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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 919 records · Page 51

Microbial carbon use efficiency promotes global soil carbon storage

Soils store more carbon than other terrestrial ecosystems. How soil organic carbon (SOC) forms and persists remains uncertain, which makes it challenging to understand how it will respond to climatic change. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Electromagnetic waves in an optical photonic lattice

Laser light propagation in a photonic lattice consisting of two parallel waveguide arrays is theoretically studied using the coupled mode method, with the interaction of each waveguide with the nearest neighbours and between the waveguides of the arrays being taken into account. Analytical expressions are obtained that make it possible to accurately predict the presence of localisation of light depending on the coupling constants. Particular solutions of a system of coupled waves are found, which describe strongly localised light propagating without transverse diffraction along the entire lattice at certain values of the coupling constants. The emergence of spatially limited transverse diffraction of light is predicted. (integral optics)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ultrafast pulse pumping of topological nanospaser

Here, we theoretically examine a topological nanospaser that is optically pumped using an ultra-fast circularly-polarized pulse. The spasing system consists of a silver nanospheroid, which supports surface plasmon (SP) excitations, and a transition metal dichalcogenide (TMDC) monolayer nanoflake. The silver nanospheroid screens the incoming pulse and creates a non-uniform spatial distribution of electron excitations in the TMDC nanoflake. These excitations decay into the localized SPs, which can be of two types with the corresponding magnetic quantum number ±1. The amount and the type of the generated SPs depend on the intensity of the optical pulse. For small pulse amplitude, only one plasmonic mode is predominantly generated, resulting in far-field elliptically polarized radiation. For large amplitude of the optical pulse, both plasmonic modes are generated in almost the same amount, resulting in linearly polarized far-field radiation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The hybrid topological longitudinal transmon qubit

We introduce a new hybrid qubit consisting of a Majorana qubit interacting with a transmon longitudinally coupled to a resonator. To do so, we equip the longitudinal transmon qubit with topological quasiparticles, supported by an array of heterostructure nanowires, and derive charge- and phase-based interactions between the Majorana qubit and the resonator and transmon degrees of freedom. Inspecting the charge coupling, we demonstrate that the Majorana self-charging can be eliminated by a judicious choice of charge offset, thereby maintaining the Majorana degeneracy regardless of the quasiparticles spatial arrangement and parity configuration. We perform analytic and numerical calculations to derive the effective qubit-qubit interaction elements and discuss their potential utility for state readout and quantum error correction. Further, we find that select interactions depend strongly on the overall superconducting parity, which may provide a direct mechanism to characterize deleterious quasiparticle poisoning processes.

36 MATERIALS SCIENCE↗

Remote sensing of cytotype and its consequences for canopy damage in quaking aspen

Abstract Mapping geographic mosaics of genetic variation and their consequences via genotype x environment interactions at large extents and high resolution has been limited by the scalability of DNA sequencing. Here, we address this challenge for cytotype (chromosome copy number) variation in quaking aspen, a drought‐impacted foundation tree species. We integrate airborne imaging spectroscopy data with ground‐based DNA sequencing data and canopy damage data in 391 km 2 of southwestern Colorado. We show that (1) aspen cover and cytotype can be remotely sensed at 1 m spatial resolution, (2) the geographic mosaic of cytotypes is heterogeneous and interdigitated, (3) triploids have higher leaf nitrogen, canopy water content, and carbon isotope shifts (δ 13 C) than diploids, and (4) canopy damage varies among cytotypes and depends on interactions with topography, canopy height, and trait variables. Triploids are at higher risk in hotter and drier conditions.

Blonder, Benjamin↗

Mycorrhizal associations of tree species influence soil nitrogen dynamics via effects on soil acid–base chemistry

Across all spatial scales, ECM-dominated forests were associated with greater soil acidity. In particular, ECM-dominated soils exhibited lower soil pH and base cations, although the magnitude of mycorrhizal-associated differences in soil acid–base chemistry depended on the biomes, with differences being more pronounced in temperate than in sub/tropical forests. Higher lignin and lower base cations in ECM tree leaf litter were related to greater soil acidity in ECM-dominated forests. Moreover, the lower inorganic N concentrations and slower N transformation rates in ECM-dominated forests were associated with their greater soil acidity. Our results indicate that the scale-invariant feedbacks between plant nutrient-use strategies and soil properties have the potential to impact forest community assembly and ecosystem processes, particularly in the context of global change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fracture Network Quantification during CO2 Injection

This is the presentation prepared for the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗

Magnetohydrodynamic Wave Mode Conversion in a Pseudostreamer Structure

The interaction of a fast magnetoacoustic wave with a magnetic null point in a pseudostreamer magnetic configuration is modeled. The incident fast wave is excited by an impulsive velocity driver located in the corona outside the Alfvén-acoustic equipartition layer. The fast wave front experiences refraction and wraps around the null point, while the front segment approaching the null point along the magnetic bisector passes through it. In the equipartition layer surrounding the null point, part of the fast wave energy is converted into slow magnetoacoustic waves. Slow waves propagate outward from the null point along the magnetic separatrices. The fronts of slow waves exhibit a characteristic chevron shape. The fast-to-slow mode conversion efficiency increases with the width of the initial perturbation, following a power-law dependence with an index of approximately 1.06. For initial wave amplitudes below about 10% of the local Alfvén speed, the dependence of the conversion efficiency on the initial amplitude is weak. After interacting with the null point, the amplitudes of the fast waves decrease significantly owing to energy conversion and the spreading of wave energy over a broad spatial domain. In contrast, the energy of slow waves remains concentrated in the vicinity of the magnetic separatrices, resulting in less pronounced geometric attenuation of these waves. These findings are consistent with observational reports of the interaction of a coronal fast wave with a pseudostreamer.

Zhong, Yu [Univ. of Warwick, Coventry (United King↗

Fracture Network Quantification during CO2 Injection

This is the conference paper accompanying an oral presentation at the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗

Particle charge distributions in the effluent of a flow-through atmospheric pressure low temperature plasma

Atmospheric pressure low-temperature plasmas are often utilized to perform particle synthesis, treatment, and removal. It is well-known that dust particles are highly negatively charged in these plasmas; however, little is known about dust particle charging behavior as particles leave the plasma volume and pass through the spatial afterglow region. In this work, monodisperse particles of various sizes and work functions were introduced into an atmospheric pressure radiofrequency capacitively coupled flow-through plasma. Dust particle electrical mobility distributions downstream of the flow-through plasma were measured utilizing a differential mobility analyzer in conjunction with a condensation particle counter at various gas flow velocities. Charge distributions were determined from the measured electrical mobility distributions. Experiments confirm that particles become less negatively charged, and even net-positively charged after leaving the plasma volume, with a distribution that follows a shifted Boltzmann charge distribution. Additionally, particle charge in the effluent of the flow-through plasma is negligibly dependent on work function but highly size and flow velocity dependent. Larger particles were shown to have a higher magnitude of charge under all studied conditions; however, particle polarity was switchable by varying gas flow velocity. The charging dynamics were simulated utilizing a constant number Monte Carlo model that accounts for electron temperature decay and the transition from ambipolar to free diffusion of electrons and ions in the spatial afterglow. Simulation results also suggest that, at the same flow velocity, larger particles obtain a greater magnitude of charge, negative or positive. Furthermore, the decrease in electron mobility and the difference between ion and electron convective loss rates create an ion-rich region in the plasma effluent that promotes ion–particle collisions and drives particle charge removal and even reversal of polarity. Larger particles more favorably collide with energetic species in these environments, which results in higher charge states.

atmospheric pressure low temperature plasma↗

A Mixed Length Scale Model for Migrating Fluvial Bedforms

With the expansion of hydropower, in-stream converters, flood-protection infrastructures, and growing concerns on deltas fragile ecosystems, there is a pressing need to evaluate and monitor bedform sediment mass flux. It is critical to estimate real-time bedform size and migration velocity and provide a theoretical framework to convert easily accessible time histories of bed elevations into spatially evolving patterns. In this study, we collected spatiotemporally resolved bathymetries from laboratory flumes and the Colorado River in statistically steady, homogeneous, subcritical flow conditions. Wave number and frequency spectra of bed elevations show compelling evidence of scale-dependent velocity for the hierarchy of migrating bedforms observed in the laboratory and field. New scaling laws were applied to describe the full range of migration velocities as function of two dimensionless groups based on the bed shear velocity, sediment diameter, and water depth. Further simplification resulted in a mixed length scale model estimating scale-dependent migration velocities, without requiring bedform classification or identification.

58 GEOSCIENCES↗

Developmental assembly of multi-component polymer systems through interconnected synthetic gene networks in vitro

Abstract Living cells regulate the dynamics of developmental events through interconnected signaling systems that activate and deactivate inert precursors. This suggests that similarly, synthetic biomaterials could be designed to develop over time by using chemical reaction networks to regulate the availability of assembling components. Here we demonstrate how the sequential activation or deactivation of distinct DNA building blocks can be modularly coordinated to form distinct populations of self-assembling polymers using a transcriptional signaling cascade of synthetic genes. Our building blocks are DNA tiles that polymerize into nanotubes, and whose assembly can be controlled by RNA molecules produced by synthetic genes that target the tile interaction domains. To achieve different RNA production rates, we use a strategy based on promoter “nicking” and strand displacement. By changing the way the genes are cascaded and the RNA levels, we demonstrate that we can obtain spatially and temporally different outcomes in nanotube assembly, including random DNA polymers, block polymers, and as well as distinct autonomous formation and dissolution of distinct polymer populations. Our work demonstrates a way to construct autonomous supramolecular materials whose properties depend on the timing of molecular instructions for self-assembly, and can be immediately extended to a variety of other nucleic acid circuits and assemblies.

Science & Technology - Other Topics↗

Predicting weather impacts on corn production in a data-limited region using a transfer learning approach

The stability of food supply and prices may depend more on annual changes in yields from year-to-year variability in weather than on longer-term average changes from changing climatic conditions. However, the absence of high-quality data on crop yields at fine spatial resolutions in many regions of the world makes it challenging to statistically model their response to interannual variability in weather patterns. Therefore, there is a need for empirical methods that can project annual crop yield changes even in limited data regions. Here, we propose a transfer learning algorithm that uses high spatial resolution data from one region to project yields in another region with more limited data. The goal of our work is to understand what data types can be beneficial for transferring learning from a source region to a very different target region with more limited data. We utilize Long Short-Term Memory to develop a transfer learning model that is trained on historical county-level corn yield in the United States and predicts district-level corn yield variations in India. Even using smaller amounts of data in India, simulating a data-scarce region, we achieve an average root mean square error of 0.48 bu acre−1 in predicting interannual yield variations. Using Shapley values to interpret results, we explore the contribution of the different weather parameters to interannual yield variability and find a larger influence of precipitation-related variables. Our study demonstrates the usefulness of this method for transferring models of weather impacts on crop yields trained on a data-rich country to one with more limited data. It suggests the potential of applying the transfer learning model to mitigate the need for extensive raw data globally.

Vishwakarma, Srishti [ORNL] (ORCID:000000031674419↗

Phase transition amplification of proton number fluctuations in nuclear collisions from a transport model approach

The time evolution of particle number fluctuations in nuclear collisions at intermediate energies (E lab = 1.23–10⁢A GeV) is studied by means of the UrQMD-3.5 transport model. The transport description incorporates baryonic interactions through a density-dependent potential. This allows for an implementation of a first-order phase transition including a mechanically unstable region at large baryon density. The scaled variance of the baryon and proton number distributions is calculated in the central cubic spatial volume of the collisions at different times. A significant enhancement of fluctuations associated with the unstable region is observed. This enhancement persists to late times, reflecting a memory effect for the fluctuations. The presence of the phase transition has a much smaller influence on the observable event-by-event fluctuations of protons in momentum space.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Scale-dependent enhancement of productivity and stability in xenic Nannochloropsis cultures

Although bacterial amendments can enhance algal productivity and stability, the development of algal-bacteria consortia for commercial-scale utilization is limited. Here, for this work, we used an established high-throughput approach to generate algal-bacteria consortia, and tested consortia performance at spatial scales from microplates to 320 L raceway ponds. We used both lab and field-reared strains of Nannochloropsis oceanica to build consortia. In some experiments, we imposed environmental perturbations to test the ability of bacteria to enhance algal culture stability. In repeated assays at the scale of well plates, flasks, and bioreactors, strong effects of bacterial amendments on N. oceanica were observed. These effects were most dramatic when cultures experienced stressors such as temperature perturbations or removal of CO 2 augmentation. Isolates that were advanced for field testing included species in the genera Algoriphagus, Oceanicaulis, and Marinobacter. When consortia were generated in the field, positive effects of bacterial amendments were not observed. The amended bacteria were outcompeted, and bacterial community composition across treatments converged after the first grow out. These results highlight the complexity of using consortia in open systems, where interactions between the existing bacterial community, inoculated bacteria, and changing environmental conditions are layered upon other differences in scale and cultivation regimes. Moreover, functionally redundant bacteria are likely present in the field. Following this work, we hypothesize that tight interactions (e.g., obligate relationships between partners) will scale more predictably to outdoor systems. We suggest relying on true synthetic ecological approaches in which the relationships between bacteria and algae partners are well understood, or synthetic ecological approaches coupled with high throughput approaches to design and test consortia. We also recommend future work to examine the effect of algae-bacteria inoculation ratios on productivity and stability, track dynamics of partners through time, and manage ponds to retain beneficial symbioses.

59 BASIC BIOLOGICAL SCIENCES↗

Can magnetogenesis driven by dynamo instabilities in chiral fermion plasmas, favor Einstein–Cartan AdS cosmology?

In this letter we show that the magnetic field (MF) bounds induced by Einstein–Cartan–de Sitter (EC) with AdS anti-de Sitter spacetime geometry and fermionic torsion with chiral dynamo plasmas instabilities, with inhomogeneous uniform chiral chemical potential, indicates that there is a possibility, as far as magnetogenesis is concerned, that we may obtain more stringent results within ECAdS gravity, compared with general relativity (GR) limits obtained by Tsagas using torsionless magnetogenesis. Spinorial fermionic source with torsion induces a chiral plasmas oscillation. The time dependent chiral chemical potential, sometimes associated formally with torsion, (de Andrade, 2018), is obtained from chiral flipping equation. The MFs obtained from the present universe ECdS chiral dynamo model, meet the criteria of galactic seed fields with better limits within Tsagas range (Tsagas, 2015) seed galactic magnetic fields for dynamo mechanisms, than the bound obtained by chiral dynamos in torsionless AdS cosmology. Majorana neutrinos are used as spatial components of axial spin-torsion source of dynamo instability from neutrino asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Impact of Individual Structural Defects in GaAs Solar Cells: A Correlative and In Operando Investigation of Signatures, Structures, and Effects

Defects usually degrade device performance. Thus, many techniques and effort are devoted to studying semiconductor defects. However, it is rarely known: i) how individual defects affect device performance; ii) how the impact depends on the device operating conditions; iii) how the impact varies from one defect to another; and iv) how these variations are correlated to the microscopic-scale defect structure. To address these crucial questions, an array of correlative and spatially resolved techniques, including electroluminescence, photoluminescence, Raman, I–V characteristics, and high-resolution electron microscopy, are used to characterize dislocation defects in GaAs solar cells. Significantly, the study is carried out in a series mode and in operando. This approach provides quantitative and definitive correlation between the atomistic structure of defects and their explicit effects on device performance, thus giving unprecedented insight into defect physics.

dislocation defects↗

Water Availability for Biorefineries in the Contiguous United States and the Implications for Bioenergy Production Distribution

Renewable biofuel production depends on many factors, including feedstock availability, refinery and shipment infrastructure, and in particular, water availability. This study assesses water requirement and availability for mainstream biorefinery technologies in the contiguous United States (CONUS). The assessment is conducted in newly defined spatial units, namely, biorefinery planning boundaries, considering feedstock availability, transportation cost, and refinery capacity requirement for cost-effectiveness. The results suggest that the total biorefinery water use in the CONUS by 2030 will be low compared to the total water availability. However, biorefinery water requirements can aggravate the water stress situation in many regions, including the Great Plains, California Central Valley, and the upper Columbia-Snake River basin in Washington. Bioenergy productions in these regions can be largely constrained by water. Here, it is projected that biofuel production will concentrate in Northern Plains, Lake States, and Corn Belt regions, which contribute 94.4% of the conventional, 86.1% of biodiesel, and 54.8% of cellulosic biofuel production mandated by the renewable fuel standard. If biorefineries are constrained to use less than 10% of the locally available water, up to 7% of planned cellulosic biofuel production will be affected. Findings from this study can aid the sustainable planning of national bioenergy production.

54 ENVIRONMENTAL SCIENCES↗