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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Electronic tuning of confined sub-nanometer cobalt oxide clusters boosting oxygen catalysis and rechargeable Zn–air batteries.

Reasonable design of robust bifunctional oxygen catalysts from an electronic structure perspective is intriguing and challenging for the development of high active rechargeable zinc-air batteries (ZABs). In this study, the favorable regulation of the electronic structure of the cobalt oxide nanoclusters was firstly predicted by density functional theory (DFT) simulation, and then experimentally verified by confining sub-nanometer CoOx clusters (0.86 nm) into the small pore of ZIF-8 derived N-doped nanomaterials (PNC) using a microporous MOFs confinement strategy. The confined effect of the MOF micropores not only enhanced the stability of the subnanometer cobalt oxide clusters, but also make it coupled with Co-Nx to further regulate the electronic structure of the former, synergistic resulting in enhanced ORR/OER actives. As a result, the optimized 0.05CoOx@PNC catalyst demonstrates outstanding bifunctional oxygen performance with a smaller potential gap of 0.67 V. Moreover, the rechargeable Zn-air batteries integrated 0.05CoOx@PNC air cathode displays encouraging performance with a peak power density of 157.1 mW cm(-2), a specific capacity of 887 mAh g(Zn)(-1)at 10 mA cm(-2) and long-term cyclability for over 200 h, significantly outperforming the benchmark electrode couple consisted of Pt/C/RuO2. DFT calculation further revealed that reducing particle size and coupling with Co-N could effectively regulate the charge distribution of CoOx nanoclusters and downshift the D-band center of Co adsorption sites in CoOx nanoclusters, which reduced the reaction barrier of intermediate O-2* and OH* and ORR/ OER over potential, thus accelerating the overall ORR/OER kinetic process. This work offers a novel reference for the construction of a robust sub-nanometer cluster catalysts in the field of ZABs.

Bifunctional oxygen electrocatalysts↗
DOE OSTI2023

Machine learning models inaccurately predict current and future high-latitude C balances

The high-latitude carbon (C) cycle is a key feedback to the global climate system, yet because of system complexity and data limitations, there is currently disagreement over whether the region is a source or sink of C. Recent advances in big data analytics and computing power have popularized the use of machine learning (ML) algorithms to upscale site measurements of ecosystem processes, and in some cases forecast the response of these processes to climate change. Due to data limitations, however, ML model predictions of these processes are almost never validated with independent datasets. To better understand and characterize the limitations of these methods, we develop an approach to independently evaluate ML upscaling and forecasting. We mimic data-driven upscaling and forecasting efforts by applying ML algorithms to different subsets of regional process-model simulation gridcells, and then test ML performance using the remaining gridcells. In this study, we simulate C fluxes and environmental data across Alaska using ecosys, a process-rich terrestrial ecosystem model, and then apply boosted regression tree ML algorithms to training data configurations that mirror and expand upon existing AmeriFLUX eddy-covariance data availability. We first show that a ML model trained using ecosys outputs from currently-available Alaska AmeriFLUX sites incorrectly predicts that Alaska is presently a modeled net C source. Increased spatial coverage of the training dataset improves ML predictions, halving the bias when 240 modeled sites are used instead of 15. However, even this more accurate ML model incorrectly predicts Alaska C fluxes under 21st century climate change because of changes in atmospheric CO 2 , litter inputs, and vegetation composition that have impacts on C fluxes which cannot be inferred from the training data. Our results provide key insights to future C flux upscaling efforts and expose the potential for inaccurate ML upscaling and forecasting of high-latitude C cycle dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Workflow to Optimize Fast Neutron Irradiation in A Thermal Neutron Spectrum Test Reactor Leveraging Open-Source Tools

The Advanced Test Reactor (ATR) located at Idaho National Laboratory (INL) is one of the key nuclear engineering research and testing facilities within the US Department of Energy (DOE). The ATR is one of few high-power research reactors in the world with different application including accelerated testing of nuclear fuel, materials irradiation in a very high neutron flux environment, and medical radioisotope production [1]. Also, the ATR offers opportunities for testing fast spectrum fission and fusion reactor materials. The key challenges in this area are in further detailing and optimizing a fast spectrum environment within a thermal test reactor. This challenge involves researching, developing, and testing novel concepts for the multiplying of neutron populations into ever higher energy spectra in high flux test reactors like ATR. The main objective of this work is to investigate candidate materials for establishing a fast neutron experiment irradiation in thermal neutron spectrum test reactors which can be accomplished by filtering thermal and epithermal neutrons and boosting fast neutrons at designated irradiation positions. However, adding these filters will render the neutron spectrum and the criticality of the system. The selection of the thickness and material layers should be accomplished by developing an optimization design algorithm that is applicable for ATR to enhance the fast neutron spectrum irradiation utilizing high-fidelity Monte Carlo methods along with advanced machine learning capabilities. This paper presents workflow for design optimization to enhance fast neutron irradiation in the ATR. The workflow leverages open-source tools to develop an algorithm that is viable to ATR and can be leveraged in other reactors. The following sections discuss the development of the experiment design optimization workflow and its application to ATR irradiation positions.

42 - ENGINEERING↗
DOE OSTI2020

Structure, Morphology, and Photovoltaic Implications of Halide Alloying in Lead-Free Cs 3 Sb 2 Cl x I 9-x 2D-Layered Perovskites

Compositional tuning has been a major driving force behind the excellent optoelectronic properties observed in typical Pb-based perovskites. For lead-free perovskite derivatives, a challenge to understanding the connection between compositional tuning and intrinsic optoelectronic properties, hence a barrier towards boosting their performance, comes from the fact that multiple crystalline substructures can form based on composition, film processing, or both. Especially with lower dimensional (0D, 1D, 2D) substructures, the particular polymorph present in the film can be a greater determinant of optoelectronic properties than the composition itself. Herein, we report a simple method to alloy the halide site in all-inorganic lead-free Cs 3 Sb 2 I 9 films while maintaining a consistent 2D-layered substructure, as a means to independently study the photovoltaic implications of halide substitution. We use a broad suite of spectroscopy and device measurements to identify an optimal stoichiometric substitution of chloride for iodide (~ 8 mol%, measured) that balances both intrinsic and bulk optoelectronic properties to achieve a top power conversion efficiency of 2.2%. This work underscores the importance of controlling substructure while investigating the impacts of compositional tuning for the development of lead-free perovskites, and more broadly validates the approach towards realizing lead-free alternative perovskite solar technologies.

14 SOLAR ENERGY↗
DOE OSTI2021

Physics-Infused AI/ML Based Digital-Twin Framework for Flow-Induced-Vibration Damage Prediction in a Nuclear Reactor Heat Exchanger

This report summarizes some of the ongoing work related to the development of an expert-elicitation-digital-twin framework for real time damage state prediction in heat exchanger components of a nuclear reactor. The framework is targeted towards predicting damage associated with coupled low cycle fatigue (associated with regular heat-up, cool-down and power operation transients) and high cycle fatigue (associated with flow induced vibration transients). The overall framework will be based on a NoSQL based database, physics-infused-geometry-dependent virtual-sensor data, different AI/ML techniques-based data-driven-predictive-model applications (Apps) and real-time plant sensor measurements available through few existing sensors. Towards this overall goal, this report updates some of the ongoing work, such as on implementation of a NoSQL Database (such as MongoDB), FE based heat transfer analysis of a heat exchanger (e.g. of a PWR steam generator) for generating geometry-dependent virtual sensor data and evaluation of various AI/ML models such as based on multivariate linear regression, ensembled decision-tree based Random-Forest and Gradient-Boosting regression and high-dimensional-kernel-function-transformation based Support-Vector-Machine regression models. The AI/ML models were evaluated for predicting multi-time-series thermal states at thousands of 3D point-clouds

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Siloxane-functional small molecule acceptor for high-performance organic solar cells with 16.6% efficiency

As one of the simple but most effective molecular design strategies, side-chain engineering has been widely employed to modify the photoelectric properties of active layer materials for boosting the photovoltaic performance of organic solar cells (OSCs). In this work, a functionalized small molecule acceptor (SMA) named BTSi-4F with a bulky siloxane-terminated solubilizing group as side-chains, derived from a classical SMA of Y6, was designed and synthesized. The results demonstrate that the introduction of siloxane-functional terminated groups into SMA not only affects the optical absorption and molecular energy levels, but also regulates the miscibility between the polymer donor and SMA. Compared to the original Y6, BTSi-4F exhibits a better solubility, upshifted lowest unoccupied molecular orbital (LUMO) energy level, more ordered molecular packing, and higher electron-mobility. Matched with a wide bandgap polymer donor PM6, the chlorobenzene-processed OSCs based on PM6:BTSi-4F achieved a superior power conversion efficiency (PCE) of 16.6% with both high open-circuit voltage (V oc ) of 0.90 V and high fill factor (FF) of 0.77, while the devices based on PM6:Y6 obtained a much lower PCE of 13.0% with a V oc of 0.81 V and FF of 0.69 under the same conditions. This work offers a promising molecular design strategy of siloxane-terminated side chain engineering to develop high-performance SMAs for efficient OSCs.

14 SOLAR ENERGY↗
DOE OSTI2021

Constraining the baryon abundance with the kinematic Sunyaev-Zel’dovich effect: Projected-field detection using Planck , WMAP , and unWISE

The kinematic Sunyaev-Zel'dovich (kSZ) effect -- the Doppler boosting of cosmic microwave background (CMB) photons scattering off free electrons with non-zero line-of-sight velocity -- is an excellent probe of the distribution of baryons in the Universe. In this paper, we measure the kSZ effect due to ionized gas traced by infrared-selected galaxies from the \emph{unWISE} catalog. We employ the "projected-field" kSZ estimator, which does not require spectroscopic galaxy redshifts. To suppress non-kSZ foreground signals associated with the galaxies (e.g., dust emission and thermal SZ), this estimator requires cleaned CMB maps, which we obtain from \emph{Planck} and \emph{WMAP} data. Using a new "asymmetric" estimator that combines different foreground-cleaned CMB maps to maximize the signal-to-noise, we measure the kSZ$^2$-galaxy cross-power spectrum for three subsamples of the \emph{unWISE} galaxy catalog, which peak at mean redshifts $z \approx$ 0.6, 1.1, and 1.5, have average halo mass $\sim 1$-$5\times 10^{13}$ $h^{-1} M_{\odot}$, and in total contain over 500 million galaxies. After marginalizing over CMB lensing contributions, we measure the amplitude of the kSZ signal $A_{\rm kSZ^2} = 0.42 \pm 0.31$, $5.02 \pm 1.01$, and $8.23 \pm 3.23$, for the three subsamples, where $A_{\rm kSZ^2} = 1$ corresponds to our fiducial model. The combined kSZ detection S/N $>$ 5. We discuss possible explanations for the excess kSZ signal associated with the $z \approx 1.1$ sample, and show that foreground contamination in the CMB maps is very unlikely to be the cause. Our measurements illustrate clearly that no baryons are missing on large scales at low redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Quantum Efficiency Gain in 2D Perovskite Photo and X‐Ray Detectors

Abstract The perovskite polycrystalline thin film detector fabricated by solution method is a promising low‐cost, scalable technology for radiation imaging, but its thin volume limits the sensing efficiency for high‐energy X‐ray photons. This work reports 2D perovskite thin film photo‐diodes with a detection gain when sensing visible and X‐ray photons. Detailed power and temperature‐dependent device characterizations reveal a charge multiplication effect to be responsible for the observed high gain. This is caused by a disparity in electron and hole transport, where electron transport is retarded by a trap/de‐trap process via shallow trap states, whereas the hole transport is fast enough to produce a photoconductive gain in satisfying the charge neutrality. The 2D perovskite made with butylamine spacers is also found to exhibit a larger efficiency gain than those made with phenylethylamines because of the higher likelihood of forming shallow traps in the former. The thin film diodes feature a high temporal response over 1 MHz due to the fast charge collection across a thin volume, and the discovery provides device physics mechanisms in connection to material structure‐function relationship for future optoelectronics design that can boost the efficiency of X‐ray sensing and dim light detection.

2D perovskites↗
DOE OSTI2026

Enhancing mobility and interface state engineering via UV-ozone treatment in BEOL-compatible ultrathin TiO 2 transistors

It has emerged as a potential candidate to improve the performance of monolithic-three-dimensional (M3D) integration of fused logic and memories through low-temperature in situ synthesis of high-performance metal–oxide–semiconductor (MOS) transistors. Here, we report the demonstration of the BEOL-compatible low thermal budget (350 °C) fabrication process of ultrathin-TiO2 transistors by the combination of RTA and UV-ozone treatment (RTA-UVOz). UV–ozone (UVOz) treatment of TiO2 anatase films significantly enhances stability, boosting ION current and field effect mobility (μ FE ) by two times of magnitude in TiO2 TFTs. UV ozone treatment helps to eliminate pre-existing oxygen vacancies and carbon contamination on TiO2 channels even at low temperature (100 °C), resulting in high-quality channel/dielectric interfaces with low interface states (D it ). During UVOz treatment, oxygen species (O x ) passivate the oxygen vacancies ($V$$^{2+}_{o}$), and hence low concentration of $V$$^{2+}_{o}$ would be left for ionization/de-ionization under PBS/NBS, leading to improved bias stress stability. Furthermore, the TiO 2 TFTs with thin ZrO 2 gate dielectric exhibited excellent performance including a lower subthreshold swing (SS) of 98 mV/dec with high drive I ON current ∼ 4.5 μA/μm, a high I ON /I OFF > 10 9 , and mobility μFE of 7 cm 2 /V-s under a battery powered voltage of 1 V. UV–ozone treatment enables high-performance, CMOS-compatible TiO 2 transistors with a low thermal budget, ideal for next-generation flexible, energy-efficient electronics.

BEOL↗
DOE OSTI2026

Integration of a thermoelectric subcooler with an air‑source heat pump to enhance heating capacity and dehumidification

This study presents an innovative configuration of a thermoelectric subcooler (TES) integrated with an air-source heat pump (ASHP). The TES is installed in the liquid line, where it absorbs heat from the refrigerant. On its hot side, it discharges heat to the return air in heating mode or to the supply air in cooling mode, enabling year-round operation. The ASHP–TES system was evaluated under various conditions to reduce supplemental heating needs and improve dehumidification. Experimental heating tests revealed that activating the TES increased the heating capacity by 12%–20%. However, this occurred with a 7.6%–10% reduction in heating coefficient of performance (COP). In cooling mode, TES operation significantly improved moisture removal. The TES reduced the sensible heat ratio (SHR) and enhanced dehumidification, removing 20%–50% more moisture than a conventional system when meeting the same sensible load. The TES can be turned off to use the refrigerant subcooler for reheat supply air or turned on to substantially boost dehumidification. When meeting the same latent load, the ASHP–TES system achieved up to 33% energy savings compared with a conventional ASHP using resistance heating. Relative to a conventional ASHP paired with a whole-house dehumidifier, the ASHP–TES system provided up to 20% energy savings. These findings underscore the potential of TES integration to improve latent load control and enhance overall energy efficiency in hybrid ASHP systems, especially in cold and humid climates.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗
DOE OSTI2024

Reliability and resilience of environmental flows under uncertainty: reconsidering water year types and inconsistent flow requirements in California

Abstract Environmental water allocation in California is a complex legal process involving various government agencies and stakeholders. E-flow requirements can be based on annual runoff typologies called water year types (WYTs), which dictate water volume, timing, and duration. In this study, we examined hydropower licensing documents of the major water and power projects in the Central Sierra Nevada to catalog e-flow requirements by WYT. In this study case, we identify how WYT classification systems and categories vary across and within different basins. Additionally, we assessed the impacts of climate change on hydrology, the frequency of WYTs identified, and the reliability and resilience of e-flows using future projections (2031–2060) of 10 Global Circulation Models (GCMs). We then propose a potential adaptation strategy using a 30 year moving percentiles approach to recalculate WYTs. We identified eight WYT classifications systems were identified, and their WYT distributions statistically significantly changes across all GCMs, even though most GCMs indicate no statistically significant change in hydrology. Disparities in future impacts are observed among and within hydropower projects, with some river reaches showing negative impacts on reliability and resilience. The adaptation strategy can generally boost resilience and improve reliability, but simply updating existing WYT thresholds without flexible regulatory frameworks reconsidering WYTs and e-flows thresholds, may not yield substantial improvements. Challenges in managing e-flows in California within regulatory and hydroclimatic contexts are intricate due to the lack of standardized approaches, leading to inconsistencies and potential conflicts among stakeholders, that will likely be exacerbated by climate change. Thus, we emphasize that targeted, site-specific, and adaptive management strategies are crucial, besides the need for a harmonized and consistent approach to defining and applying WYT categories and methods and/or e-flow assessments.

Environmental Sciences & Ecology↗
DOE OSTI2020

3D‐Printed Structure Boosts the Kinetics and Intrinsic Capacitance of Pseudocapacitive Graphene Aerogels

Abstract The performance of pseudocapacitive electrodes at fast charging rates are typically limited by the slow kinetics of Faradaic reactions and sluggish ion diffusion in the bulk structure. This is particularly problematic for thick electrodes and electrodes highly loaded with active materials. Here, a surface‐functionalized 3D‐printed graphene aerogel (SF‐3D GA) is presented that achieves not only a benchmark areal capacitance of 2195 mF cm −2 at a high current density of 100 mA cm −2 but also an ultrahigh intrinsic capacitance of 309.1 µF cm −2 even at a high mass loading of 12.8 mg cm −2 . Importantly, the kinetic analysis reveals that the capacitance of SF‐3D GA electrode is primarily (93.3%) contributed from fast kinetic processes. This is because the 3D‐printed electrode has an open structure that ensures excellent coverage of functional groups on carbon surface and facilitates the ion accessibility of these surface functional groups even at high current densities and large mass loading/electrode thickness. An asymmetric device assembled with SF‐3D GA as anode and 3D‐printed GA decorated with MnO 2 as cathode achieves a remarkable energy density of 0.65 mWh cm −2 at an ultrahigh power density of 164.5 mW cm −2 , outperforming carbon‐based supercapacitors operated at the same power density.

asymmetric supercapacitors↗
DOE OSTI2026

Weak Lensing Mass Calibration of the ACT DR5 Galaxy Clusters with the DES Year 3 Weak Lensing Data

We use weak gravitational lensing measurements from Year 3 Dark Energy Survey data to calibrate the masses of 443 galaxy clusters selected via the Sunyaev-Zel'dovich effect from Atacama Cosmology Telescope Data Release 5 maps of the cosmic microwave background. We incorporate redshift and SZ measurements for individual clusters into a hierarchical model for the stacked lensing signals and perform Bayesian analyses to constrain the hydrostatic mass bias of the clusters. Our treatment of systematic uncertainties includes a prescription for measuring and accounting for the weak lensing boost factor, consideration of a miscentering effect, as well as marginalization over uncertainties in the source galaxy photometric redshift distributions and shear calibration. The resultant constraints on the normalization of the mass-observable relation have a precision of approximately 7%, with the mean WL halo mass of M $_{500c}$ = 5.4 × 10$^{14}$ M $_{⊙}$. We measure the bias between the true cluster mass and the mass estimated from the SZ signal based on an X-ray-calibrated scaling relation assuming hydrostatic equilibrium, to be 1 - b = 0.74$^{+0.06}$ $_{-0.05}$ over the full sample. When splitting the clusters into high (z = 0.43-0.70) and low (z = 0.15-0.43) redshift bins, we measure 1 - b = 0.58$^{+0.06}$ $_{-0.05}$ and 0.81$^{+0.08}$ $_{-0.06}$, respectively. When introducing additional freedom in redshift and mass to the hydrostatic bias model, we find that 1 - b decreases with redshift (with the power law of -1.8$^{+0.5}$ $_{-0.6}$, 99.95% confidence), consistent with findings from other recent studies, while we do not find any significant trend in mass. We also demonstrate that our result is robust against various systematics such as a scale cut, priors on baryonic and miscentering parameters, and degree of scatter in mass-observable relation. The weak-lensing mass calibration presented in this study will be a useful tool for using the ACT clusters as probes of astrophysics, and as a step towards using their abundance as a cosmological probe.

Shin, T. [Carnegie Mellon U.] (ORCID:0000000263895↗
DOE OSTI2023

Hybrid Attack Graph Generation with Graph Convolutional Deep-Q Learning

Critical infrastructures such as power grids have become increasingly complex, connected, and vulnerable to adverse scenarios, including cyber and physical attacks and faults. Effective risk mitigation for such cyber-physical energy systems (CPES), requires preemptive knowledge of likely adversarial attack scenarios. Hybrid Attack Graph (HAG) is a structured way to represent an adversarial scenario as an attack sequence using a threat model. However, the scarcity of documented attack sequences hinders analysts and CPES planners’ ability to identify credible attack scenarios for a given CPES. We propose a data-driven Graph Convolutional Deep-Q Network (GCDQ) to address this data challenge through generating HAGs. By leveraging limited real-world observations from the MITRE ATT&CK knowledge base, our GCDQ model synthesizes realistic graphs with the targeted attribute of minimum detectability via reinforcement learning. This generative model is the first step in creating a tool to substantially boost the attack sequence dataset and enhance the performance of CPS defense-related tasks by providing insights into likely attack sequences with given attributes.

deep learning, artificial intelligence↗
DOE OSTI2024

A Comprehensive Strategy for Grid Forming Control in DC Coupled Photovoltaic and Battery Energy Storage Inverters

This paper presents an integrated DC-DC and DCAC grid-forming control strategy for DC-coupled photovoltaic (PV) plus battery energy storage systems, considering the effect of DC link voltage variations caused by direct PV connections. A power reference algorithm determines power distribution between the PV and battery to the grid while observing device power ratings to prevent the over-rating of components and keep the battery's state of charge within an acceptable range. The simulated utility-scale model in MATLAB/Simulink illustrates its ability against extreme phase angle variation contingencies in the grid while controlled through grid-forming control with a fast dynamic on DC link voltage. The simulation results confirm the effectiveness of the proposed control in integrating PV plus battery configurations with grid forming control and maintaining reliable grid operation under severe grid disturbances.

battery, boost, control, energy storage, grid form↗
DOE OSTI2022

H α emission in local galaxies: star formation, time variability, and the diffuse ionized gas

ABSTRACT The nebular recombination line H α is widely used as a star formation rate (SFR) indicator in the local and high-redshift Universe. We present a detailed H α radiative transfer study of high-resolution isolated Milky-Way and Large Magellanic Cloud simulations that include radiative transfer, non-equilibrium thermochemistry, and dust evolution. We focus on the spatial morphology and temporal variability of the H α emission, and its connection to the underlying gas and star formation properties. The H α and H β radial and vertical surface brightness profiles are in excellent agreement with observations of nearby galaxies. We find that the fraction of H α emission from collisional excitation amounts to fcol ∼ 5–$10{{\ \rm per\ cent}}$, only weakly dependent on radius and vertical height, and that scattering boosts the H α luminosity by $\sim 40{{\ \rm per\ cent}}$. The dust correction via the Balmer decrement works well (intrinsic H α emission recoverable within 25 per cent), though the dust attenuation law depends on the amount of attenuation itself both on spatially resolved and integrated scales. Important for the understanding of the H α–SFR connection is the dust and helium absorption of ionizing radiation (Lyman continuum [LyC] photons), which are about $f_{\rm abs}\approx 28{{\ \rm per\ cent}}$ and $f_{\rm He}\approx 9{{\ \rm per\ cent}}$, respectively. Together with an escape fraction of $f_{\rm esc}\approx 6{{\ \rm per\ cent}}$, this reduces the available budget for hydrogen line emission by nearly half ($f_{\rm H}\approx 57{{\ \rm per\ cent}}$). We discuss the impact of the diffuse ionized gas, showing – among other things – that the extraplanar H α emission is powered by LyC photons escaping the disc. Future applications of this framework to cosmological (zoom-in) simulations will assist in the interpretation of spectroscopy of high-redshift galaxies with the upcoming James Webb Space Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Distortion of a Relativistic Jet Echoing a Magnetic Flux Eruption

Magnetized accretion onto spinning black holes (BHs) can accumulate a large magnetic flux across the event horizon and launch a pair of relativistic jets via the Blandford–Znajek mechanism. In the magnetically saturated (arrested) state, excess magnetic flux is ejected from the BH in episodic magnetic flux eruptions, which result in a significant yet temporary reduction of jet power. We analyze results of a high-resolution 3D general-relativistic magnetohydrodynamic numerical simulation of geometrically thick magnetically saturated accretion onto a high-spin Kerr BH for a single cycle of magnetic flux eruption and accumulation. We show that following an eruption, a weakened jet develops a strong helical distortion with a distinct structure of magnetic fields—the poloidal field along the jet core is unaffected by the eruption; while toroidal field lines, ejected from the BH during the eruption and later readvected onto it, form poloidal “bypasses” along the inner jet sheath. Such a distortion may appear in sources fed by geometrically thick accretion flows as an asymmetric superluminal knot, strongly interacting with the jet sheath along an oblique working surface. The jet section repowered by magnetic flux reaccumulated on the BH is tilted by a few degrees, implying significant variations in radiation boost towards observers of BL Lac blazars. The intrinsic structure of the jet spine is consistent with axisymmetric semi-analytical models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Relativistic Alfvén Waves Entering Charge-starvation in the Magnetospheres of Neutron Stars

Instabilities in a neutron star can generate Alfvén waves in its magnetosphere. Propagation along the curved magnetic field lines strongly shears the wave, boosting its electric current j A . We derive an analytic expression for the evolution of the wavevector k and the growth of j A . In the strongly sheared regime, j A may exceed the maximum current j0 that can be supported by the background e ± plasma. We investigate these charge-starved waves, first using a simplified two-fluid analytic model, then with first-principles kinetic simulations. We find that the Alfvén wave is able to propagate successfully even when κ ≡ j A /j 0 $\ll$ 1. It sustains j A by compressing and advecting the plasma along the magnetic field lines with an increasing Lorentz factor, γ ≳ κ 1/2 . The simulations show how plasma instabilities lead to gradual dissipation of the wave energy. Our results suggest that an extremely high charge-starvation parameter κ ≳ 10 4 may be required in order for this mechanism to power the observed fast radio bursts (FRBs) from SGR 1935+2154. However, cosmological FRBs with much higher luminosities are unlikely to be a result of charge-starvation.

79 ASTRONOMY AND ASTROPHYSICS↗