O 3 deposition were comprehensively studied. The results indicate that the observed decline in electrical device performance is most likely due to the degradation of contact resistance over multiple measurement cycles. We successfully demonstrated that the devices with the Al 2 O 3 layer operate well up to several thousand continuous full cycles without any degradation. Our study offers valuable insights into the stability and reliability of GNR transistors, which could facilitate their large-scale integration into practical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Enhancing Streamflow Forecast and Extracting Insights Using Long-Short Term Memory Networks With Data Integration at Continental Scales

Recent observations with varied schedules and types (moving average, snapshot, or regularly spaced) can help to improve streamflow forecasts, but it is challenging to integrate them effectively. Based on a long short-term memory (LSTM) streamflow model, we tested multiple versions of a flexible procedure we call data integration (DI) to leverage recent discharge measurements to improve forecasts. DI accepts lagged inputs either directly or through a convolutional neural network unit. DI ubiquitously elevated streamflow forecast performance to unseen levels, reaching a record continental-scale median Nash-Sutcliffe Efficiency coefficient value of 0.86. Integrating moving-average discharge, discharge from the last few days, or even average discharge from the previous calendar month could all improve daily forecasts. Directly using lagged observations as inputs was comparable in performance to using the convolutional neural network unit. Importantly, we obtained valuable insights regarding hydrologic processes impacting LSTM and DI performance. Before applying DI, the base LSTM model worked well in mountainous or snow-dominated regions, but less well in regions with low discharge volumes (due to either low precipitation or high precipitation-energy synchronicity) and large interannual storage variability. DI was most beneficial in regions with high flow autocorrelation: it greatly reduced baseflow bias in groundwater-dominated western basins and also improved peak prediction for basins with dynamical surface water storage, such as the Prairie Potholes or Great Lakes regions. However, even DI cannot elevate performance in high-aridity basins with 1-day flash peaks. Despite this limitation, there is much promise for a deep-learning-based forecast paradigm due to its performance, automation, efficiency, and flexibility.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Long-Term Trends for Marine Sulfur Aerosol in the Alaskan Arctic and Relationships With Temperature

Marine aerosol plays a vital role in cloud-aerosol interactions during summer in the Arctic. The recent rise in temperature and decrease in sea ice extent have the potential to impact marine biogenic sources. Compounds like methanesulfonic acid (MSA) and non-sea-salt sulfate (nss-SO 4 2- ), oxidation products of dimethyl sulfide (DMS) emitted by marine primary producers, are likely to increase in concentration. Long-term studies are vital to understand these changes in marine sulfur aerosol and potential interactions with Arctic climate. Samples were collected over three summers at two coastal sites on the North Slope of Alaska (Utqiagvik and Oliktok Point). MSA concentrations followed previously reported seasonal trends, with evidence of high marine primary productivity influencing both sites. When added to an additional data set collected at Utqiagvik, an increase in MSA concentration of + 2.5% per year and an increase in nss-SO 4 2- of + 2.1% per year are observed for the summer season over the 20-year record (1998–2017). This study identifies ambient air temperature as a strong factor for MSA, likely related to a combination of interrelated factors including warmer sea surface temperature, reduced sea ice, and temperature-dependent chemical reactions. Analysis of individual particles at Oliktok Point, within the North Slope of Alaska oil fields, showed evidence of condensation of MSA onto anthropogenic particles, highlighting the connection between marine and oil field emissions and secondary organic aerosol. Finally, this study shows the continued importance of understanding MSA in the Arctic while highlighting the need for further research into its seasonal relationship with organic carbon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Steady Long-term Slip Rate on the Blue Cut Fault: Implications for Ongoing Block Rotation in the Eastern Transverse Ranges, CA

We report the Eastern Transverse Ranges (ETR) province of California contains a system of E-W-trending left-lateral faults accommodating clockwise block rotation between the San Andreas Fault (SAF) system in the Coachella Valley and the Eastern California Shear Zone (ECSZ) in the Mojave Desert. Building upon established geometric relationships, we estimate that this rotation across the ETR may transfer right-lateral strain from the SAF to the ECSZ at a time-averaged rate of ~4.3–7.7 mm/yr. Through geomorphic mapping and the analysis of 38 10 Be surface exposure samples, we derive a long-term slip rate of 1.26 ± 0.50 (2σ) mm/yr over the late Pleistocene, yet analysis of the displacement record indicates a rate decrease ~71 kya. While a rate change on this fault could have implications for possible plate boundary reorganization in this area, we argue that this slip rate variability more likely reflects routine fluctuation about a steady lifetime slip rate.

58 GEOSCIENCES↗
DOE OSTI2024

Simulating Long–Term Dynamics of Radiation Belt Electrons Using DREAM3D Model

Here, we compared the performance of DREAM3D simulations in reproducing the long-term radiation belt dynamics observed by Van Allen Probes over the entire year of 2017 with various boundary conditions (BCs) and model inputs. Specifically, we investigated the effects of three different outer boundary conditions, two different low-energy boundary conditions for seed electrons, four different radial diffusion (RD) coefficients (DLL), four hiss wave models, and two chorus wave models from the literature. Using the outer boundary condition driven by GOES data, our benchmark simulation generally well reproduces the observed radiation belt dynamics inside L* = 6, with a better model performance at lower μ than higher μ, where μ is the first adiabatic invariant. By varying the boundary conditions and inputs, we find that: (a) The data-driven outer boundary condition is critical to the model performance, while adding in the data-driven seed population doesn't further improve the performance. (b) The model shows comparable performance with DLL from Brautigam and Albert (2000, https://doi.org/10.1029/1999ja900344), Ozeke et al. (2014, https://doi.org/10.1002/2013ja019204), and Liu et al. (2016, https://doi.org/10.1002/2015gl067398), while with DLL from Ali et al. (2016, https://doi.org/10.1002/2016ja023002) the model shows less RD compared to data. (c) The model performance is similar with data-based hiss models, but the results show faster loss is still needed inside the plasmasphere. (d) The model performs similarly with the two different chorus models, but better capturing the electron enhancement at higher μ using the Wang et al. (2019, https://doi.org/10.1029/2018ja026183) model due to its stronger wave power, since local heating for higher energy electrons is under-reproduced in the current model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Long-Term Trends in Aerosols, Low Clouds, and Large-Scale Meteorology Over the Western North Atlantic From 2003 to 2020

Here, a continuous decrease in aerosols over the Western North Atlantic Ocean (WNAO) on a decadal timescale provides a long-term benchmark to evaluate how various natural and anthropogenic processes affect the manifestation of aerosol-cloud interactions in this region. Furthermore, the WNAO serves as a natural laboratory with diverse aerosol sources, marine boundary layer clouds more variable than those in marine stratocumulus deck regions, and unique flow regimes established by the Gulf Stream and the semi-permanent Bermuda High. We investigate how satellite-retrieved macrophysical and microphysical properties of low clouds and the surface shortwave irradiance changed from 2003 to 2020, in tandem with this aerosol decrease. The decadal changes in large-scale meteorology related to the North Atlantic Oscillation (NAO) are also examined. We find a reduction in low-cloud optical thickness, accompanied by fewer and larger cloud droplets, yet observe no significant changes in low-cloud fraction and liquid water path. Despite the reduction in low-cloud optical thickness together with aerosol decrease, a corresponding increase in the trends of surface shortwave irradiance, also known as surface brightening, is lacking. This absence of brightening is potentially related to concomitant changes found in large-scale meteorology associated with NAO—Bermuda High strengthening, sea surface warming, and atmospheric moistening— as well as an increase in high-level cloud fraction that can counteract the surface brightening. Ultimately, our findings suggest that spatial patterns of decadal meteorological variability introduce complexities in the surface cloud radiative effect over the WNAO, thereby complicating the isolation and examination of aerosol-cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Alternating Conditional Expectations: Introducing a Non‐Parametric Statistical Method to Interpret Long‐Term Greenhouse Gas Flux Measurements Over Semi‐Arid and Wetland Ecosystems

Abstract We explore the potential of using a non‐parametric statistical method called Alternating Conditional Expectations, ACE, to quantify functional relationships in biogeosciences. Here, ACE is used to quantify the non‐linear and multi‐faceted responses of greenhouse gas fluxes to a set of biophysical forcings, when the shapes of those response surfaces are unknown. We evaluated the statistical method over two contrasting ecosystems and two contrasting time steps. One case involved quantifying the biophysical controls of water vapor and carbon dioxide (CO 2 ) fluxes over a semi‐arid oak savanna using daily integrated fluxes. The other case evaluated the responses of CO 2 and methane (CH 4 ) flux measurements to a set of biophysical forcings at a restored tidal wetland using thirty‐minute averages. The statistical model, based on 4 independent variables, explained up over 90% of the variation in daily integrated flux densities of water vapor and net carbon dioxide exchange at the savanna site. This fit was defined by distinct non‐linear responses to such drivers as gross primary production, photosynthetically active radiation, air temperature, vapor pressure deficit and soil moisture. At the tidal wetland site, we evaluated net carbon dioxide and methane fluxes with short‐term measurements to capture the influence of rising and falling tides and seasonality in biological activity. The statistical model defined the shape of the forcing of fluxes due to the roles of carbon exudates, water table depth, oxygen level in the water column, temperature and vegetation status. The statistical fits of the greenhouse gas fluxes were less precise than the savanna case. The fetch varies on a run‐to‐run basis as it is comprised of a heterogeneous mosaic of open water and vegetation. Furthermore, it is difficult to monitor the environmental conditions of the archaea and bacteria in the sediments that produce methane and carbon dioxide.

Environmental Sciences & Ecology↗
DOE OSTI2024

Phenology of Photosynthesis in Winter‐Dormant Temperate and Boreal Forests: Long‐Term Observations From Flux Towers and Quantitative Evaluation of Phenology Models

Abstract We examined the seasonality of photosynthesis in 46 evergreen needleleaf (evergreen needleleaf forests (ENF)) and deciduous broadleaf (deciduous broadleaf forests (DBF)) forests across North America and Eurasia. We quantified the onset and end (Start GPP and End GPP ) of photosynthesis in spring and autumn based on the response of net ecosystem exchange of CO 2 to sunlight. To test the hypothesis that snowmelt is required for photosynthesis to begin, these were compared with end of snowmelt derived from soil temperature. ENF forests achieved 10% of summer photosynthetic capacity ∼3 weeks before end of snowmelt, while DBF forests achieved that capacity ∼4 weeks afterward. DBF forests increased photosynthetic capacity in spring faster (1.95% d −1 ) than ENF (1.10% d −1 ), and their active season length (End GPP –Start GPP ) was ∼50 days shorter. We hypothesized that warming has influenced timing of the photosynthesis season. We found minimal evidence for long‐term change in Start GPP , End GPP , or air temperature, but their interannual anomalies were significantly correlated. Warmer weather was associated with earlier Start GPP (1.3–2.5 days °C −1 ) or later End GPP (1.5–1.8 days °C −1 , depending on forest type and month). Finally, we tested whether existing phenological models could predict Start GPP and End GPP . For ENF forests, air temperature‐ and daylength‐based models provided best predictions for Start GPP , while a chilling‐degree‐day model was best for End GPP . The root mean square errors (RMSE) between predicted and observed Start GPP and End GPP were 11.7 and 11.3 days, respectively. For DBF forests, temperature‐ and daylength‐based models yielded the best results (RMSE 6.3 and 10.5 days).

Environmental Sciences & Ecology↗
DOE OSTI2025

Long‐Term Impacts of Global Solid Biofuel Emissions on Ambient Air Quality and Human Health for 2000–2019

Globally, solid biofuels (SB) have been widely used for household cooking and energy production for decades due to electricity shortages and socio-economic barriers to adopting renewable energy alternatives. This has detrimental effects on air quality, human health, and climate through trace gas and aerosol emissions. Despite numerous studies, the long-term consequences of SB emissions remain poorly understood. Here, we use the Community Earth System Model and the Community Emissions Data System emission inventory to investigate the SB emission impacts on air quality and human health for 2000–2019. Global SB emission increased the ambient PM 2.5 (particulate matter with aerodynamic diameters ≤2.5 μm) and ozone (O 3 ) concentrations up to 23.61 μg/m 3 and 13.69 ppbv, with significant effects found in India, China, and the Rest of Asia (ROA). Our study estimates total annual premature deaths (APDs) associated with global SB-attributable PM 2.5 and O 3 exposure as 1.11 million [95% confidence interval (95% CI): 1.00–1.22 million] in 2000 up to 1.43 million (95% CI: 1.30–1.56 million) in 2019. China's SB emissions and associated APDs have reduced substantially, whereas India and ROA had a major leap in both estimates in 2019 compared to 2000. China's progress in cutting residential SB emissions accounts for its improvements. Our study urges the reduction of SB usage and emissions to potentially improve overall air quality and human health conditions, especially in highly populated, low- and middle-income countries, where the poor air quality and associated health burden attributable to SB emissions are estimated to be higher.

O 3↗
DOE OSTI2026

Long-term observations reveal non-negligible temperature contributions to moist static energy during the MJO transition from suppressed to active phases

The evolution of moist static energy (MSE) is widely used to understand the organization and propagation of the Madden-Julian oscillation (MJO). Past studies, largely based on reanalysis or short-term observations, have highlighted humidity as the dominant driver of MJO evolution. Using 14 years of bias-corrected radiosonde observations from the Department of Energy – Atmospheric Radiation Measurement (DOE-ARM) Facility site at Manus in the western Pacific, we show that temperature has a significant influence on the vertically-integrated MSE during MJO’s transition from suppressed to active phase. Specifically, during the transition phase in boreal winter (spring), ~48% (~31%) of the vertically-integrated MSE anomalies are attributed to temperature anomalies. This temperature contribution is confined to the mid- and upper troposphere, where temperature and MSE anomalies exhibit a strong correlation. These findings have important implications for MJO theory and provide new constraints for evaluating MJO transition processes in models.

Alex, Nirmal↗
DOE OSTI2026

Short‐Term Hourly Weather Forecasting Using PredRNN With Image Preprocessing

Global weather forecast models are vital tools with numerous applications, including public safety, agriculture, and transportation. Recent advancements in artificial intelligence (AI) and deep learning (DL) have shown the potential to enhance weather forecasting accuracy and speed. In this study, we developed a short-term hourly weather forecast framework with a wavelet transform function for data preprocessing and a spatiotemporal DL model, PredRNN, for predicting five surface atmospheric variables, including wind speed and direction, mean sea level pressure (MSLP), temperature, and precipitation. The framework demonstrated promising results. It produces global forecasts at 0.25° (∼25 km) with a 1-day lead time RMSE of 1.8 m/s for wind components, 180 Pa for MSLP, and 1.8 K for temperature. Although our model does not surpass state-of-the-art AI weather forecast models across all metrics, it outperforms these models in precipitation forecasting and wind prediction at short lead times and achieves comparable accuracy for MSLP. Its native hourly forecasting capability, together with training on widely accessible GPU hardware, contributes meaningfully to the advancement of accessible DL weather forecasting methods. Our work highlights the importance of integrating temporal components and data transformation techniques to improve the predictability and accuracy of weather forecasts.

Tran, Hoang [Pacific Northwest National Laboratory↗
DOE OSTI2021

Intermittent fasting enhances long-term memory consolidation, adult hippocampal neurogenesis, and expression of longevity gene Klotho

Daily calorie restriction (CR) and intermittent fasting (IF) enhance longevity and cognition but the effects and mechanisms that differentiate these two paradigms are unknown. We examined whether IF in the form of every-other-day feeding enhances cognition and adult hippocampal neurogenesis (AHN) when compared to a matched 10% daily CR intake and ad libitum conditions. After 3 months under IF, female C57BL6 mice exhibited improved long-term memory retention. IF increased the number of BrdU-labeled cells and neuroblasts in the hippocampus, and microarray analysis revealed that the longevity gene Klotho (Kl) was upregulated in the hippocampus by IF only. Furthermore, we found that downregulating Kl in human hippocampal progenitor cells led to decreased neurogenesis, whereas Kl overexpression increased neurogenesis. Finally, histological analysis of Kl knockout mice brains revealed that Kl is required for AHN, particularly in the dorsal hippocampus. These data suggest that IF is superior to 10% CR in enhancing memory and identifies Kl as a novel candidate molecule that regulates the effects of IF on cognition likely via AHN enhancement.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Application of a long short-term memory for deconvoluting conductance contributions at charged ferroelectric domain walls

Ferroelectric domain walls are promising quasi-2D structures that can be leveraged for miniaturization of electronics components and new mechanisms to control electronic signals at the nanoscale. Despite the significant progress in experiment and theory, however, most investigations on ferroelectric domain walls are still on a fundamental level, and reliable characterization of emergent transport phenomena remains a challenging task. Here, we apply a neural-network-based approach to regularize local I ( V )-spectroscopy measurements and improve the information extraction, using data recorded at charged domain walls in hexagonal (Er 0.99 ,Zr 0.01 )MnO 3 as an instructive example. Using a sparse long short-term memory autoencoder, we disentangle competing conductivity signals both spatially and as a function of voltage, facilitating a less biased, unconstrained and more accurate analysis compared to a standard evaluation of conductance maps. The neural-network-based analysis allows us to isolate extrinsic signals that relate to the tip-sample contact and separating them from the intrinsic transport behavior associated with the ferroelectric domain walls in (Er 0.99 ,Zr 0.01 )MnO 3 . Our work expands machine-learning-assisted scanning probe microscopy studies into the realm of local conductance measurements, improving the extraction of physical conduction mechanisms and separation of interfering current signals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Long-term interactive corrosion between International Simple Glass and stainless steel

The interactive corrosion between stainless steel 316 (SS) and International Simple Glass (ISG) has been studied for 12 months. The samples were placed in intimate contact to create crevice corrosion conditions on SS in a 0.6 M NaCl solution with and without 142 ppm dissolved silica species enriched in 29 Si. Corrosion on SS was observed with large pits located close to the crevice mouth at the end of 1 year in 0.6 M NaCl solution. The SS corrosion was also associated with the dissolution of nearby glass in a highly localized manner. When the leaching solution was saturated with silica species, the corrosion rate of SS was suppressed. However, the presence of SS enhances ISG dissolution in both conditions. The implications of the observed phenomena on the long-term storage of nuclear waste are discussed.

36 MATERIALS SCIENCE↗