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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Systems biology-guided understanding of white-rot fungi for biotechnological applications: A review

Plant-derived biomass is the most abundant biogenic carbon source on Earth. Despite this, only a small clade of organisms known as white-rot fungi (WRF) can efficiently break down both the polysaccharide and lignin components of plant cell walls. This unique ability imparts a key role for WRF in global carbon cycling and highlights their potential utilization in diverse biotechnological applications. To date, research on WRF has primarily focused on their extracellular 'digestive enzymes', while knowledge of their intracellular metabolism remains underexplored. Systems biology has been demonstrated to be a powerful approach to elucidate biological processes in numerous organisms, including WRF. Thus, here we review systems biology methods applied to WRF to date, highlight observations related to their intracellular metabolism, and conduct a comparative extracellular proteomic analysis to establish further correlations between WRF species, enzymes, and cultivation conditions. Lastly, we discuss biotechnological opportunities of WRF as well as challenges and future research directions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Real-time visualization of particle evolution during reactive flux-assisted processing of aluminum melts

Here, a multi-modal, multi-scale correlative tomography investigation of Al-TiC metal matrix composites processed via flux-assisted reaction synthesis is reported. Synchrotron X-ray microradiography is utilized to visualize the reaction and particle evolution in real-time. Changes in particle diameter and areal number density suggest that the process is nucleation- rather than growth-dominated. At 950 °C, the bulk of the reaction takes place in a relatively short time span of less than 600 s. The microstructure is imaged at higher resolution in 2D (scanning electron microscopy) and 3D (synchrotron X-ray nanotomography), revealing the formation of carbide particles with a hexagonal platelet morphology. We propose that the morphology arises due to the incorporation of Si impurities during the experiment. It is expected that the correlative tomography workflow and analysis may guide future metal matrix composite (MMC) processing strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Insights into Rotational and Translational Dynamics in Mixtures of Ethylene Glycol and Choline Chloride Using Nuclear Magnetic Resonance Techniques

This work examines molecular dynamics and interactions in ethylene glycol–choline chloride (EG–ChCl) mixtures across 0–33 mol % ChCl, spanning the true eutectic region near 17–20 mol % and the commonly used 1:2 formulation. We combine pulsed-field-gradient (PFG) diffusion, fast-field-cycling (FFC) relaxometry, temperature-dependent 13 C T 1 , and nuclear Overhauser effect spectroscopy (NOESY) to disentangle local from macroscopic dynamics. PFG and FFC show that both translational and average rotational motions largely track the strong increase in viscosity with ChCl content, with ethylene glycol consistently diffusing faster than the choline cation and no global dynamical anomaly at the eutectic composition. More subtle, site-specific composition effects nevertheless emerge. The ratio of the diffusion coefficient of the hydroxyl group of choline to the diffusion coefficient of the methyl group of choline displays a shallow minimum in the 17–25 mol % region, indicating a modest change in how the hydroxyl-bearing end of choline samples the underlying translational motion relative to the methyl groups. 13 C T 1 analysis shows that rotational correlation times at 25 °C generally increase with ChCl, reflecting viscosity-coupled slowing, while the CH 2 –N α site exhibits a small but reproducible deviation from this monotonic trend near the eutectic. NOESY spectra at similar compositions reveal enhanced cross-relaxation between EG and choline protons, consistent with increased headgroup–solvent contact density rather than a wholesale structural rearrangement. Overall, our multitechnique study demonstrates that EG–ChCl dynamics are predominantly viscosity-dominated, with the eutectic region acting as a subtle dynamical crossover where specific choline segments become maximally coupled to the hydrogen-bond network. These insights refine the structure–dynamics picture of choline-chloride DESs and provide practical guidance for tuning composition in electrochemical, separation, and catalytic applications.

diffusion↗
DOE OSTI2025

Tuning Copolymer Microstructure Using Ring-Opening Cross-Metathesis Polymerization

The capability of ring-opening cross-metathesis (RO/CM) polymerization to produce alternating copolymers was studied. By treating commercial polybutadiene (PB) with bulky oxanorbornene monomers and Ru-based olefin metathesis catalysts, alternating copolymers were produced under mild conditions with high sequence fidelities. Here, we found that alternating copolymers could be produced starting from a variety of butadiene sources including PB, cyclooctadiene (COD), or t,t,t-1,5,9-cyclododecatriene (CDT), highlighting for the first time the kinetic pathway independence of this process. Kinetic copolymerization analysis of an oxanorbonene monomer with CDT revealed that much higher monomer conversions were obtained compared with the analogous homopolymerizations and showed evidence of alternating monomer incorporation. Copolymerization of these monomers also enabled good control when targeting different molecular weights. Copolymer thermal analysis revealed a strong correlation between thermal behavior and alternating sequence fidelity, providing a second lever beyond composition to tune thermal behavior. These data demonstrate that a broad variety of polymer microstructures can be accessed via RO/CM polymerization and highlight the potential of CDT in alternating copolymer synthesis.

Foster, Jeffrey C. [Oak Ridge National Laboratory ↗
DOE OSTI2022

Designing Glass and Crystalline Phases of Metal–Bis(acetamide) Networks to Promote High Optical Contrast

Owing to their high tunability and predictable structures, metal–organic materials offer a powerful platform to study glass formation and crystallization processes and to design glasses with unique properties. In this work, we report a novel series of glass-forming metal–ethylenebis(acetamide) networks that undergo reversible glass and crystallization transitions below 200 °C. The glass-transition temperatures, crystallization kinetics, and glass stability of these materials are readily tunable, either by synthetic modification or by liquid-phase blending, to form binary glasses. Pair distribution function (PDF) analysis reveals extended structural correlations in both single and binary metal–bis(acetamide) glasses and highlights the important role of metal–metal correlations during structural evolution across glass–crystal transitions. Notably, the glass and crystalline phases of a Co–ethylenebis(acetamide) binary network feature a large reflectivity contrast ratio of 4.8 that results from changes in the local coordination environment around Co centers. These results provide new insights into glass–crystal transitions in metal–organic materials and have exciting implications for optical switching, rewritable data storage, and functional glass ceramics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone

The spatial distribution of organics in geological samples can be used to determine when and how these organics were incorporated into the host rock. Mass spectrometry (MS) imaging can rapidly collect a large amount of data, but ions produced are mixed without discrimination, resulting in complex mass spectra that can be difficult to interpret. Here, we apply unsupervised and supervised machine learning (ML) to help interpret spectra from time-of-flight-secondary ion mass spectrometry (ToF-SIMS) of an organic-carbon-rich mudstone of the Middle Jurassic of England (UK). It was previously shown that the presence of sterane molecular biomarkers in this sample can be detected via ToF-SIMS (Pasterski, M. J. et al., Astrobiology 2023, 23, 936). We use unsupervised ML on scanning electron microscopy–electron dispersive spectroscopy (SEM-EDS) measurements to define compositional categories based on differences in elemental abundances. We then test the ability of four ML algorithms─k-nearest neighbors (KNN), recursive partitioning and regressive trees (RPART), eXtreme gradient boost (XGBoost), and random forest (RF)─to classify the ToF-SIM spectra using (1) the categories assigned via SEM-EDS, (2) organic and inorganic labels assigned via SEM-EDS, and (3) the presence or absence of detectable steranes in ToF-SIMS spectra. In terms of predictive accuracy and balanced accuracy, KNN was the best performing model and RPART the worst. The feature importance, or the specific features of the ToF-SIM spectra used by the models to make classifications, cannot be determined for KNN, preventing posthoc model interpretation. Nevertheless, the feature importance extracted from the other models was useful for interpreting spectra. In conclusion, we determined that some of the organic ions used to classify biomarker containing spectra may be fragment ions derived from kerogen which is abundant in this mudstone sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Predictive Inverse Model for Advective Heat Transfer in a Short–Circuited Fracture: Dimensional Analysis, Machine Learning, and Field Demonstration

Identifying fluid flow maldistribution in planar geometries is a well–established problem in subsurface science/engineering. Of particular importance to the thermal performance of enhanced (or “engineered”) geothermal systems is identifying the existence of nonuniform (i.e., heterogeneous) permeability and subsequently predicting advective heat transfer. Here, machine learning via a genetic algorithm (GA) identifies the spatial distribution of an unknown permeability field in a two–dimensional Hele–Shaw geometry (i.e., parallel plates). The inverse problem is solved by minimizing the L2 norm between simulated residence time distribution (RTD) and measurements of an inert tracer breakthrough curve (BTC) (C–Dot nanoparticle). Principal component analysis (PCA) of spatially correlated permeability fields enabled reduction of the parameter space by more than a factor of 10 and restricted the inverse search to reservoir–scale permeability variations. Thermal experiments and tracer tests conducted at the mesoscale Altona Field Laboratory (AFL) demonstrate that the method accurately predicts the effects of extreme flow channeling on heat transfer in a single bedding–plane rock fracture. However, this is only true when the permeability distributions provide adequate matches to both tracer RTD and frictional pressure loss. Without good agreement to frictional pressure loss, it is still possible to match a simulated RTD to measurements, but subsequent predictions of heat transfer are grossly inaccurate. Here, the results of this study suggest that it is possible to anticipate the thermal effects of flow maldistribution, but only if both simulated RTDs and frictional pressure loss between fluid inlets and outlets are in good agreement with measurements.

42 ENGINEERING↗
DOE OSTI2025

Cyclization of archaeal membrane lipids impacts membrane protein activity and archaellum formation

Enhancement of the cyclization of membrane lipids GDGTs (glycerol dialkyl glycerol tetraethers) is a critical strategy for archaea to adapt to various environmental stresses. However, the physiological function of membrane lipid cyclization remains unclear. Here, we reported that the GDGT ring synthases mutant, deficient in GDGT cyclization, inhibited archaellum formation and reduced cell motility in thermoacidophilic crenarchaeon Sulfolobus acidocaldarius . This inhibition was caused by decreased transcription of the archaellum operon, likely due to cleavage of the C-terminal domains in transmembrane proteins ArnRs, the transcription factors that regulate archaellum operon expression. The transcriptomic and proteomic analysis showed deficiency of GDGT cyclization broadly impacted the expression of membrane associate proteins, including respiratory chain proteins, and decreased cellular ATP concentration. Moreover, phylogenetic analysis demonstrated that the correlation between GDGT cyclization and archaellum formation is widespread among (hyper)thermophilic archaea, and this was further verified in the euryarchaeon Thermococcus kodakarensis. Our findings suggested that archaea modify their membrane lipids to profoundly alter cellular appendages and cell physiology to adapt to environmental fluctuations.

Yang, Wei (ORCID:0000000262755981)↗
DOE OSTI2022

Dark Energy Survey Year 3 results: galaxy clustering and systematics treatment for lens galaxy samples

ABSTRACT In this work, we present the galaxy clustering measurements of the two DES lens galaxy samples: a magnitude-limited sample optimized for the measurement of cosmological parameters, maglim, and a sample of luminous red galaxies selected with the redmagic algorithm. maglim/redmagic sample contains over 10 million/2.5 million galaxies and is divided into six/five photometric redshift bins spanning the range z ∈ [0.20, 1.05]/z ∈ [0.15, 0.90]. Both samples cover 4143 $\deg ^2$ over which we perform our analysis blind, measuring the angular correlation function with an S/N ∼ 63 for both samples. In a companion paper, these measurements of galaxy clustering are combined with the correlation functions of cosmic shear and galaxy–galaxy lensing of each sample to place cosmological constraints with a 3 × 2pt analysis. We conduct a thorough study of the mitigation of systematic effects caused by the spatially varying survey properties and we correct the measurements to remove artificial clustering signals. We employ several decontamination methods with different configurations to ensure the robustness of our corrections and to determine the systematic uncertainty that needs to be considered for the final cosmology analyses. We validate our fiducial methodology using lognormal mocks, showing that our decontamination procedure induces biases no greater than 0.5σ in the (Ωm, b) plane, where b is the galaxy bias.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Dark Energy Survey Year 3 results: Imprints of cosmic voids and superclusters in the Planck CMB lensing map

ABSTRACT The CMB lensing signal from cosmic voids and superclusters probes the growth of structure in the low-redshift cosmic web. In this analysis, we cross-correlated the Planck CMB lensing map with voids detected in the Dark Energy Survey Year 3 (Y3) data set (∼5000 deg2), expanding on previous measurements that used Y1 catalogues (∼1300 deg2). Given the increased statistical power compared to Y1 data, we report a 6.6σ detection of negative CMB convergence (κ) imprints using approximately 3600 voids detected from a redMaGiC luminous red galaxy sample. However, the measured signal is lower than expected from the MICE N-body simulation that is based on the ΛCDM model (parameters Ωm = 0.25, σ8 = 0.8), and the discrepancy is associated mostly with the void centre region. Considering the full void lensing profile, we fit an amplitude $A_{\kappa }=\kappa _{{\rm DES}}/\kappa _{{\rm MICE}}$ to a simulation-based template with fixed shape and found a moderate 2σ deviation in the signal with Aκ ≈ 0.79 ± 0.12. We also examined the WebSky simulation that is based on a Planck 2018 ΛCDM cosmology, but the results were even less consistent given the slightly higher matter density fluctuations than in MICE. We then identified superclusters in the DES and the MICE catalogues, and detected their imprints at the 8.4σ level; again with a lower-than-expected Aκ = 0.84 ± 0.10 amplitude. The combination of voids and superclusters yields a 10.3σ detection with an Aκ = 0.82 ± 0.08 constraint on the CMB lensing amplitude, thus the overall signal is 2.3σ weaker than expected from MICE.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Trigonal symmetry breaking and its electronic effects in the two-dimensional dihalides MX 2 and trihalides MX 3

We study the consequences of the approximately trigonal (D 3d ) point symmetry of the transition metal (M) site in two-dimensional van der Waals MX 2 dihalides and MX 3 trihalides. The trigonal symmetry leads to a 2-2-1 orbital splitting of the transition metal d shell, which is best represented by d orbitals that describe the trigonal rather than Oh symmetry. The ligand-ligand bond length differences (rather than metal-ligand) take the role of a Jahn-Teller-like mode and in combination with interlayer distances and dimensionality effects tune the crystal field splittings and bandwidths. These effects, in turn, are amplified by electronic correlation effects—leading to crystal field splittings of the order of 0.1–1 eV between the singlet and the lowest orbital doublet—as opposed to the often assumed degenerate 3 t 2g states. Our calculations explain why most of the materials in this family are insulating, and why these considerations have to be taken into account in realistic models of them. Further, orbital order coupled to various lower symmetry lattice modes may lift the remaining orbital degeneracies, and we explain how these may support unique electronic states using ZrI 2 and CuCl 2 as examples, and offer a brief overview of possible electronic configurations in this class of materials. By building and analyzing Wannier models adapted to the appropriate symmetry we examine how the interplay among trigonal symmetry, electronic correlation effects, and – d orbital charge transfer leads to insulating, orbitally polarized magnetic and/or orbital-selective Mott states, and we provide a simple framework and numerical tool for others. Our paper establishes a rigorous framework to understand, control, and tune the electronic states in low-dimensional correlated halides. Furthermore, our analysis shows that trigonal symmetry and its breaking is a key feature of the two-dimensional halides that needs to be accounted for in search of novel electronic states in materials ranging from CrI 3 to α–RuCl 3 .

2-dimensional systems↗
DOE OSTI2026

Measurement of the 252 Cf ⁢(sf) prompt fission neutron spectrum utilizing 12 C ⁡(𝑛, 𝑛) and 9 Be ⁢(𝑛, 𝑛) neutron scattering reference measurements

The 252 Cf spontaneous fission (sf), prompt fission neutron spectrum (PFNS) is a fundamental quantity for nuclear physics measurements of neutron-emitting reactions. This energy distribution of neutrons emitted from fission has been considered a neutron data standard for decades and has been utilized as a reference for neutron detection efficiency, validation of Monte Carlo simulations, benchmarking of dosimetry standards, and more. A significant portion of the global collection of nuclear data on neutron-induced reactions is correlated with the 252 Cf ⁢(sf) PFNS. Despite the reliance on this quantity by the nuclear physics community, the historical collection of 252 Cf PFNS measurements display systematic disagreements that are not understood or easily explained. These experimental discrepancies could potentially bias the 252 Cf PFNS Standard evaluation. On top of this, these past experiments frequently employed correlated experimental measurement or analysis methods. The artificial intelligence (AI)/machine learning (ML)-informed californium chi-nuclear data experiment (AIACHNE) project was formed to (a) investigate these discrepancies utilizing AI/ML methods to identify outlying regions of literature data, assign these regions to features of the experiment itself, and perform an improved evaluation of the 252 Cf PFNS and (b) perform a new experimental measurement of this quantity designed to improve upon the existing literature database. Here, in this work, we report on the AIACHNE 252 Cf PFNS experiment utilizing a new analysis method uncorrelated with all previous measurements: neutron efficiency determinations based on elastic neutron scattering on 12 C and 9 Be . This new method provides an independent test of the existing literature data and evaluation of the 252 Cf ⁢(sf) PFNS. The method is described with detailed covariance quantification procedures, as well as a direct discussion of the sources of uncertainty described as requirements in the “Templates” series of papers. The 252 Cf ⁢(sf) PFNS reported in this work agrees well with the overall shape of the existing standard PFNS evaluation as well as many literature measurements, thus verifying the current evaluation utilizing new techniques. However, the results suggest that there are deficiencies in the angle-differential 12 C and 9 Be ⁢(𝑛, 𝑛) evaluated nuclear data, which produce unphysical structures in the reported result. While these structures are relatively minor, they become obvious because of the high statistical precision of the data and the expected smooth continuity of the 252 Cf ⁢(sf) PFNS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Multi-body entanglement and information rearrangement in nuclear many-body systems: a study of the Lipkin–Meshkov–Glick model

Here, we examine how effective-model-space (EMS) calculations of nuclear many-body systems rearrange and converge multi-particle entanglement. The generalized Lipkin-Meshkov-Glick (LMG) model is used to motivate and provide insight for future developments of entanglement-driven descriptions of nuclei. The effective approach is based on a truncation of the Hilbert space together with a variational rotation of the qubits (spins), which constitute the relevant elementary degrees of freedom. The non-commutivity of the rotation and truncation allows for an exponential improvement of the energy convergence throughout much of the model space. Our analysis examines measures of correlations and entanglement, and quantifies their convergence with increasing cut-off. We focus on one- and two-spin entanglement entropies, mutual information, and $n$-tangles for $n=2,4$ to estimate multi-body entanglement. The effective description strongly suppresses entropies and mutual information of the rotated spins, while being able to recover the exact results to a large extent with low cut-offs. Naive truncations of the bare Hamiltonian, on the other hand, artificially underestimate these measures. The $n$-tangles in the present model provide a basis-independent measures of $n$-particle entanglement. While these are more difficult to capture with the EMS description, the improvement in convergence, compared to truncations of the bare Hamiltonian, is significantly more dramatic. We conclude that the low-energy EMS techniques, that successfully provide predictive capabilities for low-lying observables in many-body systems, exhibit analogous efficacy for quantum correlations and multi-body entanglement in the LMG model, motivating future studies in nuclear many-body systems and effective field theories relevant to high-energy physics and nuclear physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Electrolytic Etching of Germanium Substrates with Hydrogen Peroxide

Anodic electrolytic etching of germanium has been performed in hydrogen peroxide etchants with controlled external conditions. In-situ current and ex-situ etch-depths were measured and tracked with respect to etchant composition and stir rates. Gas bubbles formed during the etching process were found to cause non-uniformity in etch-current and surface quality. The effects were minimized in specific composition spaces. Quantitative analysis revealed a linear correlation of the number of electrons transferred during germanium oxidation with the number of surface atoms removed. Experimental results of 2.77 electrons/atom deviate significantly from 4 electrons/atom previously reported for silicon. The conclusion is that etching mechanisms for germanium are sufficiently different from those for silicon which invalidates the direct transfer of processing techniques between the two materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

EWTN: Quantifying Mass Transport to Enable Water Electrolyzer Architectures with Low Flow-Rate Sensitivity

To develop cost-effective and high-performing polymer electrolyte water electrolyzers (PEWEs) for gigawatt-scale applications, researchers have focused on reducing precious metal catalyst loadings and optimizing porous transport layers. However, the performance of PEWEs is also affected by system architecture. Mass transport losses are dependent on localized architecture and material interactions. In-situ measurements, such as current density distribution maps have demonstrated advantages in understanding the intricate characteristics and influence of two-phase flow within PEWEs. This study proposes the parameter of effective water transport number (EWTN) as a quantitative tool to investigate such current density distribution (CDD) measurements for PEWEs. Results show that higher flow-rates have EWTN values of 0.95 and above, indicating no mass transport limitations; while lower flow-rates with large gradients CDD have EWTN values between 0.6-0.8, indicating mass transport limited conditions. The new analysis also identified a correlation between mass transport losses due to bubble accumulation, membrane hydration, and ohmic overpotentials. To address these limitations, an unitized pin-type LGDL/flow-field design was developed, which effectively prevents local gas phase accumulation, resulting in improved mass transport characteristics. The results of this work show reduced flow-rate sensitivity with the pin-type architecture and ∼13% increased performance at 0.24 ml / min / cm 2 .

Electrochemistry↗
DOE OSTI2022

Study on Closely Related Citrus CMMs based on Chemometrics and Prediction of Components-Targets-Diseases Network by Ingenuity Pathway Analysis

As the representatives of closely related Chinese medicinal materials (CMMs) originated from Rutaceae family, Aurantii fructus immaturus (AFI), Aurantii fructus (AF), Citri reticulatae pericarpium viride (CRPV), and Citri reticulatae pericarpium (CRP) have better functions in regulating qi and promoting gastrointestinal motility. However, differences in the quality of closely related Citrus CMMs have not yet been revealed until now. Herein, this study focused on the systematic differentiation and in-depth understanding of closely related Citrus CMMs by a strategy integrating chemometrics and network pharmacology. Determined by ultra performance liquid chromatography, the content of nine flavonoids showed obvious fluctuations in the decoction pieces from different species (Citrus aurantium Linnaeus and Citrus reticulate Blanco) with decreasing levels in the samples of ripe fruits. Decoction pieces from the different species and ripening stages were well distinguished by orthogonal projection to latent structure-discriminate analysis (OPLS-DA) and cluster analysis. As a result, four active components including narirutin, naringenin, hesperidin, and 3,5,6,7,8,3′,4′-heptemthoxyflavone were filtered out by variable importance for the projection (VIP) value (VIP > 1.0), which were regarded as chemotaxonomic markers. Furthermore, a components-targets-diseases network was constructed via ingenuity pathway analysis (IPA), and the correlations were predicted between four chemotaxonomic markers, 223 targets, and three diseases including colitis, breast cancer, and colorectal cancer. The obtained results will be of great significance for identifying closely related Citrus CMMs and conduce to improving the resource utilization of CMMs.

Mu, Qixuan↗
DOE OSTI2025

CQM-Analysis v1.0

This repository contains the data and code necessary to reproduce the primary analysis and figures for the manuscript "Pathways to productivity: mapping the relationship between multimodal transportation infrastructure, commute quality, and economic vitality for the United States workforce". The analysis demonstrates a newly defined commute quality metric (CQM) characterizing the quality, as a monetized consumer surplus, of travel for the purpose of work for every census tract in the continental United States. The analysis additionally demonstrates the correlation of that CQM with key economic vitality indicators. Specifically median household income and unemployment rate.

Spurlock, C Anna [Lawrence Berkeley National Labor↗
DOE OSTI2025

Reproductive and leaf litterfall fluxes in forest ecosystem sites globally (1950-2022)

Forest allocation of net primary productivity (NPP) to reproduction is poorly quantified globally, despite its critical role in forest regeneration and a well-supported trade-off with allocation to growth. Although field measurements of total NPP are rare, our work finds that a proxy for reproductive carbon allocation constructed from leaf (L) and reproductive (R) litterfall fluxes, R/(R+L), is strongly correlated with R/NPP, facilitating analysis across a wide range of sites where biometric estimates of NPP are not available (R² = 0.85; Hanbury-Brown et al., 2022, Ward et al., in prep). To investigate relationships between ecosystem-scale reproductive allocation (RA) and climate, soil fertility, and stand age gradients, we conducted a literature search and synthesized 824 observations of annual average leaf and reproductive litterfall fluxes across forest sites globally. The zip file includes 1) a folder Data/ containing the litterfall data ("GlobalForestRA_data.csv") and metadata ("GlobalForestRA_metadata.doc") files. The data file includes geographic coordinates, long-term mean annual temperature and precipitation (1970-2000, extracted from WorldClim2.1), leaf and reproductive litterfall fluxes, sampling interval and protocols, forest characteristics (dominant leaf morphology, information pertaining to forest age and successional stage, and disturbance history) and soil properties (% sand, %silt, %clay, total phosphorus (P), nitrogen (N), cation exchange capacity (CEC) and pH) extracted from SoilGrids250 and from on-site measurements, where available. The metadata file contains information about each variable reported in the data file, including data sources, processing methods, and all references. The Data folder contains two additional files used to create Figure 1; these are described in greater detail in the README.2) R scripts GloalForestRA_analysis.r and GlobalForestRA_SI.r and a folder /Functions used to produce results, figures, and tables in the manuscript Ward et al. (in press)3) a README file describing how the data and R scripts can be used to reproduce statistical results, figures, and tables found in the manuscript. Ward et al. (in press)This repository can also be found at: https://github.com/r-ward/Global_Analysis_ForestRA.Ward, R.E., Zhang-Zheng, H. Aernethy, K., Adu-Bredu, S., Arroyo, L., Bailey, A. et al. (in press). Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally. Ecology Letters. Hanbury-Brown, A.R., Ward, R.E. & Kueppers, L.M. (2022). Forest regeneration within Earth system models: current process representations and ways forward. New Phytol., 235, 20–40.Ward et al. (2025), Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally, in prep.

54 ENVIRONMENTAL SCIENCES↗