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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 73 records · Page 4

Elucidating Instabilities Contributing to Capacity Fade in Bipyridine‐Based Materials for Non‐aqueous Flow Batteries

Abstract Metal‐based non‐aqueous redox flow batteries have the potential for long‐term energy storage if stability requirements can be achieved. One such stability issue in metal coordination complexes arises from ligand shedding in the anolyte upon reduction. Recognizing that the free ligands are relatively more stable than the metal coordination complex under highly reducing conditions, we evaluated a family of metal‐free bipyridinium materials as flow battery anolytes with the corresponding iron coordination complex as the catholyte. Bipyridinium compounds were functionalized for increased electrochemical stability, cycled in flow cells to understand efficiencies, and analyzed for degradation products. Methylation of the bipyridine nitrogens increased electrochemical stability yet left the reduced molecule susceptible to radical‐induced bond cleavage. Subsequent functionalization of bipyridine with carbomethoxy groups resulted in good battery performance with 96 % Coulombic and 90 % voltage efficiency, and improved cycling stability over a methoxy‐substituted anolyte with 14 % vs 36 % capacity fade in the first charge‐discharge cycle.

Kolesnichenko, Claudina X.↗

Subsurface Redox Interactions Regulate Ebullitive Methane Flux in Heterogeneous Mississippi River Deltaic Wetland

Abstract As interfaces connecting terrestrial and ocean ecosystems, coastal wetlands develop temporally and spatially complex redox conditions, which drive uncertainties in greenhouse gas emission as well as the total carbon budget of the coastal ecosystem. To evaluate the role of complex redox reactions in methane emission from coastal wetlands, a coupled reactive‐transport model was configured to represent subsurface biogeochemical cycles of carbon, nitrogen, and sulfur, along with production and transport of multiple gas species through diffusion and ebullition. This model study was conducted at multiple sites along a salinity gradient in the Barataria Basin at the Mississippi River Deltaic Plain. Over a freshwater to saline gradient, simulated total flux of methane was primarily controlled by its subsurface production and consumption, which were determined by redox reactions directly (e.g., methanogenesis, methanotrophy) and indirectly (e.g., competition with sulfate reduction) under aerobic and/or anaerobic conditions. At fine spatiotemporal scales, surface methane fluxes were also strongly dependent on transport processes, with episodic ebullitive fluxes leading to higher spatial and temporal variability compared to the gradient‐driven diffusion flux. Ebullitive methane fluxes were determined by methane fraction in total ebullitive gas and the frequency of ebullitive events, both of which varied with subsurface methane concentrations and other gas species. Although ebullition thresholds are constrained by local physical factors, this study indicates that redox interactions not only determine gas composition in ebullitive fluxes but can also regulate ebullition frequency through gas production.

03 NATURAL GAS↗

Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators

Dilute combustion using exhaust gas recirculation (EGR) presents a cost-effective method for increasing the efficiency of spark-ignition (SI) engines. However, the maximum amount of EGR that can be used at a given condition is limited by a rapid increment of cycle-to-cycle variability (CCV). This study describes a methodology to design a model-based stochastic optimal controller to adjust the cycle-to-cycle fuel injection quantity in order to reduce CCV and further extend the dilute limit. Given the complexity and chaotic nature of combustion events, the controller was enhanced with online learning in order to identify the statistical properties of combustion efficiency, which are needed to generate predictions for next-cycle events. This study showed that a kernel density estimator (KDE) can be used to learn the combustion properties in real time and can be incorporated into the feedback policy in order to calculate the optimal control command. Experimental results suggested that the dilute limit can be extended from 18.5% to 21% EGR fraction at an operating condition relevant for highway cruising. Additionally, the proposed controller can achieve a large CCV reduction with less fuel enrichment compared to previous methods, overall contributing to an increase in 0.2% indicated fuel conversion efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Dissection of Carbon and Nitrogen Cycling in Post-Fire Soil Environments using a Genome- Informed Experimental Community (Final Technical Report)

Wildfires are a natural part of many forest ecosystems, with globally important carbon (C) storage and nutrient cycling consequences, and they are increasing in frequency and severity in Western North America. Forest fires affect soil C stocks in complex ways; some C is released into the atmosphere through combustion, while a large percentage of the C is added to the soil in the form of pyrogenic organic matter. Worldwide, it is estimated that 16% of soil organic matter is pyrogenic, while locally, this number may be as high as 80%. Understanding how wildfires affect soil organic matter cycling requires understanding how microbes respond to pyrogenic organic matter and other post-fire soil conditions. However, our understanding of microbial interactions within post-fire soil was in its infancy at the time of our proposal. Outstanding questions included: Which microbes are capable of degrading pyrogenic organic matter? What are the relevant genes and metabolites associated with this degradation? What are the key interactions among post-fire microbes? Key highlights of outcomes supported by this grant included training eleven early-career scientists and two early-career PIs, publication of twelve peer-reviewed papers, cross-lab collaborations that empowered complex scientific approaches, the development of an open-source automated gas sampler to drive novel insights in C cycling, enhanced understanding of post-fire microbial community dynamics, and novel genetic and molecular insights into microbial responses to fire.

54 ENVIRONMENTAL SCIENCES↗

Catalytic Resonance Theory: The Catalytic Mechanics of Programmable Ratchets

Catalytic reaction networks of multiple elementary steps operating under dynamic conditions via a programmed input oscillation are difficult to interpret and optimize due to reaction system complexity. To understand these dynamic systems, individual elementary catalytic reactions oscillating between catalyst states were evaluated to identify their three fundamental characteristics that define their ability to promote reactions away from equilibrium. First, elementary catalytic reactions exhibit directionality to promote reactions forward or backward from equilibrium as determined by a ratchet directionality metric comprised of the input oscillation duty cycle and the reaction rate constants. Second, catalytic ratchets are defined by the catalyst state of strong or weak binding that permit reactants to proceed through the transition state. Third, elementary catalytic ratchets exhibit a cutoff frequency which defines the transition in applied frequency for which the catalytic ratchet functions to promote chemistry away from equilibrium. All three ratchet characteristics are calculated from chemical reaction parameters including rate constants derived from linear scaling parameters, reaction conditions, and catalyst state. The characteristics of the reaction network’s constituent elementary catalytic reactions provided an interpretation of complex reaction networks and a method of predicting the behavior of dynamic surface chemistry on oscillating catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metabolically diverse microorganisms mediate methylmercury formation under nitrate-reducing conditions in a dynamic hydroelectric reservoir

Brownlee Reservoir is a mercury (Hg)-impaired hydroelectric reservoir that exhibits dynamic hydrological and geochemical conditions and is located within the Hells Canyon Complex in Idaho, USA. Methylmercury (MeHg) contamination in fish is a concern in the reservoir. While MeHg production has historically been attributed to sulfate-reducing bacteria and methanogenic archaea, microorganisms carrying the hgcA gene are taxonomically and metabolically diverse and the major biogeochemical cycles driving mercury (Hg) methylation are not well understood. In this study, Hg speciation and redox-active compounds were measured throughout Brownlee Reservoir across the stratified period in four consecutive years (2016–2019) to identify the location where and redox conditions under which MeHg is produced. Metagenomic sequencing was performed on a subset of samples to characterize the microbial community with hgcA and identify possible links between biogeochemical cycles and MeHg production. Biogeochemical profiles suggested in situ water column Hg methylation was the major source of MeHg. These profiles, combined with genome-resolved metagenomics focused on hgcA-carrying microbes, indicated that MeHg production occurs in this system under nitrate- or manganese-reducing conditions, which were previously thought to preclude Hg-methylation. Using this multidisciplinary approach, we identified the cascading effects of interannual variability in hydrology on the redox status, microbial metabolic strategies, abundance and metabolic diversity of Hg methylators, and ultimately MeHg concentrations throughout the reservoir. This work expands the known conditions conducive to producing MeHg and suggests that the Hg-methylation mitigation efforts by nitrate or manganese amendment may be unsuccessful in some locations.

54 ENVIRONMENTAL SCIENCES↗

Biochemical responses of hairgrass (Deschampsia caespitosa) to hydrological change

Plant growth and development are closely related to water availability. Water deficit and water excess are detrimental to plants, causing a series of damage to plant morphology, physiological and biochemical processes. In the long evolutionary process, plants have evolved an array of complex mechanisms to combat against stressful conditions. In the present study, the duration-dependent changes in ascorbate (AsA) and glutathione (GSH) contents and activities of enzymes involved in the AsA-GSH cycle in hairgrass ( Deschampsia caespitosa ) in response to water stress was investigated in a pot trial using a complete random block design. The treatments were as follows: (1) heavily waterlogging, (2) moderate waterlogging, (3) light waterlogging, (4) light drought, (5) moderate drought, (6) heavily drought, and (7) a control (CK) with plant be maintained at optimum water availability. The hairgrass plants were subjected to waterlogging or drought for 7, 14, 21 and 28 days and data were measured following treatment. Results revealed that hairgrass subjected to water stress can stimulate enzymatic activities of ascorbate peroxidase (APX), glutathione peroxidase (GPX), glutathione reductase (GR), dehydroascorbate reductase (DHAR), monodehydroascorbate reductase (MDHAR) and L-galactono-1, 4-lactone dehydrogenase (GalLDH), switched on the ascorbate-glutathione (AsA-GSH) cycle and the L-galactose synthesis, up-regulated the contents of AsA and GSH, and maintained higher ratios of ascorbate to dehydroascorbate (AsA/DHA) and reduced glutathione to oxidized glutathione (GSH/GSSG) to alleviate potential oxidative damage. However, the light waterlogging did not induce hairgrass under stress to switch on the AsA-GSH pathway. In general, the critic substances and enzyme activities in AsA-GSH metabolic pathway increased as the increase of water stress intensity. As the increase of exposure duration, the critic antioxidant substances content and enzyme activities increased first and then maintained a relatively stable higher level. Our findings provide comprehensive information on biochemical responses of hairgrass to hydrological change, which would be a major step for accelerating ecological restoration of degradation alpine marshes in the Qinghai-Tibetan Plateau.

Luo, Qiaoyu↗

Building a Framework to Understand Transition Metals' Behavior in Euxinic Conditions (Final Technical Report)

This project focuses first and foremost on metal sulfide geochemistry and mineralogy as controlled by a complex matrix of environmental factors. The principal investigator’s group aim to illuminate the metal-sulfide reaction mechanisms, rates, and pathways through systematic experimentation and data collection and analyzing the relationships between the characteristics of the produced metal sulfide solid-phase/aqueous complexes and the environmental factors. This understanding is essential for obtaining a full picture of the complex cycling patterns of single or multi metal species in sulfidic environments ranging from deep-see basins, hydrothermal vents, inland seas, terrestrial water bodies, to engineered remediation systems. The specific goal of this past project was to illuminate the reaction mechanisms and kinetics of metal anions and sulfide in mixed metal cation-metal anion-sulfide systems under various aqueous conditions (which resembled a range of naturally occurring euxinic settings). For the period of this contract, we investigated the molybdenum-iron-sulfide system, with an emphasis on the conditions that caused solid phase formation. We focused on quantifying the mobility/sequestration of molybdenum under each experimental condition and identified the changes of valence states for each involved element (i.e., Mo, Fe, and S) in the precipitate. We also proposed pathways for the electron transfer that occurred in aqueous chemistry. The major analytical tools used for this study include UV-visible light spectroscopy, transmission electron microscopy, X-ray photoelectron spectroscopy, and synchrotron-based X-ray absorption spectroscopy (access gained through facility proposals to the Canadian Light Source). The biggest finding of this project was that besides pH, the iron-sulfur chemistry has a dominant control of the thiolation kinetics and subsequent reduction of Mo(VI), which are likely prerequisites of molybdenum sequestration in anoxic conditions. The results have been written up as manuscript by the end of this project (see Phillips et al.). The experimental results of this project may be critical for advancing our understanding of (1) basic chemistry involving transition metals and reduced sulfur species, (2) the validity of certain geochemical proxies, and (3) the stability and evolution of euxinic geochemical environments. It is noted that the basic results obtained through this project also have implications for Mo-S cluster-based catalyst development in inorganic chemistry and materials sciences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aging heat treatment design for Haynes 282 made by wire-feed additive manufacturing using high-throughput experiments and interpretable machine learning

Wire-feed additive manufacturing (WFAM) produces superalloys with complex thermal cycles and unique microstructures, often requiring optimized heat treatments. To address this challenge, we present a hybrid approach that combines high-throughput experiments, precipitation simulation, and machine learning to design effective aging conditions for the WFAM Haynes 282 superalloy. Our results demonstrate that the γ’ radius is the critical microstructural feature for strengthening Haynes 282 during post-heat treatment compared with the matrix composition and γ’ volume fraction. New aging conditions at 770°C for 50 hours and 730°C for 200 hours were discovered based on the machine learning model and were applied to enhance yield strength, bringing it on par with the wrought counterpart. This approach has significant implications for future AM alloy production, enabling more efficient and effective heat treatment design to achieve desired properties.

CALPHAD↗

Advanced Manufacturing Workflows for Tokamak Internal Components

The project aim was to create a new advanced manufacturing workflow for the design and creation of an internal component in a fusion device, enabling a low-cost, rapid design and fabrication cycle. As a result, two demonstration components were manufactured, and mechanical properties for two feedstock materials were tested in the context of fusion device conditions. This work shows a technological scoping toward future manufacturing of complex components in topologies relevant to magnetic fusion devices via additive manufacturing.

42 ENGINEERING↗

Radiation-Induced Plutonium Redox Chemistry

Plutonium plays a key role in global actinide research and nuclear fuel cycle technologies, and yet, our fundamental understanding of its inherent radiation-induced chemical behavior is limited. These radiation-induced processes cannot simply be switched off, as they are as fundamentally inherent to plutonium as the impact of relativistic effects on its f-electrons. In less chemically complex actinide systems, such as aqueous solutions of neptunium and americium, , radiolysis products play a significant role in the redox cycling of their oxidation states. However, plutonium's multiple, coexisting, and chemically active oxidation states, which comprise of bare ions and dioxo cations, provide additional redox pathways that complicate radiation-induced processes. Oxidation state control is critical for the manipulation of plutonium, especially in used nuclear fuel reprocessing technologies, where oxidation specific states are successfully extracted, and others rejected. Consequently, mechanistically understanding the behavior of plutonium’s multiple oxidation states in the presence of intense ionizing radiation fields is essential for predicting the behavior of this element under multiple conditions that support the development and innovation of nuclear fuel cycle technologies. Here, we present recent advances in our understanding of plutonium radiation chemistry, including the first-ever multiscale model for predicting gamma radiation-induced plutonium redox chemistry, and new chemical kinetics for the reaction of plutonium and its complexes of tributyl phosphate (TBP), N,N-di-(2-ethylhexyl)butyramide (DEHBA), and N,N-di-(2-ethylhexyl)isobutyramide (DEHiBA) with transients radiolysis products, a measured using electron pulse radiolysis.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

How AI Predicts the Untrained and Unseen

Focus Area: Model predictability improvements (Primary); Data optimization (secondary); Data complexity insights (secondary). The Scientific Challenge: If we believe that a future under extreme conditions will look very differently from today, we can likely agree that ML/AI models trained on past and present datasets will not be adequate to make reliable predictions into the future. This is true for water cycling, as well as biogeochemistry and other Earth system components and behaviors. Additionally, ML/AI models are inherently non-physical. Despite the flourishing success of ML/AI in many applications, such as computer vision, natural language process, and gaming, even the most sophisticated AI models don’t understand the very basic physical laws. Therefore, a natural question is: Can we trust ML/AI based predictions of Earth system behaviors that are fundamentally driven by physical laws? So, are physics models with meticulous process representation a better choice? Not exactly. Physical models, when firmly rooted in first principles, work great at predicting behaviors of systems with a well-defined set of boundary conditions and variables. However, as a complex system, the number of parameters and the degree of complexity and dynamics in processes, coupling, and scale dependent emergent behaviors make the Earth system behaviors very challenging to predict with physical models composed of deterministic laws. In addition, due to the lack of fundamental understandings, physical models often implement empirical correlations derived from observations with biases from locality of data generation. Because correlation is not necessarily causation or comply with first principles, scaling of model predictions beyond locality is often invalid. Beyond the limitation of models, physics or AI, our knowledge of the Earth system is limited by the lack of observational technologies and resources. Insufficient data density, dimensionality and diversity only offer a sliced (or projected) view of the Earth system, e.g. Plato’s Cave analogy, limiting our capability to better understand and represent fundamental processes in models.

54 ENVIRONMENTAL SCIENCES↗

A Fluorinated Lewis Acidic Organoboron Tunes Polysulfide Complex Structure for High–Performance Lithium–Sulfur Batteries

Many challenges in lithium-sulfur (Li–S) batteries are associated with the radical change in lithium polysulfide (LPS) solubility during cycling, but chemical approaches to address such inconsistency are still lacking. Here, the use of a strong Lewis acidic fluorinated organoboron, tri(2,2,2-trifluoroethyl) borate (TFEB), is reported as a multi-functional mediator to simultaneously overcome multiple technical barriers in practical Li–S batteries. TFEB acts as an anion acceptor and forms strong molecular complexes with Lewis basic LPS. The TFEB-LPS complexes have consistent solubility across the full polysulfide spectrum and deliver several times improved better redox kinetics, unlocking a true redox catalytic mechanism that covers the majority of redox events in thick sulfur cathodes. As a result, Li–S batteries evaluated under practical conditions exhibit significantly improved discharge capacity, rate capability, and cycling stability with the addition of the TFEB additive. More importantly, TFEB also contributes to the stabilization of lithium anode in the presence of polysulfides by generating strong interfacial film. These attributes significantly improve the cycling stability of practical Li–S pouch cells, which are assembled with a unit energy density of 219 Wh kg –1 . Finally, the results provide new molecular insights on the design of unlocking solvation networks of practical Li–S systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

High pressure, high flow rate batch mixing apparatus for high throughput experiments

An automated, high pressure, high flow rate batch mixing apparatus has been designed and constructed for rapid, stable, and repeatable mixing of multiple gases and vapors. The apparatus operates as an intermittent batch mixer with cycles of topping off fresh mixture to maintain pressure in an accumulator tank until consumed in an experimental apparatus. At high duty cycles, the apparatus can also function at steady state. This style of mixing is suitable for experiments such as high repetition rate shock tubes and other devices with intermittent flow demands. It is compact and portable, facilitating use in locations such as synchrotron light sources. The entire apparatus is heated to permit the mixing of vapors from species with low volatilities. The apparatus is fully automated and runs for extended periods with the only intervention being to refresh reagent supplies. Here, the accuracy and repeatability of the apparatus were verified by periodic gas sampling and analysis with gas chromatography. Multi-component mixtures spanning a wide range of complexity, dilution, and volatility of constituents have been prepared. The compositions of the majority of the mixture were found to be stable over several filling cycles, repeatable, and with the proper calibration of set-point conditions, accurate. Challenges were encountered preparing a mixture from multi-component liquids, and potential solutions are discussed.

47 OTHER INSTRUMENTATION↗

Update on the Investigation of Commercial Drying Cycles Using the Advanced Drying Cycle Simulator

The purpose of this report is to document updates on the apparatus to simulate commercial vacuum drying procedures at the Nuclear Energy Work Complex at Sandia National Laboratories. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system during subsequent storage and disposal. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates well-designed investigations of drying process efficacy and water retention. Scaled tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes. This report documents a new test apparatus, the Advanced Drying Cycle Simulator (ADCS). This apparatus was built to simulate commercial drying procedures and quantify the amount of residual water remaining in a pressurized water reactor (PWR) fuel assembly after drying. The ADCS was constructed with a prototypic 17×17 PWR fuel skeleton and waterproof heater rods to simulate decay heat. These waterproof heaters are the next generation design to heater rods developed and tested at Sandia National Laboratories in FY20. This report describes the ADCS vessel build that was completed late in FY22, including the receipt of the prototypic length waterproof heater rods and construction of the fuel basket and the pressure vessel components. In addition, installations of thermocouples, emissivity coupons, pressure and vacuum lines, pressure transducers, and electrical connections were completed. Preliminary power functionality testing was conducted to demonstrate the capabilities of the ADCS. In FY23, a test plan for the ADCS will be developed to implement a drying procedure based on measurements from the process used for the High Burnup Demonstration Project. While applying power to the simulated fuel rods, this procedure is expected to consist of filling the ADCS vessel with water, draining the water with applied pressure and multiple helium blowdowns, evacuating additional water with a vacuum drying sequence at successively lower pressures, and backfilling the vessel with helium. Additional investigations are expected to feature failed fuel rod simulators with engineered cladding defects and guide tubes with obstructed dashpots to challenge the drying system with multiple water retention sites.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Preliminary Simulations of Commercial Drying Cycles Using the Advanced Drying Cycle Simulator

The purpose of this report is to document updates on the apparatus to simulate commercial vacuum drying procedures at the Nuclear Energy Work Complex at Sandia National Laboratories. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system during subsequent storage and disposal. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates well-designed investigations of drying process efficacy and water retention. Scaled tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes. This report documents fiscal year 2023 (FY23) updates on the Advanced Drying Cycle Simulator (ADCS). This apparatus was built to simulate commercial drying procedures and quantify the amount of residual water remaining in a pressurized water reactor (PWR) fuel assembly after drying. The ADCS was constructed with a prototypic 17×17 PWR fuel skeleton and waterproof heater rods to simulate decay heat. These waterproof heaters are the next generation design to heater rods developed and tested at Sandia National Laboratories in FY20. In FY23, a series of four simulated commercial drying tests was completed. This report presents the temperature and pressure histories of the drying tests as well as axial temperature profiles that can be compared to data from the Electric Power Research Institute (EPRI) High Burnup Demonstration TN-32B cask. Water content measurements and dew point calculations from a Hiden Analytical HPR-30 mass spectrometer are also presented in this report. Due to familiarization with this first-of-a-kind system, refinements to equipment calibration and test procedures have been identified to better match commercial drying cycles for future simulated tests. However, the presented data demonstrate the successful construction and operation of a viable research platform for quantifying residual water content closely approaching that expected in dry storage canisters during commercial drying procedures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NGEE Arctic Authorship Guidelines

Authorship Guidelines were developed to help facilitate trust among team members as we span multiple institutions, scientific disciplines, and career stages. NGEE Arctic was built on a foundation of open science, data sharing, and collaboration. In Phase 4 of the project, it was particularly important to keep this foundation in mind as we develop new collaborations across the Arctic. Included in this package is one *.pdf. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

Iversen, Colleen [ORNL] (ORCID:0000000182933450)↗

Systems Level Understanding of Interconnected Methane and Nitrogen Cycles Using Complex Synthetic Communities

The main goal of this project was to follow up on prior discovery of the communal nature of methane utilization by the aerobic methanotrophic bacteria, resulting in carbon transfer along a food chain. This goal was approached via manipulation of specially designed, synthetic bacterial communities, fed exclusively by methane, under a variety of simulated environmental conditions. Using (meta)genomics, metatranscriptomics, stable isotope probing and mutant generation, we obtained solid evidence for the nature of the core microbiota involved in collaborative methane consumption, the major players (true methanotrophs) being the members of the family Methylococcaceae, their major partners (non-methanotrophic methylotrophs) being members of the family Methylophilaceae, and minor but persistent partners in the communities being members of the orders Burkholderiales and Bacteroidetes. Metabolic reconstruction from single genomes and metagenome-assembled genomes (MAGs), along with metatranscriptomics results delineated major pathways for carbon metabolism, suggesting that the methanotrophs share different organic compounds with different functional guilds: methanol with Methylophilaceae, acetate with Burkholderiales, and polymeric substances with Bacteroidetes. Overall, the results of this project expand our understanding of microbial metabolism of methane and, thus, provide basis for strategies for microbial methane mitigation, with obvious benefits to the society of the United States and worldwide.

54 ENVIRONMENTAL SCIENCES↗