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At least 1,117 records · Page 62

Search for dark matter produced in association with a Higgs boson decaying to tau leptons at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for dark matter produced in association with a Higgs boson in final states with two hadronically decaying τ-leptons and missing transverse momentum is presented. The analysis uses 139 fb -1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV collected by the ATLAS experiment at the Large Hadron Collider between 2015 and 2018. No evidence of physics beyond the Standard Model is found. The results are interpreted in terms of a 2HDM+a model featuring two scalar Higgs doublets and a pseudoscalar singlet field. Exclusion limits on the parameters of the model in selected benchmark scenarios are derived at 95% confidence level. Model-independent limits are also set on the visible cross-section for processes beyond the Standard Model producing missing transverse momentum in association with a Higgs boson decaying into τ-leptons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for top squark pair production in final states with one isolated lepton, jets, and missing transverse momentum in √s = 8 TeV pp collisions with the ATLAS detector

The results of a search for top squark (stop) pair production in final states with one isolated lepton, jets, and missing transverse momentum are reported. The analysis is performed with proton-proton collision data at √s = 8 TeV collected with the ATLAS detector at the LHC in 2012 corresponding to an integrated luminosity of 20 fb –1 . The lightest supersymmetric particle (LSP) is taken to be the lightest neutralino which only interacts weakly and is assumed to be stable. The stop decay modes considered are those to a top quark and the LSP as well as to a bottom quark and the lightest chargino, where the chargino decays to the LSP by emitting a W boson. A wide range of scenarios with different mass splittings between the stop, the lightest neutralino and the lightest chargino are considered, including cases where the W bosons or the top quarks are off-shell. Decay modes involving the heavier charginos and neutralinos are addressed using a set of phenomenological models of supersymmetry. No significant excess over the Standard Model prediction is observed. A stop with a mass between 210 and 640 GeV decaying directly to a top quark and a massless LSP is excluded at 95% confidence level, and in models where the mass of the lightest chargino is twice that of the LSP, stops are excluded at 95% confidence level up to a mass of 500 GeV for an LSP mass in the range of 100 to 150 GeV. As a result, stringent exclusion limits are derived for all other stop decay modes considered, and model-independent upper limits are set on the visible cross-section for processes beyond the Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spatially dependent embedded self-shielding method for nonuniform temperature distribution

The embedded self-shielding method (ESSM) is simple and robust, and applicable to any geometrical configuration to account for resonance self-shielding by performing fixed source transport calculations. ESSM is very similar to the subgroup method, which has been successful in the MPACT neutronics code developed by CASL. The subgroup method introduces errors in a least-squares fitting process that is used to generate subgroup quadrature sets and cannot be applied to thermal energy groups, as ESSM introduces error for spatially dependent self-shielded cross sections inside the fuel. This study focused on integrating the conventional ESSM with an improved Stoker-Weiss method to obtain spatially dependent resonance self-shielded cross sections for a nonuniform fuel temperature distribution. Here, the proposed method would serve as a substitute for the subgroup method in high fidelity simulations using CASL’s VERA. Benchmark results show that this new, spatially dependent ESSM (SDESSM) is an appropriate candidate to replace the subgroup method.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Life cycle greenhouse gas emissions of hydrogen fuel production from chlor-alkali processes in the United States

By-product hydrogen from chlor-alkali processes can help meet the increasing demand for hydrogen fuel in early fuel cell electric vehicle markets (e.g., California) in the U.S. Hydrogen produced from chlor-alkali plants is typically combusted for process heat on site, vented to the atmosphere (i.e., wasted), or sold to the external merchant hydrogen market. Whether it is combusted, vented, or sold as a commodity, relevant information is lacking as to the life-cycle environmental benefits or trade-offs of using by-product hydrogen from chlor-alkali plants. A life-cycle analysis framework was employed to evaluate well-to-gate greenhouse gas (GHG) emissions associated with by-product hydrogen from chlor-alkali processes in comparison with hydrogen from the conventional centralized natural gas steam methane reforming (central SMR) pathway. U.S.-specific, plant-by-plant, and up-to-date chlor-alkali production characteristics were incorporated into the analysis. In addition to the venting and combustion scenarios, to deal with the multi-functionality of the chlor-alkali processes that simultaneously produce chlorine, sodium hydroxide, and hydrogen, two different co-product allocation strategies were adopted mass allocation and market value allocation. It was estimated that by-product hydrogen production from chlor-alkali processes creates 1.3-9.8 kg CO 2 e/kg H 2 of life-cycle GHG emissions on average, which is 20-90% less than the conventional central SMR pathway. The results vary with co-product treatment scenarios, regional electric grid characteristics, on-site power generation, product prices, and hydrogen yield. Despite the variations in the results, it was concluded that the life-cycle GHG emission reduction benefits of using by-product hydrogen from chlor-alkali processes are robust. In conclusion, with a diverse set of scenario analyses, the study developed a comprehensive and detailed life-cycle GHG emissions inventory of the chlor-alkali by-product hydrogen pathway and quantified sensitivity indices in the context of different assumptions and input parameter values.

08 HYDROGEN↗

ExaCA: A performance portable exascale cellular automata application for alloy solidification modeling

Modeling the as-solidified grain structures that form during alloy processing is a critical component in understanding process-property relationships, particularly for additive manufacturing (AM) where grain structure is very sensitive to processing conditions. While cellular automata (CA)-based models have proven able to predict aspects of microstructure for several alloys and AM process conditions, long run times and large resource sets required limit the utility and the problem size to which existing CA models can be applied. As part of the ExaAM project, an initiative within the Exascale Computing Project (ECP) to develop, test, and optimize an exascale-capable coupled and self-consistent model of AM parts, we developed ExaCA (https://github.com/LLNL/ExaCA) for the liquid–solid phase transformation in the wake of AM melt pools. The CA-based code is parallelized using MPI and the Kokkos programming model, the latter enabling simulation on both CPUs and GPUs within a single-source implementation. Here, we detail the steps taken to transform a baseline, MPI-based CA code into one that is performant on CPUs and GPUs. Performance testing of ExaCA on Summit (a pre-exascale machine at Oak Ridge National Laboratory) was used to quantify CPU–GPU speedup comparing with equal numbers of nodes. Testing showed comparable CPU performance to the MPI-only CA code and a 5-20x speedup when running AM-based test problems using GPUs. The improved performance of CA through GPU utilization and the performance portable nature of ExaCA will enable accurate part-scale modeling by harnessing the power of current and future generations of high performance computing resources. Future work will include improving the strong scaling of ExaCA on GPUs by reducing load imbalance associated with the locality of the problem, and continuing performance optimization across exascale hardware.

36 MATERIALS SCIENCE↗

LAVA 1.0: A general-purpose python toolkit for calculation of material properties with LAMMPS and VASP

Here, we introduce LAVA, a general-purpose python toolkit to provide user-friendly and high throughput calculations for material properties using both LAMMPS and VASP. It contains a set of classes as well as pre-processing and post-processing functions to prepare, execute and extract information from LAMMPS/VASP simulations. An overview of the program structure is provided. The current version contains modules to calculate elastic and mechanical properties such as lattice constant, cohesive energy, cold curve, elastic constants, bulk and shear modulus, volume conserving/non-conserving deformation path, vacancy/interstitial formation energy, surface energy, stacking fault energy, melting point, radial distribution function, and thermal expansion. These functionalities are demonstrated for different interatomic potentials and DFT calculations in Al.

36 MATERIALS SCIENCE↗

Blockchain Enabled Intelligence of Federated Systems (BELIEFS): An attack-tolerant trustable distributed intelligence paradigm

In this article, a Blockchain Enabled Intelligence of Federated Systems (BELIEFS) is proposed to conduct cooperative control for the multi-regional large-scale power system with a multi-agents system (MAS). By establishing a two levels blockchain, each regional AI agent can simultaneously manage intra-regional controllers and cooperate with other AI agents. Under the consensus mechanism, the agents, which respectively conducted distributed deep reinforcement learning (DDRL) algorithm in multi-regions, can have the tolerant capability of malicious attacks in their training process. The demonstration of the proposed approach is within a multi-regional large-scale interconnected power system. Under the mode of "centralized dispatching and hierarchical management", this article aims to definite a mathematical model to deal with the control problem of the power systems. With the comparison experiments, the effectiveness and efficiency of our proposed method in the training process are verified. In addition, malicious attacks are set on the main chain and shard chains to verify the attack-tolerant capability. We expect that such approach and results can suggest a new paradigm of attack-tolerant trustable distributed AI deployment.

97 MATHEMATICS AND COMPUTING↗

DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters

Ensemble-based Data Assimilation (EDA), based on the Monte Carlo approach, has been effectively applied to estimate model parameters through inverse modeling in subsurface flow and transport problems. However, implementation of EDA approach involves a complicated workflow that include setting up and executing ensemble forward model simulations, processing observations and model simulation results for parameter updates, and repeat for sequential or iterative EDA. To facilitate the management of such workflow and lower the barriers for adopting EDA-based parameter estimation in subsurface science, we develop a generic software frame-work linking the Data Assimilation Research Testbed (DART) with a massively parallel subsurface FLOw and TRANsport code PFLOTRAN. The new DART-PFLOTRAN leverages both the core data assimilation engines in DART and the computational power afforded by PFLOTRAN. In addition to the standard smoother and filtering options, DART-PFLOTRAN enables an iterative EDA workflow based on the Ensemble Smoother for Multiple Data Assimilation method (ES-MDA) to improve estimation accuracy for nonlinear forward problems. Here, we verify the implementation of ES-MDA in DART-PFLOTRAN using two synthetic cases designed to estimate static permeability and dynamic exchange fluxes across the riverbed, respectively, from continuous temperature measurements made across a depth profile. One-dimensional hydro-thermal simulations are performed in both cases to relate temperature responses with the parameters of interest. In the case of estimating dynamic parameters, we demonstrate the flexibility of DART-PFLOTRAN in automating sequential ES-MDA workflow, which will significantly reduce the time researchers spend on managing complex workflows in similar applications. Both studies yield accurate estimations of the parameters compared to their synthetic truth, while ES-MDA leads to more accurate estimation when a high level of nonlinearity exist between observed responses and unknown parameters. With a code base in Python and Fortran, DART-PFLOTRAN paves the way for applications in large-scale subsurface inverse modeling by automating the complex workflow of sequential ES-MDA that can be executed on various computing platforms.

97 MATHEMATICS AND COMPUTING↗

Incorporating radioactive decay into charging and coagulation of multicomponent radioactive aerosols

Compositional changes by the decay of radionuclides in radioactive aerosols can influence their charging state, coagulation frequency and size distribution throughout their atmospheric lifetime. The importance of such effects is unknown as they have not been considered in microphysical and global radioactivity transport studies to date. Here, we explore the effects of compositional changes on the charging efficiency and coagulation rates of aerosols using a set of kinetic equations that couple all relevant processes (decay, charging and coagulation) and their evolution over time. Compared to a coupled aggregation-tracer model for the prediction of the radioactive composition of particulates undergoing coagulation, our kinetic approach can provide similar results using much less central processing unit time. Altogether with other considerations, our approach is computational efficient enough to allow implementation in 3D atmospheric transport models. The decay of radionuclides and the production of decay products within radioactive aerosols may significantly affect the aerosol charging rates, and either hinder or promote the coagulation of multicomponent radioactive aerosols. Our results suggest that radiological phenomena occurring within radioactive aerosols, as well as subsequent effects on aerosol microphysics, should be considered in regional and global models to more accurately predict radioactivity transport in the atmosphere in case of a nuclear plant accident.

54 ENVIRONMENTAL SCIENCES↗

Zinc oxide nanoparticles induce migration and adhesion of monocytes to endothelial cells and accelerate foam cell formation

Metal oxide nanoparticles are widely used in industry, cosmetics, and biomedicine. However, the effects of exposure to these nanoparticles on the cardiovascular system remain unknown. The present study investigated the effects of nanosized TiO{sub 2} and ZnO particles on the migration and adhesion of monocytes, which are essential processes in atherosclerogenesis, using an in vitro set-up of human umbilical vein endothelial cells (HUVECs) and human monocytic leukemia cells (THP-1). We also examined the effects of exposure to nanosized metal oxide particles on macrophage cholesterol uptake and foam cell formation. The 16-hour exposure to ZnO particles increased the level of monocyte chemotactic protein-1 (MCP-1) and induced the migration of THP-1 monocyte mediated by increased MCP-1. Exposure to ZnO particles also induced adhesion of THP-1 cells to HUVECs. Moreover, exposure to ZnO particles, but not TiO{sub 2} particles, upregulated the expression of membrane scavenger receptors of modified LDL and increased cholesterol uptake in THP-1 monocytes/macrophages. In the present study, we found that exposure to ZnO particles increased macrophage cholesterol uptake, which was mediated by an upregulation of membrane scavenger receptors of modified LDL. These results suggest that nanosized ZnO particles could potentially enhance atherosclerogenesis and accelerate foam cell formation. - Highlights: • Effects of metal oxide nanoparticles on foam cell formation were investigated. • Exposure to ZnO nanoparticles induced migration and adhesion of monocytes. • Exposure to ZnO nanoparticles increased macrophage cholesterol uptake. • Expression of membrane scavenger receptors of modified LDL was also increased. • These effects were not observed after exposure to TiO{sub 2} nanoparticles.

60 APPLIED LIFE SCIENCES↗

Combinatorial Exploration and Mapping of Phase Transformation in a Ni–Ti–Co Thin Film Library

Combinatorial synthesis and high-throughput characterization of a Ni–Ti–Co thin film materials library are reported for exploration of reversible martensitic transformation. The library was prepared by magnetron co-sputtering, annealed in vacuum at 500 °C without atmospheric exposure, and evaluated for shape memory behavior as an indicator of transformation. Composition, structure, and transformation behavior of the 177 pads in the library were characterized using high-throughput wavelength dispersive spectroscopy (WDS), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and four-point probe temperature-dependent resistance (R(T)) measurements. A new, expanded composition space having phase transformation with low thermal hysteresis and Co > 10 at. % is found. Unsupervised machine learning methods of hierarchical clustering were employed to streamline data processing of the large XRD and XPS data sets. Through cluster analysis of XRD data, we identified and mapped the constituent structural phases. Finally, composition–structure–property maps for the ternary system are made to correlate the functional properties to the local microstructure and composition of the Ni–Ti–Co thin film library.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing the reaction mechanisms of Li–O2 batteries using environmental transmission electron microscopy

The capacity, Coulombic efficiency, rate, and cyclability of a Li-O2 battery critically depend on the electrode reaction mechanism and the structure/morphology of the reaction product as well as their spatial and temporal evolution1-8, which are all further complicated by the choice of different electrolyte. For the case of aprotic cell, the discharge product, Li2O2, is formed through solution and surface mechanisms9,10, but little is known on the formation mechanism of the perplexing morphology of the reaction product11-15. For the case of Li-O2 battery using solid electrolyte, neither electrode reaction mechanism nor the nature of the reaction production is known. Herein, we reveal the full cycle reaction pathway for Li-O2 batteries and its correlation with the nature of the reaction product. Using an aberration-corrected environmental TEM under oxygen environment, we captured, for the first time, the morphology and phase evolution on the carbon nanotube (CNT) cathode of a working solid-state Li-O2 nano-battery16 and directly correlated these features with electrochemical reaction. We found that the oxygen reduction reaction on CNTs initially produces LiO2, which subsequently evolves to Li2O2 and O2 through disproportionation reaction. Surprisingly it is just the releasing of O2 that inflates the particles to a hollow structure with a Li2O outer surface layer and Li2O2 inner-shell, demonstrating that, in general, accommodation of the released O2 coupled with the Li+ ion diffusion and electron transport paths across both spatial and temporal scales critically governs the morphology of the discharging/charging product in Li-O2 system. We anticipate that the direct observation of Li-O2 reaction mechanisms and their correlation with the morphology of the reaction product set foundation for quantitative understanding/modeling of the electrochemical processes in the Li-O2 system, enabling rational design of both solid-state and aprotic Li-O2 batteries.

25 ENERGY STORAGE↗

An europium( iii ) diglycolamide complex: insights into the coordination chemistry of lanthanides in solvent extraction

The synthesis, stoichiometry, and structural characterization of a homoleptic, cationic europium(III) complex with three neutral tetraalkyldiglycolamide ligands are reported. The tri(bismuth tetrachloride)tris(N,N,N',N'-tetra-n-octyldiglycolamide)Eu salt, [Eu(TODGA)3][(BiCl4)3] obtained from methanol was examined by Eu L3-edge X-ray absorption spectroscopy (XAS) to reveal an inner-sphere coordination of Eu3+ that arises from 9 O atoms and two next-nearest coordination spheres that arise from 6 carbon atoms each. A structural model is proposed in which each TODGA ligand with its O[double bond, length as m-dash]Ca–Cb–O–Cb–Ca[double bond, length as m-dash]O backbone acts as a tridentate O donor, where the two carbonyl O atoms and the one ether O atom bond to Eu3+. Given the structural rigidity of the tridentate coordination motif in [Eu(TODGA)3]3+ with six 5-membered chelate rings, the six Eu–Ca and six Eu–Cb interactions are readily resolved in the EXAFS (extended X-ray absorption fine structure) spectrum. The three charge balancing [BiCl4]- anions are beyond the cationic [Eu(TODGA)3]3+ cluster in an outer sphere environment that is too distant to be detected by XAS. Despite their sizeable length and propensity for entanglement, the four n-octyl groups of each TODGA (for a total of twelve) do not perturb the Eu3+ coordination environment over that seen from previously reported single-crystal structures of tripositive lanthanide (Ln3+) complexes with tetraalkyldiglycolamide ligands (of the same 1 : 3 metal-to-ligand ratio stoichiometry) but having shorter i-propyl and i-butyl groups. The present results set the foundation for understanding advanced solvent extraction processes for the separation of the minor, tripositive actinides (Am, Cm) from the Ln3+ ions in terms of the local structure of Eu3+ in a solid state coordination complex with TODGA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The impact of stacking and phonon environment on energy transfer in organic chromophores: computational insights

Energy transfer in organic materials is extensively studied due to many applications in optoelectronics. The electronic and vibrational relaxations within molecular assemblies can be influenced by stacking arrangements or additions of a backbone that unites them. Here, we present the computational study of the photoexcitation dynamics of a perylene diimide monomer, and face-to-face stacked dimer and trimer. By using non-Energy transfer in organic materials is extensively studied due to many applications in optoelectronics. The electronic and vibrational relaxations within molecular assemblies can be influenced by stacking arrangements or additions of a backbone that unites them. In this work, we present the computational study of the photoexcitation dynamics of a perylene diimide monomer, and face-to-face stacked dimer and trimer. By using non-adiabatic excited-state molecular dynamics simulations, we show that the non-radiative relaxation is accelerated with the number of stacked molecules. This effect is explained by differences in the energy splitting between states that impacts their corresponding nonadiabatic couplings. Additionally, our analysis of the vibronic dynamics reveals that the passage through the different conical intersections that participate in the relaxation of the stacked systems, activate a positive feedback mechanism. This effect involves a narrow set of vibrational normal modes that accelerate the process by increasing the efficiency of its vibronic dynamics. In contrast, an addition of a biologically inspired backbone slows down the relaxation rate due to its participation in the vibronic dynamics of the molecular stacking arrangements. Our results suggest the stacking arrangements and common backbones as strategies to modulate the efficiency of electronic and vibrational relaxation of diimide-based systems and other molecular aggregates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

State-resolved differential and integral cross sections for the Ne + H{sub 2}{sup +} (v = 0–2, j = 0) → NeH{sup +} + H reaction

State-to-state quantum dynamic calculations for the proton transfer reaction Ne + H{sub 2}{sup +} (v = 0–2, j = 0) are performed on the most accurate LZHH potential energy surface, with the product Jacobi coordinate based time-dependent wave packet method including the Coriolis coupling. The J = 0 reaction probabilities for the title reaction agree well with previous results in a wide range of collision energy of 0.2-1.2 eV. Total integral cross sections are in reasonable agreement with the available experiment data. Vibrational excitation of the reactant is much more efficient in enhancing the reaction cross sections than translational and rotational excitation. Total differential cross sections are found to be forward-backward peaked with strong oscillations, which is the indication of the complex-forming mechanism. As the collision energy increases, state-resolved differential cross section changes from forward-backward symmetric peaked to forward scattering biased. This forward bias can be attributed to the larger J partial waves, which makes the reaction like an abstraction process. Differential cross sections summed over two different sets of J partial waves for the v = 0 reaction at the collision energy of 1.2 eV are plotted to illustrate the importance of large J partial waves in the forward bias of the differential cross sections.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Inverse-designed broadband low-loss grating coupler on thick lithium-niobate-on-insulator platform

A grating coupler on 700-nm-thick Z-cut lithium-niobate-on-insulator platform with high coupling efficiency, large bandwidth, and high fabrication tolerance is designed and optimized by inverse design method. The optimized grating coupler is fabricated with a single set of e-beam lithography and etching process, and it is experimentally characterized to possess peak coupling efficiency of −3.8 dB at 1574.93 nm, 1 dB bandwidth of 71.7 nm, and 3 dB bandwidth of over 120 nm, respectively.

Physics↗

artdaq : DAQ software development made simple

For a few years now, the artdaq data acquisition software toolkit has provided numerous experiments with ready-to-use components which allow for rapid development and deployment of DAQ systems. Developed within the Fermilab Scientific Computing Division, artdaq provides data transfer, event building, run control, and event analysis functionality. This latter feature includes built-in support for the art event analysis framework, allowing experiments to run art modules for real-time filtering, compression, disk writing and online monitoring; as art, also developed at Fermilab, is also used for online analysis, a major advantage of artdaq is that it allows developers to easily switch between developing online and online software. artdaq continues to be improved. Support for an alternate mode of running whereby data from some subdetector components are only streamed if requested has been added; this option will reduce unnecessary DAQ throughput. Real-time reporting of DAQ metrics has been implemented, along with the flexibility to choose the format through which experiments receive the reports; these formats include the Ganglia, Graphite and syslog software packages, along with at ASCII files. Additionally, work has been performed investigating more flexible modes of online monitoring, including the capability of being able to run multiple online monitoring processes on different hosts, each running its own set of art modules. Finally, a web-based GUI interface through which users can configure details of their DAQ system has been implemented, increasing the ease of use of the system. Already successfully deployed on the LArIAT, DarkSide-50, DUNE 35ton and Mu2e experiments, artdaq will be employed for SBND and is a strong candidate for use on ICARUS and protoDUNE. With each experiment comes new ideas for how artdaq can be made more flexible and powerful; the above improvements will be described, along with potential ideas for the future.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

CaloScore v2: single-shot calorimeter shower simulation with diffusion models

Diffusion generative models are promising alternatives for fast surrogate models, producing high-fidelity physics simulations. However, the generation time often requires an expensive denoising process with hundreds of function evaluations, restricting the current applicability of these models in a realistic setting. In this work, we report updates on the CaloScorearchitecture, detailing the changes in the diffusion process, which produces higher quality samples, and the use of progressive distillation, resulting in a diffusion model capable of generating new samples with a single function evaluation. Here we demonstrate these improvements using the Calorimeter Simulation Challenge 2022 dataset.

47 OTHER INSTRUMENTATION↗