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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Seismic Recovery of Acoustic Source Height During the OSIRIS-REx Sample Return Capsule Re-Entry

Controlled hypersonic reentries with well‐constrained trajectories are exceedingly rare, yet they provide valuable reference cases for validating geophysical source characterization methods applicable to bolides and space debris. The 24 September 2023 re‐entry of the OSIRIS‐REx Sample Return Capsule, the first interplanetary capsule to return over the contiguous United States in nearly two decades, presented such an opportunity. Here, we present seismic observations of this event recorded at 16 stations across three sites at ground distances of 7–20 km from the trajectory. Using eigenray tracing through ground‐to‐space atmospheric specifications, we invert picked acoustic‐to‐seismic travel times for effective shock‐generated acoustic source altitudes along the known trajectory. The method recovers source heights of 57.9–59.5 km with travel‐time residuals <1 s across all stations. The seismic‐derived source heights, when compared at their along‐track positions, fall within the range of previously published infrasound‐derived heights for the corresponding trajectory segment, with intermethod differences comparable with the timing‐based uncertainty. These results suggest that air‐to‐ground coupling does not introduce a resolvable systematic timing bias in the picked near‐field seismic arrivals, supporting seismic observations as a complementary tool for altitude estimation of bolides, re‐entry vehicles, and other hypersonic atmospheric sources.

Silber, Elizabeth Allaryce [Sandia National Labora↗
DOE OSTI2024

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

Introduction Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High Energy Physics (HEP). In the Exa.TrkX Project, an illustrative HEP application, preprocessed simulation data is fed into a state-of-art Graph Neural Network (GNN) model, accelerated by GPUs. However, limited GPU memory often leads to Out-of-Memory (OOM) exceptions during training, due to the large size of models and datasets. This problem is exacerbated when deploying models on High-Performance Computing (HPC) systems designed for large-scale applications. Methods We observe a high workload imbalance issue during GNN model training caused by the irregular sizes of input graph samples in HEP datasets, contributing to OOM exceptions. We aim to scale GNNs on HPC systems, by prioritizing workload balance in graph inputs while maintaining model accuracy. Our paper introduces diverse balancing strategies aimed at decreasing the maximum GPU memory footprint and avoiding the OOM exception, across various datasets. Results Our experiments showcase memory reduction of up to 32.14% compared to the baseline. We also demonstrate the proposed strategies can avoid OOM in application. Additionally, we create a distributed multi-GPU implementation using these samplers to demonstrate the scalability of these techniques on the HEP dataset. Discussion By assessing the performance of these strategies as data loading samplers across multiple datasets, we can gauge their effectiveness in both single-GPU and distributed environments. Our experiments, conducted on datasets of varying sizes and across multiple GPUs, broaden the applicability of our work to various GNN applications that handle input datasets with irregular graph sizes.

Lee, Claire Songhyun↗
DOE OSTI2023

Systematic and scalable genome-wide essentiality mapping to identify nonessential genes in phages

Phages are one of the key ecological drivers of microbial community dynamics, function, and evolution. Despite their importance in bacterial ecology and evolutionary processes, phage genes are poorly characterized, hampering their usage in a variety of biotechnological applications. Methods to characterize such genes, even those critical to the phage life cycle, are labor intensive and are generally phage specific. Here, we develop a systematic gene essentiality mapping method scalable to new phage–host combinations that facilitate the identification of nonessential genes. As a proof of concept, we use an arrayed genome-wide CRISPR interference (CRISPRi) assay to map gene essentiality landscape in the canonical coliphages λ and P1. Results from a single panel of CRISPRi probes largely recapitulate the essential gene roster determined from decades of genetic analysis for lambda and provide new insights into essential and nonessential loci in P1. We present evidence of how CRISPRi polarity can lead to false positive gene essentiality assignments and recommend caution towards interpreting CRISPRi data on gene essentiality when applied to less studied phages. Finally, we show that we can engineer phages by inserting DNA barcodes into newly identified inessential regions, which will empower processes of identification, quantification, and tracking of phages in diverse applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

13 C-Isotope-Assisted Assessment of Metabolic Quenching During Sample Collection from Suspension Cell Cultures

Metabolomics and fluxomics are core approaches to directly profile and interrogate cellular metabolism in response to various genetic or environmental perturbations. In order to accurately measure the abundance and isotope enrichment of intracellular metabolites, cell culture samples must be rapidly harvested and cold-quenched to preserve the in vivo metabolic state of the cells at the time of sample collection. When dealing with suspension cultures, this process is complicated by the need to separate the liquid culture media from cellular biomass prior to metabolite extraction. Here, we examine the efficacy of several commonly used metabolic quenching methods, using the model cyanobacterium Synechocystis sp. PCC 6803 as an example. Multiple 13 C-labeled compounds, including 13 C-bicarbonate, 13 C-glucose and 13 C-glutamine, were used as tracers during the sample collection and cold-quenching process to assess the extent of metabolic turnover after cells were harvested from culture flasks. We show that the combination of rapid filtration followed by 100% cold (–80°C) methanol quenching exhibits the highest quenching efficiency, while mixing cell samples with a partially frozen 30% methanol slurry (–24°C) followed by centrifugation is slightly less effective at quenching metabolism but enables less laborious sample processing. By contrast, rapidly mixing the cells with a saline ice slurry (~0°C) is less effective as indicated by high isotope-labeling rates after sample harvest, while mixing the cells with 60% cold methanol (–65°C) prior to centrifugation causes significant metabolite loss. Furthermore, this study demonstrates a rigorous, quantitative, and broadly applicable method for assessing the metabolic quenching efficacy of protocols used for sample collection in metabolomics and fluxomics studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Whole‐Cell MALDI‐ToF MS Coupled with Untargeted Metabolomics Facilitates Investigations of Microbial Chemical Interactions

Abstract The emergence of drug‐resistant pathogens necessitates the development of new countermeasures. In this regard, the introduction of probiotics to directly attack or competitively exclude pathogens presents a useful strategy. Application of this approach requires an understanding of how a probiotic and its target pathogen interact. A key means of probiotic‐pathogen interaction involves the production of small molecules called natural products (NPs). Here, we report the use of whole‐cell matrix‐assisted laser desorption/ionization time‐of‐flight (MALDI‐ToF) mass spectrometry to characterize NP production by candidate probiotics (mouse airway microbiome isolates) when co‐cultured with the respiratory pathogen Burkholderia . We found that a Bacillus velezensis strain inhibits growth of and elicits NP production by Burkholderia thailandensis . Dereplication of known NPs detected in the metabolome of this B. velezensis strain suggests that a previously unannotated bioactive compound is involved. Thus, we present the use of whole‐cell MALDI as a broadly applicable method for screening the NP composition of microbial co‐cultures; this can be combined with other ‐omics methods to characterize probiotic‐pathogen and other microbe‐microbe interactions.

Aiosa, Nicole↗
DOE OSTI2021

Roads less traveled: Nitrogen reduction reaction catalyst design strategies for improved selectivity

Direct electrochemical nitrogen reduction for ammonia production is necessary to reduce the use of fossil fuels from conventional Haber–Bosch methods. Applications of nitrogen reduction electrocatalysts remain inhibited by slow reaction kinetics and low faradaic efficiencies because of competitive H2 production pathways. Current strategies to address this challenge in selectivity have focused on catalyst design, reactor configuration, and electrolyte conditions. This brief review discusses the thermodynamic and kinetic challenges in the field as well as current underused approaches for selective catalyst development including bimetallic catalysts, transition metal nitrides, and carbon supports.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Dual-scale folding in cutting of commercially pure aluminum alloys

We examine a, hitherto, little-studied and curious machining chip morphology, with tell-tale signs of folding at two different length scales, that is common in cutting of certain ductile and highly strain-hardening metals like soft aluminum alloys, tantalum and niobium. This chip morphology does not appear in the usual catalogues of common chip types. The mechanics of formation of the “dual-scale folded chip” is studied in model material systems of commercially pure aluminum alloys (AA 1100 and AA 8040), that prominently exhibit this chip morphology. The flow, folding and associated plastic instabilities are investigated using micro/macro structure observations of the chip in a plane-strain cutting framework, with high-speed in situ imaging and image analysis of material flow; and force measurements. The smaller-scale folding is shown to develop in the primary deformation zone while the larger-scale folding occurs as the chip traverses the rake face of the tool. The resulting chip is composed of irregularly-spaced large folds, superimposed onto which are the quasi periodic small folds. The representative wavelengths of the two folds differ on average by an order of magnitude, 0.1 mm vs. 2 mm. The observations reveal a direct coupling between the material flow and chip morphology, and how specific attributes of the dual-scale folded chip arise from the flow mechanism. Plastic buckling is found to play a key role in the folding at both length scales. The small-scale folds are characteristic of a sinuous plastic flow mode, while the large-scale folding is characterized by buckling and stick-slip along the tool rake face, triggered by adhesive pinning of the chip to the tool. Important consequences of the dualscale folding are very large cutting forces, and force oscillations of large amplitude, despite the alloys being very soft, only ~ 25 HV. Here, the dual-scale folding is why many of these alloys are classified as “gummy” to machine. Since the dual-scale folded chip is associated with large cutting forces and poor surface quality, there is much to be gained by disrupting this flow type in practical machining applications. Methods for controlling the folding to improve machining performance with the gummy alloys are briefly discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The impact of chromium coatings on Zircaloy cladding deformation behavior under reactivity-initiated accident-like mechanical loading conditions

A reactivity-initiated accident (RIA) occurs when a control rod ejection or control blade drop causes an increase in the fission rate. The injection of energy results in an increase in fuel temperature which in turn causes rapid thermal expansion of the fuel pellet. This thermal expansion may result in pellet-cladding mechanical interaction (PCMI) in which the fuel imparts a mechanical strain to the cladding. PCMI may cause the cladding to fail, and thus, the mechanical response of cladding due to PCMI must be investigated when characterizing new cladding materials. Chromium-coated Zircaloy-4 is a near-term accident-tolerant fuel cladding that exhibits improved high-temperature oxidation resistance. Modified burst testing was utilized to experimentally simulate the effects of PCMI on both uncoated and chromium-coated Zircaloy cladding samples at hot zero power conditions. Samples were coated using either cold spraying or physical vapor deposition to understand the differences in behavior that the coating application method may cause. Digital image correlation was used to analyze images of the deforming specimens to extract the in-situ strain behavior of the cladding. The uncoated specimens burst at hoop strains ranging from 8.8 % to 17.2 %. The cold-spray chromium-coated Zircaloy specimens burst at hoop strains of 7.0 % to 11.0 %. The physical vapor deposition coated tubes burst at hoop strains of 9.1 % to 11.5 %. These results indicate that the chromium coating causes a loss in the ductility of the cladding. Furthermore, the higher burst hoop strains of the physical vapor deposition-coated samples relative to the cold-spray samples indicate that the cold-spraying technique causes more of a loss in ductility than physical vapor deposition. All samples burst at higher hoop strains than those expected to occur in an RIA for fresh cladding.

Accident-tolerant fuel↗
DOE OSTI2022

Combined Effects of Uniform Applied Pressure and Electrolyte Additives in Lithium-Metal Batteries

The development of lithium-metal batteries with good performance and long lifetimes requires fundamental insight into the mechanisms underlying performance improvements from individual design strategies and the interactions between multiple improvement approaches. Here, in this work, we investigated the individual and combined effects of applied pressure and a LiAsF 6 electrolyte additive on the performance of anode-free lithium-metal batteries; we employed various pressure application methods, which vary both in magnitude and uniformity. Both approaches individually improve cycling performance of anode-free lithium-metal batteries. Pressure increases the cycling efficiency at both the anode and cathode by promoting improved morphologies, while the LiAsF 6 additive additionally improves performance at the anode by enhancing the solid electrolyte interphase (SEI) properties. The combination of uniform applied pressure and a LiAsF 6 electrolyte additive produces lithium-metal batteries with cycling performance higher than can be achieved with either approach alone. This additional performance improvement is able to be realized due to the complementary rather than competitive nature of the mechanisms underlying applied pressure (lithium morphology) and electrolyte additives (SEI properties). Our results highlight the importance of moving beyond the investigation of isolated design strategies and demonstrate that superior cycling can be achieved by combining multiple approaches.

25 ENERGY STORAGE↗
DOE OSTI2024

Superior Piezo-/Ferro-Electricity in Antiferroelectric Ag x NbO 3-δ Thin Films by Nanopillar Local Structure Design

Antiferroelectrics are fundamental mother compounds critical in developing innovative lead-free piezoelectrics and ferroelectrics and hold great promise for wide-ranging applications in energy conversion and electronic devices. However, harnessing their superior properties presents a significant challenge due to the delicate balance required between their various states. Here, in this study, through the unique design of nanopillar structures to alleviate the local polar heterogeneity, we have achieved significantly improved piezo-/ferro-electricity in classic lead-free antiferroelectric Ag x NbO 3-δ (x = 1, 0.9, and 0.8) epitaxial thin films. The effective piezoelectric coefficient reaches 440 pm V –1 , 1 order of magnitude larger than the stoichiometric AgNbO 3 , rivaling classic lead zirconate titanate piezoelectrics. Atomic-scale electron microscopy investigations unravel the underlying mechanisms. The nanopillars, characterized by antisite occupancy of both Ag and Nb atoms and forming out-of-phase boundaries with the matrix, reduce the local crystal symmetry via interphase strain. This leads to the creation of flexible multinanodomain structures that significantly facilitate polarization rotation, thus substantially enhancing the piezoelectric performance. This study demonstrates the feasibility of engineering local heterogeneity through nanopillar design, offering a generally applicable method for property improvement of a wide range of antiferroelectrics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Functional genetic encoding of sulfotyrosine in mammalian cells

Protein tyrosine O -sulfation (PTS) plays a crucial role in extracellular biomolecular interactions that dictate various cellular processes. It also involves in the development of many human diseases. Regardless of recent progress, our current understanding of PTS is still in its infancy. To promote and facilitate relevant studies, a generally applicable method is needed to enable efficient expression of sulfoproteins with defined sulfation sites in live mammalian cells. Here we report the engineering, in vitro biochemical characterization, structural study, and in vivo functional verification of a tyrosyl-tRNA synthetase mutant for the genetic encoding of sulfotyrosine in mammalian cells. We further apply this chemical biology tool to cell-based studies on the role of a sulfation site in the activation of chemokine receptor CXCR4 by its ligand. Our work will not only facilitate cellular studies of PTS, but also paves the way for economical production of sulfated proteins as therapeutic agents in mammalian systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning

Knowing the rate at which particle radiation releases energy in a material, the “stopping power,” is key to designing nuclear reactors, medical treatments, semiconductor and quantum materials, and many other technologies. While the nuclear contribution to stopping power, i.e., elastic scattering between atoms, is well understood in the literature, the route for gathering data on the electronic contribution has for decades remained costly and reliant on many simplifying assumptions, including that materials are isotropic. We establish a method that combines time-dependent density functional theory (TDDFT) and machine learning to reduce the time to assess new materials to hours on a supercomputer and provide valuable data on how atomic details influence electronic stopping. Our approach uses TDDFT to compute the electronic stopping from first principles in several directions and then machine learning to interpolate to other directions at a cost of 10 million times fewer core-hours. We demonstrate the combined approach in a study of proton irradiation in aluminum and employ it to predict how the depth of maximum energy deposition, the “Bragg Peak,” varies depending on the incident angle—a quantity otherwise inaccessible to modelers and far outside the scales of quantum mechanical simulations. The lack of any experimental information requirement makes our method applicable to most materials, and its speed makes it a prime candidate for enabling quantum-to-continuum models of radiation damage. The prospect of reusing valuable TDDFT data for training the model makes our approach appealing for applications in the age of materials data science.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Applying Bayesian inference and deterministic anisotropy to retrieve the molecular structure ∣Ψ(R)∣2 distribution from gas-phase diffraction experiments

Abstract Currently, our general approach to retrieving molecular structures from ultrafast gas-phase diffraction heavily relies on complex ab initio electronic or vibrational excited state simulations to make conclusive interpretations. Without such simulations, inverting this measurement for the structural probability distribution is typically intractable. This creates a so-called inverse problem. Here we address this inverse problem by developing a broadly applicable method that approximates the molecular frame structure ∣Ψ( R , t )∣ 2 distribution independent of these complex simulations. We retrieve the vibronic ground state ∣Ψ( R )∣ 2 for both simulated stretched NO 2 and measured N 2 O. From measured N 2 O, we observe 40 mÅ coordinate-space resolution from 3.75 Å −1 reciprocal space range and poor signal-to-noise, a 50X improvement over traditional Fourier transform methods. In simulated NO 2 diffraction experiments, typical to high signal-to-noise levels predict 100–1000X resolution improvements, down to 0.1 mÅ. By directly measuring the width of ∣Ψ( R )∣ 2 , we open ultrafast gas-phase diffraction capabilities to measurements beyond current analysis approaches. This method has the potential to effectively turn gas-phase ultrafast diffraction into a discovery-oriented technique to probe systems that are prohibitively difficult to simulate.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Discovering causal structure with reproducing-kernel Hilbert space ε -machines

We merge computational mechanics’ definition of causal states (predictively equivalent histories) with reproducing-kernel Hilbert space (RKHS) representation inference. The result is a widely applicable method that infers causal structure directly from observations of a system’s behaviors whether they are over discrete or continuous events or time. A structural representation—a finite- or infinite-state kernel ϵ-machine—is extracted by a reduced-dimension transform that gives an efficient representation of causal states and their topology. In this way, the system dynamics are represented by a stochastic (ordinary or partial) differential equation that acts on causal states. We introduce an algorithm to estimate the associated evolution operator. Paralleling the Fokker–Planck equation, it efficiently evolves causal-state distributions and makes predictions in the original data space via an RKHS functional mapping. We demonstrate these techniques, together with their predictive abilities, on discrete-time, discrete-value infinite Markov-order processes generated by finite-state hidden Markov models with (i) finite or (ii) uncountably infinite causal states and (iii) continuous-time, continuous-value processes generated by thermally driven chaotic flows. The method robustly estimates causal structure in the presence of varying external and measurement noise levels and for very high-dimensional data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

SDSS-IV MaNGA: the chemical co-evolution of gas and stars in spiral galaxies

ABSTRACT We investigate archaeologically how the metallicity in both stellar and gaseous components of spiral galaxies of differing masses evolve with time, using data from the SDSS-IV MaNGA survey. For the stellar component, we can measure this evolution directly by decomposing the galaxy absorption-line spectra into populations of different ages and determining their metallicities. For the gaseous component, we can only measure the present-day metallicity directly from emission lines. However, there is a well-established relationship between gas metallicity, stellar mass, and star formation rate which does not evolve significantly with redshift; since the latter two quantities can be determined directly for any epoch from the decomposition of the absorption-line spectra, we can use this relationship to infer the variation in gas metallicity over cosmic time. Comparison of present-day values derived in this way with those obtained directly from the emission lines confirms the validity of the method. Application of this approach to a sample of 1619 spiral galaxies reveals how the metallicity of these systems has changed over the last 10 billion yr since cosmic noon. For lower-mass galaxies, both stellar and gaseous metallicity increase together, as one might expect in well-mixed fairly isolated systems. In higher-mass systems, the average stellar metallicity has not increased in step with the inferred gas metallicity, and actually decreases with time. Such disjoint behaviour is what one might expect if these more massive systems have accreted significant amounts of largely pristine gas over their lifetimes, and this material has not been well mixed into the galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Spin-squeezed Gottesman-Kitaev-Preskill codes for quantum error correction in atomic ensembles

Gottesman-Kitaev-Preskill (GKP) codes encode a qubit in displaced phase-space combs of a continuous-variable (CV) quantum system and are useful for correcting a variety of high-weight photonic errors. Here we propose atomic ensemble analogs of the single-mode CV GKP code by using the quantum central limit theorem to pull back the phase-space structure of a CV system to the compact phase space of a quantum spin system. We study the optimal recovery performance of these codes under error channels described by stochastic relaxation and isotropic ballistic dephasing processes using the diversity combining approach for calculating channel fidelity. Additionally, we find that the spin GKP codes outperform other spin system codes such as cat codes or binomial codes. Our spin GKP codes based on the two-axis countertwisting interaction and superpositions of SU(2) coherent states are direct spin analogs of the finite-energy CV GKP codes, whereas our codes based on one-axis twisting do not yet have well-studied CV analogs. A state preparation scheme for the spin GKP codes is proposed which uses the linear-combination-of-unitaries method, applicable to both the CV and spin GKP settings. Finally, we discuss a fault-tolerant approximate gate set for quantum computing with spin-GKP-encoded qubits, obtained by translating gates from the CV GKP setting using the quantum central limit theorem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Microscopic investigation of the 8 Li(n,γ)Li 9 reaction

Background: The 8 Li (n, γ) 9 Li reaction plays an important role in several astrophysics scenarios. It cannot be measured directly and indirect experiments have so far provided only cross section limits. Theoretical predictions differ by an order of magnitude. Purpose: In this work we study the properties of 9 Li bound states and low-lying resonances and calculate the 8 Li(n, γ) 9 Li cross section within the no-core shell model with continuum (NCSMC) with chiral nucleon-nucleon and three-nucleon interactions as input. Methods: Here, the NCSMC is an ab initio method applicable to light nuclei that provides a unified description of bound and scattering states well suited to calculate low-energy nuclear scattering and reactions. For the capture cross section calculation, we adjust calculated thresholds to experimental values. Results: Our calculations reproduce the experimentally known bound states as well as the lowest 5/2 – resonance of 9 Li. We predict a 3/2 – spin-parity assignment for the resonance observed at 5.38 MeV. In addition to the very narrow 7/2 – resonance corresponding presumably to the experimental 6.43 MeV state, we find several other broad low-lying resonances. Conclusions: Our calculated 8 Li(n, γ) 9 Li cross section is within the limits derived from the 1998 National Superconducting Cyclotron Laboratory Coulomb-dissociation experiment. However, it is higher than cross sections obtained in recent phenomenological studies. It is dominated by a direct E1 capture to the ground state with a resonant contribution at ≈ 0.2 MeV due to E2/M1 radiation enhanced by the 5/2 – resonance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Dark photon superradiance: Electrodynamics and multimessenger signals

We study the electrodynamics of a kinetically mixed dark photon cloud that forms through superradiance around a spinning black hole, and design strategies to search for the resulting multimessenger signals. A dark photon superradiance cloud sources a rotating dark electromagnetic field which, through kinetic mixing, induces a rotating visible electromagnetic field. Standard model charged particles entering this field initiate a transient phase of particle production that populates a plasma inside the cloud and leads to a system which shares qualitative features with a pulsar magnetosphere. We study the electrodynamics of the dark photon cloud with resistive magnetohydrodynamics methods applicable to highly magnetized plasma, adapting techniques from simulations of pulsar magnetospheres. We identify turbulent magnetic field reconnection as the main source of dissipation and electromagnetic emission, and compute the peak luminosity from clouds around solar-mass black holes to be as large as 10 43 erg/s for observationally allowed dark photon parameter space. The emission is expected to have a significant x-ray component and to potentially be periodic, with period set by the dark photon mass. The luminosity is comparable to the brightest x-ray sources in the Universe, allowing for searches at distances of up to hundreds of Mpc with existing telescopes. Finally, we discuss observational strategies, including targeted electromagnetic follow-ups of solar-mass black hole mergers and targeted continuous gravitational wave searches of anomalous pulsars.

79 ASTRONOMY AND ASTROPHYSICS↗