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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Warped and Hooked: Mapping the Magellanic Clouds in Three Dimensions Using Red Clump Stars

The Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC) are the Milky Way’s nearest interacting galaxy pair, offering a unique laboratory for studying tidal effects on galactic disks. Despite extensive survey efforts, the 3D geometry of the Magellanic Clouds, particularly the putative warp of the LMC, remains poorly constrained due to incompleteness in their crowded centers and the low stellar density of their peripheries, which demand wide-field coverage. Using red clump (RC) stars as standard candles, corrected for age- and metallicity-dependent population effects with empirically calibrated color–magnitude relations and spatially resolved star formation histories, we construct the most detailed distance map of the Magellanic system to date. Based on ∼2.3 million RC stars from Gaia Data Release 3 combined with modern reddening maps, we measure median heliocentric distances of 50.62 ± 2.32 kpc for the LMC (to ∼23°) and 60.75 ± 2.85 kpc for the SMC (to ∼12°). The maps reveal substructures including the LMC Northern Arm, southern hooks, the Magellanic Bridge, and SMC peripheral overdensities, with refreshed distance estimates. Fitting the LMC disk within 7° yields a global inclination of $i=25\mathop{.}\limits^{^\circ }32\pm 0\mathop{.}\limits^{^\circ }10$ and a line-of-nodes position angle of $\theta = 142\mathop{.}\limits^{^\circ }34\pm 0\mathop{.}\limits^{^\circ }21$. Most strikingly, we find the LMC periphery is warped azimuthally into a U-shaped structure reaching a vertical amplitude of ∼7 kpc at a radius of ∼15 kpc. In future work, we will perform detailed comparisons with live N-body simulations to assess possible formation scenarios for the LMC warp.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Two decades of bacterial ecology and evolution in a freshwater lake

Ecology and evolution are considered distinct processes that interact on contemporary time scales in microbiomes. Here, to observe these processes in a natural system, we collected a two-decade, 471-metagenome time series from Lake Mendota (Wisconsin, USA). We assembled 2,855 species-representative genomes and found that genomic change was common and frequent. By tracking strain composition via single nucleotide variants, we identified cyclical seasonal patterns in 80% and decadal shifts in 20% of species. In the dominant freshwater family Nanopelagicaceae, environmental extremes coincided with shifts in strain composition and positive selection of amino acid and nucleic acid metabolism genes. Further, these genes identify organic nitrogen compounds as potential drivers of freshwater responses to global change. Seasonal and long-term strain dynamics could be regarded as ecological processes or, equivalently, as evolutionary change. Rather than as distinct interacting processes, we propose a conceptualization of ecology and evolution as a continuum to better describe change in microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Link Scheduling in Satellite Networks via Machine Learning Over Riemannian Manifolds

Low Earth Orbit (LEO) satellites play a crucial role in enhancing global connectivity, serving a complementary solution to existing terrestrial systems. In wireless networks, scheduling is a vital process that allocates time-frequency resources to users for interference management. However, LEO satellite networks face significant challenges in scheduling their links towards ground users due to the satellites’ mobility and overlapping coverage. This paper addresses the dynamic link scheduling problem in LEO satellite networks by considering spatio-temporal correlations introduced by the satellites’ movements. The first step in the proposed solution involves modeling the network over Riemannian manifolds, thanks to their representation as symmetric positive definite matrices. We introduce two machine learning (ML)-based link scheduling techniques that model the dynamic evolution of satellite positions and link conditions over time and space. To accurately predict satellite link states, we present a recurrent neural network (RNN) over Riemannian manifolds, which captures spatio-temporal characteristics over time. Furthermore, we introduce a separate model, the convolutional neural network (CNN) over Riemannian manifolds, which captures geometric relationships between satellites and users by extracting spatial features from the network topology across all links. Simulation results demonstrate that both RNN and CNN over Riemannian manifolds deliver comparable performance to the fractional programming-based link scheduling (FPLinQ) benchmark. Remarkably, unlike other ML-based models that require extensive training data, both models only need 30 training samples to achieve over 99% of the sum rate while maintaining similar computational complexity relative to the benchmark.

42 ENGINEERING↗
DOE OSTI2024

Structural insights into GABA A receptor potentiation by Quaalude

Methaqualone, a quinazolinone marketed commercially as Quaalude, is a central nervous system depressant that was used clinically as a sedative-hypnotic, then became a notorious recreational drug in the 1960s-80s. Due to its high abuse potential, medical use of methaqualone was eventually prohibited, yet it persists as a globally abused substance. Methaqualone principally targets GABA A receptors, which are the major inhibitory neurotransmitter-gated ion channels in the brain. The restricted status and limited accessibility of methaqualone have contributed to its pharmacology being understudied. Here, we use cryo-EM to localize the GABA A receptor binding sites of methaqualone and its more potent derivative, PPTQ, to the same intersubunit transmembrane sites targeted by the general anesthetics propofol and etomidate. Both methaqualone and PPTQ insert more deeply into subunit interfaces than the previously-characterized modulators. Binding of quinazolinones to this site results in widening of the extracellular half of the ion-conducting pore, following a trend among positive allosteric modulators in destabilizing the hydrophobic activation gate in the pore as a mechanism for receptor potentiation. These insights shed light on the underexplored pharmacology of quinazolinones and further elucidate the molecular mechanisms of allosteric GABA A receptor modulation through transmembrane binding sites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

2025 Advances in NekRS: Supporting improved performance for nuclear applications

This report presents several 2025 advancements in NekRS, a high-fidelity spectral element CFD code developed at Argonne National Laboratory to support the NEAMS thermal-hydraulics program. The forthcoming v25 release consolidates several of these advances, adding new features for portability across heterogeneous GPU architectures, real-time in situ visualization, improved turbulence modeling, and conjugate heat transfer coupling. Over the past year, NekRS has demonstrated strong scalability and performance on DOE’s leading exascale platforms, including Aurora and Frontier, confirming its readiness for some of the largest and most complex simulations attempted to date. These achievements provide a powerful new platform for high-fidelity data generation, which in turn supports the development and validation of advanced closure models critical for reactor safety and design. Significant algorithmic innovations have also been introduced. A new global runtime h-refinement capability simplifies workflows by reducing mesh preparation burdens and enabling coarse-to-fine restarts. Building on this, a novel multigrid strategy was implemented to accelerate pressure and transport solves at scale, addressing long-standing bottlenecks in exascale CFD. Together, these developments improve both the efficiency and accessibility of high-fidelity simulations for reactor-relevant problems. Collectively, these enhancements represent a major step forward in simulation technology, positioning NekRS as a cornerstone of NEAMS efforts to enable accurate, efficient, and scalable high-fidelity analysis of advanced nuclear systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Island influences on plant functional traits and trait–trait associations across species‐ and community‐scales

The island rule predicts gigantism or dwarfism in body size of island species relative to their mainland counterparts. However, whether other functional traits shift and whether trait–trait associations on islands differ between species and community levels remains unclear. We measured 13 carbon- and water-related functional traits in 37 shared tree species across 35 eastern Chinese islands and 66 nearby mainland plots. We examined species-level trait value shifts and associations under the island rule and compared trait associations between species and communities. Most size-related, wood-anatomical, and hydraulic traits shifted on islands, with large values decreasing and small values increasing; yet, their associations remained stable, aligning with the global trait spectrum and trait–trait coevolution. This stability, despite trait value shifts, suggests evolutionary integration of functional strategies. By contrast, island community-scale trait associations diverged from shared species-level patterns and sometimes reversed, such as positive relationships between wood density and resource-acquisitive traits. Community-level trait associations were stronger on islands, likely reflecting constrained environmental filtering and migration limitation. These contrasting patterns suggest that dominant species can restructure trait associations at the community level, with implications for ecosystem functioning and carbon storage, thereby advancing understanding of plant trait strategies in island systems.

Archipelagos↗
DOE OSTI2024

Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction

ABSTRACT Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a “top 10” list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Microbiology↗
DOE OSTI2025

Environmental Evaluation of Gas Switching Reforming for Low Carbon Hydrogen: A Power-to-X Study

Gas Switching Reforming for hydrogen production (GSR-H2) offers a promising pathway for producing low-carbon hydrogen at scale, with significant implications for Power-to-X (PtX) systems that rely on clean hydrogen as a feedstock for synthetic fuels and chemicals. GSR-H2 integrates inherent carbon capture and thermal self-sufficiency, positioning it as an efficient alternative to conventional steam methane reforming (SMR), proton exchange membrane (PEM) electrolysis, and chemical looping reforming (CLR). Unlike SMR, GSR-H2 avoids external natural gas combustion by leveraging exothermic redox cycles to generate process steam and recover electricity internally. Its innovative reactor design consolidates all reforming stages within a single reactor cluster, eliminating the need for solid circulation found in CLR, thereby reducing capital costs and improving system reliability and scalability. This presentation describes the first environmental life cycle assessment (LCA) of GSR-H2, evaluating its environmental performance across U.S. grid and renewable energy scenarios. In a renewables-powered configuration, GSR-H2 achieves a global warming potential (GWP) of 2.77 kg CO2 equivalent per kg H2, substantially lower than SMR (10.4 kg) and competitive with PEM electrolysis (1.85 kg) and CLR (1.84 kg). Results across additional impact categories, including air quality and water use, support GSR-H2’s role as a complementary hydrogen source in PtX applications. Its reduced environmental burden, thermal integration, and simplified scale-up potential make GSR-H2 a viable contributor to net-zero PtX systems, particularly where renewable energy is abundant and electricity-intensive hydrogen production faces economic or infrastructure constraints.

03 NATURAL GAS↗
DOE OSTI2025

Advancing nuclear forensics competencies at the National Nuclear Center of the Republic of Kazakhstan and conceptual development of a National Nuclear Forensics Library

Since 2021, the National Nuclear Center (NNC) of the Republic of Kazakhstan has been successfully developing a project dedicated to nuclear forensics. The relevance of this project is underscored by Kazakhstan’s leading position in the global uranium mining and export market. The country operates research reactors and is involved in the production of experimental nuclear fuel. The nuclear forensics project is being implemented in several key areas: the project will develop competencies in laboratory research of samples, interpretation of results, and develop a prototype concept for the National Nuclear Forensics Library. In implementing these challenges, the NNC experts draw on the experience of colleagues from world-leading scientific and research centers. Designing a prototype National Nuclear Forensics Library (NNFL) is a challenging project. In conclusion, the solution to this task is based on the IAEA’s approaches, recommendations, and the experience gained from the construction of similar systems in other countries.

and nuclear chemistry↗
DOE OSTI2026

Compound Mesoscale Convective Systems and Low‐Pressure Systems in Tropical Monsoon Regions: Assessing Their Meteorology and Precipitation

Mesoscale convective systems (MCS) and low-pressure systems (LPS) are both strongly associated with precipitation across the regions where they occur, particularly within global monsoon systems; however, their co-occurrence and its relationship to precipitation have not been systematically examined. Here, we use LPS and MCS trackers to detect compound MCS and LPS events in five monsoon regions and assess the association of this co-occurrence with anomalies of winds, precipitation, and other atmospheric variables. Additionally, we investigate the spatial distribution of precipitating MCS and LPS events. Our results show that most (∼60%) MCS and LPS co-occurrences are located in the lower latitudes, where they contribute up to 40% of annual precipitation. We find that compound events generally produce more extreme precipitation than MCS-only or LPS-only events. Furthermore, our assessment of the synoptic and mesoscale composites reveals that the underlying dynamics of compound events exhibit anomalously positive convective available potential energy and an anomalously low-pressure within the location of the event. In terms of the synoptic environment of the features, the compound MCS and LPS events are associated with inverted troughs in three out of five monsoon locations assessed.

Environmental sciences↗
DOE OSTI2024

Adaptive Laboratory Evolution for Enhanced Performance of Cupriavidus Necator on Formic Acid

The threat of global warming, driven by rising carbon emissions, highlights the need to decarbonize our economy. This requires innovative solutions for managing carbon waste and its effective utilization. One promising method for CO2 capture and sequestration is the electrochemical reduction of CO2 to formic acid, a soluble C1 molecule that can be used to store carbon and energy, and as a feedstock for biological conversion. Cupriavidus necator H16, a soil bacterium capable of consuming and growing on formic acid as its sole carbon and energy source, is well positioned to upgrade CO2-derived formic acid into platform chemicals and fuel precursors. To improve the performance of C. necator on formic acid, adaptive laboratory evolution (ALE), a proven tool for improving microbial fitness, has been conducted using continuous pH-stat bioreactors. The system works on the basis that consumption of formic acid raises the pH and triggers the addition of more formic acid to maintain the pH (in this case 6.7), such that formic acid is provided at the same rate as it is consumed. This system has been coupled with level control to achieve continuous fermentation where cells acquiring mutations that improve growth on formic acid become more abundant in the population, from which they can be isolated and characterized. During developmental experiments it was discovered that formic acid accumulated to inhibitory levels. It was determined that the nitrogen source, ammonium hydroxide, must be tailored to the carbon consumption to avoid formic acid accumulation. The ALE ran in three lineages for approximately 3000 hours and more than 500 generations. Evolved isolates obtained from each lineage demonstrated an increase in growth rate in conjunction with improve formate utilization compared to the parental strain when evaluated in pH-stat bioreactors. The isolates with improved performance were then subjected to whole genome sequencing to identify potentially causative mutations. Mutations in several key genes across different lineages have been found and will be evaluated individually and in combination to identify those that improve growth on formic acid. Incorporating these mutations into production strains has the potential to greatly improve formic acid conversion and further industrial decarbonization.

adaptive laboratory evolution↗
DOE OSTI2025

E3SM‐Arctic: Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.

Energy Exascale Earth System Model (E3SM)↗
DOE OSTI2024

The Exoproteome and Surfaceome of Toxigenic Corynebacterium diphtheriae 1737 and Its Response to Iron Restriction and Growth on Human Hemoglobin

Toxin-producing Corynebacterium diphtheriae strains are the etiological agents of the severe upper respiratory disease, diphtheria. A global phylogenetic analysis revealed that biotype gravis is particularly lethal as it produces diphtheria toxin and a range of other virulence factors, particularly when it encounters low levels of iron at sites of infection. Here, to gain insight into how it colonizes its host, we have identified iron-dependent changes in the exoproteome and surfaceome of C. diphtheriae strain 1737 using a combination of whole-cell fractionation, intact cell surface proteolysis, and quantitative proteomics. In total, we identified 1414 of the predicted 2265 proteins (62%) encoded by its reference genome. For each protein, we quantified its degree of secretion and surface exposure, revealing that exoproteases and hydrolases predominate in the exoproteome, while the surfaceome is enriched with adhesins, particularly DIP2093. Our analysis provides insight into how components in the heme-acquisition system are positioned, showing pronounced surface exposure of the strain-specific ChtA/ChtC paralogues and high secretion of the species-conserved heme-binding HtaA protein, suggesting it functions as a hemophore. Profiling the response of the exoproteome and surfaceome after microbial exposure to human hemoglobin and iron limitation reveals potential virulence factors that may be expressed at sites of infection. Data are available via ProteomeXchange with identifier PXD051674.

cell envelope↗
DOE OSTI2026

Organic Rankine Cycle Integration and Optimization for High Efficiency CHP Genset Systems (Final Technical Report)

This project successfully advanced the integration of Organic Rankine Cycle (ORC) technology with reciprocating engine–based combined heat and power (CHP) systems to improve electrical efficiency, total CHP efficiency, and grid-responsive operation. Over three budget periods, the work progressed from high-temperature ORC component development and thermodynamic model validation to next-generation system design, working fluid transition, and techno-economic analysis. Key technical accomplishments include development and validation of a thermodynamic model capable of accurately predicting ORC performance across an expanded temperature and pressure envelope; successful identification and validation of low-global-warming-potential (GWP) working fluids—most notably R1233zd(E)—as viable replacements for R245fa; and demonstration of scalable ORC architectures suitable for integration with 1–20 MW class reciprocating engines. These advances enable flexible CHP configurations that can increase electrical output while maintaining high overall utilization of available thermal energy. The project also produced a clean-sheet design for a next-generation ORC system targeting substantially higher power output per unit, supported by detailed component selection, heat exchanger evaluation, and system-level modeling. Techno-economic analyses indicate that ORC-enabled flexible CHP systems can meet or exceed Department of Energy (DOE) efficiency targets while providing value to both facility operators and the electric grid.. Late-stage testing of the largest next-generation ORC prototype identified limitations related to pump net positive suction head (NPSH) requirements and condenser flooding under certain operating conditions. Although these issues constrained full validation of that configuration within the project timeframe, they provided clear and actionable design guidance for future system refinements. Importantly, validated modeling, smaller-scale testing, and working fluid evaluations confirmed the technical viability of the overall approach. In aggregate, this project met its core objectives by establishing validated design tools, de-risking key ORC technologies for CHP applications, and defining a credible pathway toward commercialization of flexible, high-efficiency CHP systems. The results form a strong foundation for continued development and deployment beyond the conclusion of the DOE-funded effort.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

New Era Towards Autonomous Additive Manufacturing: A Review of Recent Trends and Future Perspectives

Abstract The Additive Manufacturing (AM) landscape has significantly transformed in alignment with Industry 4.0 principles, primarily driven by the integration of Artificial Intelligence (AI) and Digital Twin (DT). However, current Intelligent Additive Manufacturing (IAM) systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction (HMI). This paper reviews existing IAM solutions, emphasizing control, monitoring, process autonomy, and end-to-end integration, and identifies key limitations, such as the absence of a high-level controller for global decision-making. To address these gaps, we propose a transition from IAM to Autonomous Additive Manufacturing (AAM), featuring a hierarchical framework with four integrated layers: knowledge, generative solution, operational, and cognitive. In the cognitive layer, AI agents notably enable machines to independently observe, analyze, plan, and execute operations that traditionally require human intervention. These capabilities streamline production processes and expand the possibilities for innovation, particularly in sectors like in-space manufacturing (ISM). Additionally, this paper discusses the role of AI in self-optimization and lifelong learning, positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy, fostering a more adaptive, resilient manufacturing ecosystem.

Fan, Haolin↗
DOE OSTI2025

Volumetric imaging of the 3D orientation of cellular structures with a polarized fluorescence light-sheet microscope

Polarized fluorescence microscopy is a valuable tool for measuring molecular orientations in biological samples, but techniques for recovering three-dimensional orientations and positions of fluorescent ensembles are limited. We report a polarized dual-view light-sheet system for determining the diffraction-limited three-dimensional distribution of the orientations and positions of ensembles of fluorescent dipoles that label biological structures. We share a set of visualization, histogram, and profiling tools for interpreting these positions and orientations. We model the distributions based on the polarization-dependent efficiency of excitation and detection of emitted fluorescence, using coarse-grained representations we call orientation distribution functions (ODFs). We apply ODFs to create physics-informed models of image formation with spatio-angular point-spread and transfer functions. We use theory and experiment to conclude that light-sheet tilting is a necessary part of our design for recovering all three-dimensional orientations. We use our system to extend known two-dimensional results to three dimensions in FM1-43-labeled giant unilamellar vesicles, fast-scarlet-labeled cellulose in xylem cells, and phalloidin-labeled actin in U2OS cells. Additionally, we observe phalloidin-labeled actin in mouse fibroblasts grown on grids of labeled nanowires and identify correlations between local actin alignment and global cell-scale orientation, indicating cellular coordination across length scales.

Science & Technology - Other Topics↗
DOE OSTI2026

Overview of the Nephele Perturbed Parameter Ensemble for Aerosol‐Cloud Interactions in E3SMv3

Aerosol-cloud interactions (aci) are the leading source of uncertainty in inferring climate sensitivity from the historical record. Earth system models (ESMs) struggle to represent aci because the processes responsible for these phenomena occur at much finer time and space scales than can be resolved by any ESM. Observational constraints provide key benchmarks to test ESMs, but cannot be used alone to fully understand aci processes except in very specific cases where causality is controlled; some degree of modeling is required to infer aci and estimate radiative forcing. Here, we generate and characterize a perturbed parameter ensemble (PPE) in version 3 of the Energy Exascale ESM (E3SMv3). We perturb 25 parameters that govern aci processes over 250 members and integrate the model over present-day and preindustrial aerosol emissions. We find that the process representation in E3SMv3 is flexible and can generate global-mean effective radiative forcings due to aci (ERFaci) ranging from −3.0 to +0.9 W m −2 . The positive ERFaci values simulated by a portion of the PPE are implausible and result from parameter combinations that produce unrealistic top-of-atmosphere energy fluxes. While global-mean cloud droplet number concentration always increases in response to anthropogenic aerosol, cloud liquid water path can both increase and decrease, suggesting that precipitation suppression is not the only aerosol-cloud adjustment represented by E3SMv3. Analysis of which processes control liquid cloud adjustment in the PPE points toward stratiform precipitation processes and aerosol activation, which is consistent with many previous ESMs, as well as the new two-moment convective cloud microphysics in E3SMv3.

Nugent, Jacqueline M. [Univ. of Wyoming, Laramie, ↗
DOE OSTI2025

Overestimated natural biological nitrogen fixation translates to an exaggerated CO 2 fertilization effect in Earth system models

CO 2 fertilization of the terrestrial biosphere is limited by nitrogen. Biological nitrogen fixation (BNF) is the dominant natural nitrogen source to the terrestrial biosphere and can alleviate nitrogen limitation but is poorly constrained in Earth system models (ESMs). Here, in this study, we compare terrestrial BNF from an ensemble of ESMs of the 6th Coupled Model Intercomparison Project to a new global synthesis of observations across natural and agricultural biomes. We find that compared to observations, ESMs underestimate agricultural BNF but overestimate natural BNF in the present day by over 50%. Natural BNF is overestimated in the most productive ecosystems that contribute most to the terrestrial carbon sink (forests and grasslands). ESMs with different BNF representations yield a range of BNF responses to CO 2 enrichment. Some ESMs with phenomenological representations of BNF predict a natural BNF increase in response to a doubling of CO 2 that aligns with a meta-analysis of CO 2 enrichment experiments (31% increase) but fail to account for the substantial carbon cost of BNF. In contrast, ESMs with mechanistic representations of BNF account for its carbon cost as well as its regulation by nitrogen limitation but overestimate the BNF response to a doubling of CO 2 (135% increase). Overall, all current BNF representations in ESMs fall short of fully capturing its response to rising atmospheric CO 2 . Finally, we find a positive correlation between modeled present-day natural BNF and the CO 2 fertilization effect across ESMs, suggesting that overestimated natural BNF translates to an exaggerated CO 2 fertilization effect of approximately 11% in ESMs.

Biological nitrogen fixation↗