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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 253 records · Page 14

Patternable Mesoporous Thin Film Quantum Materials via Block Copolymer Self-Assembly: An Emergent Technology?

Recent developments in quantum materials hold promise for revolutionizing energy and information technologies. The use of soft matter self-assembly, for example, by employing block copolymers (BCPs) as structure directing or templating agents, offers facile pathways toward quantum metamaterials with highly tunable mesostructures via scalable solution processing. Here, we report the preparation of patternable mesoporous niobium carbonitride-type thin film superconductors through spin-coating of a hybrid solution containing an amphiphilic BCP swollen by niobia sol precursors and subsequent thermal processing in combination with photolithography. Spin-coated as-made BCP-niobia hybrid thin films on silicon substrates after optional photolithographic definition are heated in air to produce a porous oxide, and subsequently converted in a multistep process to carbonitrides via treatment with high temperatures in reactive gases including ammonia. Grazing incidence small-angle X-ray scattering suggests the presence of ordered mesostructures in as-made BCP-niobia films without further annealing, consistent with a distorted alternating gyroid morphology that is retained upon thermal treatments. Wide-angle X-ray scattering confirms the synthesis of phase-pure niobium carbonitride nanocrystals with rock-salt lattices within the mesoscale networks. Electrical transport measurements of unpatterned thin films show initial exponential rise in resistivity characteristic of thermal activation in granular systems down to 12.8 K, at which point resistivity drops to zero into a superconducting state. Magnetoresistance measurements determine the superconducting upper critical field to be over 16 T, demonstrating material quality on par with niobium carbonitrides obtained from traditional solid-state synthesis methods. Here. we discuss how such cost-effective and scalable solution-based quantum materials fabrication approaches may be integrated into existing microelectronics processing, promising the emergence of a technology with tremendous academic and industrial potential by combining the capabilities of soft matter self-assembly with quantum materials.

36 MATERIALS SCIENCE↗

Focused Helium Ion Beam for Direct Patterning of Monolayer MoS 2 Nanoribbon Field Effect Devices

The helium ion microscope (HIM) focused ion beam (FIB) has emerged as a powerful tool to directly pattern nanostructures below 10 nm due to its high-resolution capabilities and the inert nature of the ion source. These attributes make HIM FIB particularly interesting for patterning 2D materials such as transition metal dichalcogenides (TMDs) to investigate transport phenomena at the nanoscale. Reported here is the fabrication of MoS 2 nanoribbon devices using HIM FIB-induced etching (FIBIE) with XeF 2 , allowing for reduced ion dose compared to direct sputtering. While patterning is efficacious, the devices exhibit performance degradation with decreasing nanoribbon width due to damage up to 150 nm beyond the patterned edge. Incorporating an hBN encapsulation improves device performance by one order of magnitude, although the lateral extent of damage remains unchanged. The spatial distribution of damage is shown to be determined by the forward- and backscattered ions and electrons, while the hBN encapsulation layer substantially reduces damage from XeF 2 interactions in unexposed regions. Raman and photoluminescence (PL) measurements corroborate these findings, while ion/solid interaction simulations further elucidate the resolution limits imposed by substrate interactions. In conclusion, this work provides critical insights and a practical pathway for utilizing HIM FIBIE in 2D TMD functional device patterning.

MoS 2↗

Perspective: The Climate-Population-Infrastructure Modeling and Simulation Fertile Area for New Research

Managing the risks posed by climate change and extreme weather to energy production and delivery is a challenge to communities worldwide. As climate conditions change, populations will shift, and demand will re-locate; and networked infrastructures will evolve to accommodate new load centers, and, hopefully, minimize vulnerability to natural disaster. Climate effects such as sea level rise, increased frequency and intensity of natural disasters, force populations to move locations. Displaced population creates new demand for built infrastructure that in turn generates new economic activity that attracts new workers and associated households to the new locations. Infrastructures and their interdependencies will change in reaction to climate drivers as the networks expand into new population areas and as portions of the networks are abandoned as people leave. Thus, infrastructures will evolve to accommodate new load centers while some parts of the network are underused, and these changes will create emerging vulnerabilities. Forecasting the location of these vulnerabilities by combining climate predictions and agent based population movement models shows promise for defining these future population distributions and changes in coastal infrastructure configurations. By combining climate and weather data, engineering algorithms and social theory it has been only recently possible to examine electricity demand response to increased climactic temperatures, population relocation in response to extreme cyclonic events, consequent net population changes and new regional patterns in electricity demand. These emerging results suggest a research agenda of coupling these disparate modelling approaches to understand the implications of climate change for protecting the nation s critical infrastructure.

Climate↗

Chemical Ecosystem Selection on Mineral Surfaces Reveals Long-Term Dynamics Consistent with the Spontaneous Emergence of Mutual Catalysis

How did chemicals first become organized into systems capable of self-propagation and adaptive evolution? One possibility is that the first evolvers were chemical ecosystems localized on mineral surfaces and composed of sets of molecular species that could catalyze each other’s formation. We used a bottom-up experimental framework; chemical ecosystem selection (CES) to evaluate this perspective and search for surface-associated; and mutually catalytic chemical systems based on the changes in chemistry they are expected to induce. Here, we report the results of preliminary CES experiments conducted using a synthetic “prebiotic soup” and pyrite grains, which yield dynamical patterns that are suggestive of the emergence of mutual catalysis. While more research is needed to better understand the specific patterns observed here and determine whether they are reflective of self-propagation, these results illustrate the potential power of CES to test competing hypotheses for the emergence of protobiological chemical systems.

autocatalysis↗

Detecting technological maturity from bibliometric patterns

We report the capability to identify emergent technologies based upon easily accessed open-source indicators, such as publications, is important for decision-makers in industry and government. The scientific contribution of this work is the proposition of a machine learning approach to the detection of the maturity of emerging technologies based on publication counts. Time-series of publication counts have universal features that distinguish emerging and growing technologies. We train an artificial neural network classifier, a supervised machine learning algorithm, upon these features to predict the maturity (emergent vs. growth) of an arbitrary technology. With a training set comprised of 22 technologies we obtain a classification accuracy ranging from 58.3% to 100% with an average accuracy of 84.6% for six test technologies. To enhance classifier performance, we augmented the training corpus with synthetic time-series technology life cycle curves, formed by calculating weighted averages of curves in the original training set. Training the classifier on the synthetic data set resulted in improved accuracy, ranging from 83.3% to 100% with an average accuracy of 90.4% for the test technologies. The performance of our classifier exceeds that of competing machine learning approaches in the literature, which report an average classification accuracy of only 85.7% at maximum. Moreover, in contrast to current methods our approach does not require subject matter expertise to generate training labels, and it can be automated and scaled.

97 MATHEMATICS AND COMPUTING↗

SPIRAL INSTABILITIES IN N-BODY SIMULATIONS. I. EMERGENCE FROM NOISE

The origin of spiral patterns in galaxies is still not fully understood. Similar features also develop readily in N-body simulations of isolated cool, collisionless disks, yet even here the mechanism has yet to be explained. In this series of papers, I present a detailed study of the origin of spiral activity in simulations in the hope that the mechanism that causes the patterns is also responsible for some of these features galaxies. In this first paper, I use a suite of highly idealized simulations of a linearly stable disk that employ increasing numbers of particles. While the amplitudes of initial non-axisymmetric features scale as the inverse square root of the number of particles employed, the final amplitude of the patterns is independent of the particle number. I find that the amplitudes of non-axisymmetric disturbances grow in two distinct phases: slow growth occurs when the relative overdensity is below {approx}2%, but above this level the amplitude rises more rapidly. I show that all features, even of very low amplitude, scatter particles at the inner Lindblad resonance, changing the distribution of particles in the disk in such a way as to foster continued growth. Stronger scattering by larger amplitude waves provokes a vigorous instability that is a true linear mode of the modified disk.

79 ASTRONOMY AND ASTROPHYSICS↗

Accelerated Stress Testing of Perovskite Photovoltaic Modules: Differentiating Degradation Modes with Electroluminescence Imaging

Herein, electroluminescence (EL) and thermal imaging are used to examine p–i–n metal halide perovskite (MHP) photovoltaic (PV) mini-modules (MA0.6FA0.4PbI3, 20 cells, 78 cm2) before and after indoor-accelerated stress testing or outdoor deployment. Distinct spatial patterns in the EL images emerge, which depend on the external stress conditions experienced by the mini-module. Imaging results highlight a distribution of dark speckle features that dominate after UV stress, attributed to widespread interfacial contact degradation. Lateral intensity gradients across cells dominate after thermal cycling (TC) stress, attributed to current crowding near scribe defects. While current–voltage analysis alone does not give full insight on the degradation process, this study shows that distinct degradation modes can be further defined by multimodal electro-optical imaging (i.e., EL combined with photoluminescence and dark lock-in thermography). Neither UV exposure nor TC-accelerated stress testing alone replicates the same degradation signatures observed after outdoor deployment, suggesting that multiple degradation modes occur under concurrent stressors outdoors. Finally, spatial characterization of degradation modes in MHP PV mini-modules before and after accelerated stress testing lays the groundwork for developing targeted accelerated stress testing procedures through comparison with outdoor aging.

14 SOLAR ENERGY↗

Numerical Analysis of Offshore Wind-Farm-Induced Drag Effects on Coastal Upwelling Dynamics

Wind farms extract momentum from the atmospheric flow, generating wind-speed deficits both within the plant, and extending downstream. When located offshore, these deficits modulate air-sea coupling, potentially impacting coastal upwelling in sensitive regions. We investigate impacts of wind farms on coastal upwelling using kilometre-scale, three-way-coupled simulations with the coupled ocean-atmosphere-wave-sediment transport system for the US West Coast. Wind-farm effects are represented by a generalised turbine drag formulation, an idealised, height-dependent body force whose magnitude is systematically varied. This approach isolates the leading-order fluid-dynamical response in a realistic coastal configuration. The atmospheric adjustment exhibits an approximately linear relation between drag force and wind-speed deficit, with wakes that expand downstream and increase in magnitude as drag increases. An empirical orthogonal function analysis of sea-surface-temperature anomalies reveals the emergence of a canonical dipole pattern under strong drag forcing. Subsurface diagnostics show consistent shoaling of the mixed layer and suppressed upward velocities in areas near wind-farm region, accompanied by compensating enhancements of shoaling closer to the coast. These results identify turbine drag as a control parameter in assessing interactions between wind-farm wake and coastal upwelling and provide scaling relationships for understanding offshore wind-farm effects on the coastal circulation dynamics.

16 TIDAL AND WAVE POWER↗

Quantifying Progress Across Different CMIP Phases With the ESMValTool

Abstract More than 40 model groups worldwide are participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6), providing a new and rich source of information to better understand past, present, and future climate change. Here, we use the Earth System Model Evaluation Tool (ESMValTool) to assess the performance of the CMIP6 ensemble compared to the previous generations CMIP3 and CMIP5. While CMIP5 models did not capture the observed pause in the increase in global mean surface temperature between 1998 and 2013, the historical CMIP6 simulations agree well with the observed recent temperature increase, but some models have difficulties in reproducing the observed global mean surface temperature record of the second half of the twentieth century. While systematic biases in annual mean surface temperature and precipitation remain in the CMIP6 multimodel mean, individual models and high‐resolution versions of the models show significant reductions in many long‐standing biases. Some improvements are also found in the vertical temperature, water vapor, and zonal wind speed distributions, and root‐mean‐square errors for selected fields are generally smaller with reduced intermodel spread and higher average skill in the correlation patterns relative to observations. An emerging property of the CMIP6 ensemble is a higher effective climate sensitivity with an increased range between 2.3 and 5.6 K. A possible reason for this increase in some models is improvements in cloud representation resulting in stronger shortwave cloud feedbacks than in their predecessor versions.

Bock, L.↗

Examining the Robustness of Weakened Orographic Influence on Precipitation in Downscaled Climate Projections Over the Western US

Assessing local climate change impacts often requires downscaling coarse global climate model (GCM) output to finer resolution. Two main approaches exist: dynamical downscaling using high-resolution regional climate models, and statistical downscaling based on historical relationships between large-scale and local variables. In a recent analysis of five dynamically downscaled simulations over the western United States, Koszuta et al. (2024, https://doi.org/10.1029/2023gl107298) found that warming weakens orographic influence on winter precipitation, damping increases on windward slopes and amplifying them in rain-shadowed regions. Here we show that this effect is robust across seasons and multiple dynamically downscaled ensembles, and is more pronounced at higher model resolutions. However, it is absent in projections from a widely used statistical model (LOCA2), even when trained on high-resolution future simulations (LOCA2-Hybrid). This highlights a key limitation of many statistical downscaling methods: their preservation of parent GCM trends, which usually fail to capture emergent changes in orographic precipitation patterns.

54 ENVIRONMENTAL SCIENCES↗

Finite momentum Cooper pairing in three-dimensional topological insulator Josephson junctions

Abstract Unconventional superconductivity arising from the interplay between strong spin–orbit coupling and magnetism is an intensive area of research. One form of unconventional superconductivity arises when Cooper pairs subjected to a magnetic exchange coupling acquire a finite momentum. Here, we report on a signature of finite momentum Cooper pairing in the three-dimensional topological insulator Bi 2 Se 3 . We apply in-plane and out-of-plane magnetic fields to proximity-coupled Bi 2 Se 3 and find that the in-plane field creates a spatially oscillating superconducting order parameter in the junction as evidenced by the emergence of an anomalous Fraunhofer pattern. We describe how the anomalous Fraunhofer patterns evolve for different device parameters, and we use this to understand the microscopic origin of the oscillating order parameter. The agreement between the experimental data and simulations shows that the finite momentum pairing originates from the coexistence of the Zeeman effect and Aharonov–Bohm flux.

36 MATERIALS SCIENCE↗

Materializing rival ground states in the barlowite family of kagome magnets: quantum spin liquid, spin ordered, and valence bond crystal states

The spin- 1 2 kagome antiferromagnet is considered an ideal host for a quantum spin liquid ground state. We find that when the bonds of the kagome lattice are modulated with a periodic pattern, new quantum ground states emerge. Newly synthesized crystalline barlowite (Cu 4 (OH) 6 FBr) and Zn-substituted barlowite demonstrate the delicate interplay between singlet states and spin order on the spin- 1 2 kagome lattice. Comprehensive structural measurements demonstrate that our new variant of barlowite maintains hexagonal symmetry at low temperatures with an arrangement of distorted and undistorted kagome triangles, for which numerical simulations predict a pinwheel va- lence bond crystal (VBC) state instead of a quantum spin liquid (QSL). The presence of interlayer spins eventually leads to an interesting pinwheel q=0 magnetic order. Partially Zn-substituted bar- lowite (Cu 3.44 Zn 0.56 (OH) 6 FBr) has an ideal kagome lattice and shows QSL behavior, indicating a surprising robustness of the QSL against interlayer impurities. The magnetic susceptibility is simi- lar to that of herbertsmithite, even though the Cu 2+ impurities are above the percolation threshold for the interlayer lattice and they couple more strongly to the nearest kagome moment. This system is a unique playground displaying QSL, VBC, and spin order, furthering our understanding of these highly competitive quantum states.

36 MATERIALS SCIENCE↗

New insights on the propagation of pulsed atmospheric plasma streams: From single jet to multi jet arrays

Atmospheric pressure plasma propagation inside long dielectric tubes is analyzed for the first time through nonintrusive and nonperturbative time resolved bi-directional electric field (EF) measurements. This study unveils that plasma propagation occurs in a region where longitudinal EF exists ahead the ionization front position usually revealed from plasma emission with ICCD measurement. The ionization front propagation induces the sudden rise of a radial EF component. Both of these EF components have an amplitude of several kV/cm for helium or neon plasmas and are preserved almost constant along a few tens of cm inside a capillary. All these experimental measurements are in excellent agreement with previous model calculations. The key roles of the voltage pulse polarity and of the target nature on the helium flow patterns when plasma jet is emerging in ambient air are documented from Schlieren visualization. The second part of this work is then dedicated to the development of multi jet systems, using two different setups, based on a single plasma source. Plasma splitting in dielectric tubes drilled with sub millimetric orifices, but also plasma transfer across metallic tubes equipped with such orifices are reported and analyzed from ICCD imaging and time resolved EF measurements. This allows for the design and the feasibility validation of plasma jet arrays but also emphasizes the necessity to account for voltage pulse polarity, target potential status, consecutive helium flow modulation, and electrostatic influence between the produced secondary jets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Magnetic properties and pairing tendencies of the iron-based superconducting ladder BaFe 2 S 3 : Combined ab initio and density matrix renormalization group study

The recent discovery of superconductivity under high pressure in the two-leg ladder compound BaFe 2 S 3 [H. Takahashi et al., Nat. Mater. 14, 1008 (2015)] opens a broad avenue of research, because it represents the first report of pairing tendencies in a quasi-one-dimensional iron-based high-critical-temperature superconductor. Similarly, as in the case of the cuprates, ladders and chains can be far more accurately studied using many-body techniques and model Hamiltonians than their layered counterparts, particularly if several orbitals are active. In this publication, we derive a two-orbital Hubbard model from first principles that describes individual ladders of BaFe 2 S 3 . The model is studied with the density matrix renormalization group. These first reported results are exciting for two reasons: (i) at half-filling, ferromagnetic order emerges as the dominant magnetic pattern along the rungs of the ladder, and antiferromagnetic order along the legs, in excellent agreement with neutron experiments; and (ii) with hole doping, pairs form in the strong coupling regime, as found by studying the binding energy of two holes doped on the half-filled system. In addition, orbital selective Mott phase characteristics develop with doping, with only oneWannier orbital receiving the hole carriers while the other remains half-filled. Lastly, these results suggest that the analysis of models for iron-based two-leg ladders could clarify the origin of pairing tendencies and other exotic properties of iron-based high-critical-temperature superconductors in general.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

In-beam γ-ray spectroscopy of 68 Fe from charge exchange on 68 Co projectiles

Excited states in the neutron-rich nucleus 68 Fe were populated using a 9 Be( 68 Co, 68 Fe + γ)X charge-exchange reaction at 95 MeV/u. The new γ-ray transitions reported here for the first time complement data from β-decay studies and nucleon knockout reactions. In comparison to shell-model calculations with the LNPS effective interaction, two candidate states for the $6$$^{+}_{1}$ level emerge. Here, the distinct population pattern of excited states and the magnitude of the cross section, σ inc = 0.51(6) mb, make this reaction a promising one for future in-beam γ -ray spectroscopy. Reaction calculations with nuclear structure input from a new, locally optimized Hamiltonian, f7j4a, together with general considerations for heavy-ion-induced charge-exchange reactions appear consistent with most of the observations, although challenges remain.

59 ≤ A ≤ 89↗

An overview of the gene regulatory network controlling trichome development in the model plant, Arabidopsis

Trichomes are specialized epidermal cells located on aerial parts of plants and are associated with a wide array of biological processes. Trichomes protect plants from adverse conditions including UV light and herbivore attack and are also an important source of a number of phytochemicals. The simple unicellular trichomes of Arabidopsis serve as an excellent model to study molecular mechanism of cell differentiation and pattern formation in plants. The emerging picture suggests that the developmental process is controlled by a transcriptional network involving three major groups of transcription factors (TFs): the R2R3 MYB, basic helix-loop-helix (bHLH), and WD40 repeat (WDR) protein. These regulatory proteins form a trimeric activator complex that positively regulates trichome development. The single repeat R3 MYBs act as negative regulators of trichome development. They compete with the R2R3 MYBs to bind the bHLH factor and form a repressor complex. In addition to activator–repressor mechanism, a depletion mechanism may operate in parallel during trichome development. In this mechanism, the bHLH factor traps the WDR protein which results in depletion of WDR protein in neighboring cells. Consequently, the cells with high levels of bHLH and WDR proteins are developed into trichomes. A group of C2H2 zinc finger TFs has also been implicated in trichome development. Phytohormones, including gibberellins and jasmonic acid, play significant roles in this developmental process. Recently, microRNAs have been shown to be involved in trichome development. Furthermore, it has been demonstrated that the activities of the key regulatory proteins involved in trichome development are controlled by the 26S/ubiquitin proteasome system (UPS), highlighting the complexity of the regulatory network controlling this developmental process. To complement several excellent recent relevant reviews, this review focuses on the transcriptional network and hormonal interplay controlling trichome development in Arabidopsis.

59 BASIC BIOLOGICAL SCIENCES↗

Infrared spectra of rotating protostars

Earlier calculations of the infrared emission expected from stars in the process of being made are corrected to include the most important observable effects of rotation and generalized. An improved version of the spherical model of a previous paper is developed, and the corresponding emergent spectral energy distributions are calculated for the theoretically expected mass infall rate in the cores of cool and quiescent molecular clouds. The dust grain opacity model and the temperature profile parameterization are improved. It is shown that the infrared spectrum of the IRAS source 04264+2426, which is associated with a Herbig-Haro object, can be adequately represented in terms of a rotating and accreting protostar. This strengthens the suggestion that collimated outflows in young stellar objects originate when a stellar wind tries to emerge and reverse the swirling pattern of infall which gave birth to the central star.

Adams, F. C.↗