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At least 379 records · Page 21

Simulation and analysis of the 3D double shock-induced recompression of spall using a hybrid PAGOSA with FLIP+MPM

In this work, an innovative hybrid algorithm PAGOSA with FLIP + MPM is first presented by coupling PAGOSA with the particle FLIP + MPM, and applied to systematically exploring the 3D recompression of spall induced by double-shock waves in ductile materials as the few existing studies are currently limited to the pure longitudinal recompression of spall, and ignore the 3D effects. This algorithm solves the difficulties the grid-based methods encounter when applied to capturing the fracture in material. We first validate the capabilities of PAGOSA with FLIP + MPM to predict different fracture/fragmentation cases by solving two benchmark problems and comparing with the analytical solutions or the experiment results. The convergences and the infinity-norm errors are also investigated. Subsequently, the 3D effects are demonstrated by simulating the spallation in material using PAGOSA with FLIP + MPM and comparing with those in the longitudinal cases. Additionally, some factors that affect the spallation with 3D effects are also discussed. Finally, the recompressions of spall in material with/without 3D effects are systematically simulated and analyzed. The recompression of spall driven by a high explosive is also simulated to show the ability of PAGOSA with FLIP + MPM to handle this kind of problem. The conditions that can lead to a recompression of spall are explored. Also, numerical results show that PAGOSA with FLIP + MPM can accurately predict different fracture cases, that the 3D effects play an important role in fracture/fragmentation, and the recompression of spall is very sensitive to the occurrence conditions, shows great differences when considering 3D effects in real applications. Moreover, the present hybrid method can be easily extended to other grid-based techniques employed for fracture in materials.

3D effects↗

Second gadolinium loading to Super-Kamiokande

The first loading of gadolinium (Gd) into Super-Kamiokande in 2020 was successful, and the neutron capture efficiency on Gd reached 50%. To further increase the Gd neutron capture efficiency to 75%, 26.1 tons of Gd 2 (SO 4 ) 3 ∙ 8H 2 O was additionally loaded into Super-Kamiokande (SK) from May 31 to July 4, 2022. As the amount of loaded Gd 2 (SO 4 ) 3 ∙ 8H 2 O was doubled compared to the first loading, the capacity of the powder dissolving system was doubled. We also developed new batches of gadolinium sulfate with even further reduced radioactive impurities. In addition, a more efficient screening method was devised and implemented to evaluate these new batches of Gd 2 (SO 4 ) 3 ∙ 8H 2 O. Following the second loading, the Gd concentration in SK was measured to be 333.5 ± 2.5 ppm via an Atomic Absorption Spectrometer (AAS). From the mean neutron capture time constant of neutrons from an Am/Be calibration source, the Gd concentration was independently measured to be 332.7 ± 6.8(sys.) ± 1.1(stat.) ppm, consistent with the AAS result. Furthermore, during the loading the Gd concentration was monitored continually using the capture time constant of each spallation neutron produced by cosmic-ray muons, and the final neutron capture efficiency was shown to become 1.5 times higher than that of the first loaded phase, as expected.

Gadolinium↗

Machine learning for detection of 3D features using sparse x-ray tomographic reconstruction

In many inertial confinement fusion (ICF) experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy suggests that there are three dimensional effects that may be significant. Sources of these effects include defects in the shells and defects in shell interfaces, the fill tube of the capsule, and the joint feature in double shell targets. Due to their ability to penetrate materials, x rays are used to capture the internal structure of objects. Methods such as computational tomography use x-ray radiographs from hundreds of projections, in order to reconstruct a three dimensional model of the object. In experimental environments, such as the National Ignition Facility and Omega-60, the availability of these views is scarce, and in many cases only consists of a single line of sight. Mathematical reconstruction of a 3D object from sparse views is an ill-posed inverse problem. These types of problems are typically solved by utilizing prior information. Neural networks have been used for the task of 3D reconstruction as they are capable of encoding and leveraging this prior information. We utilize half a dozen, different convolutional neural networks to produce different 3D representations of ICF implosions from the experimental data. Deep supervision is utilized to train a neural network to produce high-resolution reconstructions. These representations are used to track 3D features of the capsules, such as the ablator, inner shell, and the joint between shell hemispheres. Machine learning, supplemented by different priors, is a promising method for 3D reconstructions in ICF and x-ray radiography, in general.

Wolfe, Bradley T. (ORCID:0000000268301614)↗

Machine learning force field model for kinetic Monte Carlo simulations of itinerant Ising magnets

Here, we present a scalable machine learning (ML) framework for large-scale kinetic Monte Carlo (kMC) simulations of itinerant electron Ising systems. As the effective interactions between Ising spins in such itinerant magnets are mediated by conducting electrons, the calculation of energy change due to a local spin update requires solving an electronic structure problem. Such repeated electronic structure calculations could be overwhelmingly prohibitive for large systems. Assuming the locality principle, a convolutional neural network (CNN) model is developed to directly predict the effective local field and the corresponding energy change associated with a given spin update based on Ising configuration in a finite neighborhood. As the kernel size of the CNN is fixed at a constant, the model can be directly scalable to kMC simulations of large lattices. Our approach is reminiscent of the ML force field models widely used in first-principles molecular dynamics simulations. Applying our ML framework to a square-lattice double-exchange Ising model, we uncover unusual coarsening of ferromagnetic domains at low temperatures. Our work highlights the potential of ML methods for large-scale modeling of similar itinerant systems with discrete dynamical variables.

machine learning↗

Analysis of Double-Output CLL Resonant Converter for All-Electric UAV Applications

This paper presents a double-output resonant converter with high-frequency isolation for unmanned aerial vehicle (UAV) applications. The proposed topology is developed by using a full-bridge resonant inverter and double-output half-bridge active rectifiers. For the control system, a phase-shifted pulse width modulation (PS-PWM) method is utilized to adjusts the power flow among the output rectifiers in a wide voltage range regulation with a central control. The theoretical analysis of the converter is explored using the system model under different load conditions with constant frequency. The proposed system is validated with experimental results using 60 V input source and generating 0 - 100 V in each output at a full power of 500 W with 96% maximum efficiency in the laboratory experimental setup.

Asa, Erdem↗

Ultrahigh strength, modulus, and conductivity of graphitic fibers by macromolecular coalescence

Theoretical considerations suggest that the strength of carbon nanotube (CNT) fibers be exceptional; however, their mechanical performance values are much lower than the theoretical values. To achieve macroscopic fibers with ultrahigh performance, we developed a method to form multidimensional nanostructures by coalescence of individual nanotubes. The highly aligned wet-spun fibers of single- or double-walled nanotube bundles were graphitized to induce nanotube collapse and multi-inner walled structures. These advanced nanostructures formed a network of interconnected, close-packed graphitic domains. Their near-perfect alignment and high longitudinal crystallinity that increased the shear strength between CNTs while retaining notable flexibility. The resulting fibers have an exceptional combination of high tensile strength (6.57 GPa), modulus (629 GPa), thermal conductivity (482 W/m·K), and electrical conductivity (2.2 MS/m), thereby overcoming the limits associated with conventional synthetic fibers.

36 MATERIALS SCIENCE↗

Comprehensive Review of 2$β$ Decay Half-Lives

The double-beta (2β)-decay is the rarest nuclear physics process, and its experimental half-lives (T 1/2 ) exceed the age of the Universe from nine to fourteen orders of magnitude. Double-beta decay was observed, and its half-life was measured in 14 parent nuclei using direct, radiochemical, and geochemical methods. The decay observables are analyzed using the Evaluated Nuclear Structure Data File (ENSDF) procedures, and the recommended T 1/2 were deduced. Using the calculated values of phase factors, the effective nuclear matrix elements were extracted and compared with available data. Thousands of theoretical and experimental works have been dedicated to these topics in the last 85 years, and we present two data sets of recommended values to encapsulate the results.

2β-decay↗

4.3.1.1 TCF: Recovery of Lithium from Geothermal Brine with Lithium-Aluminum Layered Double Hydroxide Chloride Sorbents

Lithium has gained importance as a near-critical element for various energy storage applications, and efforts are ongoing to develop simple and cost-effective methods for lithium recovery. For instance, in a typical 50 MW geothermal power plant in the Salton Sea, United States, approximately 15,000 metric tons of Li 2 CO 3 or LiOH salts can be produced annually by recovering and converting LiCl from geothermal plant waste solutions. Currently, approximately 390 MW of geothermal power is generated in the Salton Sea Known Geothermal Resource Area, which corresponds to potential Li 2 CO 3 production of approximately 120,000 metric tons per year. This makes lithium recovery from geothermal brines a promising, potentially low-cost source of lithium, contributing significantly to the global supply chain.

15 GEOTHERMAL ENERGY↗

Metamagnetism and kinetic arrest in a long-range ferromagnetically ordered multicaloric double perovskite Y 2 CoMnO 6

A systematic magnetic study of the double perovskite oxide Y 2 CoMnO 6 (YCMO) has been performed. A monoclinic P21/n phase of YCMO was synthesized using a sol-gel method. Neutron diffraction (ND) measurements evidence the onset of long-range ferromagnetic (FM) ordering at TC ~ 76 K, which persists down to 5 K. The presence of 25% antisite disorder, estimated from the ND data, leads to the appearance of short-range antiferromagnetic (AFM) interactions. The existence of thermal hysteresis due to competing interactions between FM and AFM phases is observed in the M vs. T measurements. The pinning of magnetic domain walls at the Co/Mn antiphase boundaries results in a metamagnetic-like behavior. The field dependence of thermomagnetic irreversibility and the nature of virgin curves indicate the occurrence of a kinetic arrest phenomenon, which is further verified via cooling and heating of the system in an unequal fields (CHUF) protocol. In full agreement with the ND data, a detailed analysis of critical exponents near the paramagnetic (PM)-FM phase transition also establishes YCMO as a long-range interacting mean-field system. A close examination of the temperature- and field-dependent magnetic entropy change yields an in-depth understanding of coexisting magnetically ordered and disordered phases in YCMO, leading to a comprehensive magnetic phase diagram of this multifunctional double perovskite system.

36 MATERIALS SCIENCE↗

Coupled cluster benchmarks of large noncovalent complexes: The L7 dataset as well as DNA–ellipticine and buckycatcher–fullerene

In this work, benchmark binding energies for dispersion-bound complexes in the L7 dataset, the DNA–ellipticine intercalation complex, and the buckycatcher–C60 complex with 120 heavy atoms using a focal-point method based on the canonical form of second-order Møller−Plesset theory (MP2) and the domain based local pair natural orbital scheme for the coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] extrapolated to the complete basis set (CBS) limit are reported. This work allows for increased confidence given the agreement with respect to values recently obtained using the local natural orbital CCSD(T) for L7 and the canonical CCSD(T)/CBS result for the coronene dimer (C2C2PD). Therefore, these results can be considered pushing the CCSD(T)/CBS binding benchmark to the hundred-atom scale. The disagreements between the two state-of-the-art methods, CCSD(T) and fixed-node diffusion Monte Carlo, are substantial with at least 2.0 (∼10%), 1.9 (∼5%), and 10.3 kcal/mol (∼25%) differences for C2C2PD in L7, DNA–ellipticine, and buckycatcher–C60, respectively. Such sizable discrepancy above “chemical accuracy” for large noncovalent complexes indicates how challenging it is to obtain benchmark binding interactions for systems beyond small molecules, although the three up-to-date density functionals, PBE0+D4, ωB97M-V, and B97M-V, agree better with CCSD(T) for these large systems. In addition to reporting these values, different basis sets and various CBS extrapolation parameters for Hartree–Fock and MP2 correlation energies were tested for the first time in large noncovalent complexes with the goal of providing some indications toward optimal cost effective routes to approach the CBS limit without substantial loss in quality.

Ballesteros, Francisco (ORCID:0000000325732307)↗

Quantifying Energetic and Entropic Pathways in Molecular Systems

When examining dynamics occurring at nonzero temperatures, both energy and entropy must be taken into account to describe activated barrier crossing events. Furthermore, good reaction coordinates need to be constructed to describe different metastable states and the transition mechanisms between them. Here we use a physics-based machine learning method called state predictive information bottleneck (SPIB) to find nonlinear reaction coordinates for three systems of varying complexity. SPIB is able to correctly predict an entropic bottleneck for an analytical flat-energy double-well system and identify the entropy- and energy-dominated pathways for an analytical four-well system. Lastly, for a simulation of benzoic acid permeation through a lipid bilayer, SPIB is able to discover the entropic and energetic barriers to the permeation process. Given these results, we thus establish that SPIB is a reasonable and robust method for finding the important entropy, energy, and enthalpy barriers in physical systems, which can then be used to enhance the understanding and sampling of different activated mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Removing Fluoride from Double Four-Membered Rings Yielding Defect-Free Zeolites under Mild Conditions Using Ozone

We have investigated ozone treatment of as-made LTA zeolites under mild temperature conditions (175 °C) using experiments and periodic DFT as a method of energy savings and engineering defects such as silanol nests in comparison with conventional calcination at 550 °C. We have studied ozone treatment on LTA samples synthesized with 1,2-dimethyl-3-(4-methylbenzyl) imidazolium (denoted as “BULKY”) as the primary organic structure-directing agent (OSDA) and with various amounts of tetramethylammonium (TMA) as a secondary OSDA. Ozone treatment of LTA-BULKY at 175 °C was found to give defect-free, pristine LTA materials as determined by 29 Si NMR, 13 C NMR, Raman spectra, and DFT to assign the spectra. This represents a significant and unexpected finding: that fluoride ions can be completely removed from double four-membered rings (D4Rs) under such mild conditions. Furthermore, ozone treatment of LTA-BULKY-TMA samples removed BULKY but left behind TMA/F, giving a new and more diverse structural landscape of Si environments in LTA. Ab initio MetaDynamics calculations provide pathways with relatively low barriers, explaining how fluoride ions can be removed from D4Rs, leaving behind defect-free LTA materials under mild conditions.

36 MATERIALS SCIENCE↗

Demonstration of neutrinoless double beta decay searches in gaseous xenon with NEXT

The NEXT experiment aims at the sensitive search of the neutrinoless double beta decay in 136 Xe, using high-pressure gas electroluminescent time projection chambers. The NEXT-White detector is the first radiopure demonstrator of this technology, operated in the Laboratorio Subterráneo de Canfranc. Achieving an energy resolution of 1% FWHM at 2.6 MeV and further background rejection by means of the topology of the reconstructed tracks, NEXT-White has been exploited beyond its original goals in order to perform a neu- trinoless double beta decay search. The analysis considers the combination of 271.6 days of 136 Xe-enriched data and 208.9 days of 136Xe-depleted data. A detailed background modeling and measurement has been developed, ensuring the time stability of the radiogenic and cosmogenic contributions across both data samples. Limits to the neutrinoless mode are obtained in two alternative analyses: a background-model-dependent approach and a novel direct background-subtraction technique, offering results with small dependence on the background model assumptions. With a fiducial mass of only 3.50 ± 0.01 kg of 136 Xe-enriched xenon, 90% C.L. lower limits to the neutrinoless double beta decay are found in the $T^{0v}_{1/2} > 5.5 \times 10^{23} - 1.3 \times 10^{24}$ yr range, depending on the method. The presented techniques stand as a proof-of-concept for the searches to be implemented with larger NEXT detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Computation of high-frequency magnetoelastic waves in layered materials

Here, the direct calculation of magnetoelastic wave dispersion in layered media is presented using an efficient, accurate computational technique. The governing, coupled equations for elasticity and magnetism, the Navier and Landau-Lifshitz equations, respectively, are linearized to form a quadratic eigenvalue problem that determines a complex web of wave-number–frequency dispersion branches and their corresponding mode profiles. Numerical discretization of the eigenvalue problem via a spectral collocation method (SCM) is employed to determine the complete dispersion maps for both a single, finite-thickness magnetic layer and a finite magnetic-nonmagnetic double-layer. The SCM, previously used to study elastic waves in nonmagnetic media, is fast, accurate, and adaptable to a variety of sample configurations and geometries. Emphasis is placed on the extremely high-frequency regimes being accessed in ultrafast magnetism experiments. The dispersion maps and modes provide insight into how energy propagates through the coupled system, including how energy can be transferred between elastic- and magnetic-dominated waves as well as between different layers. The numerical computations for a single layer are further understood by a simplified analytical calculation in the high-frequency, exchange-dominated regime where the resonance condition required for energy exchange (an anticrossing) between quasi-elastic and quasi-magnetic dispersion branches is determined. Nonresonant interactions are shown to be well approximated by the dispersion of uncoupled elastic and magnetic waves. The methods and results provide fundamental theoretical tools to model and understand current and future magnetic devices powering spintronic innovation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantitatively controlled electrophoretic deposition of nanocrystal films from non-aqueous suspensions

This study presents a novel method to correlate the mass and charge transfer kinetics during the electrophoretic deposition of nanocrystal films by using a purpose-built double quartz crystal microbalance combined with simultaneous current-measurement. Our data support a multistep process for film formation: generation of charged nanocrystal flux, charge transfer at the electrode, and polarization of neutral nanocrystals near the electrode surface. The polarized particles are then subject to dielectrophoretic forces that reduce diffusion away from the interface, generating a sufficiently high neutral particle concentration at the interface to form a film. The correlation of mass and charge transfer enables quantification of the nanocrystal charge, the fraction of charged nanocrystals, and the initial sticking coefficient of the particles. These quantities permit calculation of the film thickness, providing a theoretical basis for using concentration and voltage as process parameters to grow films of targeted thicknesses.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Bacteria-mediated dsRNA delivery for mosquito-borne virus control

Mosquito-borne viruses represent an increasing global public health threat, exacerbated by urbanisation and climate change, thus making effective mosquito control essential. RNA interference (RNAi), a sequence-specific gene regulation mechanism, can be a flexible vector control tool. RNAi effectors, such as double-stranded RNA (dsRNA), can target mosquito genes or the viruses they carry, disrupting development or suppressing infection. However, current RNAi delivery methods are ineffective. Engineered bacterial symbionts offer a promising alternative for delivery, as they can produce dsRNA directly within mosquitoes. However, bacterial RNAi delivery in mosquitoes remains underexplored. We review emerging genetic tools, insights from RNAi and bacteria–mosquito interactions to outline priorities for realising bacterial RNAi as an efficient and sustainable vector control strategy.

Biological and medical sciences↗

Helium droplet infrared spectroscopy of the butyl radicals

Butyl radicals (n-, s-, i-, and tert-butyl) are formed from the pyrolysis of stable precursors (1-pentyl nitrite, 2-methyl-1-butyl nitrite, isopentyl nitrite, and azo-tert-butane, respectively). The radicals are doped into a beam of liquid helium droplets and probed with infrared action spectroscopy from 2700 to 3125 cm -1 , allowing for a low temperature measurement of the CH stretching region. The presence of anharmonic resonance polyads in the 2800–3000 cm -1 region complicates its interpretation. To facilitate spectral assignment, the anharmonic resonances are modeled with two model Hamiltonian approaches that explicitly couple CH stretch fundamentals to HCH bend overtones and combinations: a VPT2+K normal mode model based on coupled-cluster with single, double, and perturbative triple excitations [CCSD(T)] quartic force fields and a semi-empirical local mode model. Both of these computational methods provide generally good agreement with the experimental spectra.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

53BP1 Repair Kinetics for Prediction of In Vivo Radiation Susceptibility in 15 Mouse Strains

We present a novel mathematical formalism to predict the kinetics of DNA damage repair after exposure to both low- and high-LET radiation (X rays; 350 MeV/n 40 Ar; 600 MeV/n 56 Fe). Our method is based on monitoring DNA damage repair protein 53BP1 that forms radiation-induced foci (RIF) at locations of DNA double-strand breaks (DSB) in the nucleus and comparing its expression in primary skin fibroblasts isolated from 15 mice strains. We previously reported strong evidence for clustering of nearby DSB into single repair units as opposed to the classic "contact-first" model where DSB are considered immobile. Here we apply this clustering model to evaluate the number of remaining RIF over time. We also show that the newly introduced kinetic metrics can be used as surrogate biomarkers for in vivo radiation toxicity, with potential applications in radiotherapy and human space exploration. In particular, we observed an association between the characteristic time constant of RIF repair measured in vitro and survival levels of immune cells collected from irradiated mice. Moreover, the speed of DNA damage repair correlated not only with radiation-induced cellular survival in vivo, but also with spontaneous cancer incidence data collected from the Mouse Tumor Biology database, suggesting a relationship between the efficiency of DSB repair after irradiation and cancer risk.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗