Search NASA⌕ Search

SEARCH · Search NASA

Results for “Most representative cycle”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13

Global-Scale Convergence Obscures Inconsistencies in Soil Carbon Change Predicted by Earth System Models

Soil carbon (C) responses to environmental change represent a major source of uncertainty in the global C cycle. Feedbacks between soil C stocks and climate drivers could impact atmospheric CO 2 levels, further altering the climate. Here, we assessed the reliability of Earth system model (ESM) predictions of soil C change using the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). ESMs predicted global soil C gains under the high emission scenario, with soils taking up 43.9 Pg (95% CI: 9.2–78.5 Pg) C on average during the 21st century. The variation in global soil C change declined significantly from CMIP5 (with average of 48.4 Pg [95% CI: 2.0–94.9 Pg] C) to CMIP6 models (with average of 39.3 Pg [95% CI: 23.9–54.7 Pg] C). For some models, a small C increase in all biomes contributed to this convergence. For other models, offsetting responses between cold and warm biomes contributed to convergence. Although soil C predictions appeared to converge in CMIP6, the dominant processes driving soil C change at global or biome scales differed among models and in many cases between earlier and later versions of the same model. Random Forest models, for soil carbon dynamics, accounted for more than 63% variation of the global soil C change predicted by CMIP5 ESMs, but only 36% for CMIP6 models. Although most CMIP6 models apparently agree on increased soil C storage during the 21st century, this consensus obscures substantial model disagreement on the mechanisms underlying soil C response, calling into question the reliability of model predictions.

54 ENVIRONMENTAL SCIENCES↗

Intralattice-bonded phase-engineered ultrahigh-Ni single-crystalline cathodes suppress strain evolution

Single crystallization remains a debated strategy for advancing Ni-rich cathode materials. While it mitigates particle cracking and improves tap density by eliminating particle boundaries, extended diffusion pathways introduce volumetric and lattice distortions, compromising electrochemical and structural stability. These challenges hinder the commercialization of high-Ni single-crystal cathodes, calling for a reassessment of their viability. Here, in this study, we report a structural design: intralattice-bonded phase single-crystal LiNi 0.92 Co 0.03 Mn 0.05 O 2 (IBP-SC92). This architecture maintains structural integrity while shortening diffusion pathways, resulting in almost zero electrochemical degradation during cycling. The robust structure and fast ion transport mitigate lattice strain, as confirmed by multiscale high-resolution diffraction and imaging techniques, preventing intragranular cracks and irreversible phase transitions. As a result, IBP-SC92 shows outstanding cycling stability, with nearly 100% capacity retention after 100 cycles in half cells and 94.5% retention after 1,000 cycles in full cells. This redefined single-crystal cathode represents a significant step towards the industrial adoption of high-energy-density materials.

36 MATERIALS SCIENCE↗

Computational Modeling of Photovoltaic Mini-Modules Undergoing Accelerated Stress Testing

A finite element model of a four-cell photovoltaic mini-module was developed and compared to experimental results from an accelerated stress test protocol in order to validate that computational models can accurately represent their physical counterparts when subjected to mechanical loading and to assess mini-module representativeness against full scale photovoltaic modules. Deflected shapes across the simulated mini-modules were compared to measured mini-module shapes when subjected to various pressure loads. Displaced mini-module shape results constrained to the experimental protocols of 0.4 mm and 1.1 mm of displacement at the mini-module center were compared to experimental results of full-size modules subjected to module qualification test load levels of 1.0 kPa and 2.4 kPa, to assess if the bending of mini-modules was representative of full-sized modules under the load. Temperature cycling was incorporated into the model to simulate the impacts of stress due to thermal expansion of the backsheet and cells. A preliminary uncertainty analysis was performed to show how variations in material properties and geometric parameters change the simulation results.

computational modeling↗

Warming drives a ‘hummockification’ of microbial communities associated with decomposing mycorrhizal fungal necromass in peatlands

Dead fungal mycelium (necromass) represents a critical component of soil carbon (C) and nutrient cycles. Assessing how the microbial communities associated with decomposing fungal necromass change as global temperatures rise will help in determining how these belowground organic matter inputs contribute to ecosystem responses. Here, in this study, we characterized the structure of bacterial and fungal communities associated with multiple types of decaying mycorrhizal fungal necromass incubated within mesh bags across a 9°C whole ecosystem temperature enhancement in a boreal peatland. We found major taxonomic and functional shifts in the microbial communities present on decaying mycorrhizal fungal necromass in response to warming. These changes were most pronounced in hollow microsites, which showed convergence towards the necromass-associated microbial communities present in unwarmed hummocks. We also observed a high colonization of ericoid mycorrhizal fungal necromass by fungi from the same genera as the necromass. These results indicate that microbial communities associated with mycorrhizal fungal necromass decomposition are likely to change significantly with future climate warming, which may have strong impacts on soil biogeochemical cycles in peatlands. Additionally, the high enrichment of congeneric fungal decomposers on ericoid mycorrhizal necromass may help to explain the increase in ericoid shrub dominance in warming peatlands.

59 BASIC BIOLOGICAL SCIENCES↗

Observationally constrained analysis on the distribution of fine- and coarse-mode nitrate in global models

Nitrate plays an important role in the Earth system and air quality. A key challenge in simulating the life cycle of nitrate aerosol in global models is to accurately represent mass size distribution of nitrate aerosol. In this study, we evaluate the performance of the Energy Exascale Earth System Model version 2 (E3SMv2) and the Community Earth System Model version 2 (CESM2), along with Aerosol Comparisons between Observations and Models (AeroCom) phase III models, in simulating spatial distribution of fine-mode nitrate, the mass size distribution of fine- and coarse-mode nitrate, and the gas–aerosol partitioning between nitric acid gas and nitrate, using long-term ground-based observations and measurements from multiple aircraft campaigns. We find that most models underestimate the annual mean PM 2.5 (particulate matter with diameter less than 2.5 µm) nitrate surface concentration averaged over all sites. The observed nitrate PM 2.5 / PM 10 and PM 1 / PM 4 ratios are influenced by the relative contribution of fine sulfate or organic particles and coarse dust or sea salt particles. Overall, the ground-based observations give an annual mean surface nitrate PM 2.5 / PM 10 ratio of 0.7. Most models underestimate the annual mean PM 2.5 / PM 10 ratio in all regions. There are large spreads in the modeled nitrate PM 1 / PM 4 ratios, which span the full range from 0 to 1. Most models underestimate the surface molar ratio of nitrate to total inorganic nitrate averaged across all sites. Our study indicates the importance of gas–aerosol partition parameterization and the simulation of dust and sea salt in correctly simulating the mass size distribution of nitrate.

Nitrate↗

Wildfire impact on soil microbiome life history traits and roles in ecosystem carbon cycling

Abstract Wildfires, which are increasing in frequency and severity with climate change, reduce soil microbial biomass and alter microbial community composition and function. The soil microbiome plays a vital role in carbon (C) and nitrogen (N) cycling, but its complexity makes it challenging to predict post-wildfire soil microbial dynamics and resulting impacts on ecosystem biogeochemistry. The application of biogeochemically relevant conceptual trait-based frameworks to the soil microbiome can distill this complexity, enabling enhanced predictability of soil microbiome recovery following wildfire and subsequent impacts to biogeochemical cycles. Conceptual frameworks that have direct links to soil C and N cycling have been developed for the soil microbiome; the Y-A-S framework overviews soil microbiome life history strategies that have tradeoffs with one another and others have proposed frameworks specific to wildfire. Here, we aimed to delineate post-wildfire changes of bacterial traits in western US coniferous forests to inform how severe wildfire influences soil microbiome recovery and resultant biogeochemical cycling. We utilized a comprehensive metagenome-assembled genome catalog from post-wildfire soils representing 1 to 11 years following low- and high-severity burning to identify traits that enable the persistence of microbial taxa in burned soils and influence ecosystem C and N cycling. We found that high-severity wildfire initially selects for fast growers and, up to a decade post-fire, taxa that invest in genes for acquiring diverse resources from the external environment, which in combination could increase soil C losses. This work begins to disentangle how climate change–induced shifts in wildfire behavior might alter microbially mediated soil biogeochemical cycling.

Nelson, Amelia R.↗

A Machine‐Learning‐Assisted Stochastic Cloud Population Model as a Parameterization of Cumulus Convection

Abstract A machine‐learning‐assisted stochastic cloud population model is coupled with the Advanced Research Weather Research and Forecasting (WRF) model to represent fluctuations in the cloud‐base mass flux associated with the life cycles and interactions among cumulus convection cells. In this cloud population model, the size distribution and the associated cloud‐base mass flux of the convective cells are related to their previous state and to the change in the total convective area via a transition function. The convective area tendency in turn is assumed to depend on the cloud‐base mass flux that is resolved by the host WRF model. The transition function is represented by a single hidden‐layer neural network trained by the evolution of convective cell size distributions in a 1‐km grid‐spacing WRF simulation run over the Australian Monsoon region. At every grid point of the host model, the cloud population model predicts the cell size and cloud‐base mass flux distributions from which a random sample of cells is fed to an entraining parcel model that calculates precipitation as well as the associated liquid water potential temperature and total moisture tendencies. These tendencies are averaged over the cells and provided to the host model. Several regional simulations are performed over tropical and midlatitude domains to test this as a potential approach to scale‐aware parameterization. It is shown that such an approach could be a new promising path to simulating realistic precipitation statistics and propagation of precipitation associated with the Madden‐Julian Oscillation while maintaining realistic depictions of the diurnal cycle over both land and ocean.

54 ENVIRONMENTAL SCIENCES↗

Structural, Spectroscopic, and Kinetic Insight into the Heating Rate Dependence of Studtite and Metastudtite Dehydration

Uranyl peroxide minerals studtite (UO 2 O 2 ·4H 2 O) and metastudtite (UO 2 O 2 ·2H 2 O) are important materials in the nuclear fuel cycle. When heated, they dehydrate and transform to amorphous uranium oxides (UO x ), yet phase stability and heating rate dependence of these transformations are poorly understood. This information is critical to proper management of fuel cycle materials. In this work, we use in situ powder X-ray diffraction (PXRD), Raman spectroscopy, and thermogravimetric analysis (TGA) to monitor the dehydration of studtite and metastudtite. Strong linear correlation between the heating rate and phase transition temperature is observed. Geometric contraction and diffusion-related kinetic models describe studtite dehydration at slow heating rates, whereas Avrami–Erofeev or reaction order models become more accurate for faster thermal treatments. A second order model describes the transition from metastudtite to UO x regardless of the heating rate. Water retention during studtite dehydration is indicated by PXRD, Raman spectroscopy, and TGA. Here, we observe mixed-phase UO x dehydration products of metastudtite with a likely formation mechanism involving conversion of some uranyl centers from hexagonal to pentagonal bipyramidal coordination units via peroxide liberation. Our observations clarify over 100 years of measurements on these materials and represent an advancement in understanding the chemical behavior of nuclear fuel cycle materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Functional capacities of microbial communities to carry out large scale geochemical processes are maintained during ex situ anaerobic incubation

Mechanisms controlling CO 2 and CH 4 production in wetlands are central to understanding carbon cycling and greenhouse gas exchange. However, the volatility of these respiration products complicates quantifying their rates of production in the field. Attempts to circumvent the challenges through closed system incubations, from which gases cannot escape, have been used to investigate bulk in situ geochemistry. Efforts towards mapping mechanistic linkages between geochemistry and microbiology have raised concern regarding sampling and incubation-induced perturbations. Microorganisms are impacted by oxygen exposure, increased temperatures and accumulation of metabolic products during handling, storage, and incubation. We probed the extent of these perturbations, and their influence on incubation results, using high-resolution geochemical and microbial gene-based community profiling of anaerobically incubated material from three wetland habitats across a permafrost peatland. We compared the original field samples to the material anaerobically incubated over 50 days. Bulk geochemistry and phylum-level microbiota in incubations largely reflected field observations, but divergence between field and incubations occurred in both geochemistry and lineage-level microbial composition when examined at closer resolution. Despite the changes in representative lineages over time, inferred metabolic function with regards to carbon cycling largely reproduced field results suggesting functional consistency. Habitat differences among the source materials remained the largest driver of variation in geochemical and microbial differences among the samples in both incubations and field results. While incubations may have limited usefulness for identifying specific mechanisms, they remain a viable tool for probing bulk-scale questions related to anaerobic C cycling, including CO 2 and CH 4 dynamics.

59 BASIC BIOLOGICAL SCIENCES↗

Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)

Explicit consideration of microbial physiology in soil biogeochemical models that represent coupled carbon–nitrogen dynamics presents opportunities to deepen understanding of ecosystem responses to environmental change. The MIcrobial-MIneral Carbon Stabilization (MIMICS) model explicitly represents microbial physiology and physicochemical stabilization of soil carbon (C) on regional and global scales. Here we present a new version of MIMICS with coupled C and nitrogen (N) cycling through litter, microbial, and soil organic matter (SOM) pools. The model was parameterized and validated against C and N data from the Long-Term Inter-site Decomposition Experiment Team (LIDET; six litter types, 10 years of observations, and 13 sites across North America). The model simulates C and N losses from litterbags in the LIDET study with reasonable accuracy (C: R 2 =0.63; N: R 2 =0.29), which is comparable with simulations from the DAYCENT model that implicitly represents microbial activity (C: R 2 =0.67; N: R 2 =0.30). Subsequently, we evaluated equilibrium values of stocks (total soil C and N, microbial biomass C and N, inorganic N) and microbial process rates (soil heterotrophic respiration, N mineralization) simulated by MIMICS-CN across the 13 simulated LIDET sites against published observations from other continent-wide datasets. We found that MIMICS-CN produces equilibrium values in line with measured values, showing that the model generates plausible estimates of ecosystem soil biogeochemical dynamics across continental-scale gradients. MIMICS-CN provides a platform for coupling C and N projections in a microbially explicit model, but experiments still need to identify the physiological and stoichiometric characteristics of soil microbes, especially under environmental change scenarios.

58 GEOSCIENCES↗

Cradle-to-gate life cycle assessment of advanced composite panels incorporating CO 2 -derived multi-walled carbon nanotubes and hemp fiber for sustainable building applications

Advanced composite panels represent a promising pathway to reducing carbon emissions in the construction industry, yet comprehensive environmental impact assessments remain limited. Here, in this study, we conduct a life cycle assessment (LCA) to evaluate the environmental impacts of innovative composite panels produced from multi-walled carbon nanotubes (MWCNTs), hemp fiber (HF), recycled carbon fiber (rCF), and recycled polypropylene (PP), exploring their potential as baseline structural equivalents to conventional gypsum board. MWCNTs and HF play a critical role in sequestering carbon during raw material production, while the recycling processes for CF and PP generally require less energy compared to virgin material production. The LCA evaluates environmental performance using the TRACI 2.1 method, covering global warming potential (GWP), ozone depletion, smog formation, acidification, eutrophication, carcinogenic and non-carcinogenic effects, respiratory impacts, ecotoxicity, and fossil fuel depletion. Compositional variations—resin type (virgin vs. recycled), rCF content (9–29 wt%), and HF content (10–30 wt%)—are introduced for sensitivity and hotspot analyses. Results demonstrate that, when compared on the basis of preliminary structural equivalence, increasing recycled PP, rCF, and HF content can significantly reduce global warming potential compared to gypsum board. Beyond carbon reduction, the composite panels show trade-offs across other environmental categories. With the growing demand for composite materials in interior panels, ceiling systems, and exterior claddings, these findings highlight the environmental benefits and potential trade-offs of the proposed composites, establishing a foundational framework to support their continued development toward full building-system integration.

Advanced composite manufacturing↗

Data for Zheng et al. (2025), "AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry"

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystems and soil function. Salinity affects soil carbon cycling by directly impacting microbial activity and indirectly altering soil physicochemical properties, but current models inadequately represent these complexities. This dataset contains the observational and modeling data from Zheng et al. (2025), which described a process-based modeling framework that couples soil solution chemistry with microbial carbon cycling reactions to study the impacts of soil salinization. This conceptual model is implemented numerically into the open-source geochemical program PHREEQC 3.0 (Parkhurst and Appelo, 2013). This dataset consists of: - Figure2_AquaMEND_salinity_buffer: Contains model simulation outputs to assess the impact of three different cation exchange and surface complexation processes on salinity buffering (Fig. 2 from Zheng et al. 2025). - Figure3_Salinity_function: Contains salinity function fitting for literature data (Fig. 3 from Zheng et al. 2025). - Figure4_AquaMEND_microbial_mechanisms: Contains model simulation outputs for testing various microbial process-based hypotheses related to soil salinization, including microbial mortality, carbon use efficiency (CUE), extracellular enzyme activity, and other microbial mechanisms (Fig. 4 from Zheng et al. 2025). - Figure5_AquaMEND_Redox: Contains on model simulation outputs to evaluate shifts among key redox processes, such as aerobic respiration, sulfate reduction, and methanogenesis (Fig.5 from Zheng et al. 2025). - Figure6_AquaMEND_sorption: Contains on model simulation outputs for investigating the effects of salinity on dissolved organic matter (DOM) sorption and desorption processes (Fig. 6 from Zheng et al. 2025). - Figure7_AquaMEND_process_couple: Contains on model simulation outputs for exploring coupled biotic-abiotic processes and their interactions (Fig. 7 from Zheng et al. 2025). - data: Includes datasets used to develop salinity response functions and evaluate salinity buffering capacity. Datasets for MEND model calibration. - database: Contains the `.dat` file required by PHREEQC for model execution. - README.md: A Markdown plain text file describing the computational tools and directories. Files are a mixture of plain text CSV (comma-separated value) and plain text *.dat files written by the model; no special software is required to read them.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL SALINIT↗

Results of Application Demonstration of Autonomous Offshore Power System Supporting Multiple Mobile and Static Assets

Over the last decade, several technology trends have dominated the innovation cycle within the terrestrial economy. Electrification, cloud computing, decarbonization, digitization, and autonomy are representative examples of macro trends that have had a rapid and fundamental impact; an impact felt not only in user-facing technologies, such as electric vehicles and software-as-a-service, but also in the infrastructure required to deliver those technologies. However, the scale of the impact and rollout has not been felt equally between the terrestrial and ocean economies. Here, the innovation cycle in the ocean economy is significantly slower. What accounts for the difference and are there solutions to this issue?

16 TIDAL AND WAVE POWER↗

The Role of Oxidation Resistance in High Temperature Alloy Selection for a Future with Green Hydrogen

Hydrogen is being considered integral to the future energy landscape but there is limited mechanistic understanding and a lack of predictive models to describe the combined effects of alloy and gas composition, temperature, thermal cycling and water vapor contents on the oxidation behavior of high-temperature materials. Experimental evaluations were combined with coupled thermodynamic-kinetic modeling to investigate the oxidation behavior of five representative Ni-based superalloys in two water vapor contents (10%, 60% H 2 O) under thermal cycling (1-h, 100-h cyles) conditions at 800°C and 1000°C. The alloy with the highest Ti content demonstrated the poorest cyclic oxidation behavior while the alloy with highest Cr and Al contents was expected to continue to support protective formation of a compact Al 2 O 3 scale. Finally, accelerated degradation of the chromia-forming alloys was observed in the higher water vapor content but the impact on transient oxidation of the alumina-forming alloys needs further investigations.

36 MATERIALS SCIENCE↗

Mitigating Interfacial Mismatch between Lithium Metal and Garnet-Type Solid Electrolyte by Depositing Metal Nitride Lithiophilic Interlayer

Solid-state lithium batteries are generally considered as the next-generation battery technology that benefits from inherent nonflammable solid electrolytes and safe harnessing of high-capacity lithium metal. Among various solid-electrolyte candidates, cubic garnet-type Li 7 La 3 Zr 2 O 12 ceramics hold superiority due to their high ionic conductivity (10 –3 to 10 –4 S cm -1 ) and good chemical stability against lithium metal. However, practical deployment of solid-state batteries based on such garnet-type materials has been constrained by poor interfacing between lithium and garnet that displays high impedance and uneven current distribution. Herein, we propose a facile and effective strategy to significantly reduce this interfacial mismatch by modifying the surface of such garnet-type solid electrolyte with a thin layer of silicon nitride (Si 3 N 4 ). This interfacial layer ensures an intimate contact with lithium due to its lithiophilic nature and formation of an intermediate lithium–metal alloy. The interfacial resistance experiences an exponential drop from 1197 to 84.5 Ω cm 2 . Lithium symmetrical cells with Si 3 N 4 -modified garnet exhibited low overpotential and long-term stable plating/stripping cycles at room temperature compared to bare garnet. Furthermore, a hybrid solid-state battery with Si 3 N 4 -modified garnet sandwiched between lithium metal anode and LiFePO 4 cathode was demonstrated to operate with high cycling efficiency, excellent rate capability, and good electrochemical stability. This work represents a significant advancement toward use of garnet solid electrolytes in lithium metal batteries for the next-generation energy storage devices.

25 ENERGY STORAGE↗

Unraveling the Intermediate Reaction Complexes and Critical Role of Support-Derived Oxygen Atoms in CO Oxidation on Single-Atom Pt/CeO 2

CeO 2 -supported Pt single-atom catalysts have been extensively studied due to their relevance in automobile emission control and for the fundamental understanding of CeO 2 -based catalysts. Though CeO 2 -supported Pt nanoparticles are often more active than their single-atom counterparts, the former could easily redisperse to Pt single atom under oxidizing diesel conditions. Therefore, to maximize the reactivity of every Pt atom, it is important to fully understand the reaction mechanism of CeO 2 -supported Pt single atoms. Here, we report a CO oxidation study on a Pt/CeO 2 single-atom catalyst, where we can account for all of the neighbors using in situ and operando spectroscopy techniques and microcalorimetric measurements. Coupled with density functional theory calculations, we present a comprehensive picture of the dynamics of the surface species, the role of surface intermediates, and explain the observed reaction kinetics. We started with a catalyst containing exclusively single atoms and used in situ/operando spectroscopy to provide evidence for their stability during the reaction and to identify the Pt 1 complexes before and during the reaction and their binding to CO. The results reveal that in the precatalyst, Pt is present as Pt(O) 4 on the CeO 2 (111) step edge sites, but during CO oxidation, we find that two Pt 1 complexes coexist, representing two states of the same active site in the reaction cycle. The dominant state/complex remains Pt(O) 4 , which adsorbs CO very weakly as shown by CO microcalorimetry. The second, minority state/complex, Pt(CO)(O) 3 is generated through the reaction of Pt(O) 4 with CO, and CO is bound strongly to Pt 1 . Labile oxygen adatoms from the CeO 2 surface play a major role in the regeneration of Pt(O) 4 either directly from Pt(O) 3 or by reaction with the strongly adsorbed CO in Pt(CO)(O) 3 . We show that the formation of an oxygen vacancy and generation of a labile O* are not barrierless, which explains the long lifetime of Pt(CO)(O) 3 and its detectability despite being a minority complex. The results help to develop a comprehensive view of the dynamic evolution of Pt 1 complexes along the reaction cycle and provide mechanistic insights to guide the design of Pt-based single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Technoeconomic Assessment of a Sequential Step-Leaching Process for Rare Earth Element Extraction from Acid Mine Drainage Precipitates

Herein, Coal waste products have been studied as a new source of Rare Earth Elements (REEs) and other Critical Minerals (CM) essential for the development of renewable energy technologies, but the economic viability of these source materials is not well understood. This paper examines the technoeconomic performance of a novel process for rare earth element extraction from acid mine drainage precipitates (AMDp) in the Appalachian Coal Basin. The three phase extraction process includes excavation and transportation of AMDp, multi-phase pH driven step-leaching of REEs at ambient conditions, and commercial solvent extraction to produce a saleable grade rare earth oxide material that can be reduced to a pure metal. We estimate the life-cycle cost of bench-scale extraction of REEs from two representative Appalachian AMDp feedstock chemistries at between 4000 – 6000 $/kg of mixed REE concentrate produced. Both the AMDp composition and process parameters affect the profitability of REE extraction, with the REE concentration and distribution of REE in the feedstock, extraction and precipitation reagent consumption rates, and the potential for reagent recycling as the key variables. Economically profitable valorization of REE from AMDp will require a combination of continued process innovation and sizable financial incentives to substantially influence domestic supply of REEs.

36 MATERIALS SCIENCE↗

Interactions Between the Amazonian Rainforest and Cumuli Clouds: A Large‐Eddy Simulation, High‐Resolution ECMWF, and Observational Intercomparison Study

Abstract The explicit coupling at meter and second scales of vegetation's responses to the atmospheric‐boundary layer dynamics drives a dynamic heterogeneity that influences canopy‐top fluxes and cloud formation. Focusing on a representative day during the Amazonian dry season, we investigate the diurnal cycle of energy, moisture and carbon dioxide at the canopy top, and the transition from clear to cloudy conditions. To this end, we compare results from a large‐eddy simulation technique, a high‐resolution global weather model, and a complete observational data set collected during the GoAmazon14/15 campaign. The overall model‐observation comparisons of radiation and canopy‐top fluxes, turbulence, and cloud dynamics are very satisfactory, with all the modeled variables lying within the standard deviation of the monthly aggregated observations. Our analysis indicates that the timing of the change in the daylight carbon exchange, from a sink to a source, remains uncertain and is probably related to the stomata closure caused by the increase in vapor pressure deficit during the afternoon. We demonstrate quantitatively that heat and moisture transport from the subcloud layer into the cloud layer are misrepresented by the global model, yielding low values of specific humidity and thermal instability above the cloud base. Finally, the numerical simulations and observational data are adequate settings for benchmarking more comprehensive studies of plant responses, microphysics, and radiation.

Vilà‐Guerau de Arellano, J.↗