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At least 433 records · Page 24

Effect of reaction media on hydrogenolysis of polyethylene plastic waste: Polymer-surface interactions in small alkane/polymer blends

The polymer reaction media and its properties can be altered by recycling a fraction of liquid products or adding alkane solvents. Less clear is whether this strategy affects hydrogenolysis. Herein, we investigated the effect of short-chain alkanes C n consisting of n carbons (n=8, 16, and 32) on the upcycling of high-density polyethylene (HDPE) plastic waste to lubricant-range products over Ru/TiO 2 catalysts by multiscale simulations and experiments. First, we trained a force field for polymer/surface interactions on a Ru 22 nanoparticle (NP) supported on TiO 2 . Using replica exchange molecular dynamics simulations, we studied the effect of small hydrocarbons on the adsorption of a surrogate polymer, C 142 , on the catalyst. We found segregation of long chains (C 142 ) at the catalyst surface due to the enthalpy gained by adsorbing more C-C bonds of the long chains, compensating for entropic losses upon adsorption. Short-chain molecules decrease the adsorbed carbons of long chains on the Ru NP due to blocking Ru active sites. Compared to the bulk chains, competitive adsorption results in a broader, heavy-tailed distribution of end-to-end distance of adsorbed chains. Our experiments demonstrated that catalyst activity declines significantly beyond simple dilution due to changes in polymer adsorption, and tuning the reaction media by creating suitable blends impacts hydrogenolysis. Density distributions for a 50:50%wt mixture of PP and PE show that PE chains are segregated at the surface, so they are prone to C-C bond breaking much faster than PP chains. H/D exchange experiments show preferential deuteration of PE, while CH 3 groups of PP remain undeuterated. Furthermore, this may be explained by the preferential sorption of PE over PP, leading to specific distribution in the polymer blend.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulated effect of edge plasma density parameters on lower hybrid wave scattering in EAST

The incorporation of lower hybrid (LH) wave spectrum broadening in the poloidal wavenumber (⁠k θ ) space at the last close field surface (LCFS) is reported to lead to better agreement of the modeled LH wave current profile with the experimental results [Baek et al., Nucl. Fusion 61, 106034 (2021)]. To further understand its underlying mechanism and find the possible influence factors, effects of wave scattering caused by drift-wave type density fluctuation on the probability distribution of the LH wave polar refractive index (⁠N θ ) at the LCFS are studied under density parameters in the scrape-off-layer. According to a scattering model [P. T. Bonoli and E. Ott, Phys Fluids 25(2), 359–375 (1982)], scattering probability and scattering angle distribution are two main factors that determine the degree of spectral broadening. Studies presented here show that the total scattering probability increases first and then decreases as the wave propagates toward a smaller normalized radius of poloidal magnetic flux (⁠ρ⁠). The degree of spectral broadening is found to depend on the density and density fluctuation together by changing the intensity and a proportion of the geometrical optics approximation term and the E×B drift term in the scattering model. Additionally, the fluctuation correlation length can significantly modify the probability distribution of N θ at the LCFS, which is found to significantly change the LH wave current profile.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Search for baryon junctions in photonuclear processes and isobar collisions at RHIC

During the early development of quantum chromodynamics, it was proposed that baryon number could be carried by a non-perturbative Y-shaped topology of gluon fields, called the gluon junction, rather than by the valence quarks as in the QCD standard model. A puzzling feature of ultra-relativistic nucleus-nucleus collisions is the apparent substantial baryon excess in the mid-rapidity region that could not be adequately accounted for in most conventional models of quark and diquark transport. The transport of baryonic gluon junctions is predicted to lead to a characteristic exponential distribution of net-baryon density with rapidity and could resolve the puzzle. In this context we point out that the rapidity density of net-baryons near mid-rapidity indeed follows an exponential distribution with a slope of –0.61 ± 0.03 as a function of beam rapidity in the existing global data from A+A collisions at AGS, SPS and RHIC energies. To further test if quarks or gluon junctions carry the baryon quantum number, we propose to study the absolute magnitude of the baryon vs. charge stopping in isobar collisions at RHIC. We also argue that semi-inclusive photon-induced processes (γ + p/A) at RHIC kinematics provide an opportunity to search for the signatures of the baryon junction and to shed light onto the mechanisms of observed baryon excess in the mid-rapidity region in ultra-relativistic nucleus-nucleus collisions. Such measurements can be further validated in A+A collisions at the LHC and e + p/A collisions at the EIC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Loss Factors for Small Distributed Wind Turbines Based on Field Data in the United States

While wind energy production loss due to unavailability, environmental impacts, curtailment, and other causes has been studied and characterized at the utility-scale wind farm level, observation-based characterization of project loss is lacking for distributed wind energy, particularly for projects involving small wind turbines. Contemporary tools and research that support pre-construction distributed wind energy characterization present a wide range of default loss factors to convert gross energy estimates to net: 7-18%. We hypothesize that we can use generation observations from operational distributed wind projects to develop more accurate representations of loss. Using a density-based filtering technique on distributed wind power generation timeseries, we determine periods of typical performance and use them with regression algorithms in a measure-correlate-predict fashion to simulate what the generation would have been during periods of atypical or unreported performance. From there, the actual versus predicted generation leads to the establishment of observation-informed loss factors (median = 17%) for small, single turbine installation distributed wind projects.

17 WIND ENERGY↗

Particle control via cryopumping and its impact on the edge plasma profiles of Alcator C-Mod

At the high n e proposed for high-field fusion reactors, it is uncertain whether ionization, as opposed to plasma transport, will be most influential in determining n e at the pedestal and separatrix. A database of Alcator C-Mod discharges is analyzed to evaluate the impact of source modification via cryopumping. The database contains similarly-shaped H-modes at fixed I P = 0.8 MA and B t = 5.4 T, spanning a large range in P net and ionization. Measurements from an edge Thomson scattering system are combined with those from a midplane-viewing Ly α camera to evaluate changes to n e and T e in response to changes in ionization rates, S ion ∙ $n^{sep}_e$ and $T^{ped}_e$ are found to be most sensitive to changes to $S^{sep}_{ion}$, as opposed to $n^{ped}_e$ and $T^{sep}_e$. Dimensionless quantities, namely α MHD and v*, are found to regulate attainable pedestal values. Select discharges at different values of P net and in different pumping configurations are analyzed further using SOLPS-ITER. It is determined that changes to plasma transport coefficients are required to self-consistently model both plasma and neutral edge dynamics. Pumping is found to modify the poloidal distribution of atomic neutral density, n 0 , along the separatrix, increasing n 0 at the active X-point. Opaqueness to neutrals from high n e in the divertor is found to play a role in mediating neutral penetration lengths and hence, the poloidal distribution of neutrals along the separatrix. Pumped discharges thus require a larger particle diffusion coefficient than that inferred purely from 1D experimental profiles at the outer midplane.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Modeling Urban Acoustic Noise in the Las Vegas, NV Region

Ambient infrasound noise in quiet, rural environments has been extensively studied and well-characterized through noise models for several decades. More recently, creating noise models for high-noise rural environments has also become an area of active research. However, far less work has been done to create generalized low-frequency noise models for urban areas. The high ambient noise levels expected in cities and other highly populated areas means that these environments are regarded as poor locations for acoustic sensors, and historically, sensor deployment in urban areas were avoided for this reason. However, there are several advantages to placing sensors in urban environments, including convenience of deployment and maintenance, and increasingly, necessity, as more previously rural areas become populated. This study seeks to characterize trends in low-frequency urban noise by creating a background noise model for Las Vegas, NV, using the Las Vegas Infrasound Array (LVIA): a network of eleven infrasound sensors deployed throughout the city. Data included in this study spans from 2019 to 2021 and provides a largely uninterrupted record of noise levels in the city from 0.1–500 Hz, with only minor discontinuities on individual stations. We organize raw data from the LVIA sensors into hourly power spectral density (PSD) averages for each station and select from these PSDs to create frequency distributions for time periods of interest . These frequency distributions are converted into probability density functions (PDFs), which are then used to evaluate variations in frequency and amplitude over daily to seasonal timescale s. In addition to PDFs, the median, 5 th percentile, and 95 th percentile amplitude values are calculated across the entire frequency range. This methodology follows a well-established process for noise model creation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Evidence of Two-Source King Plot Nonlinearity in Spectroscopic Search for New Boson

Optical precision spectroscopy of isotope shifts can be used to test for new forces beyond the standard model, and to determine basic properties of atomic nuclei. We measure isotope shifts on the highly forbidden 2 S 1/2 → 2 F 7/2 octupole transition of trapped 168,170, 172, 174, 176 Yb ions. When combined with previous measurements in Yb + and very recent measurements in Yb, the data reveal a King plot nonlinearity of up to 240σ. Furthermore, the trends exhibited by experimental data are explained by nuclear density functional theory calculations with the Fayans functional. We also find, with 4.3σ confidence, that there is a second distinct source of nonlinearity, and discuss its possible origin.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Control of polymer architectures by living ring-opening metathesis copolymerization

In an aspect, a method of synthesizing a graft copolymer comprises the steps of: copolymerizing a first macromonomer and a first reactive diluent; wherein said first macromonomer comprises a first backbone precursor directly or indirectly covalently linked to a first polymer side chain group; wherein said reactive diluent is provided in the presence of the first macromonomer at an amount selected so as to result in formation said graft copolymer having a first backbone incorporating said diluent and said first macromonomer in a first polymer block characterized by a preselected first graft density or a preselected first graft distribution of said first macromonomer. In some embodiments of this aspect, said preselected first graft density is any value selected from the range of 0.05 to 0.75. In some methods, the composition and amount of said diluent is selected to provide both a first preselected first graft density and a first preselected first graft distribution.

Grubbs, Robert H.↗

Differential charge radii: Proton-neutron interaction effects

The analysis of self-consistency and proton-neutron interaction effects in the buildup of differential charge radii were carried out in covariant density functional theoretical calculations without pairing interaction on the example of selected configurations in the Pb isotopes. The proton-neutron interaction of neutron(s) added to the neutron 𝑁 = 126 core and the protons forming the 𝑍 = 82 proton core is responsible for a major contribution to the buildup of differential charge radii. It depends on the products of proton and neutron wave functions and thus on their nodal structure. This interaction leads to a redistribution of single-particle density of occupied proton states which in turn modifies the charge radii. Furthermore, the microscopic origin of this redistribution and its consequences for differential charge radii were investigated for the first time. Self-consistency effects affecting the shape of proton potential, total proton densities and the energies of the single-particle proton states provide only minor contribution to differential charge radii.

190 ≤ A ≤ 219↗

Exploring Si Heterojunction Solar Cell Degradation: Bulk and Interface Processes Analyzed by Simulations and Experiments in Order to Develop Mitigation Strategies

The Si technology with the highest conversion efficiency is a-Si/c-Si heterojunction (HJ) PV. Its market penetration, however, is slowed by reports that fielded HJ modules degraded at twice the rate of regular c-Si modules. Our very recent work confirmed this degradation and attributed it to enhanced recombination at the a-Si/c-Si interface, caused by the slow, order-of-magnitude increase of the defect density. We propose to comprehensively explore degradation mechanisms in Si HJ cells by combining simulations and experiments. Theoretically, we will: (1) simulate structure of a-Si and a-Si/c-Si interfaces, identify defects; (2) determine statistics of energy barriers that control defect formation; (3) compute growth of defect density from the barrier distribution, and the resulting degradation of Voc. Experimentally, we will: (1) create a series of HJ-cell-representative stacks with varying layer thicknesses and deposition conditions by using PECVD tools; (2) use temperature and injection-dependent lifetime spectroscopy to determine effective lifetimes; (3) deconvolve the data to separate bulk and interface effects, and the effects of charge density and interface defects to analyze long time degradation. The goal is to identify material and device degradation mechanisms, to develop mitigation strategies for improved stability, such as the introduction of capping layers and hydrogen diffusion control.

14 SOLAR ENERGY↗

Using distributions to understand neutron and x-ray production in ICF ignition capsules and other high energy density plasmas

Here this paper describes how x-ray and neutron distribution functions can be useful tools to visualize the conditions measured in many types of plasma physics experiments. In particular, we model a standard inertial confinement fusion ignition capsule that consists of a Si doped plastic ablator surrounding a layer of deuterium–tritium (DT) ice as the yield varies from 18 kJ to 16.7 MJ and use the distribution functions to show that neutrons and high energy x rays (15 keV) are produced under similar conditions when the yield is low. However, as the capsule starts to support a propagating burn due to alpha heating, the x rays and neutrons are produced under somewhat different conditions in different parts of the plasma. In particular, the x-ray production takes place mainly in the hot plastic ablator for the full yield ignition capsule under quite different plasma conditions from the DT region producing the 14 MeV neutrons, which results in x-ray images with larger radii than the corresponding neutron images. These same distribution functions can be applied to many other plasma physics experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Physics-driven learning of Wasserstein GAN for density reconstruction in dynamic tomography

Object density reconstruction from projections containing scattered radiation and noise is of critical importance in many applications. Existing scatter correction and density reconstruction methods may not provide the high accuracy needed in many applications and can break down in the presence of unmodeled or anomalous scatter and other experimental artifacts. Incorporating machine-learning models could prove beneficial for accurate density reconstruction, particularly in dynamic imaging, where the time evolution of the density fields could be captured by partial differential equations or by learning from hydrodynamics simulations. In this work, we demonstrate the ability of learned deep neural networks to perform artifact removal in noisy density reconstructions, where the noise is imperfectly characterized. Here, we use a Wasserstein generative adversarial network (WGAN), where the generator serves as a denoiser that removes artifacts in densities obtained from traditional reconstruction algorithms. We train the networks from large density time-series datasets, with noise simulated according to parametric random distributions that may mimic noise in experiments. The WGAN is trained with noisy density frames as generator inputs, to match the generator outputs to the distribution of clean densities (time series) from simulations. A supervised loss is also included in the training, which leads to an improved density restoration performance. In addition, we employ physics-based constraints such as mass conservation during the network training and application to further enable highly accurate density reconstructions. Our preliminary numerical results show that the models trained in our frameworks can remove significant portions of unknown noise in density time-series data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Relationship between microporous structure and light gas transport through glassy polymeric membranes revealed by molecular simulations

Microporous glassy polymers are attractive materials for gas separation membranes, due to their high permeability and tailorable selectivity, provided physical aging can be delayed. The archetypal microporous glassy polymer, PTMSP, can be blended with a hyper-crosslinked isatin–triptycene porous polymer network (PPN) to delay physical aging. However, while PPN is effective at reducing physical aging, it also affects the permeability of light gases through PTMSP. Molecular dynamics simulations were used here to shed fundamental light on the mechanisms responsible for these effects. Atomistic models are developed that satisfactorily reproduce experimental observations such as matrix density and cavity size distributions for neat PTMSP as well as for PTMSP–PPN blends. Analysis of the simulation results suggests that physical aging is delayed because the PPN inclusions slow down PTMSP relaxation while reducing the connectivity between free volume pockets. To understand how PPN inclusions affect light gas permeability, the atomistic models developed are used to probe CO 2 and CH 4 diffusion and sorption. These simulations are conducted for PTMSP matrices exhibiting varying density, towards reproducing experimental permeability data. Interrogating the simulation trajectories, it is discovered that while CH 4 travels preferentially through the free volume cavities, CO 2 preferentially interacts with the available surfaces, especially in the presence of PPN. These differences help interpret experimental observations. The transport of C 2 H 6 and H 2 S through PTMSP matrices was also investigated. These gases, and in particular H 2 S, were found to absorb within PTMSP, yielding very low diffusion coefficients. The ability to predict differences in diffusion pathways for various natural gas components unveils the possibility of engineering membranes to control permeability and selectivity towards large-scale applications.

Bao Le, Tran Thi [Univ. of Oklahoma, Norman, OK (U↗

Investigation of the iodate sorption mechanism by CoAl LDH through experiments and ab initio molecular dynamics simulations

Radioiodine released during the nuclear-fuel cycle constitutes a persistent radiological hazard. In this study, the IO 3 – uptake mechanism of CoAl LDH was resolved by combining pH-controlled sorption experiments, synchrotron XAFS, and DFT-based AIMD simulations. At pH close to 6, approximately 90% of IO 3 – was removed, and the equilibrium distribution coefficient reached about 1.7 × 10 4 mL g –1 . EXAFS analysis indicated an average iodine–oxygen bond length of 1.81 Å and a coordination number near 3, with the fit R-factor equal to 0.002. The simulations faithfully reproduced the experimental spectrum and revealed transient proton hopping events that generated metastable I–O–H species inside the interlayer, thereby confirming nitrate-to-iodate exchange as the controlling capture pathway. Atomic density profiles and radial distribution functions further showed that IO 3 – adopt an end-on orientation perpendicular to the hydroxide sheets, while water molecules mediate proton migration without disturbing the host lattice. In conclusion, the integrated experimental–computational evidence demonstrates that CoAl LDH can rapidly and selectively sequester IO 3 – under near-neutral conditions, offering atomic scale guidance for the rational engineering of layered sorbents for advanced radioactive-waste treatment.

Kang, Jaehyuk [Jeju National Univ. (Korea, Republi↗

The Galaxy–Halo Connection of DESI Luminous Red Galaxies with Subhalo Abundance Matching

Abstract We use subhalo abundance and age distribution matching to create magnitude-limited mock galaxy catalogs at z ∼ 0.43, 0.52, and 0.63 with z -band and 3.4 μ m W 1-band absolute magnitudes and r − z and r − W 1 colors. From these magnitude-limited mocks, we select mock luminous red galaxy (LRG) samples according to the ( r − z )-based (optical) and ( r − W 1)-based (infrared) selection criteria for the LRG sample of the Dark Energy Spectroscopic Instrument (DESI) survey. Our models reproduce the number densities, luminosity functions, color distributions, and projected clustering of the DESI Legacy Surveys that are the basis for DESI LRG target selection. We predict the halo occupation statistics of both optical and IR DESI LRGs at fixed cosmology and assess the differences between the two LRG samples. We find that IR-based SHAM modeling represents the differences between the optical and IR LRG populations better than using the z band and that age distribution matching overpredicts the clustering of LRGs, implying that galaxy color is uncorrelated with halo age in the LRG regime. Both the optical and IR DESI LRG target selections exclude some of the most luminous galaxies that would appear to be LRGs based on their position on the red sequence in optical color–magnitude space. Both selections also yield populations with a nontrivial LRG–halo connection that does not reach unity for the most massive halos. We find that the IR selection achieves greater completeness (≳90%) than the optical selection across all redshift bins studied.

Berti, Angela M. (ORCID:0000000335826649)↗