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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 217 records · Page 12

Research to Confront Climate Change Complexity: Intersectionality, Integration, and Innovative Governance

Abstract Climate impacts increasingly unfold in interlinked systems of people, nature, and infrastructure. The cascading consequences are revealing sometimes surprising connections across sectors and regions, and prospects for climate responses also depend on complex, difficult‐to‐understand interactions. In this commentary, we build on the innovations of the United States Fifth National Climate Assessment to suggest a framework for understanding and responding to complex climate challenges. This approach involves: (a) integration of disciplines and expertise to understand how intersectionality shapes complex climate impacts and the wide‐ranging effects of climate responses, (b) collaborations among diverse knowledge holders to improve responses and better encompass intersectionality, and (c) sustained experimentation with and learning about governance approaches capable of handling the complexity of climate change. Together, these three pillars underscore that usability of climate‐relevant knowledge requires transdisciplinary coordination of research and practice. We outline actionable steps for climate research to incorporate intersectionality, integration, and innovative governance, as is increasingly necessary for confronting climate complexity and sustaining equitable, ideally vibrant climate futures.

54 ENVIRONMENTAL SCIENCES↗

Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics

In inland water covering lakes, reservoirs, and ponds, the gas exchange of slightly soluble gases such as carbon dioxide, dimethyl sulfide, methane, or oxygen across a clean and nearly flat air‐water interface is routinely described using a water‐side mean gas transfer velocity $\overline{k_{L}}$, where overline indicates time or ensemble averaging. The micro‐eddy surface renewal model predicts $\overline{k_{L}}$ = α o Sc -1/2 ($v\bar{ϵ}$) 1/4 , where Sc is the molecular Schmidt number, $v$ is the water kinematic viscosity, and $\bar{ϵ}$ is the waterside mean turbulent kinetic energy dissipation rate at or near the interface. While α o = 0.39 - 0.46 has been reported across a number of data sets, others report large scatter or variability around this value range. It is shown here that this scatter can be partly explained by high temporal variability in instantaneous ϵ around $\bar{ϵ}$, a mechanism that was not previously considered. As the coefficient of variation (CV e ) in ϵ increases, α o must be adjusted by a multiplier (1 = CV e 2 ) -3/32 that was derived from a log‐normal model for the probability density function of ϵ. Reported variations in α o with a macro‐scale Reynolds number can also be partly attributed to intermittency effects in ϵ. Such intermittency is characterized by the long‐range (i.e., power‐law decay) spatial auto‐correlation function of ϵ. That α o varies with a macro‐scale Reynolds number does not necessarily violate the micro‐eddy model. Instead, it points to a coordination between the macro‐ and micro‐scales arising from the transfer of energy across scales in the energy cascade.

Batchelor scale↗

A Novel Emergent Constraint Approach for Refining Regional Climate Model Projections of Peak Flow Timing

Abstract Global climate models (GCMs) are unable to produce detailed runoff conditions at the basin scale. Assumptions are commonly made that dynamical downscaling can resolve this issue. However, given the large magnitude of the biases in downscaled GCMs, it is unclear whether such projections are credible. Here, we use an ensemble of dynamically downscaled GCMs to evaluate this question in the Sierra‐Cascade mountain range of the western US. Future projections across this region are characterized by earlier seasonal shifts in peak flow, but with substantial inter‐model uncertainty (−25 ± 34.75 days, 95% confidence interval (CI)). We apply the emergent constraint (EC) method for the first time to dynamically downscaled projections, leading to a 39% (−28.25 ± 20.75 days, 95% CI) uncertainty reduction in future peak flow timing. While the constrained results can differ from bias corrected projections, the EC is based on GCM biases in historical peak flow timing and has a strong physical underpinning.

54 ENVIRONMENTAL SCIENCES↗

Investigation of the Sensitivity of Tropical Cyclogenesis to Aerosol Intervention

Abstract As risks from tropical cyclones (TCs) are fueled by climate change escalation, there is an urgent need for transformational solutions to complement traditional approaches. Seeding TCs using aerosols can be a promising method to reduce cyclone intensity, supported by theoretical understanding of the microphysical effects of aerosols on TC clouds. The ideal time to intervene effectively in TCs is likely during their initial stage, before TC wind speeds reach their peak. However, studies exploring potential aerosol effects on TC formation remain scarce. This study investigates how a TC embryo responds to the addition of aerosols of varying sizes using the Weather Research & Forecasting (WRF) model coupled with a spectral‐bin microphysics model. We found that aerosols of different sizes and concentrations distinctively affect the pre‐TC vortex's microstructure and dynamics. Fine and ultrafine aerosols enhance the latent heat of condensation, freezing, deposition, and riming, initially intensifying the vortex. However, this results in enhancement of the cold pool, thereby reducing inflow and surface fluxes, subsequently weakening the vortex. Coarse aerosols produce the opposite effect to that of fine and ultrafine aerosols. Coarse aerosols lead to a slower initial acceleration owing to enhanced warm rain. However, the resulting weaker cold pool is insufficient to effectively reduce the strength of the vortex at the later stage. This study provides critical insights into how aerosols of varying sizes and concentrations modulate the energy cascade and impact the evolution of a TC embryo, laying the groundwork for further research on TC risk management through aerosol intervention.

54 ENVIRONMENTAL SCIENCES↗

Why Firn Quakes

Snow dampens sounds, but anecdotal reports concisely describe audible propagating collapse events—firnquakes—in Antarctic and Arctic snowfields. We propose combining granular and continuum mechanics to form a testable theory for conditioning, triggering, and propagation of firnquakes consistent with scarce data. A central condition for collapse events is unconsolidated firn at depth. As firn grains compact, stresses are transmitted along force chains which carry the overburden and transition into a continuous medium by pressure sintering. This granular legacy creates solid-like supports of denser layers that keep the material below unconsolidated. Dynamic amplification triggers local brittle failure of the supports, which induces a cascade of collapse propagation. Using bulk density from ice cores as proxy for stiffness, we find the flexural wave speed by collapsing supports matches the recorded firnquake velocities on the order of 100 m/s. Our theory is to be tested in firn sheets and other compacting granular materials.

Voigtländer, A. [Lawrence Berkeley National Labora↗

Nonlinear encoding in diffractive information processing using linear optical materials

Nonlinear encoding of optical information can be achieved using various forms of data representation. Here, we analyze the performances of different nonlinear information encoding strategies that can be employed in diffractive optical processors based on linear materials and shed light on their utility and performance gaps compared to the state-of-the-art digital deep neural networks. For a comprehensive evaluation, we used different datasets to compare the statistical inference performance of simpler-to-implement nonlinear encoding strategies that involve, e.g., phase encoding, against data repetition-based nonlinear encoding strategies. We show that data repetition within a diffractive volume (e.g., through an optical cavity or cascaded introduction of the input data) causes the loss of the universal linear transformation capability of a diffractive optical processor. Therefore, data repetition-based diffractive blocks cannot provide optical analogs to fully connected or convolutional layers commonly employed in digital neural networks. However, they can still be effectively trained for specific inference tasks and achieve enhanced accuracy, benefiting from the nonlinear encoding of the input information. Our results also reveal that phase encoding of input information without data repetition provides a simpler nonlinear encoding strategy with comparable statistical inference accuracy to data repetition-based diffractive processors. Our analyses and conclusions would be of broad interest to explore the push-pull relationship between linear material-based diffractive optical systems and nonlinear encoding strategies in visual information processors.

42 ENGINEERING↗

Tunable superconductivity coexisting with the anomalous Hall effect in a transition metal dichalcogenide

Transition metal dichalcogenides display a high technological potential due to their wide range of electronic ground states. Here, we unveil that by tuning hydrostatic pressure P, a cascade of electronic phase transitions can be induced in the few-layer transition metal dichalcogenide 1 T ’-WS 2 . As P increases, we observe the suppression of superconductivity with the concomitant emergence of an anomalous Hall effect (AHE) at P ≈ 1.15 GPa. Above 1.6 GPa, we uncover a reentrant superconducting state emerging from a state still exhibiting AHE. This superconducting state competes with the AHE state and shows a marked increase in superconducting anisotropy with respect to the ambient pressure phase, suggesting a distinct pairing symmetry. We demonstrate that 1 T ’-WS 2 concomitantly transitions into a strong topological phase with different band orbital characters and Fermi surfaces contributing to the superconductivity. These findings position 1T’-WS 2 as a tunable superconductor, wherein superconductivity, AHE, and band features can be tuned reversibly.

Superconducting properties and materials↗

How extreme rainfall and failing dams unleashed the Derna flood disaster

On September 11, 2023, Storm Daniel unleashed unprecedented rainfall over the Wadi Derna watershed, triggering one of the most devastating floods in modern history, striking Derna, a coastal city in Libya. This study reconstructs the disaster using an integrated modeling approach that combines satellite imagery, hydrologic, hydraulic, and geotechnical simulations, machine learning, eyewitness accounts, and digital elevation data to assess the impact of cascading dam failures. Our findings reveal that the region’s dams, even if structurally sound, would have provided minimal protection against the extreme runoff. However, their failure unleashed a destructive surge wave, amplifying the disaster’s magnitude and devastation. Here, we show that the collapse of aging flood control infrastructures, compounded by inadequate risk assessment and emergency preparedness, dramatically escalated the disaster’s impact. Our findings underscore the urgent need for systematic dam safety evaluations, enhanced flood forecasting, and adaptive risk management strategies that address climate extremes and infrastructure vulnerabilities.

Hydrology↗

Sub-10 nm upconversion nanocrystals for long-term single-particle tracking

Lanthanide-doped upconversion nanoparticles are attractive single-molecule imaging probes due to their high photostability and anti-Stokes luminescence. However, achieving both small particle size and strong brightness has remained a major challenge, as reducing size often leads to dimmer emission. Herein, we fabricate a sub-10 nm cascade actively protected upconversion nanoparticles, which shows a 33-fold enhanced upconversion efficiency at the single-particle level compared to larger ~19 nm conventional nanoparticles. Theoretical modeling and time-resolved measurements show that emission loss mainly comes from energy leakage of Er 3+ ions to surface defects. By introducing a NaYbF 4 layer as photon-harvesting and protective intermediate layer, we minimize this energy loss and significantly boost brightness. A monolayer of inert NaLuF 4 can effectively suppress the surface quenching to Yb 3+ . Using these ultra-small bright probes, we successfully tracked single epidermal growth factor receptor molecules on live cells for up to one hour, revealing dynamic switching between different diffusion modes.

Qiu, Xiaochen [Fudan Univ., Shanghai (China); Shen↗

Acid-base bifunctional porous liquids

Basic solutions are essential for gas-involved catalytic transformations, yet their ultralow free volume limits gas solubility and diffusivity. Engineering permanent porosity in such reactive liquids has remained a longstanding challenge. Here, we introduce a surface-sacrifice strategy that incorporates Brønsted-acidic zeolite nanocrystals into strong organic bases to create permanently porous reactive liquids. Stereochemically controlled acid–base neutralization at the external zeolite surface forms a thin ionic solvation shell that stabilizes the dispersion while fully preserving the internal microporosity and crystallinity of the zeolite framework. The resulting basic media exhibit persistent microporosity, confirmed by inert-gas sorption, 129Xe nuclear magnetic resonance, neutron scattering, and theoretical simulations. These porous liquids show significantly enhanced catalytic performance in CO2 conversion and hydrogenation reactions. The coexisting acidic and basic sites further enable antagonistic cascade catalysis within a single liquid phase. This surface-sacrifice approach provides a general route to introduce permanent porosity into reactive media, enabling boosted gas transformations.

Qiu, Liqi [University of Tennessee, Knoxville (UTK↗

Molecular dynamics study of grain boundaries as defect sinks under irradiation in LiAlO 2 and LiAl 5 O 8

Lithium aluminate ceramics, LiAlO 2 and LiAl 5 O 8 , show promise in nuclear environments due to their excellent radiation tolerance. Molecular dynamics simulations investigate grain boundaries (GB) and their role in defect evolution. Results reveal that GBs act as efficient defect sinks, with Li and Al atoms exhibiting distinct behaviors during displacement cascades. Tritium migration in LiAlO 2 is also studied, showing rapid diffusion and stable configurations with oxygen, corroborated by ab initio simulations from the literature. The calculated tritium diffusion coefficient of 1.33 × 10 - ¹⁴ m²/s aligns with the literature, validating the model. LiAl 5 O 8 demonstrates superior defect healing compared to LiAlO 2 , attributed to enhanced atomic transfer between grains and GBs. These findings reveal key insights into defect dynamics, providing essential insights for their application in tritium-producing burnable absorber rods (TPBARs).

36 MATERIALS SCIENCE↗

Grain Boundary Effects on Radiation Damage and Tritium Diffusion in Li–Al–O Ceramics from Molecular Dynamics and Experiments

Understanding irradiation damage and tritium transport in LiAlO2 ceramics is essential for their deployment in tritium-producing burnable absorber rods (TPBARs). Grain boundaries (GBs) play an important role in governing radiation response and tritium transport in LiAlO2 and its secondary phase LiAl5O8. Using molecular dynamics simulations, we investigated defect evolution and tritium diffusion during displacement cascades in single-crystal and bicrystal LiAlO2 and LiAl5O8 at 600 K. The results reveal that GBs suppress the damage in the LiAlO2 bicrystals as compared to single crystals, via interstitial emission. The effect is more pronounced for Li defects, than for Al and O. In LiAl5O8 the damage reduction due to introduction of GB is less pronounced overall. Tritium diffusion coefficients at GBs are higher by factors of 2–10 relative to diffusion inside grain bulk. The effect is particularly pronounced in LiAlO2, where S5, S17, and S25 GBs promote rapid tritium transport, whereas LiAl5O8 exhibits slower diffusion due to reduced free volume at its GBs. These findings evince a trade-off that while GBs mitigate radiation damage by absorbing interstitials, they simultaneously provide fast pathways for tritium migration which is not desirable for TPBAR application. The mechanistic insights gained here establish a foundation for microstructural design strategies to balance radiation tolerance and tritium retention in ceramic breeder materials.

Roy, Ankit↗

Frieze charge-stripes in a correlated kagome superconductor

In kagome metals, geometric frustration, electronic correlations and band topology combine to produce a wide range of intriguing phenomena. Among them, CsCr$_3$Sb$_5$ offers an opportunity to investigate unconventional superconductivity in a strongly correlated kagome system, with indications of frustrated magnetism and quantum criticality. Here, we demonstrate a cascade of density-wave transitions with distinct symmetries in bulk single crystals of CsCr$_3$Sb$_5$. Using spectroscopic imaging scanning tunneling microscopy, we uncover a unidirectional density wave that breaks all mirror symmetries -- resembling a chiral density wave -- but that also retains a mirror glide symmetry. We refer to this as a frieze charge stripe order phase, as its symmetry properties correspond to one of the fundamental frieze symmetry groups. A combination of high-resolution imaging, Fourier analysis and theoretical simulations reveal the key role of sublattice degrees of freedom in stabilizing this phase, characterized by internal chiral textures of opposite handedness. These findings suggest that superconductivity in CsCr$_3$Sb$_5$ emerges from this distinct density wave state and provide fresh insight into realizing electronic phases governed by frieze symmetry groups in quantum materials.

Cheng, Siyu [Boston College, Chestnut Hill, MA (Un↗

Genomes of multicellular algal sisters to land plants illuminate signaling network evolution

Zygnematophyceae are the algal sisters of land plants. Here we sequenced four genomes of filamentous Zygnematophyceae, including chromosome-scale assemblies for three strains of Zygnema circumcarinatum . We inferred traits in the ancestor of Zygnematophyceae and land plants that might have ushered in the conquest of land by plants: expanded genes for signaling cascades, environmental response, and multicellular growth. Zygnematophyceae and land plants share all the major enzymes for cell wall synthesis and remodifications, and gene gains shaped this toolkit. Co-expression network analyses uncover gene cohorts that unite environmental signaling with multicellular developmental programs. Our data shed light on a molecular chassis that balances environmental response and growth modulation across more than 600 million years of streptophyte evolution.

59 BASIC BIOLOGICAL SCIENCES↗

De novo design of proteins housing excitonically coupled chlorophyll special pairs

Natural photosystems couple light harvesting to charge separation using a ‘special pair’ of chlorophyll molecules that accepts excitation energy from the antenna and initiates an electron-transfer cascade. To investigate the photophysics of special pairs independently of the complexities of native photosynthetic proteins, and as a first step toward creating synthetic photosystems for new energy conversion technologies, we designed C 2 -symmetric proteins that hold two chlorophyll molecules in closely juxtaposed arrangements. X-ray crystallography confirmed that one designed protein binds two chlorophylls in the same orientation as native special pairs, whereas a second designed protein positions them in a previously unseen geometry. Spectroscopy revealed that the chlorophylls are excitonically coupled, and fluorescence lifetime imaging demonstrated energy transfer. The cryo-electron microscopy structure of a designed 24-chlorophyll octahedral nanocage with a special pair on each edge closely matched the design model. The results suggest that the de novo design of artificial photosynthetic systems is within reach of current computational methods.

59 BASIC BIOLOGICAL SCIENCES↗

Challenges and Opportunities in the Enzymatic Recycling of Nylons

Enzymatic depolymerization has the potential to contribute to nylon waste recycling. However, the implementation of a viable industrial process still lags far behind progress in enzymatic polyester recycling. Here we review the current biocatalytic nylon recycling landscape, highlighting biochemical, structural, and materials science barriers that currently limit depolymerization extents. We detail efforts to identify, engineer, and characterize new nylon depolymerases, where currently even the best biocatalysts rarely exceed ~1 wt% conversion of solid polymer to products. Based on our analyses, we suggest that limited substrate accessibility due to substrate crystallinity and hydrogen bonding, rather than intrinsic enzyme inefficiency or instability, is the primary bottleneck to enhanced depolymerization. Guided by successes in polyester enzymatic recycling, we outline a research roadmap combining nylonase engineering with polymer pretreatment, chemo-enzymatic cascades, and process analyses to accelerate development of viable enzymatic nylon recycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unified 0.25-degree gridded infrastructure-critical extreme weather for the United States from 1979 to 2100

Extreme weather events can severely disrupt critical infrastructure, triggering cascading effects on power, transportation, and essential services. However, standard weather and climate datasets often lack specialized variables necessary for hazard assessments. We present a unified dataset of infrastructure-critical weather and climate variables across the United States at 0.25° resolution, covering daily or sub-daily intervals from 1979 to 2100. The dataset includes temperature, dew point, wind gusts, precipitation partitioned by rain, snow, and freezing rain or ice pellets, lightning, and wildfire metrics. Historical conditions (1979-2023) are synthesized from observations and reanalysis products, while future projections are derived from 14 CMIP6 global climate models (historical, SSP245, and SSP585 experiments). Physically based and data-driven methods are used to estimate variables not directly provided by existing models. By integrating these variables into a single unified dataset, we enable consistent, high-resolution assessments of weather-related infrastructure risks across past and future periods, supporting wide-ranging applications in energy, transportation, water resources, emergency management, and beyond.

Climate and Earth system modelling↗

Uncertainty of 21st Century western U.S. snowfall loss derived from regional climate model large ensemble

Abstract The western United States is dependent on winter snowfall over its major mountain ranges, which gradually melts each year, serving as a natural reservoir for water resources. In a future warmer climate, much of this snowfall could be replaced by rain, making it more challenging to capture and store water. In this study, we utilize an ensemble of dynamically downscaled simulations forced by 14 global climate models (GCMs). These GCMs project wildly different futures, in terms of both temperature and precipitation change, producing significant uncertainty in snowfall projections. Here we exploit the robust statistics of the downscaled ensemble, and diagose the sensitivity of end-of-century snowfall loss across the region to both warming and regional wetting/drying in the driving GCM. The windward slopes of the Sierra Nevada and Cascades are particularly sensitive to warming (losing ~ 15% annual snowfall per degree warming), with little influence of precipitation. By contrast, snowfall loss in the inter-mountain west is less sensitive to warming (~ 5% K −1 ), but is significantly offset/exacerbated by precipitation changes (~ 0.5% snow per 1% precipitation). Combining such sensitivities with the warming and regional precipitation signals in the full CMIP6 ensemble, we can fully quantify likely snowfall loss and its uncertainty at any location, for any emissions scenario. We find that the western U.S. as a whole will lose 34 ± 8% of its total volumetric snowfall by end-of-century under the high-emissions SSP3-7.0 scenario, but 25 ± 6% and 17 ± 6% under the lower-emissions SSP2-4.5 and SSP1-2.6 scenarios.

Norris, Jesse (ORCID:0000000289883326)↗