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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

Influence of temporal variations in plasma conditions on the electric potential near self-organized dust chains

Self-organization of dust grains into stable filamentary dust structures (or “chains”) largely depends on dynamic interactions between individual charged dust grains and complex electric potential arising from the distribution of charges within a local plasma environment. Recent studies have shown that the positive column of the gas discharge plasma in the Plasmakristall-4 (PK-4) experiment at the International Space Station supports the presence of fast-moving ionization waves, which lead to variations of plasma parameters by up to an order of magnitude from the average background values. The highly variable environment resulting from ionization waves may have interesting implications for the dynamics and self-organization of dust particles, particularly concerning the formation and stability of dust chains. Here, we investigate the electric potential surrounding dust chains in the PK-4 experiment by employing a molecular dynamics model of the dust and ions with boundary conditions supplied by a particle-in-cell with Monte Carlo collision simulation of the ionization waves. The model is used to examine the effects of the plasma conditions within different regions of the ionization wave and compare the resulting dust structure to that obtained by employing the time-averaged plasma conditions. Here, the comparison between simulated dust chains and experimental data from the PK-4 experiment shows that the time-averaged plasma conditions do not accurately reproduce observed results for dust behavior, indicating that more careful treatment of plasma conditions in the presence of ionization waves is required. It is further shown that commonly used analytic forms of the electric potential do not accurately describe the electric potential near charged dust grains under these plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Surfactant-free syntheses and pair distribution function analysis of osmium nanoparticles

A surfactant-free synthesis of precious metal nanoparticles (NPs) performed in alkaline low-boiling-point solvents has been recently reported. Monoalcohols are here investigated as solvents and reducing agents to obtain colloidal Os nanoparticles by using low-temperature (<100 °C) surfactant-free syntheses. The effect of the precursor (OsCl 3 or H 2 OsCl 6 ), precursor concentration (up to 100 mM), solvent (methanol or ethanol), presence or absence of a base (NaOH), and addition of water (0 to 100 vol %) on the resulting nanomaterials is discussed. It is found that no base is required to obtain Os nanoparticles as opposed to the case of Pt or Ir NPs. The robustness of the synthesis for a precursor concentration up to 100 mM allows for the performance of X-ray total scattering with pair distribution function (PDF) analysis, which shows that 1–2 nm hexagonal close packed (hcp) NPs are formed from chain-like [OsO x Cl y ] complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DIGS: deep inference of galaxy spectra with neural posterior estimation

Abstract With the advent of billion-galaxy surveys with complex data, the need of the hour is to efficiently model galaxy spectral energy distributions (SEDs) with robust uncertainty quantification. The combination of simulation-based inference (SBI) and amortized neural posterior estimation (NPE) has been successfully used to analyse simulated and real galaxy photometry both precisely and efficiently. In this work, we utilise this combination and build on existing literature to analyse simulated noisy galaxy spectra. Here, we demonstrate a proof-of-concept study of spectra that is (a) an efficient analysis of galaxy SEDs and inference of galaxy parameters with physically interpretable uncertainties; and (b) amortized calculations of posterior distributions of said galaxy parameters at the modest cost of a few galaxy fits with Markov chain Monte Carlo (MCMC) methods. We utilise the SED generator and inference framework Prospector to generate simulated spectra, and train a dataset of 2 × 10 6 spectra (corresponding to a five-parameter SED model) with NPE. We show that SBI—with its combination of fast and amortized posterior estimations—is capable of inferring accurate galaxy stellar masses and metallicities. Our uncertainty constraints are comparable to or moderately weaker than traditional inverse-modelling with Bayesian MCMC methods (e.g. 0.17 and 0.26 dex in stellar mass and metallicity for a given galaxy, respectively). We also find that our inference framework conducts rapid SED inference (0.9–1.2 × 10 5 galaxy spectra via SBI/NPE at the cost of 1 MCMC-based fit). With this work, we set the stage for further work that focuses of SED fitting of galaxy spectra with SBI, in the era of JWST galaxy survey programs and the wide-field Roman Space Telescope spectroscopic surveys.

spectroscopy↗

Coordination of two redundant robots

A solution is presented for the optimal force distributions of two redundant coordinating robots. Two robots whose end-effectors firmly grasp a common inertial load form a closed-chain structure, and thus the robots must observe a set of constraint conditions on (1) the end-effector positions, orientations, linear and angular velocities and (2) the forces and torques inserted onto the end-effectors by the load. To achieve the maximum load capability, the optimal force distribution under the known posture is developed. If the robots are redundant, joint solutions may be obtained if some optimization criterion such as manipulability is imposed. The singularity, manipulability, and force ellipsoids are investigated in terms of the two manipulator Jacobian matrices. The manipulability is shown to correspond to the cascade structure, while the force ellipsoid corresponds to the parallel structure in terms of the manipulator Jacobian matrices.

Tao, Jian M.↗

Arctic Cloud‐Base Ice Precipitation Properties Retrieved Using Bayesian Inference

Abstract Cloud‐climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long‐lived, and nearly continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud‐base properties a more appealing target for inference and evaluation of model simulations. Here I describe an inverse model for the estimation of cloud base ice precipitation properties over Utqiagvik, North Slope of Alaska, using the synthesis of ground‐based radar and lidar measurements. By leveraging a Markov Chain Monte Carlo algorithm as the core of the inverse model, a wide range of particle size distributions are sampled, and different combinations of ice habit models are examined, both of which are typically fixed in other retrieval methods. Results show intriguing links between different cloud base thermodynamic and ice precipitation properties. Apparent ice number concentration enhancements at temperatures of −5 and −15°C suggest possible secondary ice production (SIP). The analysis alludes to an overestimation of SIP occurrence and intensity, especially in studies relying only on radar or lidar measurements. Finally, reflectivity‐dependent ice precipitation rate and ice water content parameterizations are presented.

54 ENVIRONMENTAL SCIENCES↗

Critical Minerals and Materials Matchmaker-CM3

This is the Critical Minerals and Materials Matchmaker (CM3) survey form. CM3 is an online information resource created to help connect users across the critical minerals and materials supply chain. The survey is designed to allow organizations to self-identify their critical minerals and materials-aligned activities and interests, and an interactive map that displays those on-going activities in a dynamic way. To include your critical minerals management activity or activities in CM3, please open and fill out the Critical Minerals and Materials Survey. If your organization has many ongoing or planned activities that would be onerous to enter in the form, or if your activities are difficult to geolocate (such as a transport network), please email the team at edxspatial@netl.doe.gov. This initiative is aligned with the approach of DOE’s H2 Matchmaker and Carbon Matchmaker. Read more information on H2 Matchmaker and Carbon Matchmaker. Below are some questions to help understand if you should fill out the CM3 survey: Does your company work with elements such as lithium, cobalt, copper, graphite, nickel, rare earth minerals, or platinum group metals? Does your organization have research and development activities related to critical materials or their supply chains? Does your company currently work in the critical minerals or materials supply chain? Do you have prospective work in critical minerals or materials in the next 5 years? Does your company mine, process, refine or distribute critical minerals or materials? Do you want to network with other facilities or organizations working in the same areas? Are you curious about the critical mineral and material activity in your surrounding area? Are you interested in aligning your potential needs across the supply chain to different geographic areas within the U.S? For more information, please see the CM3 website (https://www.energy.gov/fecm/articles/critical-minerals-materials-matchmaker-cm3) or email our team at edxspatial@netl.doe.gov.

CM3↗

Explanation and Application of the Evolving Contact Traction Fields in Shallow Foundation Systems

The present paper provides a qualitative discussion of the evolution of contact traction fields beneath rigid shallow foundations resting on granular materials. A phenomenological similarity is recognized in the measured contact traction fields of rigid footings and at the bases of sandpiles. This observation leads to the hypothesis that the stress distributions are brought about by the same physical phenomena, namely the development of arching effects through force chains and mobilized intergranular friction. A set of semi-empirical equations are suggested for the normal and tangential components of this contact traction based on past experimental measurements and phenomenological assumptions of frictional behaviors at the foundation system scale. These equations are then applied to the prescribed boundary conditions for the analysis of the settlement, resistance, and stress fields in supporting granular materials beneath the footing. A parametric sensitivity study is performed on the proposed modelling method, highlighting solutions to the boundary-value problems in an isotropic, homogeneous elastic half-space.

42 ENGINEERING↗

Chain-length-controllable upcycling of polyolefins to sulfate detergents

Escalating global plastic pollution and the depletion of fossil-based resources underscore the urgent need for innovative end-of-life plastic management strategies in the context of a circular economy. Thermolysis is capable of upcycling end-of-life plastics to intermediate molecules suitable for downstream conversion to eventually high-value chemicals, but tuning the molar mass distribution of the products is challenging. Here, in this study, we report a temperature-gradient thermolysis strategy for the conversion of polyethylene and polypropylene into hydrocarbons with tunable molar mass distributions. The whole thermolysis process is catalyst- and hydrogen-free. The thermolysis of polyethylene and polyethylene/polypropylene mixtures with tailored temperature gradients generated oil with an average chain length of ~C 14 . The oil featured a high concentration of synthetically useful α-olefins. Computational fluid dynamics simulations revealed that regulating the reactor wall temperature was the key to tuning the hydrocarbon distributions. Subsequent oxidation of the obtained α-olefins by sulfuric acid and neutralization by potassium hydroxide afforded sulfate detergents with excellent foaming behaviour and emulsifying capacity and low critical micelle concentration. Overall, this work provides a viable approach to producing value-added chemicals from end-of-life plastics, improving the circularity of the anthropogenic carbon cycle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Monte Carlo lattice models for adsorbed polymer conformation

The adhesion between a polymer film and a metal surface is of great technological interest. However, the prediction of adhesion and wear properties of polymer coated metals is quite difficult because a fundamental understanding of the polymer surface interaction does not yet exist. A computer model for the conformation of a polymer molecule adsorbed on a surface is discussed. The chain conformation is assumed to be described by a partially directed random walk on a three dimensional simple cubic lattice. An attractive surface potential is incorporated into the model through the use of a random walk step probability distribution that is anisotropic in the direction normal to the attractive surface. The effects of variations in potential characteristics are qualitatively included by varying both the degree of anisotropy of the step distribution and the range of the anisotropy. Polymer conformation is characterized by the average end to end distance, average radius of gyration, and average number of chain segments adsorbed on the surface.

Good, B. S.↗

Substrate Effects on Electronic Properties of Atomic Chains

When the device size is reduced down to 0.07 micrometers, the number of dopant atoms in the channel will no longer be macroscopic, typically less than a hundred. A spatial distribution of these dopant atoms will fluctuate statistically from device to device even in identically designed devices, and this places a serious limitation for integration. It is, however, impractical to control dopant positions within atomic dimension. One fundamental solution to this problem is to create electronics with atomically precise, but preferably simple structures. Atomic chains, precise structures of adatoms created on an atomically regulated surface, are candidates for constituent components in future electronics. All the adatoms will be placed at designated positions on the substrate, and all the device structures will be precise, free from any deviations. It was predicted using the tight-binding calculation with universal parameters that silicon chains were metallic and magnesium chains were semiconducting regardless of the lattice spacing, and a possible doping method was also proposed. In these treatments, the substrate was assumed to serve as a non-interacting template holding the adatoms without a formation of chemical bonding with substrate atoms. However, this scheme may not be easy to implement experimentally. Adatoms will have to be fixed with a van der Waals force on the substrate, but the force is generally weak and an extremely low temperature environment has to be prepared to suppress their unwanted thermal displacement. It may be logical to seek a scheme to allow the adatoms to form chemical bonding with the substrate atoms and secure their positions. The substrate effects are studied in detail.

Yamada, Toshishige↗

Gridtrust: Electricity Grid Root-of-Trust Decentralized Supply Chain Cyber-Security (Final Scientific/Technical Report)

GridTrust represents a departure from reliance on a single organization or a single person to multiple organizations and therefore multiple people across organizational structures. The motivating idea behind involving multiple organizations is the increase in security due to human factors. More specifically, the requirement that distinct people in different organizations sign off on a change or an update makes a cyberattack much less likely due to the inherent requirement that both organizations be penetrated and fooled. GridTrust focuses on the software update process as the primary exemplar for the research and development work. A novel hardware-based technology referred to as a Physical Unclonable Function (PUF) provides a microchip Root-of-Trust (RoT), i.e., a starting point for verifying that the hardware being communicated with is the hardware the control center believes the hardware to be. As a result, staff at power grid control centers can ensure the accurate and reliable identification of hardware devices from the outset. The GridTrust protocol introduces two key innovations, as detailed in this report. Firstly, the utilization of a PUF as a root-of-trust in the initial phase of a software or firmware update. Secondly, the application of multiple cryptographic signatures from two or more organizations to the update binary. These signatures are verified before implementing the update on a power grid device in the field. In terms of GridTrust hardware design, this report outlines two main components. The first is the GridTrust Native Device, integrating PUF technology intrinsically into the hardware device itself. The second is the GridTrust Interfacing Device, which incorporates PUF technology and multiple cryptographic signatures. These signatures are cross-checked within a separate hardware positioned between the power grid control center and the legacy power grid device, functioning as an intermediary. While the GridTrust Interfacing Device offers the advantage of being applicable to existing power grid equipment, it may have reduced security if the intermediary component is targeted. On the other hand, the GridTrust Native Device boasts increased security due to protocol integration within a unified form factor. The effectiveness of GridTrust technology has been extensively demonstrated, with multiple external red-team attackers unable to breach GridTrust's security measures. This was observed both in controlled laboratory settings during Phase 1 of the project and in real-world conditions within a City of Marietta substation during Phase 2 of the project.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distribution of aurora and ionospheric currents observed simultaneously on a global scale

The instantaneous spatial distribution of auroral emissions is observed with auroral imaging photometers on board the spacecraft Dynamics Explorer 1 (DE 1) as ground-based meridian chains of magnetometers simultaneously detect the magnetic signatures of ionospheric and field-aligned currents flowing at northern polar latitudes. Ionospheric conductivities at nighttime auroral latitudes are estimated from the measured auroral luminosities and used with the measured polar magnetic variations to compute model distributions of ionospheric and field-aligned currents. Temporal resolution for the coordinated observations and model calculations is 12 minutes. Model ionospheric and field-aligned current distributions are overlayed on global auroral images to illustrate spatial relations on a global scale at the maximum epoch of an auroral substorm. Eccentric-dipole-latitude and magnetic-local-time coordinates are used. A model field-aligned current distribution is compared quantitatively with the distribution of field-aligned currents inferred from simultaneous observations by the DE-2 magnetometer.

Craven, J. D.↗

Domestic Manufacturing & Supply Summary for Transmission Components [Slides]

The purpose of this presentation is to describe how the input assumptions for transmission grid supply constraints were developed. These assumptions will be used in a subsequent paper to evaluate the ability of transmission supply chains to meet anticipated transmission development needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Using Metadynamics to Reveal Extractant Conformational Free Energy Landscapes

Understanding the impact of extractant functionalization on metal-binding energetics in liquid-liquid extraction is essential to guide the development of better separation processes. Traditionally, computational extractant design uses electronic structure calculations on metal-ligand clusters to determine the metal-binding energy of the lowest energy state. Although highly accurate, this approach does not account for all of the relevant physics encountered under experimental conditions. Such methodologies often neglect entropic contributions such as temperature effects and ligand flexibility, in addition to approximating solvent-extractant interactions with implicit solvent models. In this study, we use classical molecular dynamics simulations with an advanced sampling method, metadynamics, to map out extractant molecule conformational free energies in the condensed phase. Here we generate the complete conformational landscape in solution for a family of bidentate malonamide-based extractants with different functionalizations of the headgroup and the side chains. In particular, we show how such alkyl functionalization reshapes the free energy landscape, affecting the free energy penalty of organizing the extractant into the cis-like metal-binding conformation from the trans-like conformation of the free extractant in solution. Specifically, functionalizing alkyl tails to the center of the headgroup has a greater influence on increasing molecular rigidity and disfavoring the binding conformation than functionalizing side chains. These findings are consistent with trends in metal-binding energetics based on experimentally reported distribution ratios. We also consider a different bidentate extractant molecule, carbamoylmethylphosphine oxide, and show how the choice of solvent can further reshape the conformational energetic landscape. This study demonstrates the feasibility of using molecular dynamics simulations with advanced sampling techniques to investigate extractant conformational energetics in solution, which, more broadly, will enable extractant design that accounts for entropic effects and explicit solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the Morphology and Mobility of Amines in Porous Silica CO 2 Sorbents by 1 H T 1 – T 2 Relaxation Correlation NMR

Molecular and oligomeric amines supported in porous oxide supports are a promising class of CO 2 sorbent materials studied for CO 2 removal from diverse streams such as flue gas and ambient air. Among the various amines investigated, low molecular weight, hyperbranched poly(ethyleneimine) (PEI), and tetraethylenepentamine (TEPA) are among the most extensively studied. While macroscopic structure–performance relationships relating the support structure, amine loading, and other factors affecting CO 2 sorption capacities and kinetics have been developed, structural and dynamic information about the organic amine phase in the porous support is less plentiful. The structure and mobility of amines impregnated in the pores of porous supports directly impact gas sorption, as the accessibility of amine sites in the pores directly relates to amine distribution in the pores and overall pore filling as well as the dynamics of the amine chains. Here, we prepare a family of mesoporous silica SBA-15 materials containing varying loadings of oligomeric (PEI) and molecular (TEPA) amines. 1 H T 1 –T 2 relaxation correlation solid-state NMR experiments are used to characterize the structural and dynamic properties of the confined amines. Both TEPA and PEI are shown to form multiple different domains in the pores, each with distinguishable dynamic properties. TEPA and PEI form more rigid layers around the silica support walls at lower organic loading fractions, characterized by lower mobilities, followed by the formation of more mobile domains less engaged in pore wall interactions at higher loadings. TEPA shows faster mobilities than PEI because of its lower molecular weight. TEPA also appears to more easily transfer between domains within the pores, leading to generally faster CO 2 uptake rates with higher sorption capacities, while PEI located closer to the pore walls remained much less mobile and is thus less engaged in CO 2 capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generative machine learning for detector response modeling with a conditional normalizing flow

In this paper, we explore the potential of generative machine learning models as an alternative to the computationally expensive Monte Carlo (MC) simulations commonly used by the Large Hadron Collider (LHC) experiments. Our objective is to develop a generative model capable of efficiently simulating detector responses for specific particle observables, focusing on the correlations between detector responses of different particles in the same event and accommodating asymmetric detector responses. Here, we present a conditional normalizing flow model ($\mathcal{CNF}$) based on a chain of Masked Autoregressive Flows, which effectively incorporates conditional variables and models high-dimensional density distributions. We assess the performance of the $\mathcal{CNF}$ model using a simulated sample of Higgs boson decaying to diphoton events at the LHC. We create reconstruction-level observables using a smearing technique. We show that conditional normalizing flows can accurately model complex detector responses and their correlation. This method can potentially reduce the computational burden associated with generating large numbers of simulated events while ensuring that the generated events meet the requirements for data analyses. We make our code available at https://github.com/allixu/normalizing_flow_for_detector_response

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Influenza A viral burst size from thousands of infected single cells using droplet quantitative PCR (dqPCR)

An important aspect of how viruses spread and infect is the viral burst size, or the number of new viruses produced by each infected cell. Surprisingly, this value remains poorly characterized for influenza A virus (IAV), commonly known as the flu. In this study, we screened tens of thousands of cells using a microfluidic method called droplet quantitative PCR (dqPCR). The high-throughput capability of dqPCR enabled the measurement of a large population of infected cells producing progeny virus. By measuring the fully assembled and successfully released viruses from these infected cells, we discover that the viral burst sizes for both the seasonal H3N2 and the 2009 pandemic H1N1 strains vary significantly, with H3N2 ranging from 10 1 to 10 4 viruses per cell, and H1N1 ranging from 10 1 to 10 3 viruses per cell. Some infected cells produce average numbers of new viruses, while others generate extensive number of viruses. In fact, we find that only 10% of the single-cell infections are responsible for creating a significant portion of all the viruses. This small fraction produced approximately 60% of new viruses for H3N2 and 40% for H1N1. On average, each infected cell of the H3N2 flu strain produced 709 new viruses, whereas for H1N1, each infected cell produced 358 viruses. This novel method reveals insights into the flu virus and can lead to improved strategies for managing and preventing the spread of viruses.

60 APPLIED LIFE SCIENCES↗