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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Improving initialization and evolution accuracy of cosmological neutrino simulations

Neutrino mass constraints are a primary focus of current and future large-scale structure (LSS) surveys. Non-linear LSS models rely heavily on cosmological simulations — the impact of massive neutrinos should therefore be included in these simulations in a realistic, computationally tractable, and controlled manner. Here, a recent proposal to reduce the related computational cost employs a symmetric neutrino momentum sampling strategy in the initial conditions. We implement a modified version of this strategy into the Hardware/Hybrid Accelerated Cosmology Code (HACC) and perform convergence tests on its internal parameters. We illustrate that this method can impart Script $\mathcal{O}$(1%) numerical artifacts on the total matter field on small scales, similar to previous findings, and present a method to remove these artifacts using Fourier-space filtering of the neutrino density field. Moreover, we show that the converged neutrino power spectrum does not follow linear theory predictions on relatively large scales at early times at the 15% level, prompting a more careful study of systematics in particle-based neutrino simulations. We also present an improved method for backscaling linear transfer functions for initial conditions in massive neutrino cosmologies that is based on achieving the same relative neutrino growth as computed with Boltzmann solvers. Our self-consistent backscaling method yields sub-percent accuracy in the total matter growth function. Comparisons for the non-linear power spectrum with the Mira-Titan emulator at a neutrino mass of m ν = 0.15 eV are in very good agreement with the expected level of errors in the emulator and in the direct N-body simulation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Next Generation Noble Liquid Detectors

The research program here combines Generic and Directed R\&D for Liquid Noble Gas detectors for neutrino physics and dark matter. In neutrino physics and dark matter research, we are addressing some of the most fundamental questions in particle physics today by studying these tiny particles in the electron family. To study them, detectors must be large, high precision, and ideally have the ability to collect detailed information from both charge and light from neutrino and dark matter interactions. Precision detection combined with large scales can be challenging. Liquid Argon detectors mitigate some of these challenges given the nature of its interaction medium and it’s relatively inexpensive cost per ton. Significant progress has been made in the last 15 years in developing these kinds of detectors to be built and operated at large scales. However there are still challenges and new ideas in moving these detectors from ton scale to kiloton scale. To be able to get the most out of these kinds of detectors directed questions with respect to specific components running and colleting data in the detectors must be understood. As well, new ideas on how to best combine charge and light measurements may lead to new ways to learn new things with these detectors. Experimental test stands to conduct this work, as is done in this proposal, to accomplish both of these goals are critical to address both of these questions. In the test stand enabled under this grant at Yale University’s Wright lab, new developments in efficient small scale setups were developed, instrumentation developed for running and future experiments (the SBND experiment at Fermilab at present, the DUNE experiment in the future) were and will be tested, and new ideas for charge and light determination for new measurements are under study. The long term impact of this work in neutrino physcis is both for the short and long baseline programs originating at Fermi National Accelerator Laboratory. At long baselines, the US flagship DUNE experiment will measure neutrino properties through neutrino oscillations using a beam originating at Fermilab and a massive LArTPC detector sited about a mile underground at the Sanford Underground Research Facility in Lead, South Dakota. Studies here on the high voltage for thes detectors, and ongoing work on charge and light production and collection in the TPC are relevant for the design and data taking of this and other LArTPC detectors to enable them to best measure the neutrinos created at Fermilab that then pass through the detector in South Dakota. What we learn in these detectors may ultimately change the course of how we understand neutrino’s impact in the early universe. What we learn about how to improve this detection technology and develop new ideas in Lar detectors in general may impact both future neutrino experiments and dark matter experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Cloud droplet diffusional growth in homogeneous isotropic turbulence: bin microphysics versus Lagrangian super-droplet simulations

The increase in the spectral width of an initially monodisperse population of cloud droplets in homogeneous isotropic turbulence is investigated by applying a finite-difference fluid flow model combined with either Eulerian bin microphysics or a Lagrangian particle-based scheme. The turbulence is forced applying a variant of the so-called linear forcing method that maintains the mean turbulent kinetic energy (TKE) and the TKE partitioning between velocity components. The latter is important for maintaining the quasi-steady forcing of the supersaturation fluctuations that drive the increase in the spectral width. We apply a large computational domain (64 3 m 3 ), one of the domains considered in Thomas et al. (2020). The simulations apply 1 m grid length and are in the spirit of the implicit large eddy simulation (ILES), that is, with small-scale dissipation provided by the model numerics. This is in contrast to the scaled-up direct numerical simulation (DNS) applied in Thomas et al. (2020). Two TKE intensities and three different droplet concentrations are considered. Analytic solutions derived in Sardina et al. (2015), valid for the case when the turbulence integral timescale is much larger than the droplet phase relaxation timescale, are used to guide the comparison between the two microphysics simulation techniques. The Lagrangian approach reproduces the scalings relatively well. Representing the spectral width increase in time is more challenging for the bin microphysics because appropriately high resolution in the bin space is needed. The bin width of 0.5 µm is only sufficient for the lowest droplet concentration (26 cm -3 ). For the highest droplet concentration (650 cm -3 ), an order of magnitude smaller bin size is barely sufficient. The scalings are not expected to be valid for the lowest droplet concentration and the high-TKE case, and the two microphysics schemes represent similar departures. Finally, because the fluid flow is the same for all simulations featuring either low or high TKE, one can compare point-by-point simulation results. Such a comparison shows very close temperature and water vapor point-by-point values across the computational domain and larger differences between simulated mean droplet radii and spectral width. The latter are explained by fundamental differences in the two simulation methodologies, numerical diffusion in the Eulerian bin approach and a relatively small number of Lagrangian particles that are used in the particle-based microphysics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Improving Stratocumulus Cloud Amounts in a 200‐m Resolution Multi‐Scale Modeling Framework Through Tuning of Its Interior Physics

Abstract High‐Resolution Multi‐scale Modeling Frameworks (HR)—global climate models that embed separate, convection‐resolving models with high enough resolution to resolve boundary layer eddies—have exciting potential for investigating low cloud feedback dynamics due to reduced parameterization and ability for multidecadal throughput on modern computing hardware. However low clouds in past HR have suffered a stubborn problem of over‐entrainment due to an uncontrolled source of mixing across the marine subtropical inversion manifesting as stratocumulus dim biases in present‐day climate, limiting their scientific utility. We report new results showing that this over‐entrainment can be partly offset by using hyperviscosity and cloud droplet sedimentation. Hyperviscosity damps small‐scale momentum fluctuations associated with the formulation of the momentum solver of the embedded large eddy simulation. By considering the sedimentation process adjacent to default one‐moment microphysics in HR, condensed phase particles can be removed from the entrainment zone, which further reduces entrainment efficiency. The result is an HR that can produce more low clouds with a higher liquid water path and a reduced stratocumulus dim bias. Associated improvements in the explicitly simulated sub‐cloud eddy spectrum are observed. We report these sensitivities in multi‐week tests and then explore their operational potential alongside microphysical retuning in decadal simulations at operational 1.5° exterior resolution. The result is a new HR having desired improvements in the baseline present‐day low cloud climatology, and a reduced global mean bias and root mean squared error of absorbed shortwave radiation. We suggest it should be promising for examining low cloud feedbacks with minimal approximation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The complex intracluster medium of Abell 1569 and its interaction with central radio galaxies

ABSTRACT We present the first in-depth study of X-ray emission from a nearby (z ∼ 0.0784) galaxy cluster Abell 1569 using an archival Chandra observation. A1569 consists of two unbound subclusters – a northern subcluster (A1569N) hosting a double-lobed radio galaxy 1233+169 at its centre, and a southern subcluster (A1569S) harbouring a wide-angle-tailed (WAT) radio source 1233+168. X-ray emission from A1569N and A1569S extends to a radius r ∼248 kpc and r ∼370 kpc, respectively, indicating that the two gas clumps are group-scale systems. The two subclusters have low X-ray luminosities (∼1042–43 erg s−1), average elemental abundances ∼1/4 Z⊙, low average temperatures (∼2 keV), and lack large (r ≳ 40–50 kpc) cool cores associated with the intracluster gas. We detect a pair of cavities coincident with the radio lobes of 1233+169 in A1569N. The total mechanical power associated with the cavity pair is an order of magnitude larger than the X-ray radiative loss in the cavity-occupied region, providing corroborating evidence for cavity-induced heating of the intragroup gas in A1569N. A1569S exhibits possible evidence for a small-scale cluster-subcluster merger, as indicated by its high central entropy, and the presence of local gas elongation and a density discontinuity in between the bent radio tails of 1233+168. The discontinuity is indicative of a weak merger shock with Mach Number, M ∼ 1.7. The most plausible geometry for the ongoing interaction is a head-on merger occurring between A1569S and a subcluster falling in from the west along the line bisecting the WAT tails.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Production of alternate realizations of DESI fiber assignment for unbiased clustering measurement in data and simulations

A critical requirement of spectroscopic large scale structure analyses is correcting for selection of which galaxies to observe from an isotropic target list. This selection is often limited by the hardware used to perform the survey which will impose angular constraints of simultaneously observable targets, requiring multiple passes to observe all of them. In SDSS this manifested solely as the collision of physical fibers and plugs placed in plates. In DESI, there is the additional constraint of the robotic positioner which controls each fiber being limited to a finite patrol radius. A number of approximate methods have previously been proposed to correct the galaxy clustering statistics for these effects, but these generally fail on small scales. To accurately correct the clustering we need to upweight pairs of galaxies based on the inverse probability that those pairs would be observed (Bianchi & Percival 2017). This paper details an implementation of that method to correct the Dark Energy Spectroscopic Instrument (DESI) survey for incompleteness. To calculate the required probabilities, we need a set of alternate realizations of DESI where we vary the relative priority of otherwise identical targets. These realizations take the form of alternate Merged Target Ledgers (AMTL), the files that link DESI observations and targets. We present the method used to generate these alternate realizations and how they are tracked forward in time using the real observational record and hardware status, propagating the survey as though the alternate orderings had been adopted. We detail the first applications of this method to the DESI One-Percent Survey (SV3) and the DESI year 1 data. We include evaluations of the pipeline outputs, estimation of survey completeness from this and other methods, and validation of the method using mock galaxy catalogs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Advanced Microstructured BaTiO 3 -Embedded PVDF–HFP/PEO Film for Enhanced Triboelectric Interface in Self-Sufficient Energy Generation and Sensing

The global reliance on fossil fuels and natural gas has largely dominated the energy production field, but due to finite resource depletion and escalating greenhouse gas emissions, the immediate exploration of sustainable energy alternatives to mitigate climate change and ensure resource security has been a major concern. There has been extensive research into other more renewable methods of energy production, such as wind and hydropower. Of these current energy generation types, there are many areas of untapped potential from the mechanical movements generated ambiently not only in the large scale of power generation but also on a smaller scale. The piezoelectric and triboelectric effects are phenomena where these ambient mechanical movements can generate electrical energy. Developing a hybrid system that leverages both mechanical stress and surface charges presents an ideal opportunity to exploit these untapped energy sources. Producing a hybrid PVDF–HFP/PEO film with perovskite BaTiO 3 (BTO) enables ambient power harvesting from both mechanical movement and surface charge. The optimized cell produced a potential of up to 15 V and a current of 200 nA with a 68 kΩ resistor, a substantial increase from a base system with an average of 2.1 V and 40 nA. These hybrid TENGs offer significant potential for energy harvesting in small-scale applications, such as health monitoring devices and indicators in electric circuits.

Ybarra, Rigobert [University of Texas Rio Grande V↗
DOE OSTI2026

Development of Industrial Scale Rare Earth Master Alloys from Their Native Oxides for Magnet Production

The objective of the project is to develop an energy-efficient, reduced cost, and single-step critical metal oxide reduction and alloying methodology for the production of NdFeB and SmCo magnets to facilitate the establishment of a sustainable domestic critical materials supply chain. The method consists of an immiscible molten salt flux layer and a higher density molten metal alloy pool (FeB or Co). The rare earth (RE) oxide and a reductant are added to the molten salt layer, where the reductant first strips the oxygen from the rare earth oxide. Subsequently, the separated RE metal diffuses into the molten metal pool below, creating a RE-saturated master alloy. Towards this end, thermodynamic calculations of the reactions between RE oxides, metallic reducing agent, and molten salt bath chemistry have been performed, and the ideal feeds and conditions for extraction and diffusion to produce master alloys were established. Small-scale and scaled experimentation was performed to validate and optimize the feasibility of viable reactions, temperatures, and process conditions with regards to yield, composition, and process efficiency. Finally, full-scale experiments for the production of NdFeB and SmCo magnets were performed, and their performance characteristics were established.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamics in a stellar convective layer and at its boundary: Comparison of five 3D hydrodynamics codes

Our ability to predict the structure and evolution of stars is in part limited by complex, 3D hydrodynamic processes such as convective boundary mixing. Hydrodynamic simulations help us understand the dynamics of stellar convection and convective boundaries. However, the codes used to compute such simulations are usually tested on extremely simple problems and the reliability and reproducibility of their predictions for turbulent flows is unclear. We define a test problem involving turbulent convection in a plane-parallel box, which leads to mass entrainment from, and internal-wave generation in, a stably stratified layer. We compare the outputs from the codes FLASH, MUSIC, PPMSTAR, PROMPI, and SLH, which have been widely employed to study hydrodynamic problems in stellar interiors. The convection is dominated by the largest scales that fit into the simulation box. All time-averaged profiles of velocity components, fluctuation amplitudes, and fluxes of enthalpy and kinetic energy are within ≲3σ of the mean of all simulations on a given grid (128 3 and 256 3 grid cells), where σ describes the statistical variation due to the flow’s time dependence. They also agree well with a 512 3 reference run. The 128 3 and 256 3 simulations agree within 9% and 4%, respectively, on the total mass entrained into the convective layer. The entrainment rate appears to be set by the amount of energy that can be converted to work in our setup and details of the small-scale flows in the boundary layer seem to be largely irrelevant. Our results lend credence to hydrodynamic simulations of flows in stellar interiors. We provide in electronic form all outputs of our simulations as well as all information needed to reproduce or extend our study.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Flow visualization in high-energy-density laboratory plasmas

Flow visualization is often essential for evaluating high-energy-density (HED) laboratory plasmas, examining their dynamics, and assessing design strategies. However, imaging at fine phenomenological flow scales is a major challenge. Here, a zone-plate–based radiography system tailored for applications in HED physics is demonstrated. The burst-mode radiography system combines a dual-flash laser-generated x-ray source, a high-magnification zone plate optic, and a multiple frame hybrid complementary metal-oxide-semiconductor (hCMOS) sensor for image detection. Operating at a magnification of 42 x⁠, a pair of radiographs is measured in rapid succession, each time gated by a 4.75 keV flash of x rays lasting 100 ps. The system achieves a spatial resolution below 3 μm. The potential of this approach for applications in HED physics is exemplified by observing small-scale spike morphologies at a pusher-foam interface impacted by a strong, laser-driven blast wave.

Flow instabilities↗
DOE OSTI2020

Patterning of magneto-optical nanomaterials

Patterning of colloidal particles in precisely organized architectures has attracted intense research interest for decades. This is due to their potential applications in flexible electronics, magnetic and optical devices, sensors, biotechnology, communications, etc. However, creation of mesoscale assemblies at commercial scale received less attention. The mesoscale systems reside between the micro- and macroscopic scales, with length dimensions from ≈ 100 um to 5mm. One way to create mesoscale materials is to leverage decades of experimental and theoretical research in nanomaterials field that allows us to precisely create and control the placement of nanoscale materials. We developed a versatile and automatic mesoscale patterning technology that provide precise and consistent control and special arrangement of functional nanomaterials. The versatility of the strategy is demonstrated by patterning nanoparticles with different dimensions, shapes and compositions, tethered with various functionalities and subjected to different external stimuli. Nanomaterials were created via the paten t pending automated flow-throughput domain process (AFTDP), aka nano-additive manufacturing approach, recently developed by us, based on a unique small-scale fluidics concept, that enables a uniform reaction environment for production of high-quality materials in large quantities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Field Validation of a Pilot-Scale Black Liquor Membrane for Water Removal

Pulp and paper processing is considered one of the most energy-intensive industries in the manufacturing sector. Concentrating black liquor is a particularly energy-intensive process in this industry, used to recover pulping chemicals and generate high-pressure steam from dissolved wood solids. About 7% of pulp and paper energy usage, or nearly 164 trillion British thermal units (Btu) per year, is used to remove water from black liquor in U.S. kraft mills. The U.S. Department of Energy’s Industrial Efficiency and Decarbonization Office is interested in this black liquor membrane technology because it offers the potential for a more energy-efficient and less carbon-intensive kraft pulping process. The membrane is intended to pretreat black liquor to reduce natural gas usage in evaporators that remove water from black liquor. This technology has the potential to be replicated across 99 kraft pulp mills in 24 states. This membrane technology is considered precommercial, and the demonstration was a small-scale side-stream field validation. To make an assessment on performance with a higher level of certainty, additional studies at larger scales are recommended.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Benchmarking the Performance of Neuromorphic and Spiking Neural Network Simulators

Software simulators play a critical role in the development of new algorithms and system architectures in any field of engineering. Neuromorphic computing, which has shown potential in building brain-inspired energy-efficient hardware, suffers a slow-down in the development cycle due to a lack of flexible and easy-to-use simulators of either neuromorphic hardware itself or of spiking neural networks (SNNs), the type of neural network computation executed on most neuromorphic systems. While there are several openly available neuromorphic or SNN simulation packages developed by a variety of research groups, they have mostly targeted computational neuroscience simulations, and only a few have targeted small-scale machine learning tasks with SNNs. Evaluations or comparisons of these simulators have often targeted computational neuroscience-style workloads. In this work, we seek to evaluate the performance of several publicly available SNN simulators with respect to non-computational neuroscience workloads, in terms of speed, flexibility, and scalability. We evaluate the performance of the NEST, Brian2, Brian2GeNN, BindsNET and Nengo packages under a common front-end neuromorphic framework. Our evaluation tasks include a variety of different network architectures and workload types to mimic the computation common in different algorithms, including feed-forward network inference, genetic algorithms, and reservoir computing. We also study the scalability of each of these simulators when running on different computing hardware, from single core CPU workstations to multi-node supercomputers. Our results show that the BindsNET simulator has the best speed and scalability for most of the SNN workloads (sparse, dense, and layered SNN architectures) on a single core CPU. However, when comparing the simulators leveraging the GPU capabilities, Brian2GeNN outperforms the others for these workloads in terms of scalability. NEST performs the best for small sparse networks and is also the most flexible simulator in terms of reconfiguration capability NEST shows a speedup of at least 2x compared to the other packages when running evolutionary algorithms for SNNs. The multi-node and multi-thread capabilities of NEST show at least 2x speedup compared to the rest of the simulators (single core CPU or GPU based simulators) for large and sparse networks. We conclude our work by providing a set of recommendations on the suitability of employing these simulators for different tasks and scales of operations. We also present the characteristics for a future generic ideal SNN simulator for different neuromorphic computing workloads.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Low Temperature Time-to-Explosion Experiments on HMX in the LLNL's ODTX/P-ODTX System (FY 2020 Annual Report)

Over the last few decades, there has been a considerable research effort on the thermal decomposition and thermal explosion violence of energetic materials at elevated temperatures in different sample geometries and confinements. Thermal explosion studies on various energetic materials in two-dimensional geometry such as the Scaled-Thermal-Explosion-Experiment (STEX) system and the Sandia-Instrumented-Thermal-Ignition (SITI) system have been reported. The One-Dimensional Time to Explosion (ODTX) system, designed and built by LLNL, has been used since 1970s for thermal explosion studies. The system is attractive because of the one-dimensional geometry and minimal sample requirement. With the recent integration of a pressure monitoring element, the system can study pressure behavior of materials subjected to and during thermal exposure. Rapid pressure monitoring in µsec intervals allow for enhanced pressure determination in the time right before thermal explosion. The test data can be used for the validation of existing thermal models, particularly for introducing pressure terms. This report summarizes the efforts in performing small-scale safety tests, particle size measurements and conducting 7 ODTX/P-ODTX experiments on the Cl5 HMX material that Hunting uses for oil field applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi‐Scale Seismic Imaging of the Ridgecrest, CA, Region With Waveform Inversion of Regional and Dense Array Data

Abstract We develop an inversion procedure for deriving multi‐scale velocity models with waveform inversions of earthquake and ambient noise data at multi‐frequency bands recorded by regional and dense sensor configurations. The method is applied for the area around the 2019 Ridgecrest earthquake rupture zones, utilizing data recorded by regional stations and dense 2D and 1D arrays with station spacings of ∼5 km and ∼100 m, respectively. Starting with regional Vp, Vs models and locations of Ridgecrest aftershocks, the velocity models and event locations are improved iteratively by inversions of waveforms recorded by regional stations and the 2D array, using a minimum spectral element size of ∼600 m. Waveforms from local events recorded by dense 1D arrays across the M7.1 rupture zone with frequencies of up to 10 Hz are used to resolve small‐scale features of the rupture zone and shallow crust with a local spectral element size of 80 m. The refined models provide self‐consistent descriptions of the rupture zone and the shallow crust embedded in the regional structures. The results reveal pronounced low Vs and high Vp/Vs in the M6.4 and M7.1 rupture zones coinciding with concentrations of seismicity, and also around the Garlock fault and in several local basins. We also observe clear velocity contrasts across the Garlock fault with polarity reversals along strike and with depth. The obtained multi‐scale velocity models can be used to improve derivations of earthquake source properties, simulations of dynamic ruptures and ground motions, and the understanding of fault and tectonic processes in the region.

Geochemistry & Geophysics↗
DOE OSTI2021

Physics-informed machine learning of the Lagrangian dynamics of velocity gradient tensor

Reduced models describing the Lagrangian dynamics of the velocity gradient tensor (VGT) in homogeneous isotropic turbulence (HIT) are developed under the physics-informed machine learning (PIML) framework. We consider the VGT at both Kolmogorov scale and coarse-grained scale within the inertial range of HIT. Building reduced models requires resolving the pressure Hessian and subfilter contributions, which is accomplished by constructing them using the integrity bases and invariants of the VGT. The developed models can be expressed using the extended tensor basis neural network (TBNN) introduced by Ling et al. [J. Fluid Mech. 807, 155 (2016)]. Physical constraints, such as Galilean invariance, rotational invariance, and incompressibility condition, are thus embedded in the models explicitly. Our PIML models are trained on the Lagrangian data from a high-Reynolds number direct numerical simulation (DNS). To validate the results, we perform a comprehensive out-of-sample test. We observe that the PIML model provides an improved representation for the magnitude and orientation of the small-scale pressure Hessian contributions. Statistics of the flow, as indicated by the joint PDF of second and third invariants of the VGT, show good agreement with the “ground-truth” DNS data. A number of other important features describing the structure of HIT are reproduced by the model successfully. We have also identified challenges in modeling inertial range dynamics, which indicates that a richer modeling strategy is required. This helps us identify important directions for future research, in particular towards including inertial range geometry into the TBNN.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

FLAMINGO: combining kinetic SZ effect and galaxy–galaxy lensing measurements to gauge the impact of feedback on large-scale structure

Energetic feedback processes associated with accreting supermassive black holes can expel gas from massive haloes and significantly alter various measures of clustering on $\sim$Mpc scales, potentially biasing the values of cosmological parameters inferred from analyses of large-scale structure (LSS) if not modelled accurately. Here, we use the state-of-the-art FLAMINGO suite of cosmological hydrodynamical simulations to gauge the impact of feedback on large-scale structure by comparing to Planck + ACT stacking measurements of the kinetic Sunyaev–Zel’dovich (kSZ) effect of SDSS BOSS galaxies. We make careful like-with-like comparisons to the observations, aided by high precision KiDS and DES galaxy–galaxy lensing measurements of the BOSS galaxies to inform the selection of the simulated galaxies. In qualitative agreement with several recent studies using dark matter only simulations corrected for baryonic effects, we find that the kSZ effect measurements prefer stronger feedback than predicted by simulations which have been calibrated to reproduce the gas fractions of low redshift X-ray-selected groups and clusters. We find that the increased feedback can help to reduce the so-called $S_8$ tension between the observed and CMB-predicted clustering on small scales as probed by cosmic shear (although at the expense of agreement with the X-ray group measurements). However, the increased feedback is only marginally effective at reducing the reported offsets between the predicted and observed clustering as probed by the thermal SZ (tSZ) effect power spectrum and tSZ effect – weak lensing cross-spectrum, both of which are sensitive to higher halo masses than cosmic shear.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Scaling-up up-flow microbial electrolysis cells with a compact electrode configuration for continuous hydrogen production

Maintaining high current densities is a key challenge in scaling-up microbial electrolysis cell (MEC) reactors. In this study, a novel 10 L MEC reactor with a total electrode surface area > 1 m 2 was designed and evaluated to maximize the current density and H 2 recovery. Performances of the reactor suggest that the longitudinal structure with parallel vertical orientation of the electrodes encouraged high fluid mixing and the sheet metal electrode frames provided distributed electrical connection. Results also demonstrated that the electrode pairs located next to reactor walls decreased current density, as did separating the electrodes with separators. High volumetric H 2 production rate of 5.9 L/L/d was achieved at a volumetric current density of 970 A/m 3 (34 A/m 2 ). Furthermore, the observed current densities of the large reactor were accurately predicted based on the internal resistance analysis of small scale MECs (0.15 L), demonstrating the scalability of the single chamber MEC design.

08 HYDROGEN↗