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DOE OSTI2026

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Surface Atmosphere Integrated Field Laboratory (SAIL) Science Plan

Mountains are the natural water towers of the world, effectively turning water vapor into readily available fresh water through precipitation, snowpack, and runoff. Unfortunately, Earth system models (ESMs) have persistently been unable to predict the timing and availability of water resources from mountains because the source(s) of model error are difficult to isolate in complex terrain with limited atmospheric or land-surface observations. Further complications arise from the gross scale mismatch between ESM grid box sizes and the relevant scales of mountainous hydrological processes. The mountain hydrometeorology community has repeatedly called for integrated atmospheric and land observations of water and energy budgets in complex terrain that span these scales to establish benchmarks against which scale-dependent models can be further developed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Idealized Large-Eddy Simulations of Stratocumulus Advecting over Cold Water. Part I: Boundary Layer Decoupling

Abstract We explore the decoupling physics of a stratocumulus-topped boundary layer (STBL) moving over cooler water, a situation mimicking warm-air advection (WADV). We simulate an initially well-mixed STBL over a doubly periodic domain with the sea surface temperature decreasing linearly over time using the System for Atmospheric Modeling large-eddy model. Due to the surface cooling, the STBL becomes increasingly stably stratified, manifested as a near-surface temperature inversion topped by a well-mixed cloud-containing layer. Unlike the stably stratified STBL in cold-air advection (CADV) that is characterized by cumulus coupling, the stratocumulus deck in the WADV is unambiguously decoupled from the sea surface, manifested as weakly negative buoyancy flux throughout the subcloud layer. Without the influxes of buoyancy from the surface, the convective circulation in the well-mixed cloud-containing layer is driven by cloud-top radiative cooling. In such a regime, the downdrafts propel the circulation, in contrast to that in CADV regime for which the cumulus updrafts play a more determinant role. Such a contrast in convection regime explains the difference in many aspects of the STBLs including the entrainment rate, cloud homogeneity, vertical exchanges of heat and moisture, and lifetime of the stratocumulus deck, with the last being subject to a more thorough investigation in Part II. Finally, we investigate under what conditions a secondary stratus near the surface (or fog) can form in the WADV. We found that weaker subsidence favors the formation of fog whereas a more rapid surface cooling rate does not. Significant Statement The low-lying blanketlike clouds, called stratocumulus (Sc), reflect much incoming sunlight, substantially modulating Earth’s temperature. While much is known about how the Sc evolves when it moves over warmer water, few studies examine the opposite situation of Sc moving over colder water. We used a high-resolution numerical model to simulate such a case. When moving over cold water, the Sc becomes unambiguously decoupled from the water surface, distinctive from its warm counterpart in which the Sc interacts with the water surface via intermittent cauliflower-like clouds called cumulus clouds. Such decoupling influences many aspects of the Sc–sea surface system, which combine to alter the ability of the Sc to reflect sunlight, thereby influencing the climate. This work laid the foundation for future work that quantifies the contribution of such a decoupled Sc regime to Earth’s radiative budget and climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A systematic study of lanthanide titanates (A 2 Ti 2 O 7 ) chemical durability: corrosion mechanisms and control parameters

Dense lanthanide titanates ranging from La 2 Ti 2 O 7 to Yb 2 Ti 2 O 7 were synthesized by spark plasma sintering with similar micro-sized microstructure, and their chemical durability and degradation mechanisms were investigated by semi-dynamic leaching tests. Different corrosion mechanisms from incongruent to congruent dissolution were observed with preferential elemental releases of lanthanides in A 2 Ti 2 O 7 (A = La to Gd) and Ti in Er 2 Ti 2 O 7 and Yb 2 Ti 2 O 7 . Initial leaching was controlled by surface dissolution and long-term dissolution shifted to a diffusion-controlled mechanism for titanate pyrochlores from Sm 2 Ti 2 O 7 to Yb 2 Ti 2 O 7 . Both short-term and long-term leaching rates decreased from La 2 Ti 2 O 7 to Yb 2 Ti 2 O 7 , and materials became more corrosion resistant with decreasing ionic radius ratios of the rare-earth elements and titanium. Amorphous passivation films of several nm-thick enriched with Ti formed on the surfaces of the corroded materials, and the formation mechanisms were governed either by surface reorganization with preferential release of lanthanides or dissolution-precipitation from saturated bulk solutions with preferential release of titanium. Finally, these results demonstrate that the ionic size plays a dominant role in determining chemical durability of lanthanide titanates and a strong correlation is established among chemical composition/structural variation, passivation film formation and corrosion mechanisms, and materials chemical durability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Recent Weakening of the Global Radiative Feedback

Earth's climate stability, characterized by the global radiative feedback parameter (𝜆), varies decadally due to changing surface temperature patterns. Recent variations in 𝜆 are poorly understood as coordinated model simulations typically end in 2014. We apply a convolutional neural network trained on climate model simulations to observation-based surface temperature reconstructions to estimate variations in 𝜆 up to 2025. We find that 𝜆 reached a minimum (maximum stability) around the mid 1990s (𝜆 ≃ −3 Wm −2 /K), but has since weakened significantly (𝜆 ≃ −2 Wm −2 /K). We confirm these results with climate model simulations extended to 2022. The recent 𝜆 weakening is not significantly affected by El Niño Southern Oscillation or Pacific Decadal Oscillation. Attribution reveals that warming in the subtropical Northeast Pacific is an important driver of the recently weakened feedback, confirmed by targeted experiments in E3SMv2. Our approach enables near real-time monitoring of Earth's climate stability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Grounding our Understanding of the Impacts of Boreal Forest Expansion on Shallow Cumulus Clouds with a Simple Modeling Framework

Abstract The expansion of the boreal forest poleward is a potentially important driver of feedbacks between the land surface and Arctic climate. A growing body of work has highlighted the importance of differences in evaporative resistance between different possible future Arctic land covers, which in turn alters humidity and cloudiness in the boundary layer, for these feedbacks. While thus far this problem has been studied primarily with complex Earth system models, we turn to a locally focused, idealized model capable of diagnosing and testing the sensitivity of first-order processes connecting vegetation, the atmospheric boundary layer, and low clouds in this critical region. This allows us to benchmark the mechanisms and results at the center of predictions from larger-scale simulations. A surface dominated by broadleaf trees, characterized by higher albedo and lower surface evaporative resistance, drives cooling and moistening of the boundary layer relative to a surface of needleleaf trees, characterized by lower albedo and higher surface evaporative resistance. Differences in evaporative resistance between these hypothetical Arctic vegetation covers are of equal importance to changes in albedo for the initial response of the boundary layer to boreal expansion, even with our idealized approach. However, compensation between the elevation of the lifting condensation level (LCL) and more rapid growth of the mixed layer over higher evaporative resistance surfaces can minimize changes in the favorability of shallow clouds over different land cover types under some conditions. We then perform two tests on the sensitivity of this compensating effect, to changes in water availability, represented first by a reduction in boundary layer humidity and then by both a reduction in humidity and soil moisture available to our vegetation surface. Finally, given the importance of this potential LCL–mixed-layer height compensation in our idealized modeling results, we look to determine its relevance in observational data from a field campaign in boreal Finland. These observations do confirm that such a coupling plays an important role in cumulus-topped boundary layers over a needleleaf forest surface. While our results confirm some underlying mechanisms at the center of prior work with Earth system models, they also provide motivation for future work to constrain the impact of boreal forest expansion. This will include both large eddy simulations to examine the impact of processes and feedbacks not resolved by a mixed-layer model, as well as a more systematic evaluation and comparison of relevant observations at the site in Finland and sites from prior boreal field campaigns. Significance Statement Clouds and vegetation are both important components of the climate system that interact across a range of scales. These interactions are central to understanding how changes at the land surface feedback on climate. For example, if a forest expands or recedes, diagnosing how that will impact clouds will determine whether you predict warming or cooling temperatures from that shift in the forest area. These predictions are often made with complex Earth system models, but we look to a more idealized representation of the land–atmosphere system to diagnose how shallow clouds should respond to changes in surface properties with different scenarios of boreal forest expansion at a more foundational level. This both grounds our understanding of previous analysis and provides helpful direction for future studies of this relevant and impactful land cover change.

Meteorology & Atmospheric Sciences↗

DOE OSTI2025

Representing lateral groundwater flow from land to river in Earth system models

Lateral groundwater flow (LGF) is an important hydrologic process in controlling water table dynamics. Due to the relatively coarse spatial resolutions of land surface models, the representation of this process is often overlooked or overly simplified. In this study, we developed a hillslope-based lateral groundwater flow model. Specifically, we first developed a hillslope definition model based on an existing watershed delineation model to represent the subgrid spatial variability in topography. Building upon this hillslope definition, we then developed a physical-based lateral groundwater flow using Darcy’s equation. This model explicitly considers the relationships between the groundwater table along the hillslope and the river water table levels. We coupled this intra-grid model to the land component (E3SM Land Model: ELM) and river component (MOdel for Scale Adaptive River Transport: MOSART) of the Energy Exascale Earth System Model (E3SM). We tested both the hillslope definition model and the lateral groundwater flow model and performed sensitivity experiments using different configurations. Simulations for a single grid cell at 0.5°×0.5° within the Amazon basin show that the definition of hillslope is the key to modeling lateral flow processes and the runoff partition between surface and subsurface can be dramatically changed using the hillslope approach. Although our method provides a pathway to improve the lateral flow process, future improvements are needed to better capture the subgrid structure to account for the spatial variability in hillslopes within the simulated grid of land surface models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Elliptical ejecta of asteroid Dimorphos is due to its surface curvature

Kinetic deflection is a planetary defense technique delivering spacecraft momentum to a small body to deviate its course from Earth. The deflection efficiency depends on the impactor and target. Among them, the contribution of global curvature was poorly understood. The ejecta plume created by NASA’s Double Asteroid Redirection Test impact on its target asteroid, Dimorphos, exhibited an elliptical shape almost aligned along its north-south direction. Here, we identify that this elliptical ejecta plume resulted from the target’s curvature, reducing the momentum transfer to 44 ± 10% along the orbit track compared to an equivalent impact on a flat target. We also find lower kinetic deflection of impacts on smaller near-Earth objects due to higher curvature. A solution to mitigate low deflection efficiency is to apply multiple low-energy impactors rather than a single high-energy impactor. Rapid reconnaissance to acquire a target’s properties before deflection enables determining the proper locations and timing of impacts.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Three influential factors on colloidal nanoparticle deposition for heat conduction enhancement in 3D chip stacks

Thermal management is one of the major challenges facing the development of three-dimensional (3D) chip stacks. Recently, experimental studies have shown that neck-based thermal structure (NTS) between chip layers formed by drying of colloidal suspension in cavity filled with micro-size particles can improve the vertical heat conduction threefold. However, a deep understanding of the mechanisms of neck formation and its influence on heat conduction is still lacking. In this paper, we numerically study the effects of three parameters, i.e., initial nanoparticle concentration, drying temperature and chip surface wettability on neck formation between filler particles and on the resulting heat conduction of the NTS. With increasing nanoparticle concentration, the size and number of necks increase, resulting in an increased effective thermal conductivity (ETC) of NTS. The drying temperature is found to have only little influence on the ETC of resultant NTS, while the neck size and spatial distribution become more uniform at higher drying temperature. When reducing the wettability of the top and bottom surfaces of the cavity, the necks shrink in size until completing evacuating at the top and bottom layers, while the size of the necks between filler particles in the middle height of the cavity expands slowly. In consequence, the ETC of NTS drops at an increasing rate. Being able to reveal the underlying multiple mechanisms of two-phase flow, phase change and heat transport, the current numerical study suggests optimal values for the deposition process, with initial nanoparticle concentration over 0.8%, a drying temperature of 60°C and a uniform contact angle of 30° for practical production of NTS.

3D chip stacks↗

DOE OSTI2020

Boosting electrosynthesis of ammonia on surface-engineered MXene Ti 3 C 2

Seeking a breakthrough in the development of efficient nitrogen fixation catalysts has become the frontier of energy and chemical conversion schemes. In this work, we report that the MXene Ti 3 C 2 can serve as a promising catalyst for the electrochemical N 2 reduction reaction (NRR) under ambient conditions. The electrocatalytic performance of Ti 3 C 2 can be further optimized through surface engineering. Specifically, Ti 3 C 2 with the increased surface hydroxyl moieties demonstrates enhanced production of NH 3 with a yield rate of 1.71 μg h -1 cm -2 , a Faradaic efficiency of 7.01% at -0.2 V vs. RHE at 20 °C and an even higher yield rate of 12.46 μg h -1 cm -2 together with a Faradaic efficiency of 9.03% at -0.2 V vs. RHE at 60 °C. The detailed electrochemical analysis suggests that the surface hydroxyl modification can effectively facilitate the electron transfer, surface adsorption and activation of dinitrogen. Our work sheds light on the development of efficient NRR catalysts based on earth-abundant elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Groundwater regulates interannual variations in evapotranspiration in a riparian semiarid ecosystem

Dryland ecosystems are an important component of Earth’s carbon, water, and energy budgets. Changes in hydroclimatic conditions can significantly alter land surface fluxes in these ecosystems. In regions with groundwater-river water exchange, land surface fluxes are strongly modulated by groundwater table fluctuations in response to river stage variations; however, interactions between fluxes and groundwater remain poorly understood in drylands. Here, we use eddy covariance data collected in paired upland and riparian semiarid ecosystems during two years with contrasting river flow conditions to examine interactions among river stage conditions, water table dynamics, meteorological drivers, and ecosystem fluxes. Elevated groundwater availability resulting from groundwater-surface water exchange at the riparian site enhanced the latent heat flux (LE, the energy form of evapotranspiration), which was sustained longer in the growing season during both years. At the upland site, mean LE during the dry season differed by less than 2% between the two years. In contrast, at the riparian site contrasting river flow conditions resulted in a 41% difference in peak monthly LE between the two years. The two-year mean LE in the summer at the riparian site was twice that at the upland site. Carbon uptake (NEP) and LE were well correlated at the upland site during both years, but at the riparian site enhanced summertime LE during the high river flow year did not correspond t enhanced NEP. Our results demonstrate that enhanced groundwater availability modulated by river stage variability is a critical driver of land surface fluxes in semiarid riparian ecosystems.

Missik, Justine E.↗

DOE OSTI2024

Physical properties of asteroid Dimorphos as derived from the DART impact

On 26 September 2022, NASA’s Double Asteroid Redirection Test (DART) mission successfully impacted Dimorphos, the natural satellite of the binary near-Earth asteroid (65803) Didymos. Numerical simulations of the impact provide a means to find the surface material properties and structures of the target that are consistent with the observed momentum deflection efficiency, ejecta cone geometry and ejected mass. Our simulation that best matches the observations indicates that Dimorphos is weak, with a cohesive strength of less than a few pascals, like asteroids (162173) Ryugu and (101955) Bennu. We find that the bulk density of Dimorphos ρ B is lower than ~2,400 kg m – 3 and that it has a low volume fraction of boulders (≲40 vol%) on the surface and in the shallow subsurface, which are consistent with data measured by the DART experiment. These findings suggest that Dimorphos is a rubble pile that might have formed through rotational mass shedding and reaccumulation from Didymos. Our simulations indicate that the DART impact caused global deformation and resurfacing of Dimorphos. ESA’s upcoming Hera mission may find a reshaped asteroid rather than a well-defined crater.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Hybridized kagome bands and induced Ti magnetism in RTi3Bi4 (R = Nd, Sm, Gd) kagome metals studied using angle-resolved photoemission spectroscopy and x-ray magnetic circular dichroism

Kagome materials are known for hosting emergent quantum phenomena driven by the interaction between different lattice, charge and spin orders. Here, we present a detailed angle resolved photoemission (ARPES), density functional theory (DFT) and x-ray magnetic circular dichroism (XMCD) study of the electronic and magnetic structure of RTi3Bi4 (R = Nd, Sm, Gd). ARPES and DFT demonstrate that the bulk electronic band structure is dominated by the hybridization of the Ti bands, and the weak electron-like pocket at Γ is identified as a surface state. The isotropic XAS profile of the M 4,5-edge of the rare earth is consistent with the presence of R 3+ oxidation state. Using the XMCD sum rules, backed by the atomic multiplet theory calculations, we obtain the spin and orbital magnetic moments. The Ti L2,3-edge XMCD reveals the presence of a small magnetic moment in GdTi3Bi4, presumably driven by the proximity of the Ti kagome layers to the zigzag chains of Gd, while the total magnetic moment of Gd is shared by the f and d electrons. Our combined XMCD, ARPES and DFT study brings an important piece of information to understand the spin flip transitions and anomalous Hall effect observed in the RTi3Bi4 kagome metals.

Lim, C.↗

DOE OSTI2021

Response of Global SSTs and ENSO to the Atlantic and Pacific Meridional Overturning Circulations

Consequences from a slowdown or collapse of the Atlantic meridional overturning circulation (AMOC) could include modulations to El Niño–Southern Oscillation (ENSO) and development of the Pacific meridional overturning circulation (PMOC). Despite potential ramifications to the global climate, our understanding of the influence of various AMOC and PMOC states on ENSO and global sea surface temperatures (SSTs) remains limited. Five multicentennial, fully coupled model simulations created with the Community Earth System Model were used to explore the influence of AMOC and PMOC on global SSTs and ENSO. We found that the amplitude of annual cycle SSTs across the tropical Pacific decreases and ENSO amplitude increases as a result of an AMOC shutdown, irrespective of PMOC development. However, active deep overturning circulations in both the Atlantic and Pacific basins reduce ENSO amplitude and variance of monthly SSTs globally. Furthermore, the underlying physical reasons for changes to global SSTs and ENSO are also discussed, with the atmospheric and oceanic mechanisms that drive changes to ENSO amplitude differing based on PMOC state. These results suggest that if climate simulations projecting AMOC weakening are realized, compounding climate impacts could occur given the far-reaching ENSO teleconnections to extreme weather and climate events. More broadly, these results provide us with insight into past geologic era climate states, when PMOC was active.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Global evaluation of terrestrial biogeochemistry in the Energy Exascale Earth System Model (E3SM) and the role of the phosphorus cycle in the historical terrestrial carbon balance

Abstract. The importance of carbon (C)–nutrient interactions to the prediction of future C uptake has long been recognized. The Energy Exascale Earth System Model (E3SM) land model (ELM) version 1 is one of the few land surface models that include both N and P cycling and limitation (ELMv1-CNP). Here we provide a global-scale evaluation of ELMv1-CNP using the International Land Model Benchmarking (ILAMB) system. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. Compared to simulations with optimal P availability, simulations with ELMv1-CNP produce better performance, particularly for simulated biomass, leaf area index (LAI), and global net C balance. We also show ELMv1-CNP-simulated N and P cycling is in good agreement with data-driven estimates. We compared the ELMv1-CNP-simulated response to CO2 enrichment with meta-analysis of observations from similar manipulation experiments. We show that ELMv1-CNP is able to capture the field-observed responses for photosynthesis, growth, and LAI. We investigated the role of P limitation in the historical balance and show that global C sources and sinks are significantly affected by P limitation, as the historical CO2 fertilization effect was reduced by 20 % and C emission due to land use and land cover change was 11 % lower when P limitation was considered. Our simulations suggest that the introduction of P cycle dynamics and C–N–P coupling will likely have substantial consequences for projections of future C uptake.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

A Bayesian Deep Learning Approach to Near-Term Climate Prediction

Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a complementary machine-learning-based approach to climate prediction. The example problem setting we consider consists of predicting natural variability of the North Atlantic sea surface temperature on the interannual timescale in the pre-industrial control simulation of the Community Earth System Model. While previous works have considered the use of recurrent networks such as convolutional LSTMs and reservoir computing networks in this and other similar problem settings, we currently focus on the use of feedforward convolutional networks. In particular, we find that a feedforward convolutional network with a Densenet architecture is able to outperform a convolutional LSTM in terms of predictive skill. Next, we go on to consider a probabilistic formulation of the same network based on Stein variational gradient descent and find that in addition to providing useful measures of predictive uncertainty, the probabilistic (Bayesian) version improves on its deterministic counterpart in terms of predictive skill. Finally, we characterize the reliability of the ensemble of machine learning models obtained in the probabilistic setting by using analysis tools developed in the context of ensemble numerical weather prediction.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Modeling and observations of North Atlantic cyclones: Implications for U.S. Offshore wind energy

To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. Here, this paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere–ocean–wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions.

17 WIND ENERGY↗

DOE OSTI2025

Perovskite Catalysts for Pure-Water-Fed Anion-Exchange-Membrane Electrolyzer Anodes: Co-design of Electrically Conductive Nanoparticle Cores and Active Surfaces

Anion-exchange-membrane water electrolyzers (AEMWEs) are a possible low-capital-expense, efficient, and scalable hydrogen-production technology with inexpensive hardware, earth-abundant catalysts, and pure water. However, pure-water-fed AEMWEs remain at an early stage of development and suffer from inferior performance compared with proton-exchange-membrane water electrolyzers (PEMWEs). One challenge is to develop effective non-platinum-group-metal (non-PGM) anode catalysts and electrodes in pure-water-fed AEMWEs. We show how LaNiO3-based perovskite oxides can be tuned by cosubstitution on both A- and B-sites to simultaneously maintain high metallic electrical conductivity along with a degree of surface reconstruction to expose a stable Co-based active catalyst. The optimized perovskite, Sr0.1La0.9Co0.5Ni0.5O3, yielded pure-water AEMWEs operating at 1.97 V at 2.0 A cm-2 at 70 °C with a pure-water feed, thus illustrating the utility of the catalyst design principles.

Zhai, Tingting↗