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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Search for new physics in top quark production with additional leptons in proton-proton collisions at $\sqrt{s} = $ 13 TeV using effective field theory

Events containing one or more top quarks produced with additional prompt leptons are used to search for new physics within the framework of an effective field theory (EFT). The data correspond to an integrated luminosity of 41.5 fb$^{−1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV at the LHC, collected by the CMS experiment in 2017. The selected events are required to have either two leptons with the same charge or more than two leptons; jets, including identified bottom quark jets, are also required, and the selected events are divided into categories based on the multiplicities of these objects. Sixteen dimension-six operators that can affect processes involving top quarks produced with additional charged leptons are considered in this analysis. Constructed to target EFT effects directly, the analysis applies a novel approach in which the observed yields are parameterized in terms of the Wilson coefficients (WCs) of the EFT operators. A simultaneous fit of the 16 WCs to the data is performed and two standard deviation confidence intervals for the WCs are extracted; the standard model expectations for the WC values are within these intervals for all of the WCs probed.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Hydraulic constraints to stomatal conductance in flooded trees

Stomatal closure is a pervasive response among trees exposed to flooded soil. We tested whether this response is caused by reduced hydraulic conductance in the soil-to-leaf hydraulic continuum (k total ), and particularly by reduced root hydraulic conductance (k root ), which has been widely hypothesized. We tracked stomatal conductance at the leaf level (g s ) and canopy scale (G s ) along with physiological conditions in two temperate tree species, Magnolia grandiflora and Quercus virginiana, that were subjected to flood and control conditions in a greenhouse experiment. Flooding reduced g s , G s , k root and k total . Path analysis showed strong support for direct effects of k total on g s and for flood duration on k total , but not k root on k total . A process-based model that accounted for the k total reduction predicted the timeseries of G s in flood and control treatment trees reasonably well (predicted versus observed G s R 2 = 0.80 and 0.51 for M. grandiflora and Q. virginiana, respectively). However, accounting only for k root reduction in flooded trees was insufficient for predicting observed G s reduction. Together, these results suggest that hydraulic constraints were not limited to roots and highlight the need to account for flooding effects on k total when projecting forest ecosystem function using process-based models.

Plant stress↗
DOE OSTI2026

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗
DOE OSTI2020

An integrated methane dehydroaromatization and chemical looping process

Most of the natural gas co-produced in oil wells is flared due to the high transportation costs of bringing it to market. Onsite upgrading of natural gas to liquid products could address this issue but there are few processes for effective direct conversion of natural gas to liquid products. Methane dehydroaromatization (DHA) over Mo/HZSM- 5 offers a potential route to a value-added liquid product, however, DHA conversion is severely limited by thermodynamics at most industrially relevant temperatures. Here we propose an integrated process coupling methane DHA, chemical looping for selective hydrogen oxidation, and subsequent water removal to achieve higher yields of aromatic products limited by the thermodynamics in one-pass systems. Here, we validate this process via the construction and operation of a one-of-a-kind multibed recirculating reactor, and achieve a combined aromatics yield of 42%. Detailed technoeconomic analysis of the process for mobile applications show that such a process could be economically viable under certain circumstances.

03 NATURAL GAS↗
DOE OSTI2026

From models to reality: a systematic review on simulated and measured residential heat pump energy savings

High-performance HVAC solutions are central to residential energy management. A substantial share of these are electric, reversible-cycle systems, with heat pumps representing the largest portion of current and near-term adoption. This review synthesizes peer-reviewed and grey literature on residential space heating and cooling heat pumps. The academic literature is dominated by modeling (73.8%), with limited field measurement (13.1%). Grey literature from United States serve as a supplemental resource providing measured savings. Conversions from electric-resistance heating consistently show the largest site energy reductions, while oil/propane baselines yield moderate savings, and gas baseline scenario often deliver small and region-dependent savings. This study cross-checks the grey literature measured data with simulation data filtered from the ResStock dataset. The comparison indicates a discrepancy between simulations and measured data: simulated site EUIs are typically lower than measured EUIs, but percentage energy savings fall in similar ranges, implying simulations capture directional effects while underestimating energy use. Factors associated with variability and model–measurement differences include system characterization and control representation (e.g., backup heat engagement, thermostat/setpoint strategies, commissioning/installation quality), occupant behavior, weather normalization, metering scope, and envelope characterization. This paper also outlines the proposed methodology for comparing simulation and measured data for heat pumps. It emphasizes the metrics used for comparison and units harmonization, building characteristics matching, and compact metadata are needed for simulations to match measured data. The proposed methodology is expected to improve the credibility of simulated savings as measured evidence grows.

Yu, Lili↗
DOE OSTI2024

Impacts of caking on corn stover – An assessment of moisture content and consolidating pressure

Caking or time consolidation of powders is a serious problem which can hinder productivity and overall feasibility of various industrial processes. Here this study focuses on the impacts moisture content and consolidating pressures can have on 2 mm corn stover samples after undergoing a drying treatment at different times. Individually, moisture content and consolidating pressure did not exhibit any significant changes throughout the modified variable flow rate tests using the FT4 powder rheometer. However, applying both variables simultaneously yielded higher-than-usual energy outputs from the corn stover, indicative of biomass agglomeration due to the moisture and its subsequent evaporation while under pressure via the induced consolidating pressure. However, despite the increase in energy usage, time dried did not have a direct effect and demonstrated no trend.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The electric vehicles-solar photovoltaics Nexus: Driving cross-sectoral adoption of sustainable technologies

Residential and transportation energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics [PVs]) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market shares for both EVs and PVs continue to grow, both of these emerging technologies are deployed rather disjointly, without considering the existence of potential similarities among users who own (or aspire to own) these technologies. This might be due to lack of understanding of the behavioral interdependence in consumer preferences toward these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores interactive EV and PV adoption behaviors. A structural equation model is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values, and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive bundled adoption of EV-PV systems could accelerate the adoption of both of these sustainable technologies. In conclusion, this study highlights the need to consider transport and building energy-efficient technology adoption behavior in a single integrated structure.

14 SOLAR ENERGY↗
DOE OSTI2023

Characterization of the aerosol vertical distributions and their impacts on warm clouds based on multi-year ARM observations

Aerosol vertical distribution plays a crucial role in cloud development and thus precipitation since both aerosol indirect and semi-direct effects significantly depend on the relative position of aerosol layer in reference to cloud, but its precise influence on cloud remains unclear. In this study, we integrated multi-year Raman Lidar measurements of aerosol vertical profiles from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) facility with available Value-Added Products of cloud features to characterize aerosol vertical distributions and their impacts on warm clouds over the continental and marine ARM atmospheric observatories, i.e., Southern Great Plains (SGP) and Eastern North Atlantic (ENA). A unimodal seasonal distribution of aerosol optical depths (AODs) with a peak in summer is found at upper boundary layer over SGP, while a bimodal distribution is observed at ENA for the AODs at lower levels with a major winter-spring maximum. The diurnal mean of upper-level AOD at SGP shows a maximum in the early evening. According to the relative positions of aerosol layers to clouds we further identify three primary types of aerosol vertical distribution, including Random, Decreasing, and Bottom. It is found that the impacts of aerosols on cloud may or may not vary with aerosol vertical distribution depending on environmental conditions, as reflected by the wide variations of the relations between AOD and cloud properties. For example, as AOD increases, the liquid water paths (LWPs) tend to be reduced at SGP but enhanced at ENA. The relations of cloud droplet effective radius with AOD largely depend on aerosol vertical distributions, particularly showing positive values in the Random type under low-LWP condition (<50gm -2 ). In conclusion, the distinct features of aerosol-cloud interactions in relation to aerosol vertical distribution are likely attributed to the continental-marine contrast in thermodynamic environments and aerosol conditions between SGP and ENA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystem function and soil quality. Salinity influences carbon cycling through direct effects on microbial activity and indirect alterations to soil physicochemical properties including cation exchange, pH, and soil organic carbon availability. Current models inadequately represent these complexities, relying on linear reduction functions that overlook specific physicochemical changes induced by salinity. To address this gap, we propose an integrated model framework, AquaMEND, that combines microbial-explicit carbon decomposition and geochemical models. This model allows cation exchange and surface complexation processes to capture solute chemistry and nutrient availability in soils upon saltwater intrusion. Using response functions that capture salinity impacts on both salt-sensitive and salt-resistant microbial processes, AquaMEND simulates how the abiotic and biotic mechanisms work individually and collectively to regulate organic and inorganic pools and fluxes. Here, the parallel structure of aqueous and non-aqueous phases, together with microbial functions, result in a versatile model for solving dynamic coupling of organics, minerals and microbes under various environmental settings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Many-Body Perspective of Nuclear Quantum Effects in Aqueous Clusters

Nuclear quantum effects play an important role in the structure and thermodynamics of aqueous systems. Here, by performing a many-body expansion with nuclear-electronic orbital (NEO) theory, we show that proton quantization can give rise to significant energetic contributions for many-body interactions spanning several molecules in single-point energy calculations of water clusters. Although zero-point motion produces a large increase in energy at the one-body level, nuclear quantum effects serve to stabilize higher-order molecular interactions. These results are significant because they demonstrate that nuclear quantum effects play a nontrivial role in many-body interactions of aqueous systems. Our approach also provides a pathway for incorporating nuclear quantum effects into water potential energy surfaces. The NEO approach is advantageous for many-body expansion analyses because it includes nuclear quantum effects directly in the energies.

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

Unexpected Photodriven Linker-to-Node Hole Transfer in a Zirconium-Based Metal–Organic Framework

Zr 6 (μ 3 -O) 4 (μ 3 -OH) 4 node cores are indispensable building blocks for almost all zirconium-based metal–organic frameworks. Consistent with the insulating nature of zirconia, they are generally considered electronically inert. Contrasting this viewpoint, we present spectral measurements and calculations indicating that emission from photoexcited NU-601, a six-connected Zr-based MOF, comes from both linker-centric locally excited and linker-to-node charge-transfer (CT) states. The CT state originates from a hole transfer process enabled by favorable energy alignment of the HOMOs of the node and linker. This alignment can be manipulated by changing the pH of the medium, which alters the protonation state of multiple oxy groups on the Zr-node. Thus, the acid–base chemistry of the node has a direct effect on the photophysics of the MOF following linker-localized electronic excitation. In conclusion, these new findings open opportunities to understand and exploit, for energy conversion, unconventional mechanisms of exciton formation and transport in MOFs.

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

Enhanced Methanol Synthesis from CO 2 Hydrogenation Achieved by Tuning the Cu–ZnO Interaction in ZnO/Cu 2 O Nanocube Catalysts Supported on ZrO 2 and SiO 2

The nature of the Cu–Zn interaction and especially the role of Zn in Cu/ZnO catalysts used for methanol synthesis from CO 2 hydrogenation are still debated. Migration of Zn onto the Cu surface during reaction results in a Cu–ZnO interface, which is crucial for the catalytic activity. However, whether a Cu–Zn alloy or a Cu–ZnO structure is formed and the transformation of this interface under working conditions demand further investigation. Here, ZnO/Cu 2 O core–shell cubic nanoparticles with various ZnO shell thicknesses, supported on SiO 2 or ZrO 2 were prepared to create an intimate contact between Cu and ZnO. The evolution of the catalyst’s structure and composition during and after the CO 2 hydrogenation reaction were investigated by means of operando spectroscopy, diffraction, and ex situ microscopy methods. The Zn loading has a direct effect on the oxidation state of Zn, which, in turn, affects the catalytic performance. High Zn loadings, resulting in a stable ZnO catalyst shell, lead to increased methanol production when compared to Zn-free particles. Low Zn loadings, in contrast, leading to the presence of metallic Zn species during reaction, showed no significant improvement over the bare Cu particles. Therefore, our work highlights that there is a minimum content of Zn (or optimum ZnO shell thickness) needed to activate the Cu catalyst. Furthermore, in order to minimize catalyst deactivation, the Zn species must be present as ZnO x and not metallic Zn or Cu–Zn alloy, which is undesirably formed during the reaction when the precatalyst ZnO overlayer is too thin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Ambient ion focusing from a field-free region to a detector: enhanced signal for explosives and drug detection with mass spectrometry

This study demonstrates ion focusing at ambient pressure and increased ion signal by creating a voltage gradient from a field-free region to a detector, thereby improving the detection of chemicals, such as explosives and drugs. At ambient pressure, ion loss and resulting signal reduction pose challenges that limit detection sensitivity in analytical instruments. Techniques to increase sensitivity, such as atmospheric flow tube-mass spectrometry (AFT-MS), extend ion-molecule reaction times but result in significant overall ion loss due to diffusion. Ion manipulation techniques, though challenging at ambient pressure, can mitigate these losses by concentrating ions toward the detector inlet. Using SIMION, ion trajectories were modeled with a voltage gradient applied between a flow tube and a detector, revealing ion focusing at ambient pressure. Experimental verification with an atmospheric flow tube employed both mass spectrometry and Faraday plate detectors to measure ion beam profiles across varying flow rates, tube diameters, and voltage gradients. Application of a voltage gradient effectively directed ions to the axial center of the flow tube, narrowed ion beam width, and increased signal intensity by 5 to 10 times compared to conditions without a voltage gradient. This ion focusing approach shows promise for improving sensitivity in ambient-pressure instruments. This technique has the potential to enhance detection levels in security and forensic applications, with particular benefits for field-portable devices used at checkpoints to identify explosives and drugs.

ambient pressure↗
DOE OSTI2021

A data-driven global soil heterotrophic respiration dataset and the drivers of its inter-annual variability

Soil heterotrophic respiration (SHR), one of the primary carbon fluxes from terrestrial ecosystems to the atmosphere, is important for carbon-climate feedbacks because of its sensitivity to available litter and soil carbon, climatic conditions, and nutrient availability. However, until recently limited SHR data were available, and most published global SHR estimates have either a short time span, coarse spatial resolution, or reply on overly-simple model formulations. To better understand and quantify the global distribution of SHR and its sensitivity to climate variability, we produced a new global SHR dataset using Random Forest algorithms, up-scaling 455 point data from the Global Soil Respiration Database (SRDB 4.0) with gridded fields of climatic, edaphic and productivity as explanatory variables. We estimated a global total SHR of 46.8 Pg C yr-1 over 1985-2013 (95% confidence interval: 38.6-56.3 Pg C yr-1), with a significant increasing trend of 0.03 Pg C yr-2 during this period. We found that the choice of soil moisture datasets contributes more to the difference among these data-driven SHR members rather than that of productivity, temperature and precipitation data sources. We also analyzed the influence of climatic variables on the inter-annual variability (IAV) of our SHR product. Water availability was the dominant driver of IAV at global scales, although the inferred sensitivity depends on the choice of the soil moisture gridded dataset. At the ecosystem scale, temperature strongly controls the IAV of SHR in tropical forests, while water availability dominates in extra-tropical forest and semi-arid regions. Our machine-learning gridded SHR dataset and outputs from process-based land surface models (TRENDYv6) show agreement for a strong association between water variability and SHR IAV at the global scale, but the two approaches lead to different temporal trend globally and different controlling variables for IAV at the ecosystem scale. Our study provides evidence for the pervasive and important role of water availability in driving SHR, indicating both a direct effect limiting decomposition rates and an indirect effect through the amount of fresh organic matter made available to SHR from productivity. In consideration of potential limitations and uncertainties remaining in our data-driven SHR datasets, we call for a more scientifically designed observation network for SHR, more observation data compilation, and increased use of deep learning methods making maximum use of observation data in hand. This will benefit process-based models, and improve our understanding of SHR response to future anomalous environmental conditions.

Yao, Yitong↗
DOE OSTI2020

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

Abstract Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be combined to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets, efficient library construction of metabolic pathway designs, and high-throughput biosensor-enabled screening for training diverse machine learning algorithms. From a single data-generation cycle, this enables successful forward engineering of complex aromatic amino acid metabolism in yeast, with the best machine learning-guided design recommendations improving tryptophan titer and productivity by up to 74 and 43%, respectively, compared to the best designs used for algorithm training. Thus, this study highlights the power of combining mechanistic and machine learning models to effectively direct metabolic engineering efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Materializing efficient methanol oxidation via electron delocalization in nickel hydroxide nanoribbon

Achieving a functional and durable non-platinum group metal-based methanol oxidation catalyst is critical for a cost-effective direct methanol fuel cell. While Ni(OH) 2 has been widely studied as methanol oxidation catalyst, the initial process of oxidizing Ni(OH) 2 to NiOOH requires a high potential of 1.35 V vs. RHE. Such potential would be impractical since the theoretical potential of the cathodic oxygen reduction reaction is at 1.23 V. Here we show that a four-coordinated nickel atom is able to form charge-transfer orbitals through delocalization of electrons near the Fermi energy level. As such, our previously reported periodically arranged four-six-coordinated nickel hydroxide nanoribbon structure (NR-Ni(OH) 2 ) is able to show remarkable methanol oxidation activity with an onset potential of 0.55 V vs. RHE and suggests the operability in direct methanol fuel cell configuration. Thus, this strategy offers a gateway towards the development of high performance and durable non-platinum direct methanol fuel cell.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Control of structure and spin texture in the van der Waals layered magnet CrSBr

Controlling magnetism at nanometer length scales is essential for realizing high-performance spintronic, magneto-electric and topological devices and creating on-demand spin Hamiltonians probing fundamental concepts in physics. Van der Waals (vdW)-bonded layered magnets offer exceptional opportunities for such spin texture engineering. Here, we demonstrate nanoscale structural control in the layered magnet CrSBr with the potential to create spin patterns without the environmental sensitivity that has hindered such manipulations in other vdW magnets. We drive a local phase transformation using an electron beam that moves atoms and exchanges bond directions, effectively creating regions that have vertical vdW layers embedded within the initial horizontally vdW bonded exfoliated flakes. We calculate that the newly formed two-dimensional structure is ferromagnetically ordered in-plane with an energy gap in the visible spectrum, and weak antiferromagnetism between the planes, suggesting possibilities for creating spin textures and quantum magnetic phases.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

A central arctic extreme aerosol event triggered by a warm air-mass intrusion

Frequency and intensity of warm and moist air-mass intrusions into the Arctic have increased over the past decades and have been related to sea ice melt. During our year-long expedition in the remote central Arctic Ocean, a record-breaking increase in temperature, moisture and downwelling-longwave radiation was observed in mid-April 2020, during an air-mass intrusion carrying air pollutants from northern Eurasia. The two-day intrusion, caused drastic changes in the aerosol size distribution, chemical composition and particle hygroscopicity. Here we show how the intrusion transformed the Arctic from a remote low-particle environment to an area comparable to a central-European urban setting. Additionally, the intrusion resulted in an explosive increase in cloud condensation nuclei, which can have direct effects on Arctic clouds’ radiation, their precipitation patterns, and their lifetime. Thus, unless prompt actions to significantly reduce emissions in the source regions are taken, such intrusion events are expected to continue to affect the Arctic climate.

54 ENVIRONMENTAL SCIENCES↗