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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 343 records · Page 19

Optimal Design of Sustainable Ammonia-Based Food–Energy–Water Systems with Nitrogen Management

As the basis for virtually any form of nitrogen fertilizers, ammonia plays a vital role in agriculture; in addition, there has been an increased interest in its use as a carbon-free energy carrier. However, ammonia is also associated with two major environmental concerns: CO 2 emissions from the conventional production process and nitrogen pollution from the excessive use of ammonia-based fertilizers. To mitigate these environmental impacts, we develop an optimization framework for the design of a sustainable ammonia-based agricultural system that synergistically integrates the production of ammonia from renewable resources and effective measures for nitrogen management. The proposed model captures the effect of intermittency by incorporating both design and detailed operational decisions. Here, by applying a multiscale time representation that reduces the problem size and a tailored surrogate model that accurately approximates model nonlinearity, we are able to achieve optimal solutions within reasonable computation times. A computational case study is conducted using real-world data from a local farm in Morris, Minnesota, and the results indicate the trade-off between cost and nitrogen loss. Importantly, we show that practicing effective nitrogen management can significantly reduce the nitrogen loss with only a small increase in net present cost.

10 SYNTHETIC FUELS↗

Indolo[2,3- b ]quinoxaline as a Low Reduction Potential and High Stability Anolyte Scaffold for Nonaqueous Redox Flow Batteries

Redox flow batteries (RFBs) are a promising stationary energy storage technology for leveling power supply from intermittent renewable energy sources with demand. A central objective for the development of practical, scalable RFBs is to identify affordable and high-performance redox-active molecules as storage materials. Herein, we report the design, synthesis, and evaluation of a new organic scaffold, indolo[2,3-b]quinoxaline, for highly stable, low-reduction potential, and high-solubility anolytes for nonaqueous redox flow batteries (NARFBs). The mixture of 2- and 3-(tert-butyl)-6-(2-methoxyethyl)-6H-indolo[2,3-b]quinoxaline exhibits a low reduction potential (-2.01 V vs Fc/Fc + ), high solubility (>2.7 M in acetonitrile), and remarkable stability (99.86% capacity retention over 49.5 h (202 cycles) of H-cell cycling). This anolyte was paired with N-(2-(2-methoxyethoxy)-ethyl)phenothiazine (MEEPT) to achieve a 2.3 V all-organic NARFB exhibiting 95.8% capacity retention over 75.1 h (120 cycles) of cycling.

25 ENERGY STORAGE↗

Electrochemical C–N Bond Formation within Boron Imidazolate Cages Featuring Single Copper Sites

Electrocatalysis expands the ability to generate industrially relevant chemicals locally and on-demand with intermittent renewable energy, thereby improving grid resiliency and reducing supply logistics. Herein, we report the feasibility of using molecular copper boron-imidazolate cages, BIF-29(Cu), to enable coupling between the electroreduction reaction of CO 2 (CO 2 RR) with NO 3 – reduction (NO 3 RR) to produce urea with high selectivity of 68.5% and activity of 424 μA cm –2 . Remarkably, BIF-29(Cu) is among the most selective systems for this multistep C–N coupling to-date, despite possessing isolated single-metal sites. The mechanism for C–N bond formation was probed with a combination of electrochemical analysis, in situ spectroscopy, and atomic-scale simulations. We found that NO 3 RR and CO 2 RR occur in tandem at separate copper sites with the most favorable C–N coupling pathway following the condensation between *CO and NH 2 OH to produce urea. In conclusion, this work highlights the utility of supramolecular metal–organic cages with atomically discrete active sites to enable highly efficient coupling reactions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Nanoscale Hybrid Electrolytes with Viscosity Controlled Using Ionic Stimulus for Electrochemical Energy Conversion and Storage

As renewable energy is rapidly integrated into the grid, the challenge has become storing intermittent renewable electricity. Technologies including flow batteries and CO 2 conversion to dense energy carriers are promising storage options for renewable electricity. To achieve this technological advancement, the development of next generation electrolyte materials that can increase the energy density of flow batteries and combine CO 2 capture and conversion is desired. Liquidlike nanoparticle organic hybrid materials (NOHMs) composed of an inorganic core with a tethered polymeric canopy (e.g., polyetheramine (HPE)) have a capability to bind chemical species of interest including CO 2 and redox-active species. In this study, the unique response of NOHM-I-HPE-based electrolytes to salt addition was investigated, including the effects on solution viscosity and structural configurations of the polymeric canopy, impacting transport behaviors. The addition of 0.1 M NaCl drastically lowered the viscosity of NOHM-based electrolytes by up to 90%, reduced the hydrodynamic diameter of NOHM-I-HPE, and increased its self-diffusion coefficient, while the ionic strength did not alter the behaviors of untethered HPE. This study is the first to fundamentally discern the changes in polymer configurations of NOHMs induced by salt addition and provides a comprehensive understanding of the effect of ionic stimulus on their bulk transport properties and local dynamics. These insights could be ultimately employed to tailor transport properties for a range of electrochemical applications.

25 ENERGY STORAGE↗

Probing Slow Earthquakes With Deep Learning

Abstract Slow earthquakes may trigger failure on neighboring locked faults that are stressed sufficiently to break, and slow slip patterns may evolve before a nearby great earthquake. However, even in the clearest cases such as Cascadia, slow earthquakes and associated tremor have only been observed in intermittent and discrete bursts. By training a convolutional neural network to detect known tremor on a single seismic station in Cascadia, we isolate and identify tremor and slip preceding and following known larger slow events. The deep neural network can be used for the detection of quasi‐continuous tremor, providing a proxy that quantifies the slow slip rate. Furthermore, the model trained in Cascadia recognizes tremor in other subduction zones and also along the San Andreas Fault at Parkfield, suggesting a universality of waveform characteristics and source processes, as posited from experiments and theory.

58 GEOSCIENCES↗

High Vapor Pressure Deficit Decreases the Productivity and Water Use Efficiency of Rain‐Induced Pulses in Semiarid Ecosystems

Abstract Intermittent rain events drive dynamic pulses of carbon and water exchange in many arid and semiarid ecosystems. Although soil moisture is known to control these pulses, the effect of atmospheric dryness on pulses is not well documented. Here we hypothesized that vapor pressure deficit ( VPD ) modulates net ecosystem production ( NEP ) and ecosystem‐scale water use efficiency ( WUE ) during pulse events due to its effects on canopy stomatal conductance and evapotranspiration. We quantified relationships between VPD and carbon and water exchange during growing season rain events and tested their generality across four semiarid flux sites with varied vegetation in the southwest United States. Across grassland, shrubland, and savanna sites, we found that high VPD during pulses suppressed ecosystem photosynthesis and surface conductance to a greater degree than respiration or evapotranspiration, particularly when soil moisture was high. Thus, periods of high VPD were associated with a 13–64% reduction in NEP and an 11–25% decrease in WUE , relative to moderate VPD conditions. Sites dominated by shrubs with the C3 photosynthetic pathway were more sensitive to VPD than sites dominated by C4 grasses. We found that a 1 kPa increase in VPD reduced the average NEP of pulse events by 13–56%, which illustrates the potential for projected increases in atmospheric demand to reduce the net productivity of semiarid ecosystems.

Roby, Matthew C.↗

Vertical Structure of Clouds and Precipitation During Arctic Cold–Air Outbreaks and Warm–Air Intrusions: Observations From COMBLE

The Arctic is marked by deep intrusions of warm, moist air, alternating with outbreaks of cold air down to lower latitudes. The typical vertical structure of clouds and precipitation during these two synoptic weather extremes is examined at a coastal site at 69°N in Norway. The Norwegian Sea is a corridor for warm-air intrusions (WAIs) and frequently witnesses cold-air outbreaks (CAOs). This study uses data from profiling radar, lidar, and microwave radiometer, radiosondes and other probes that were collected during the CAOs in the Marine Boundary Layer Experiment (COMBLE) between 1 December 2019 and 31 May 2020. Marine CAOs are defined in terms of thermal instability relative to the sea surface temperature, and WAIs in terms of equivalent potential temperature stratification between the surface and 850 hPa. Cloud structures in CAOs are convective, driven by strong surface heat fluxes over a long fetch of open water, with cloud tops rarely exceeding 6 km above sea level. The mostly open-cellular convection produces intermittent moderately-heavy precipitation at the observational site, notwithstanding the low precipitable water vapor (PWV). In contrast, WAIs are marked by high values of PWV and integrated vapor transport. Here, WAI clouds are synoptically driven, stratiform, with cloud tops often exceeding 5 km, sometimes layered, and generally producing persistent precipitation that can be heavier than in CAOs.

54 ENVIRONMENTAL SCIENCES↗

New Perspective on Phase Space Density Analysis for Outer Radiation Belt Enhancements: The Influence of MeV Electron Injections

Observation of growing phase space density (PSD) peak in the outer electron radiation belt has been considered evidence for local wave-driven acceleration as a primary cause of radiation belt enhancement. However, recent studies showed that strong substorm-associated MeV electron injections can also cause significant radiation belt enhancements on fast timescales (~10s min). Such rapid enhancements pose challenges for determining true spatial PSD profiles. To address this, we conduct a detailed spatiotemporal analysis of electron flux and PSD during an enhancement event, using Van Allen Probes data. Our analysis reveals rapid and intermittent flux enhancements. During these rapid enhancements, inbound spacecraft observed false PSD peaks, due to spacecraft's relatively slow movement. However, we identify time intervals of stable fluxes between enhancements, enabling us to determine quasi-stationary PSD profiles with no noticeable peaks. This study provides new insights into accurate PSD analysis, critical for understanding the mechanisms underlying radiation belt enhancements.

79 ASTRONOMY AND ASTROPHYSICS↗

On the Interplay Between Distributed Bulk Plasticity and Local Fault Slip in Evolving Fault Zone Complexity

Abstract We numerically investigate the role of plastic strain accumulation on the mechanical response of a planar strike‐slip fault. Our models show that fault‐zone strength significantly impacts the ensuing sequence of earthquakes. Weaker fault zones accumulating more plastic strain promote more complexity in the seismicity pattern through aperiodic earthquake occurrences and intermittent episodes of rupture and arrest. However, if the fault zone strength is high enough, the overall earthquake sequence is characterized by periodic fault‐spanning events. We find that both the fault normal stress and the fault geometric profile evolve throughout the earthquake sequence, suggesting a self‐roughening mechanism. Despite the significant impact of plasticity on the fault response, the width of the plastically deforming region in the fault zone is small compared to the fault length. Our results suggest a rich behavior in dynamically evolving fault zones and support the need for further high‐resolution studies of the highly non‐linear near‐fault region.

Geology↗

Mapping Glacier Basal Sliding Applying Machine Learning

During the RESOLVE project (“High-resolution imaging in subsurface geophysics: development of a multi-instrument platform for interdisciplinary research”), continuous surface displacement and seismic array observations were obtained on Glacier d’Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic cryospheric environment. In particular, the physical processes controlling glacial basal motion are poorly understood and remain challenging to observe directly. Especially in the Alpine region for temperate based glaciers where the ice rapidly responds to changing climatic conditions and thus, processes are strongly intermittent in time and heterogeneous in space. Spatially dense seismic and Global Positioning System (GPS) measurements are analyzed applying machine learning to gain insight into the processes controlling glacial motions of Glacier d’Argentière. Using multiple bandpass-filtered copies of the continuous seismic waveforms, we compute energy-based features, develop a matched field beamforming catalog and include meteorological observations. Features describing the data are analyzed with a gradient boosting decision tree model to directly estimate the GPS displacements from the seismic noise. We posit that features of the seismic noise provide direct access to the dominant parameters that drive displacement on the highly variable and unsteady surface of the glacier. The machine learning model infers daily fluctuations and longer term trends. The results show on-ice displacement rates are strongly modulated by activity at the base of the glacier. The techniques presented provide a new approach to study glacial basal sliding and discover its full complexity.

58 GEOSCIENCES↗

Scaling Exponents of Turbulent Static Pressure Structure Function in the Inertial Subrange

The measured variations in the turbulent static pressure structure function D pp (r) with scale $r$ in the roughness sublayer above a subarctic forest are empirically shown to exhibit exponents that are smaller than $r$ 4/3 predicted for the inertial subrange (ISR). Three hypotheses are offered to explain these deviations. The first is based on conventional intermittency correction to the averaged turbulent kinetic energy dissipation rate, the second is based on shearing introducing deviations from locally isotropic state that must be sensed by both velocity and pressure structure functions, and the third is based on large and inertial scale pressure interactions that persist at values of $r$ within the resolvable ISR. The third hypothesis is shown to yield superior results, which allows a new formulation for D pp (r) to be derived that accommodates such finite interactions.

structure function↗

A Deep State Space Model for Rainfall‐Runoff Simulations

The classical way of studying the rainfall‐runoff processes in the water cycle relies on conceptual or physically‐based hydrologic models. Deep learning (DL) has recently emerged as an alternative and blossomed in the hydrology community for rainfall‐runoff simulations. However, the decades‐old Long Short‐Term Memory (LSTM) network remains the benchmark for this task, outperforming newer architectures like Transformers. In this work, we propose a State Space Model (SSM), specifically the Frequency Tuned Diagonal State Space Sequence (S4D‐FT) model, for rainfall‐runoff simulations. The proposed S4D‐FT is benchmarked against the established LSTM and a physically‐based Sacramento Soil Moisture Accounting model under in‐sample and out‐of‐sample simulation setups across 531 watersheds in the contiguous United States (CONUS). Results show that S4D‐FT is able to outperform the LSTM model across diverse regions under both simulation setups, especially for regions that feature snowmelt‐driven or intermittent flow regimes. In contrast, S4D‐FT tends to underperform in flashier, high‐magnitude flow regimes, likely due to its global state‐space convolution computation that emphasizes slow, storage‐driven dynamics, which makes it less effective at picking up short bursts and noisy spikes in the data. In summary, our pioneering introduction of the S4D‐FT for rainfall‐runoff simulations challenges the dominance of LSTM in the hydrology community and expands the arsenal of DL tools available for hydrological modeling.

Wang, Yihan [Univ. of Oklahoma, Norman, OK (United↗

Air, surface, and wastewater surveillance of SARS-CoV-2; a multimodal evaluation of COVID-19 detection in a built environment

Environmental surveillance of infectious organisms holds tremendous promise to reduce human-to-human transmission in indoor spaces through early detection. In this study we determined the applicability and limitations of wastewater, indoor high-touch surfaces, in-room air, and rooftop exhaust air sampling methods for detecting SARS-CoV-2 in a real world building occupied by residents recently diagnosed with COVID-19. We concurrently examined the results of three 24-hour environmental surveillance techniques, indoor surface sampling, exhaust air sampling and wastewater surveillance, to the known daily census fluctuations in a COVID-19 isolation dormitory. Additionally, we assessed the ability of aerosol samplers placed in the large volume lobby to detect SARS-CoV-2 multiple times per day. Our research reveals an increase in the number of individuals confirmed positive with COVID-19 as well as their estimated human viral load to be associated with statistically significant increases in viral loads detected in rooftop exhaust aerosol samples (p = 0.0413), wastewater samples (p = 0.0323,), and indoor high-touch surfaces (p < 0.001)). We also report that the viral load detected in lobby aerosol samples was statistically higher in samples collected during presence of occupants whose COVID-19 diagnostic tests were confirmed positive via qPCR compared to periods when the lobby was occupied by either contact-traced (suspected positive) individuals or during unoccupied periods (p = 0.0314 and <2e–16). We conclude that each daily (24h) surveillance method, rooftop exhaust air, indoor high-touch surfaces, and wastewater, provide useful detection signals for building owner/operator(s). Furthermore, we demonstrate that exhaust air sampling can provide spatially resolved signals based upon ventilation exhaust zones. Additionally, we find that indoor lobby air sampling can provide temporally resolved signals useful during short duration sampling periods (e.g., 2-4 hours) even with intermittent occupancy by occupants diagnosed with COVID-19.

60 APPLIED LIFE SCIENCES↗

Power sector investment implications of climate impacts on renewable resources in Latin America and the Caribbean

Climate change mitigation will require substantial investments in renewables. In addition, climate change will affect future renewable supply and hence, power sector investment requirements. We study the implications of climate impacts on renewables for power sector investments under deep decarbonization using a global integrated assessment model. We focus on Latin American and Caribbean, an under-studied region but of great interest due to its strong role in international climate mitigation and vulnerability to climate change. We find that accounting for climate impacts on renewables results in significant additional investments ($12–114 billion by 2100 across Latin American countries) for a region with weak financial infrastructure. We also demonstrate that accounting for climate impacts only on hydropower—a primary focus of previous studies—significantly underestimates cumulative investments, particularly in scenarios with high intermittent renewable deployment. Our study underscores the importance of comprehensive analyses of climate impacts on renewables for improved energy planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Low coordination number copper catalysts for electrochemical CO 2 methanation in a membrane electrode assembly

The electrochemical conversion of CO 2 to methane provides a means to store intermittent renewable electricity in the form of a carbon-neutral hydrocarbon fuel that benefits from an established global distribution network. The stability and selectivity of reported approaches reside below technoeconomic-related requirements. Membrane electrode assembly-based reactors offer a known path to stability; however, highly alkaline conditions on the cathode favour C-C coupling and multi-carbon products. In computational studies herein, we find that copper in a low coordination number favours methane even under highly alkaline conditions. Experimentally, we develop a carbon nanoparticle moderator strategy that confines a copper-complex catalyst when employed in a membrane electrode assembly. In-situ XAS measurements confirm that increased carbon nanoparticle loadings can reduce the metallic copper coordination number. At a copper coordination number of 4.2 we demonstrate a CO 2 -to-methane selectivity of 62%, a methane partial current density of 136 mA cm –2 , and > 110 hours of stable operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gold-in-copper at low *CO coverage enables efficient electromethanation of CO 2

The renewable-electricity-powered CO 2 electroreduction reaction provides a promising means to store intermittent renewable energy in the form of valuable chemicals and dispatchable fuels. Renewable methane produced using CO 2 electroreduction attracts interest due to the established global distribution network; however, present-day efficiencies and activities remain below those required for practical application. Here we exploit the fact that the suppression of *CO dimerization and hydrogen evolution promotes methane selectivity: we reason that the introduction of Au in Cu favors *CO protonation vs. C-C coupling under low *CO coverage and weakens the *H adsorption energy of the surface, leading to a reduction in hydrogen evolution. We construct experimentally a suite of Au-Cu catalysts and control *CO availability by regulating CO 2 concentration and reaction rate. This strategy leads to a 1.6× improvement in the methane:H 2 selectivity ratio compared to the best prior reports operating above 100 mA cm -2 . We as a result achieve a CO 2 -to-methane Faradaic efficiency (FE) of (56 ± 2)% at a production rate of (112 ± 4) mA cm -2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A DNA packaging motor inchworms along one strand allowing it to adapt to alternative double-helical structures

Abstract Ring ATPases that translocate disordered polymers possess lock-washer architectures that they impose on their substrates during transport via a hand-over-hand mechanism. Here, we investigate the operation of ring motors that transport ordered, helical substrates, such as the bacteriophage ϕ29 dsDNA packaging motor. This pentameric motor alternates between an ATP loading dwell and a hydrolysis burst wherein it packages one turn of DNA in four steps. When challenged with DNA-RNA hybrids and dsRNA, the motor matches its burst to the shorter helical pitches, keeping three power strokes invariant while shortening the fourth. Intermittently, the motor loses grip on the RNA-containing substrates, indicating that it makes optimal load-bearing contacts with dsDNA. To rationalize these observations, we propose a helical inchworm translocation mechanism in which, during each cycle, the motor increasingly adopts a lock-washer structure during the ATP loading dwell and successively regains its planar form with each power stroke during the burst.

59 BASIC BIOLOGICAL SCIENCES↗

Inner southern magnetosphere observation of Mercury via SERENA ion sensors in BepiColombo mission

Mercury’s southern inner magnetosphere is an unexplored region as it was not observed by earlier space missions. In October 2021, BepiColombo mission has passed through this region during its first Mercury flyby. Here, we describe the observations of SERENA ion sensors nearby and inside Mercury’s magnetosphere. An intermittent high-energy signal, possibly due to an interplanetary magnetic flux rope, has been observed downstream Mercury, together with low energy solar wind. Low energy ions, possibly due to satellite outgassing, were detected outside the magnetosphere. The dayside magnetopause and bow-shock crossing were much closer to the planet than expected, signature of a highly eroded magnetosphere. Different ion populations have been observed inside the magnetosphere, like low latitude boundary layer at magnetopause inbound and partial ring current at dawn close to the planet. These observations are important for understanding the weak magnetosphere behavior so close to the Sun, revealing details never reached before.

79 ASTRONOMY AND ASTROPHYSICS↗