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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18

Parametric and Robustness Studies of Qudit Mediated Quantum State Transfer and Entanglement Creation

The large number of available states participating in quantum state evolution in a system of qudits translates into better thermal resilience, for quantum state transfer (QST) and distributed entangled states, than a system of 2-level qubits. In this report we study the dependence of fidelities of the above processes on various system parameters. Sensitivity to modes of dissipation and errors is also studied. An alternative and potentially more efficient scheme to create Bell states is used.

Chao, Yu-Chiu [Fermilab] (ORCID:000900039584159X)↗

Robotic Assembly of SRF Cavity Pair

Superconducting Radio Frequency (SRF) cavities for particle accelerators require tight tolerances, ultrahigh vacuum, and strict cleanliness during assembly. As in the semiconductor industry, defects such as particles and residues are deleterious to performance, possibly rendering a cavity unfit for use. This problem is addressed primarily through cleanroom assembly during sensitive steps and rigorous chemical processing to prevent and remove such defects. Human workers are often the largest source of contamination, even with proper gowning and practices. The semiconductor industry has long integrated robots in cleanroom operation, but this has not occurred for SRF cavity production; SRF cavities, unlike wafers, are complex shapes, require more hands-on mechanical assembly, and are low-volume production items. At Jefferson Laboratory, a co-operative robot (cobot) has been setup to overcome these problems. Cobots are safe for use alongside human workers and can integrate new tools such as a 3D camera part detection and gripper for item manipulation. Therefore, cobots represent a promising avenue for reducing particulate generated during a variety of assembly tasks. A mockup of a cavity pair and coupler was setup and the cobot programmed to automatically pick up the coupler and place on the mating cavity flange. Particle counting methods were setup to measure human vs cobot assembly particulate generation inside a cavity mockup. Other potential uses will be discussed for further improving SRF cavity assembly steps, where a cobot can replace or assist a human operator, and what potential gains are expected.

Duzik, Adam [Thomas Jefferson National Accelerator↗

Energy Transfer in Lanthanide Luminescent Complexes

The primary objective of this project was to investigate the mechanisms of energy transfer in lanthanide luminescent complexes, focusing on elucidating the role of ligand-to-metal charge transfer processes and the efficiency of sensitization mechanisms. Specifically, this work aimed to determine the mechanistic details of energy transfer pathways in systems incorporating lanthanide ions such as terbium and europium, with a focus on advancing the application of these complexes in molecular imaging and photonic technologies.

Raymond, Kenneth [University of California, Berkel↗

Extreme Heating of Minor Ions in Imbalanced Solar-wind Turbulence

Minor ions in the solar corona are heated to extreme temperatures, far in excess of those of the electrons and protons that comprise the bulk of the plasma. These highly nonthermal distributions make minor ions sensitive probes of the collisionless processes that heat the corona and power the solar wind. The recent discovery of the "helicity barrier" offers a mechanism in which imbalanced Alfvénic turbulence in low-β plasmas preferentially heats protons over electrons, generating high-frequency, proton-cyclotron-resonant fluctuations. We use the hybrid-kinetic particle-in-cell code Pegasus++ to drive imbalanced Alfvénic turbulence in a 3D low-β plasma with additional passive ion species, He 2+ and O 5+ . A helicity barrier naturally develops, followed by clear phase-space signatures of oblique proton-cyclotron-wave heating and Landau-resonant heating from the imbalanced Alfvénic fluctuations. The former results in characteristically arced ion velocity distribution functions, whose non-bi-Maxwellian features are shown by linear ALPS calculations to be critical to the heating process. Additional features include a steep transition-range electromagnetic spectrum, proton-cyclotron waves propagating in the direction of the imbalance, significantly enhanced proton-to-electron heating ratios, ion temperatures that are considerably more perpendicular with respect to magnetic field, and extreme heating of heavier species in a manner consistent with mass scalings inferred from spacecraft measurements. None of these features are realized in an otherwise equivalent simulation of balanced turbulence. If seen simultaneously in the fast solar wind, these signatures of the helicity barrier would testify to the necessity of incorporating turbulence imbalance in a complete theory for the evolution of the solar wind.

79 ASTRONOMY AND ASTROPHYSICS↗

Acidification in the Southern Ocean – current state and future challenges

The Southern Ocean is especially sensitive to ocean acidification, a process where carbon dioxide in the atmosphere is absorbed by the ocean, thereby changing its acidity levels. Observations show that open ocean waters across the Southern Ocean experienced faster rates of acidification over the past four decades than non-polar waters. Model simulations project more severe ocean acidification in Antarctic coastal waters than in the open ocean. Ocean acidification negatively impacts many Southern Ocean species, but our understanding of whole-ecosystem impacts is incomplete. Furthermore, it is important that we both maintain and expand observational capabilities and mechanistic experiments in this rapidly changing and vulnerable region of the ocean to understand the impacts of ocean acidification on Southern Ocean ecosystems.

Nissen, Cara [University of Amsterdam (The Netherl↗

DEVELOPMENT OF INEXPENSIVE HIGH TEMPERATURE NITI-BASED SHAPE MEMORY ALLOYS FOR POWDER BED ADDITIVE MANUFACTURING

NiTi and NiTi-based Shape Memory Alloys (SMA) exhibit a reversible solid-state phase transformation from martensite to austenite driven by thermal energy. High temperature (Mf>100°C) SMAs are martensite at room temperature and can be fabricated into solid-state actuators that return to a pre-programmed shape against a designed load after heating to transformation threshold. Reactive as-fabricated additively manufactured parts (4-D printing) is the current state of the art in manufacturing of SMAs but requires compositions compliant to rapid solidification. Existing actuator designs are developed from commercially available, highly investigated material compositions. However, existing high temperature high performance (high actuation strain, low thermal hysteresis) shape memory alloys contain significant (>10% at.) portions of high-cost Platinum Group Metals (PGMs). It is of significant scientific interest to investigate material compositions that are peer performing or superior to PGMs whose constituent elements represent a significant cost savings. Shape memory alloy properties vary significantly with small (0.1% at.) compositional changes making robust investigative sample sets very large. Computational material design can be deployed to shrink the compositional space of possible alloy combinations and reduce the experimental load in material discovery. Investigating shape memory effect (SME) and validating process additive process parameters for a single novel composition is cost intensive in both time and consumed materials. Additionally, sub-optimal processing, oxygen, or solidification rate sensitivity could render additively manufacturing specimens without micro, macro cracks, or significant chemical variance impossible. Unfortunately, such failure susceptibility cannot be simulated. Therefore, a research pathway to validate novel shape memory alloy compositions for powder bed fusion additive manufacturing without the need for powdered feedstock is also proposed. This research investigates novel high temperature shape memory alloys for actuators without platinum group alloying elements to discover one that could be commercially viable as an additive manufacturing feedstock.

Sundermann, Tayler↗

Improved Single-Cell Proteome Coverage Using Narrow-Bore Packed NanoLC Columns and Ultrasensitive Mass Spectrometry

Single-cell proteomics can provide unique insights into biological processes by resolving heterogeneity that is obscured by bulk measurements. Gains in the overall sensitivity and proteome coverage through improvements in sample processing and analysis increase the information content obtained from each cell, particularly for less abundant proteins. Here we report on improved single-cell proteome coverage through the combination of the previously developed Nanodroplet Processing in One Pot for Trace Samples (nanoPOTS) platform with further miniaturization of liquid chromatography (LC) separations and implementation of an ultrasensitive latest-generation mass spectrometry (MS) instrument. Following nanoPOTS sample preparation, protein digest from single cells were separated using a 20-µm-i.d. in-house-packed nanoLC column. Separated peptides were ionized using an etched fused silica emitter capable of stable ionization at the ~20 nL/min flow rate provided by the LC separation. Ultrasensitive LC-MS analysis was achieved using the Orbitrap Eclipse Tribrid mass spectrometer. An average of 362 protein groups were identified by MS/MS from single HeLa cells, and 874 protein groups were identified using the Match Between Runs (MBR) feature of MaxQuant. This represents a >70% increase in label-free proteome coverage for single cells relative to previous efforts using larger-bore (30-µm-i.d.) LC columns coupled to a previous-generation MS (Orbitrap Fusion Lumos).

Cong, Yongzheng↗

Fabrication of bulk alumina structures with humidity sensing capabilities using direct ink write technique

Purpose The purpose of this study is to evaluate different 3D structures for humidity sensing that will enable the fabrication of complex geometries with high moisture sensitivity. Design/methodology/approach Humidity sensors based on alumina ceramics were fabricated using direct ink write (DIW) technique. Different engineered surface area, polymer binder ratio and post-processing treatment were considered to increase moisture sensitivity. Findings It was found that the binder ratio plays an important role in controlling the rheology of the paste during printing and determining the pore size after post-processing treatment. The sensibility of the fabricated humidity sensor was investigated by measuring its capacitance response toward relative humidity (RH) varying from 40% to 90% RH at 25°C. It is shown that using 3D lattice design, printed alumina humidity sensor could improve sensitivity up to 31.6 pF/RH%, over an order of magnitude higher than solid alumina. Originality/value Most of the alumina humidity sensors available are films in nature because of manufacturing difficulties, which limited its potential of higher sensitivity, and thus broader applications. In this paper, a novel 3D alumina humidity sensor was fabricated using DIW 3D printing technology.

Engineering↗

Photoelectrochemical NADH Regeneration is Highly Sensitive to the Nature of Electrode Surface

(Photo)electrochemistry enables the synthesis of high-value fine chemicals and highly selective activation of molecules that are difficult to prepare using conventional chemical methods. In this study, light-driven NADH (reduced nicotinamide adenine dinucleotide) regeneration is achieved using a molecular Rh(III) mediator on Si photoelectrodes. This process is observed to be highly sensitive to the surface nature of Si photoelectrodes, exhibiting an overpotential reduction up to 600 mV on Si nanowires (SiNWs) as compared to planar Si. The use of a molecular mediator and SiNWs enables 100% selectivity toward NADH synthesis within a broad potential window. The origin of the striking difference is identified as the multifaceted nature of SiNWs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An underestimated negative cloud feedback from cloud lifetime changes

As the atmosphere warms, part of the cloud population shifts from ice and mixed phase (“cold”) to liquid (“warm”) clouds. Because warm clouds are more reflective and longerlived, this phase change reduces the solar flux absorbed by Earth and constitutes a negative radiative feedback. This cooling feedback is weaker in CMIP6 than in CMIP5, contributing to greater greenhouse warming. While this change is often attributed to improvements in simulated cloud phase, another model bias persists: warm clouds precipitate too readily, potentially leading to underestimated negative lifetime feedbacks. In this work, we modify a climate model to better simulate warm rain probability and find it exhibits a cloud lifetime feedback nearly three times larger than the default model. This suggests model errors in cloud-precipitation processes may bias cloud feedbacks as much as CMIP5–CMIP6 climate sensitivity differences. Reliable climate model projections therefore require improved cloud process realism guided by process-oriented observations and observational constraints.

54 ENVIRONMENTAL SCIENCES↗

Data, figures, animations, and scripts associated with the manuscript "Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Carbon Cycling at the Coastal Terrestrial Aquatic Interface"

This package contains the data, figures, animations, and scripts used in "Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Carbon Cycling at the Coastal Terrestrial Aquatic Interface" (Li et al., 2023). This study examines the interactions between soil, vegetation and hydrologic conditions in coastal areas, with a focus on the Chesapeake Bay region. The researchers used a mechanistic model called ATS-PFLOTRAN to explore how these interactions affect exchange process in different regions and the carbon/nitrogen cycle across the terrestrial-aquatic interface (TAI). Simulation scenarios isolate the effects of control factors and reaction constants derived from laboratory experiments. The results show a carbon cycle "hot zone" in coastal wetlands and in the transition zone between wetlands and uplands. Transpiration enhances fluxes between the surface and subsurface domains and increases dissolved oxygen in TAI. The decomposition of leaf-derived organic carbon provides an additional source of carbon for aerobic respiration and denitrification in the TAI. Microbial activity plays a key role in controlling redox conditions and their variability. This modeling study improves the understanding of complex TAI interactions and facilitates the representation of coastal ecosystems in larger-scale Earth system models.Several files can be found from this data package.1. Readme,md: This file describe the Title, Target Journal, Target submission date, Co-author, Science Questions, Hypotheses, Key words, Key message, Model and Data, Repo Structure. The user can read this file first and then go to details.2. mesh.zip: This file contains the mesh file for simulation cases. 3. Figure.zip: This file contains figures used in the manuscript . 4. animation.zip: This file contains animations used in the manuscript . 5. Data.zip: This file contains all required input data, such as concentration and flow boundaries. Also, it contains the DEM and processes results on area fraction. 6. Simulation_setup_and_results.zip: This file contains setup of cases used in the manuscript . The result files are too large, if you need that data, please contact to the Author. 7. notebooks.zip: This file contains the Jupyter notebooks for performing sensitivity analysis and other pre-process and post-process analyses.

54 ENVIRONMENTAL SCIENCES↗

The Role of Deep Convection and Large-scale Circulation in Driving Model Spread in Low Cloud Feedback and Equilibrium Climate Sensitivity

This project aims to advance the understanding of the processes that drive the large uncertainties in climate change projections, use observations to constrain model physics and reduce the inter-model spread in equilibrium climate sensitivity (ECS). There are three major goals: 1) Characterize the representation of the physical pathways that link deep convection, large-scale circulation and low cloud feedback in CMIP6 model simulations and determine the relative contribution of each pathway to the CMIP6 model spread in low cloud feedback and ECS; 2) Use process-oriented diagnostics and multiple observations to evaluate CMIP6 model performance in capturing the observed cloud-circulation relation and deep convection characteristics including convective transition statistics and the bulk properties of mesoscale convective systems (MCSs). Error decomposition in CMIP6 models will be performed. 3) Conduct E3SM short-range hindcasts following the DOE Cloud-Associated Parameterizations Testbed (CAPT) protocol to pinpoint specific model parameters/processes that are crucial to the representation of deep convection, circulation, clouds and the pathways that connect them. We will modify convective parameters in E3SM and analyze the perturbed physics experiments (PPEs) to isolate model parameters that are critical to the uncertainty of ECS.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity Analysis in the Presence of Intrinsic Stochasticity for Discrete Fracture Network Simulations

Abstract Large‐scale discrete fracture network (DFN) simulators are standard fare for studies involving the sub‐surface transport of particles since direct observation of real world underground fracture networks is generally infeasible. While these simulators have successfully been used in several engineering applications, estimates of output quantities of interest (QoI) — such as breakthrough time of particles reaching the edge of the system — suffer from two distinct types of uncertainty. A run of a DFN simulator requires several parameters to be set that dictate the placement and size of fractures, the density of fractures, and the overall permeability of the system; uncertainty on the proper parameters will lead to uncertainty in the QoI, called epistemic uncertainty. Furthermore, since these input settings to DFN simulators control the stochastic processes which place fractures and govern flow, understanding how this randomness affects the QoI requires several runs of the simulator at distinct random seeds. The uncertainty in the QoI attributed to different realizations (i.e., different seeds) of the same random process (i.e., identical input parameters) leads to a second type of uncertainty, called aleatoric uncertainty. In this paper, we perform a Sensitivity Analysis, which directly attributes the uncertainty observed in the QoI to the epistemic uncertainty from each input parameter and to the aleatoric uncertainty. Beyond the specific takeaways on which input variables influence uncertainty in the QoI the most, a major contribution of this paper is the introduction of a statistically rigorous workflow for characterizing the uncertainty in DFN flow simulations that exhibit heteroskedasticity.

58 GEOSCIENCES↗

Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin

Abstract. Mountain hydrology is controlled by interacting processes extending from the atmosphere through the bedrock. Integrated process models (IPMs), one of the main tools needed to interpret observations and refine conceptual models of the mountainous water cycle, require meteorological forcing that simulates the atmospheric process to predict hydroclimate then subsequently impacts surface–subsurface hydrology. Complex terrain and extreme spatial heterogeneity in mountainous environments drive uncertainty in several key considerations in IPM configurations and require further quantification and sensitivity analyses. Here, we present an IPM using the Weather Research and Forecasting (WRF) model which forces an integrated hydrologic model, ParFlow-CLM, implemented over a domain centered over the East River watershed (ERW), located in the Upper Colorado River basin (UCRB). The ERW is a heavily instrumented 300 km2 region in the headwaters of the UCRB near Crested Butte, CO, with a growing atmosphere-through-bedrock observation network. Through a series of experiments in the water year 2019 (WY19), we use four meteorological forcings derived from commonly used reanalysis datasets, three subgrid-scale physics scheme configurations in WRF, and two terrain shading options within WRF to test the relative importance of these experimental design choices for key hydrometeorological metrics including precipitation and snowpack, as well as evapotranspiration, groundwater storage, and discharge simulated by the ParFlow-CLM. Our hypothesis is that uncertainty from synoptic-scale forcings produces a much larger spread in surface–subsurface hydrologic fields than subgrid-scale physics scheme choice. Results reveal that the WRF subgrid-scale physics configuration leads to larger spatiotemporal variance in simulated hydrometeorological conditions, whereas variance across meteorological forcing with common subgrid-scale physics configurations is more spatiotemporally constrained. Despite reasonably simulating precipitation, a delay in simulated discharge peak is due to a systematic cold bias across WRF simulations, suggesting the need for bias correction. Discharge shows greater variance in response to the WRF simulations across subgrid-scale physics schemes (26 %) rather than meteorological forcing (6 %). The topographic radiation option has minor effects on the watershed-average hydrometeorological processes but adds profound spatial heterogeneity to local energy budgets (±30 W m−2 in shortwave radiation and 1 K air temperature differences in late summer). This is the first presentation of sensitivity analyses that provide support to help guide the scientific community to develop observational constraints on atmosphere-through-bedrock processes and their interactions.

54 ENVIRONMENTAL SCIENCES↗

Measurements of the groomed and ungroomed jet angularities in pp collisions at $ \sqrt{s}$ = 5.02 TeV

The jet angularities are a class of jet substructure observables which characterize the angular and momentum distribution of particles within jets. These observables are sensitive to momentum scales ranging from perturbative hard scatterings to nonperturbative fragmentation into final-state hadrons. We report measurements of several groomed and ungroomed jet angularities in pp collisions at $\sqrt{s}$ = 5.02 TeV with the ALICE detector. Jets are reconstructed using charged particle tracks at midrapidity (|η| < 0.9). The anti-$k_T$ algorithm is used with jet resolution parameters R = 0.2 and R = 0.4 for several transverse momentum $p^{ch jet}_{T}$ intervals in the 20–100 GeV/c range. Using the jet grooming algorithm Soft Drop, the sensitivity to softer, wide-angle processes, as well as the underlying event, can be reduced in a way which is well-controlled in theoretical calculations. We report the ungroomed jet angularities, λ α , and groomed jet angularities, λ α,g , to investigate the interplay between perturbative and nonperturbative effects at low jet momenta. Various angular exponent parameters α = 1, 1.5, 2, and 3 are used to systematically vary the sensitivity of the observable to collinear and soft radiation. Results are compared to analytical predictions at next-to-leading-logarithmic accuracy, which provide a generally good description of the data in the perturbative regime but exhibit discrepancies in the nonperturbative regime. Moreover, these measurements serve as a baseline for future ones in heavy-ion collisions by providing new insight into the interplay between perturbative and nonperturbative effects in the angular and momentum substructure of jets. They supply crucial guidance on the selection of jet resolution parameter, jet transverse momentum, and angular scaling variable for jet quenching studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Comparative techno-economic analysis of synthetic renewable natural gas production via reactive CO 2 capture and conversion

Reactive CO 2 capture and conversion (RCC) is an emerging carbon management strategy that integrates CO 2 capture and conversion and avoids intermediate CO 2 purification. In this study, we design an RCC process to capture atmospheric CO 2 and react it with renewable hydrogen to produce synthetic renewable natural gas (SRNG), which serves as a carbon-neutral energy source and a chemical form of long-duration renewable energy storage. We assess the technological potential of RCC through process modeling, techno-economic, carbon footprint, and sensitivity analyses. Our findings demonstrate that RCC offers energy savings and comparable cost to separated capture and conversion processes. The cost is dominated by renewable hydrogen and material replacement cost. SRNG produced via RCC is competitive with existing low-carbon natural gas technologies and presents a promising low-cost option for long-duration energy storage. This work highlights the potential for deploying RCC technologies within a circular carbon economy and the scientific and technical challenges that must be overcome for material and technology developers.

03 NATURAL GAS↗

Microbial and Environmental Processes Shape the Link between Organic Matter Functional Traits and Composition

Dissolved organic matter (DOM) is a large and complex mixture of molecules that fuels biogeochemical reaction in virtually all ecosystems on Earth. However, the relative importance of deterministic and stochastic processes in structuring DOM composition remains poorly characterized. Here we develop a framework for partitioning molecular composition based on key molecular traits, including lability vs. recalcitrance and activity vs. inactivity. Within this framework, we examine the ecological processes governing the assembly of DOM fractions by deploying aquatic microcosms on mountainsides that span gradients of temperature and nutrient loading in subtropical and subarctic ecosystems. Across study regions, deterministic and stochastic processes primarily structure active and inactive fractions, respectively. However, recalcitrant molecules are more deterministically assembled than labile molecules in the inactive fraction. Deterministic processes leading to variable selection generally exhibit more variation across the energy supply gradient for inactive fractions, and their importance increases with energy supply for recalcitrant molecules in both active and inactive fractions. Together, our results indicate that active and inactive fractions of DOM assemblages are structured by contrasting ecological processes, and their recalcitrant components are sensitive to global change. In conclusion, our framework opens new avenues to understand the assembly and turnover of DOM in a changing world, which can be used to predict carbon cycling at local to global scales.

54 ENVIRONMENTAL SCIENCES↗