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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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Correction for ‘Interfacial rheology of lanthanide binding peptide surfactants at the air–water interface’ by Stephen A. Crane et al. , Soft Matter , 2024, 20 , 9161–9173, https://doi.org/10.1039/D4SM00493K.
Ether-based PFAS, such as ADONA, show a unique influence on their adsorption properties with different mineral interfaces.
High field side lower hybrid current drive (HFS LHCD) is promising method for efficient, off axis current drive. To operate this system, development of an expandable combination radio frequency (RF) and vacuum interface was necessary to allow the long (~2 m) waveguides to thermally expand with respect to the DIII-D 0 degree R-1 port extension without damage to the waveguide or excessive force on the vacuum seals which was previously observed when baking the waveguides during operations that were installed in 2024. Design of a custom bellows assembly with RF feedthrough that allows >20mm of waveguide thermal expansion is presented. Fabrication of this bellows assembly required simultaneously vacuum brazing multiple 304 stainless steel flanges to an oxygen free high conductivity copper waveguide section which required significant manufacturing development.
Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.
In this work, we derive from first principles the dispersion relation for electromagnetic radiation that is spontaneously emitted at a 2D curved plasma–vacuum interface in the absence of both background and external electric and magnetic fields. This plasma geometry is motivated by plasmas generated through hypervelocity impact projectiles—an area that is of importance to satellite safety in the aerospace community, and may be of importance for the developing study of projectile impact-driven inertial confinement fusion. We find spontaneous radiation occurs when thermal surface waves propagate along the edge of a circular plasma, with a frequency lower than the plasma frequency and spatial decay proportional to 1/r. This is distinct from more well-known mechanisms of radiation, in which the radiation frequency is greater than or equal to the plasma frequency. This theory is validated against 2D, electromagnetic particle-in-cell simulations and shows reasonable agreement. Finally, we discuss the effects of plasma geometry and attribute the radiation generation mechanism to the acceleration of charged surface waves as they traverse azimuthally along a curved path.
The transient receptor potential melastatin (TRPM) tetrameric cation channels are involved in a wide range of biological functions, from temperature sensing and taste transduction to regulation of cardiac function, inflammatory pain, and insulin secretion. The structurally conserved TRPM cytoplasmic domains make up >70 % of the total protein. To investigate the mechanism by which the TRPM cytoplasmic domains contribute to gating, we employed electrophysiology and cryo-EM to study TRPM5—a channel that primarily relies on activation via intracellular Ca 2+ . Here, we show that activation of mammalian TRPM5 channels is strongly altered by Ca 2+ -dependent desensitization. Structures of rat TRPM5 identify a series of conformational transitions triggered by Ca 2+ binding, whereby formation and dissolution of cytoplasmic interprotomer interfaces appear to control activation and desensitization of the channel. This study shows the importance of the cytoplasmic assembly in TRPM5 channel function and sets the stage for future investigations of other members of the TRPM family.
Two-dimensional (2D) absolute measurements of hydrogen peroxide (H 2 O 2 ) and approximations of the hydroperoxyl radical (HO 2 ) in the effluent of a COST Reference Microplasma Jet operated with a He/H 2 O feed gas are presented. Gas-phase densities are mapped using photofragmentation laser-induced fluorescence (PF-LIF) under three boundary conditions: open effluent, a solid target, and a liquid target. A novel method is presented for separating PF-LIF signals from H 2 O 2 and HO 2 using comparative measurements in oxygen-rich and oxygen-free environments to exploit the preferential formation of HO 2 in the presence of molecular oxygen. This separation strategy is supported by results from a plug-flow plasma chemistry model. Measured densities agree closely with model predictions in both magnitude and trend, while the 2D experimental distributions provide additional insight into the spatial dependencies of these species. In particular, the results show distinct differences in species transport depending on the target type: solid surfaces induce lateral deflection and reduced centerline densities, whereas liquid interfaces promote axial accumulation and higher near-axis concentrations.
The frequency, scale, and severity of wildfires are steadily increasing in the Western United States. Sustainable forest management practices through forest thinning could reduce the impact of wildfires and provide lumber for wood-based, long-lived, and low-carbon building materials. This study explores the potential for harvesting biomass in California (CA) to mitigate wildfire risk and provide multi-decade carbon storage in the form of cross-laminated timber (CLT) for use in buildings. First, we assessed biomass resource availability, finding that the total live hardwood and live softwood available in the wildland-urban interfaces (WUIs) across CA sums to 14.1 million metric tons (MMT) and 34.9 MMT, respectively, which contains the equivalent of 90 MMT of atmospheric carbon dioxide. Then, we conducted a life cycle assessment of CLT considering softwood and hardwood sources to provide insights into emissions and energy demand associated with utilization of the wood removed for wildfire risk management. We found that the net life cycle carbon footprint of live hardwood and softwood when including biogenic carbon storage/emissions is 414 and 317 kg CO2e/m3 CLT, respectively. To incorporate the timing of these emissions and uptake, we have also conducted a cradle-to-grave time-dependent global warming potential (GWP) analysis. The time-adjusted GWP for live hardwood and live softwood is −227 and −104 kg CO2e/m3 CLT, respectively. In terms of total CLT production potential, 0.03 and 0.005 million m3 CLT can be sourced from live softwood and hardwood, respectively, in WUI on gentle slopes in CA. The resulting insights and approaches from this study are broadly applicable to other forested regions and WUIs across the US and the world, and provide a holistic approach to use forest thinning as a wildfire mitigation strategy in combination with a novel approach for life cycle assessment of building materials with a limited dataset.
At the extreme densities in neutron stars, a phase transition to deconfined quark matter is anticipated. Yet masses, radii, and tidal deformabilities offer only indirect measures of a first-order phase transition, requiring many detections to resolve or being ineffective observables if the discontinuity exists at lower densities. Here, we report on a smoking-gun gravitational-wave signature of a first-order transition: the resonant tidal excitation of an interface mode. Using relativistic perturbation theory with an equation-of-state family informed by chiral effective field theory, we show that such a resonance may be detectable with next-generation interferometers and possibly already with LIGO A+ for sufficiently loud events.
The viscous fingering instability, which forms when a less-viscous fluid invades a more-viscous one within a confined geometry, is an iconic system for studying pattern formation. For both miscible and immiscible fluid pairs the growth dynamics change after the initial instability onset and the global structures, typical of late-time growth, are governed by the viscosity ratio. Here we introduce an experimental technique to measure flow throughout the inner and outer fluids. This probes the existence of a new length scale associated with the local pressure gradients around the interface and allows us to compare our results to the predictions of a previously proposed model for late-time finger growth. Published by the American Physical Society 2024
Here, we demonstrate the onset of Rayleigh-Bénard convection (RBC) near the fuel-ablator interface of inertial confinement fusion (ICF) implosion simulations for the scenario in which Rayleigh-Taylor or Richtmyer-Meshkov instabilities are suppressed. This convective heating within the cold fuel can degrade the adiabat and therefore performance of ICF implosions even without mixing of fuel and ablator. Our work suggests additional considerations to realize design adiabats in otherwise ideal ICF implosions: first, via control of the temperature differences between ablator and fuel and, second, control of the fuel acceleration which we show has a complex interplay with the RBC dynamics.
Spin-orbit coupling (SOC) lifts molecular orbital degeneracy, enabling bilevel electronic platforms suitable for next-generation digital devices. However, common light-atom molecular feedstocks exhibit weak SOC due to the absence of heavy elements. To enhance SOC without synthesizing new materials, we leverage interfacial interactions between molecules and transition-element-based solid-state materials. This computational study investigates SOC splitting in metal-phthalocyanine adsorbed on transition metal dichalcogenides (TMDs) using density functional theory (DFT). The enhanced SOC splitting is attributed to strong orbital hybridization at the molecule-substrate interface. Specifically, Zn-phthalocyanine (ZnPC) on monolayer MoS 2 achieves a notable SOC splitting of ∼8 meV. Furthermore, when ZnPC forms self-assembled chains on MoS 2 , the splitting increases to ∼20 meV, driven by the formation of hybrid bands modulated by molecular periodicity. Furthermore, these findings highlight the role of interfacial and intermolecular interactions in inducing and enhancing SOC in surface-adsorbed molecules, providing a new strategy for molecular spintronic materials without complex synthetic efforts.
Large-scale capacity expansion models typically rely on estimates of the power transfer limits between modeled zones. Accurate estimation of these interface transfer limits (ITLs) requires modeling the underlying transmission network. Here we expand on a maximum flow optimization method that uses linearized power flow to estimate transfer limits. We apply this method to a data set of the U.S. transmission network to estimate ITLs between U.S. counties. By calculating ITLs using different subsets of the network, we evaluate how the size of the network used in the estimation affects the results. The results show diminishing returns to ITL accuracy after six hops, suggesting that a network subset can reasonably be used to approximate ITLs. The county-level estimates produced in this study will support more spatially resolved capacity expansion modeling and will help inform policy making at local and national levels.
Integrating artificial intelligence (AI) capabilities into software applications typically involves two common paths. For developers, AI assists in generating and documenting source code and other related software engineering efforts. For users, AI assists them through question-and-answer exchanges via chatbots. Both approaches have their value, but neither effectively leverages the modularity of component-based architectures that modern web application frameworks offer. We implement a proof of concept within a centralized suite of applications used for the Atmospheric Radiation Measurement (ARM) Data Center Operational Tools, where we introduce a third integration path through the ARM Context Engine (ACE). ACE is a context driven system that uses structured contextual specifications to enable Large Language Models (LLMs) to render interactive and feature-rich user interface (UI) components directly within chat responses, alongside or in place of conventional text outputs. These specifications serve two important purposes across what we call code context and UI context. Code context provides AI-assisted development tools with structured application knowledge beyond raw code, including component relationships, architectural patterns and schematic information, enabling the generation of consistent, well-structured code. UI context defines the rules for enabling and rendering component features at runtime based on the user's natural language input, allowing end users to activate capabilities such as data export, filtering, and pagination within chat responses, without requiring code changes or redeployment. We demonstrate, through a comparative evaluation against general-purpose AI chatbots, that context-driven component rendering provides interactive capabilities that text-based responses cannot replicate, including deterministic component behavior, application-consistent design language, and on-demand feature activation. A development effort comparison further shows that features that traditionally require multi-step development cycles can be activated with a single naturallanguage request. In this ongoing work, we present ACE as an emerging approach to AI integration that positions modular, well-documented software architecture as the foundation for AI-ready applications. ACE treats context as a shared resource across both development and user-facing AI, bringing cohesion to conventionally disconnected efforts, bridging developer tooling and end-user capabilities within a single framework.
Here, the multipoint Thomson scattering (MPTS) diagnostic system at the National Spherical Torus Experiment Upgrade (NSTX-U) facility is undergoing an upgrade to operate in real-time and interface with the plasma control system (PCS) for NSTX-U. Previous prototyping efforts have shown that spectral analysis and rapid calculations of electron temperature and density are possible on a real-time Linux machine when using up to a 100-Hz laser pulse repetition rate. A remaining challenge was transferring the real-time data to NSTX-U’s PCS, which utilizes the front panel data port (FPDP) protocol. The original proposed method was to convert the real-time data into analog values, but a new solution was developed to keep the output format digital by using an Ethernet controller with a field-programmable gate array (FPGA). This article focuses on a new input module that has been developed to accept incoming user datagram protocol (UDP) packets sent over Ethernet, convert into FPDP format, and integrate into the existing data stream under NSTX-U’s real-time framework.
Unlike synchronous generators, the fault response of grid-forming (GFM) inverter-interfaced distributed generators (IIDGs) is notably governed by the selection of control and current limiting strategies rather than inherent physical traits. While recent research has focused on the sequence domain fault model of GFM IIDGs, a research gap exists in elucidating the influence of control and current limiting schemes on this model's characteristics. This article aims to fill this void by examining how different control and current limiting schemes influence the positive and negative sequence impedances in the phasor-domain fault model of GFM IIDGs. This investigation encompasses droop-based, virtual synchronous machine-based, and virtual oscillator-based reference generation controls alongside rotating and stationary reference-frame-based voltage controls. Furthermore, saturation-based, latching-based, circular and virtual impedance-based current limiting schemes are analyzed. To achieve this goal, a thorough numerical simulation study is conducted. Findings indicate that outer reference generation controls exhibit minimal impact. Conversely, the choice of voltage control and various current limiting schemes emerge as the predominant factors shaping the sequence models of GFM IIDGs. These analyses and results are instrumental in devising reliable protection strategies within inverter-based grids, as a comprehensive understanding of electrical elements in the sequence domain is imperative for effective protective measures.
The recent adoption of artificial intelligence in socio-technical systems raises concerns about the black-box nature of the resulting decisions in fields such as hiring, finance, admissions, etc. If data subjects—such as job applicants, loan applicants, and students—receive an unfavorable outcome, they may be interested in algorithmic recourse, which involves updating certain features to yield a more favorable result when re-evaluated by algorithmic decision-making. Unfortunately, when individuals do not fully understand the incremental steps needed to change their circumstances, they risk following misguided paths that can lead to significant, long-term adverse consequences. Existing recourse approaches focus exclusively on the final recourse goal but neglect the possible incremental steps to reach the goal with real-life constraints, user preferences, and model artifacts. To address this gap, we formulate a visual analytic workflow for incremental recourse planning in collaboration with AI/ML experts and contribute an interactive visualization interface that helps data subjects efficiently navigate the recourse alternatives and make an informed decision. We also present one of the many usage scenarios, developed during exploratory feedback sessions with twelve graduate students using a real-world dataset, which demonstrates that our approach can be instrumental for data subjects in choosing a suitable recourse path.
In magnetic pyrochlore materials, the interplay of spin-orbit coupling, electronic correlations, and geometrical frustration gives rise to exotic quantum phases, including topological semimetals and spin ice. While these phases have been observed in isolation, the interface-driven phenomena emerging from their interaction have never been realized previously. Here, we report on the discovery of interfacial electronic anisotropy and rotational symmetry breaking at a heterostructure consisting of the Weyl semimetal Eu 2 Ir 2 O 7 and spin ice Dy 2 Ti 2 O 7 . Subjected to magnetic fields, we unveil a sixfold anisotropic transport response that is theoretically accounted by a Kondo-coupled heterointerface, where the spin ice’s field-tuned magnetism induces electron scattering in the Weyl semimetal’s topological Fermi-arc states. Furthermore, at elevated magnetic fields, we reveal a twofold anisotropic response indicative of the emergence of a symmetry-broken many-body state. This discovery showcases the potential of pyrochlore frustrated magnet/topological semimetal heterostructures in search of emergent interfacial phenomena.