Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “VS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Variation in hyphal production rather than turnover regulates standing fungal biomass in temperate hardwood forests

Abstract Soil fungi link above‐ and belowground carbon (C) fluxes through their interactions with plants and contribute to C and nutrient dynamics through the production, turnover, and activity of fungal hyphae. Despite their importance to ecosystem processes, estimates of hyphal production and turnover rates are relatively uncommon, especially in temperate hardwood forests. We sequentially harvested hyphal ingrowth bags to quantify the rates of Dikarya (Ascomycota and Basidiomycota) hyphal production and turnover in three hardwood forests in the Midwestern United States, where plots differed in their abundance of arbuscular (AM)‐ vs. ectomycorrhizal (ECM)‐associated trees. Hyphal production rates increased linearly with the percentage of ECM trees and annual production rates were 66% higher in ECM‐ than AM‐dominated plots. Hyphal turnover rates did not differ across the mycorrhizal gradient (plots varying in their abundance of AM vs. ECM trees), suggesting that the greater fungal biomass in ECM‐dominated plots relates to greater fungal production rather than slower fungal turnover. Differences in hyphal production across the gradient aligned with distinctly different fungal communities and activities. As ECM trees increased in dominance, fungi inside ingrowth bags produced more extracellular enzymes involved in degrading nitrogen (N)‐bearing relative to C‐bearing compounds, suggesting greater fungal (and possibly plant) N demand in ECM‐dominated soils. Collectively, our results demonstrate that shifts in temperate tree species composition that result in changes in the dominant type of mycorrhizal association may have strong impacts on Dikarya hyphal production, fungal community composition and extracellular enzyme activity, with important consequences for soil C and N cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Switching CO 2 Electroreduction Selectivity Between C 1 and C 2 Hydrocarbons on Cu Gas-Diffusion Electrodes

We report that regulating the selectivity toward a target hydrocarbon product is still the focus of CO 2 electroreduction. Here, we discover that the original surface Cu species in Cu gas-diffusion electrodes plays a more important role than the surface roughness, local pH, and facet in governing the selectivity toward C 1 or C 2 hydrocarbons. The selectivity toward C 2 H 4 progressively increases, while CH 4 decreases steadily upon lowering the Cu oxidation species fraction. At a relatively low electrodeposition voltage of 1.5 V, the Cu gas-diffusion electrode with the highest Cu δ+ /Cu 0 ratio favors the pathways of hydrogenation to form CH 4 with maximum Faradaic efficiency of 65.4% and partial current density of 228 mA cm -2 at -0.83 V vs RHE. At 2.0 V, the Cu gas-diffusion electrode with the lowest Cu δ+ /Cu 0 ratio prefers C–C coupling to form C 2+ products with Faradaic efficiency topping 80.1% at -0.75 V vs RHE, where the Faradaic efficiency of C 2 H 4 accounts for 46.4% and the partial current density of C 2 H 4 achieves 279 mA cm -2 . This work demonstrates that the selectivity from CH 4 to C 2 H 4 is switchable by tuning surface Cu species composition of Cu gas-diffusion electrodes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ligand and Linkage Isomers of Bis(ethylthiocarbamato) Copper Complexes with Cyclic C 6 H 8 Backbone Substituents: Synthesis, Characterization, and Antiproliferation Activity

Abstract A series of isomeric bis(alkylthiocarbamate) copper complexes have been synthesized, characterized, and evaluated for antiproliferation activity. The complexes were derived from ligand isomers with 3‐methylpentyl (H 2 L 2 ) and cyclohexyl (H 2 L 3 ) backbone substituents, which each yield a pair of linkage isomers. The thermodynamic products CuL 2a/3a have two imino N and two S donors resulting in three five‐member chelate rings (555 isomers). The kinetic isomers CuL 2b/3b have one imino and one hydrazino N donor and two S donors resulting in four‐, six‐, and five‐member rings (465 isomers). The 555 isomers have more accessible Cu II/I potentials (E 1/2 =−811/−768 mV vs. ferrocenium/ferrocene) and lower energy charge transfer bands than their 465 counterparts (E 1/2 =−923/‐854 mV). Antiproliferation activities were evaluated against the lung adenocarcinoma cell line (A549) and nonmalignant lung fibroblast cell line (IMR‐90) using the MTT assay. CuL 2a was potent ( A549 EC 50 =0.080 μM) and selective ( IMR‐90 EC 50 / A549 EC 50 =25) for A549. Its linkage isomer CuL 2b had equivalent A549 activity, but lower selectivity ( IMR‐90 EC 50 / A549 EC 50 =12.5). The isomers CuL 3a and CuL 3b were less potent with A549 EC 50 values of 1.9 and 0.19 M and less selective with IMR‐90 EC 50 / A549 EC 50 ratios of 2.3 and 2.65, respectively. There was no correlation between reduction potential and A549 antiproliferation activity/selectivity.

Chemistry↗
DOE OSTI2024

Association of female reproductive and hormonal factors with gallbladder cancer risk in Asia: A pooled analysis of the Asia Cohort Consortium

Abstract The female predominance of gallbladder cancer (GBC) has led to a hypothesis regarding the hormone‐related aetiology of GBC. We aimed to investigate the association between female reproductive factors and GBC risk, considering birth cohorts of Asian women. We conducted a pooled analysis of 331,323 women from 12 cohorts across 4 countries (China, Japan, Korea, and Singapore) in the Asia Cohort Consortium. Cox proportional hazard models were used to estimate the hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) to assess the association between reproductive factors (age at menarche, parity, age at first delivery, breastfeeding, and age at menopause) and GBC risk. We observed that a later age at menarche was associated with an increased risk of GBC (HR 1.4, 95% CI 1.16–1.70 for 17 years and older vs. 13–14 years), especially among the cohort born in 1940 and later (HR 2.5, 95% CI 1.50–4.35). Among the cohort born before 1940, women with a later age at first delivery showed an increased risk of GBC (HR 1.56, 95% CI 1.08–2.24 for 31 years of age and older vs. 20 years of age and younger). Other reproductive factors did not show a clear association with GBC risk. Later ages at menarche and at first delivery were associated with a higher risk of GBC, and these associations varied by birth cohort.

Shin, Aesun↗
DOE OSTI2020

No–till establishment improves the climate benefit of bioenergy crops on marginal grasslands

Expanding biofuel production is expected to accelerate the conversion of unmanaged marginal lands to meet biomass feedstock needs. Greenhouse gas production during conversion jeopardizes the ensuing climate benefits, but most research to date has focused only on conversion to annual crops and only following tillage. Here we report the global warming impact of converting USDA Conservation Reserve Program (CRP) grasslands to three types of bioenergy crops using no–till (NT) vs. conventional tillage (CT). We established replicated NT and CT plots in three CRP fields planted to continuous corn, switchgrass, or restored prairie. For the 2 yr following an initial soybean year in all fields, we found that, on average, NT conversion reduced nitrous oxide (N 2 O) emissions by 50% and CO 2 emissions by 20% compared with CT conversion. Differences were higher in Year 1 than in Year 2 in the continuous corn field, and in the two perennial systems the differences disappeared after Year 1. In all fields net CO 2 emissions (as measured by eddy covariance) were positive for the first 2 yr following CT establishment, but following NT establishment net CO 2 emissions were close to zero or negative, indicating net C sequestration. Overall, NT improved the global warming impact of biofuel crop establishment following CRP conversion by over 20–fold compared with CT (–6.01 Mg CO 2 e ha –1 yr –1 for NT vs. –0.25 Mg CO 2 e ha –1 yr –1 for CT, on average). We also found that Intergovernmental Panel on Climate Change estimates of N 2 O emissions (as measured by static chambers) greatly underestimated actual emissions for converted fields regardless of tillage. Policies should encourage adoption of NT for converting marginal grasslands to perennial bioenergy crops to reduce C debt and maximize climate benefits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Structure of Shock Waves and Inelasticity in Shock-Compressed Cemented Tungsten Carbides

In this study, shock wave experiments are conducted on General Carbide cemented tungsten carbide with 3.7wt.% cobalt binder to determine its shock-induced compression behavior up to 100 GPa. The measured wave profiles indicate the cemented tungsten carbide to undergo elastic-plastic deformation during shock compression. A three-stage particle velocity profile is observed in the experiments -- an initial elastic-rise to the Hugoniot Elastic Limit (HEL), an elastic-plastic ramp indicating substantial post-yield hardening, and finally a rise to the peak shocked Hugoniot state. The results of the experiments are used to determine the HEL, the shock velocity (U s ) vs. particle velocity (u p ) Hugoniot relation, and the longitudinal stress (σ x ) vs. specific volume (V) curve for the samples. The HEL of the material was determined to lie between 4.41 GPa and 4.58 GPa. The U s - u p relation was determined to be U s = 4.97 + 1. 457u p for particle velocities greater than 0.75 km/s. The measured plastic shock velocities for particle velocities less than 0.7 km/s were found to be larger than those predicted using the linear U s - u p Hugoniot relationship, indicating the cemented WC samples to preserve substantial shear strength in the post-yield deformation region. No phase transformation was observed up to 100 GPa.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Is infrared-collinear safe information all you need for jet classification?

Machine learning-based jet classifiers are able to achieve impressive tagging performance in a variety of applications in high-energy and nuclear physics. However, it remains unclear in many cases which aspects of jets give rise to this discriminating power, and whether jet observables that are tractable in perturbative QCD such as those obeying infrared-collinear (IRC) safety serve as sufficient inputs. In this article, we introduce a new classifier, Jet Flow Networks (JFNs), in an effort to address the question of whether IRC unsafe information provides additional discriminating power in jet classification. JFNs are permutation-invariant neural networks (deep sets) that take as input the kinematic information of reconstructed subjets. The subjet radius and a cut on the subjet’s transverse momenta serve as tunable hyperparameters enabling a controllable sensitivity to soft emissions and nonperturbative effects. We demonstrate the performance of JFNs for quark vs. gluon and Z vs. QCD jet tagging. For small subjet radii and transverse momentum cuts, the performance of JFNs is equivalent to the IRC-unsafe Particle Flow Networks (PFNs), demonstrating that infrared-collinear unsafe information is not necessary to achieve strong discrimination for both cases. As the subjet radius is increased, the performance of the JFNs remains essentially unchanged until physical thresholds that we identify are crossed. For relatively large subjet radii, we show that the JFNs may offer an increased model independence with a modest tradeoff in performance compared to classifiers that use the full particle information of the jet. These results shed new light on how machines learn patterns in high-energy physics data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Differential effects of redox conditions on the decomposition of litter and soil organic matter

Soil redox conditions exert substantial influence on biogeochemical processes in terrestrial ecosystems. Humid tropical forests are often characterized by fluctuating redox dynamics, yet how redox fluctuations affect patterns in soil versus litter decomposition and associated CO2 fluxes are not well understood in these ecosystems. We used a 13C-labeled litter addition to explicitly follow the decomposition of litter-derived vs. native soil-derived organic matter in response to four different soil redox regimes—static oxic or anoxic, and two oscillating treatments—in soil from the Luquillo Experimental Forest, Puerto Rico. We coupled this incubation experiment with high-resolution mass spectrometry analysis to characterize the preferential decomposition of specific classes of organic molecules. CO2 production from litter and soil organic matter (SOM) showed distinctly different responses to redox manipulation. The cumulative production of SOM-derived CO2 was positively correlated with the length of soil exposure to an oxic headspace (r = 0.89, n = 20), whereas cumulative 13C-litter-derived CO2 production was not linked to oxygen availability. The CO2 production rate from litter was highest under static anoxic conditions in the first half of the incubation period, and later dropped to the lowest among all redox treatments. In the consistently anoxic soils, we observed the depletion of more oxidized water-extractable organic matter (especially amino sugars, carbohydrates, and proteins) over time, suggesting that under anaerobic conditions, microbes preferentially used more oxidized litter-derived compounds during the early stages of decomposition. Results from kinetic modeling showed that more frequent anoxic exposure limited the decomposition of a slow-cycling C pool, but not a fast-cycling pool. Overall, our results demonstrate that substrate source—freshly added litter vs. native organic matter—plays an important role in the redox sensitivity of organic matter decomposition. In soil environments that regularly experience redox fluctuations, anaerobic heterotrophs can be surprisingly effective in degrading fresh plant litter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Calibration of cohesive parameters for fracture test simulations of sub-sized bend specimens of AM steels

In this work, crack extensions in sub-sized side-grooved bend specimens of AM steels are examined with changing cohesive parameters. Two-dimensional FE analyses are first conducted to simulate crack extensions by nodal release. The simulation results indicate the near-tip maximum opening stress and separation work rate increase and then slightly decrease for the bend specimens. The hydrogen-charged bend specimens have lower near-tip maximum opening stresses and average separation work rates than those of the uncharged bend specimens. The changing near-tip maximum opening stresses and the separation work rates with increasing crack extension are determined as references for the changing cohesive strengths and energies, respectively. Two-dimensional FE analyses with different changing cohesive parameters are then performed. The simulation results with calibrated cohesive parameters can match well with the test results. The hydrogen-charged specimens have the lower changing cohesive strength vs crack growth curves compared with those of the uncharged specimens. The hydrogen-charged specimens have either lower or similar changing cohesive energy vs crack growth curves compared with those of the uncharged specimens. Finally, a three-dimensional FE analysis is conducted to simulate crack extension by nodal release in one bend specimen to examine the stress triaxialities in front of the growing crack fronts at different locations from the center plane to the planes near the side groove front with increasing crack extension to identify possible physical reasons for the changing cohesive parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Scalable synthesis of nanoporous silicon microparticles for highly cyclable lithium-ion batteries

Nanoporous silicon is a promising anode material for high energy density batteries due to its high cycling stability and high tap density compared to other nanostructured anode materials. However, the high cost of synthesis and low yield of nanoporous silicon limit its practical application. Here, we develop a scalable, low-cost top-down process of controlled oxidation of Mg 2 Si in the air, followed by HCl removal of MgO to generate nanoporous silicon without the use of HF. By controlling the synthesis conditions, the oxygen content, grain size and yield of the porous silicon are simultaneously optimized from commercial standpoints. In situ environmental transmission electron microscopy reveals the reaction mechanism; the Mg 2 Si microparticle reacts with O 2 to form MgO and Si, while preventing SiO 2 formation. Owing to the low oxygen content and microscale secondary structure, the nanoporous silicon delivers a higher initial reversible capacity and initial Coulombic efficiency compared to commercial Si nanoparticles (3,033 mAh/g vs. 2,418 mAh/g, 84.3% vs. 73.1%). Synthesis is highly scalable, and a yield of 90.4% is achieved for the porous Si nanostructure with the capability to make an excess of 10 g per batch. Our synthetic nanoporous silicon is promising for practical applications in next generation lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Matching high resolution satellite data and flux tower footprints improves their agreement in photosynthesis estimates

Mapping canopy photosynthesis in both high spatial and temporal resolution is essential for carbon cycle monitoring in heterogeneous areas. However, well established satellites in sun-synchronous orbits such as Sentinel-2, Landsat and MODIS can only provide either high spatial or high temporal resolution but not both. Recently established CubeSat satellite constellations have created an opportunity to overcome this resolution trade-off. In particular, Planet Fusion allows full utilization of the CubeSat data resolution and coverage while maintaining high radiometric quality. In this study, we used the Planet Fusion surface reflectance product to calculate daily, 3-m resolution, gap-free maps of the near-infrared radiation reflected from vegetation (NIRvP). We then evaluated the performance of these NIRvP maps for estimating canopy photosynthesis by comparing with data from a flux tower network in Sacramento-San Joaquin Delta, California, USA. Overall, NIRvP maps captured temporal variations in canopy photosynthesis of individual sites, despite changes in water extent in the wetlands and frequent mowing in the crop fields. When combining data from all sites, however, we found that robust agreement between NIRvP maps and canopy photosynthesis could only be achieved when matching NIRvP maps to the flux tower footprints. In this case of matched footprints, NIRvP maps showed considerably better performance than in situ NIRvP in estimating canopy photosynthesis both for daily sum and data around the time of satellite overpass (R2 = 0.78 vs. 0.60, for maps vs. in situ for the satellite overpass time case). This difference in performance was mostly due to the higher degree of consistency in slopes of NIRvP-canopy photosynthesis relationships across the study sites for flux tower footprint-matched maps. Our results show the importance of matching satellite observations to the flux tower footprint and demonstrate the potential of CubeSat constellation imagery to monitor canopy photosynthesis remotely at high spatio-temporal resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deep convolutional autoencoders as generic feature extractors in seismological applications

The idea of using a deep autoencoder to encode seismic waveform features and then use them in different seismological applications is appealing. In this paper, we designed tests to evaluate this idea of using autoencoders as feature extractors for different seismological applications, such as event discrimination (i.e., earthquake vs. noise waveforms, earthquake vs. explosion waveforms), and phase picking. These tests involve training an autoencoder, either undercomplete or overcomplete, on a large amount of earthquake waveforms, and then using the trained encoder as a feature extractor with subsequent application layers (either a fully connected layer, or a convolutional layer plus a fully connected layer) to make the decision. By comparing the performance of these newly designed models against the baseline models trained from scratch, we conclude that the autoencoder feature extractor approach may only outperform the baseline under certain conditions, such as when the target problems require features that are similar to the autoencoder encoded features, when a relatively small amount of training data is available, and when certain model structures and training strategies are utilized. The model structure that works best in all these tests is an overcomplete autoencoder with a convolutional layer and a fully connected layer to make the estimation.

58 GEOSCIENCES↗
DOE OSTI2022

Electrocatalytic decarboxylation of carboxylic acids over RuO 2 and Pt nanoparticles

Here, we report electrocatalytic decarboxylation (ECDX) of valeric acid into paraffins, olefins, and alcohols via (non-)Kolbe electrolysis on electrodes with RuO 2 and Pt nanoparticles (NPs) as a greener alternative to thermocatalytic decarboxylation. The turnover frequency of ECDX increases, while the specific activity peaks as RuO 2 NP size increases. These opposing trends make the particle size of ∼ 12 nm the optimum size for ECDX on RuO 2 . Bulk Pt was active for ECDX, while Pt NPs were only active for the oxygen evolution reaction under our conditions. ECDX current efficiency remained constant in the studied potential range on RuO 2 NPs. Esterification was the favored reaction at 2.5 V vs. RHE; however, Kolbe electrolysis was the favored reaction at the expense of the esterification at 4.5 V vs. RHE. This work highlights the performance of nanostructured materials as an alternative to bulk materials as anodes for oxidative upgrading of carboxylic acids.

Kolbe electrolysis↗
DOE OSTI2021

Thermochemical reduction modeling in a high-temperature moving-bed reactor for energy storage: 1D model

The design of robust and efficient high-temperature thermochemical reactors and determination of operating conditions are critical steps toward enabling high-efficiency long-duration solar energy storage. This work presents a computational model for the thermal reduction of a metal oxide material (Mg-Mn-O) up to 1450 °C and the coupled complex transport phenomena in a novel tubular thermal reactor design that features the capability for a high extent-of-reduction (high energy storage density) and inherent heat recuperation. A one-dimensional model coupling counter-current gas–solid flow, two-phase heat transfer, thermochemical redox reactions, and species transport in a moving-bed reactor is developed. Simplified versions of the model are validated with published results in the literature for packed beds with both inert and reactive particles; the fully coupled model is also validated with experimental measurements of a moving-bed reactor in terms of local temperatures and oxygen release at the exit. Detailed comparisons on the effects of different boundary conditions in the reaction zone (prescribed wall temperature vs. heat flux conditions) and formulations based on a simple uniform flow assumption vs. plug flow using Ergun equation for gas flow are investigated. The results are compared with experimental measurements, and for all cases, the energy flow components in the reactor system and the thermal to chemical conversion efficiency and overall system efficiency are computed. Finally, the predicted high thermal-to-chemical efficiency ~95% and system efficiency ~30% agree with experimental measurements.

25 ENERGY STORAGE↗
DOE OSTI2022

Application of a Novel Heat Pump Model for Estimating Economic Viability and Barriers of Heat Pumps in Dairy Applications in the United States

Heat pumps represent an important opportunity for energy savings and decarbonization. This work investigates the techno-economic performance of high-temperature heat pumps (HTHPs) for use in the U.S. dairy industry. The studied heat pump performs a 50 °C temperature lift on a waste heat stream of cleaning water and applies the upgraded heat stream to a fluid milk pasteurization process. This work involved the creation of a HTHP model that estimated the coefficient of performance (COP), internal rate of return (IRR), net present value (NPV), and payback period (PBP), and emissions saved for a heat pump replacing a natural gas boiler. Capital costs, operations, and maintenance (O&M) cost, heat pump lifetime, electricity prices, natural gas prices, and a cost of carbon were varied to perform a parametric study on the factors affecting the break-even price of HTHPs. The results show that HTHP economics are highly sensitive to COP and energy price environment, and less sensitive to capital and O&M cost variance, leading to a large scatter of positive and negative NPVs based on U.S. location. PBPs demonstrate a defined threshold, based on energy price environment, below which favorable two-to-three-year PBPs predominate. This work is focused on the U.S. dairy industry, but international application in relation to fossil vs. electricity price regimes. Heat pumps have seen wider adoption in regions with a high ratio of fossil energy to electricity prices ($/MMBTU vs. $/kWh). The U.S. has plentiful natural gas resulting in lower fossil energy prices which has reduced heat pump adoption. This paper identifies potential first mover industries for HTHP adoption and their associated price regimes even in regions with lower ratios of fossil energy to electricity prices that exist many places globally.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗
DOE OSTI2022

What you get is not always what you see—pitfalls in solar array assessment using overhead imagery

Effective integration planning for small, distributed solar photovoltaic (PV) arrays into electric power grids requires access to high quality data: the location and power capacity of individual solar PV arrays. Unfortunately, national databases of small-scale solar PV do not exist; those that do are limited in their spatial resolution, typically aggregated up to state or national levels. While several promising approaches for solar PV detection have been published, strategies for evaluating the performance of these models are often highly heterogeneous from study to study. The resulting comparison of these methods for practical applications for energy assessments becomes challenging and may imply that the reported performance evaluations overly optimistic. The heterogeneity comes in many forms, each of which we explore in this work: the degree of diversity of the locations and sensors (e.g. different satellites, aerial photography) from which the training and validation data originate, the validation of ground truth (manual annotation of imagery vs known solar PV locations), the level of spatial aggregation (e.g. array-level vs regional estimates), and inconsistencies in the training and validation datasets (e.g. different datasets are used for each study and those data are not always made accessible). For each, we discuss emerging practices from the literature to address them or suggest directions of future research. As part of our investigation, we evaluate solar PV identification performance in two large regions: the entire state of Connecticut and the city of San Diego, CA. In Connecticut, we also use 33,114 known parcel-level solar PV installations from Berkeley Lab’s Tracking the Sun dataset to evaluate parcel-level performance and evaluate capacity estimates using 169 municipalities. We also make our code (which we call SolarMapper), pre-trained models, training data, and predictions publicly available and provide a web portal for interactively inspecting each prediction that was made. Here our findings suggest that traditional performance evaluation of the automated identification of solar PV from satellite imagery may be optimistic due to common limitations in the validation process. The takeaways from this work are intended to inform and catalyze the large-scale practical application of automated solar PV assessment techniques by energy researchers and professionals.

14 SOLAR ENERGY↗
DOE OSTI2021

Aspects of rare earth element enrichment in Allegheny Plateau coals, Pennsylvania, USA

The Allegheny Plateau in western Pennsylvania, western Maryland, and northern West Virginia has relatively flat-lying strata with southwest-northeast-trending anticlines cored by splay faults originating from the thrust faults and southeast-northwest-trending lineaments. The lineaments define both the structural relief of the anticlines and the coal rank. Coal rank in the Pennsylvanian Allegheny Group coals is medium volatile bituminous in the region of less-prominent structural relief and low volatile bituminous in the region with more pronounced anticlines. Zinc and Cl exhibit high values in coals in the vicinity of the lineaments. Although coal rank was not a parameter in the Principal components analysis, the highest rank coals clustered together in a quadrant defined, in part, by the Zn concentration. Zinc was selected as a parameter due to its possible link with hydrothermal mineralization and Zr and TiO 2 /Al 2 O 3 were selected based on their presumed association with detrital mineral influences. The highest rare earths + Y values in benches of the Lower Kittanning coal were found at sites close to the lineaments. Negative or negligible Ce anomalies (δCe) and strongly positive Gd anomalies (δGd) suggest marine or hydrothermal influences and negative Eu anomalies (δEu) along with high TiO 2 /Al 2 O 3 values suggest a terrestrial input. In conclusion, the plots of δCe vs. δGd and δCe vs. δEu show that the low volatile bituminous coals are segregated from the other coals, suggesting that the factors that influenced coal rank also influenced the distribution of the rare earth elements.

58 GEOSCIENCES↗
DOE OSTI2025

Manganese concentration influences nitrogen cycling in agricultural soil

Manganese (Mn) can modulate nitrogen (N) transformations in soil, yet its role in agroecosystems remains understudied. We conducted a 51-day microcosm incubation with agricultural soils differing in long-term N history (N 0 , no added N; N 1 , added 225 kg N ha −1 for a duration of 27 years) and amended with soluble Mn at 0 (M 0 ), 50 (M 1 ), or 250 (M 2 ) mg kg −1 and Glyceria striata (Lam.) residue. In N 1 soils, Mn additions (both M 1 and M 2 ) lowered total mineral N by 25 % relative to N 1 M 0 at day 51 and reduced 51-day cumulative N₂O by 32 % (N 1 M 1 ) and 42 % (N 1 M 2 ) vs. N 1 M 0 , whereas effects in N 0 were negligible. Mn also depressed ammonia-oxidizing bacterial amoA gene transcripts at day 15 in N 1 M 2 vs. N 1 M 0 (2.5 fold change). This reduction was likely due to increased N loss via complete denitrification to N₂ through microbial pathways such as nitrate/nitrite-dependent manganese oxidation (NDMO), where bacteria directly used the added Mn 2+ to reduce nitrate (NO 3 − ) and nitrite (NO 2 − ) to N 2 or as Mn dependent-ammonia oxidation (Mnammox) where bacteria oxidized ammonium (NH 4 + ) to N 2 , using Mn oxides as electron acceptors that formed from the oxidation of the added Mn. Other contributing mechanisms may include Mn-induced N immobilization, toxicity, and changes in the microbial community. These mechanistic results indicate that background Mn availability and redox dynamics can shape nitrification–denitrification pathways under N-rich conditions. In conclusion, we highlight how native Mn pools and redox state may help explain observed variability in N losses and greenhouse gas production across agricultural soils.

Decomposition↗