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In the paper the asymptotic structure of eigenfunctions of the absolutely continuous spectrum of the scattering problem is described. The case of three one-dimensional quantum particles interacting by repulsive pair potentials with a compact support is considered.
A Gamma-Ray and Neutron Spectrometer (GRNS) instrument has been developed as part of the science payload for NASA’s Discovery Program Psyche mission to the M-class asteroid (16) Psyche. The GRNS instrument is designed to measure the elemental composition of Psyche with the goal to understand the origin of this mysterious, potentially metal-rich planetary body. The GRNS will measure the near-surface abundances for the elements Ni, Fe, Si, K, S, Al, and Ca, as well as the spatial distribution of Psyche’s metal-to-silicate fraction (or metal fraction). These measurements address three of the five Psyche mission science objectives: determine if Psyche is a core; determine whether small metal bodies incorporate light elements into the metal phase; and determine whether Psyche was formed under reducing conditions. The Gamma-Ray Spectrometer (GRS) uses a cryocooled, high-purity Ge (HPGe) sensor to detect cosmic-ray generated gamma rays in the 60 to 9000-keV energy range. The HPGe sensor is surrounded by a borated plastic anticoincidence shield that provides three functions: active background rejection from charged particle interactions in the HPGe sensor; fast neutron measurements; and direct measurements of the incident galactic cosmic ray flux. The Neutron Spectrometer (NS) uses three 3 He gas proportional sensors, each with different material wraps to measure thermal (<0.4 eV), low-energy epithermal (0.4 eV to 1 keV), and high-energy epithermal (up to 100 keV) neutrons. This paper provides an overview of the Psyche GRNS, including: its science and measurement objectives; the design of the instrument hardware, software, and operation; pre-launch performance measurements and its initial performance in space; and an overview of its data products and expected operation for different Psyche mission phases.
Roadside proximity and exposure to mixed vehicular emissions (MVE) have been linked to adverse pulmonary and vascular outcomes. However, because of the complex nature of the contribution of particulate matter (PM) versus gases, it is difficult to decipher the precise causative factors regarding PM and the copollutant gaseous fraction. To this end, C57BL/6 and apolipoprotein E knockout mice (ApoE −/− ) were exposed to either filtered air (FA), fine particulate (FP), FP+gases (FP+G), ultrafine particulate (UFP), or UFP+gases (UFP+G). Two different timeframes were employed: 1-day (acute) or 30-day (subchronic) exposures. Examined biological endpoints included aortic vasoreactivity, aortic lesion quantification, and aortic mRNA expression. Impairments in vasorelaxation were observed following acute exposure to FP+G in C57BL/6 animals and FP, UFP, and UFP+G in ApoE −/− animals. These effects were completely abrogated or markedly reduced following subchronic exposure. Aortic lesion quantification in ApoE −/− animals indicated a significant increase in atheroma size in the UFP-, FP-, and FP+G-exposed groups. Additionally, ApoE −/− mice demonstrated a significant fold increase in TNFα expression following FP+G exposure and ET-1 following UFP exposure. Interestingly, C57BL/6 aortic gene expression varied widely across exposure groups. TNFα decreased significantly following FP exposure and CCL-5 decreased in the UFP-, FP-, and FP+G-exposed groups. Conversely, ET-1, CCL-2, and CXCL-1 were all significantly upregulated in the FP+G group. These findings suggest that gas–particle interactions may play a role in vascular toxicity, but the contribution of surface area is not clear.
Time dependent quantum problems defined by quadratic Hamiltonians are solved using canonical transformations. The Green’s function is obtained and a comparison with the classical Hamilton–Jacobi method leads to important geometrical insights like exterior differential systems, Monge cones and time dependent Gaussian metrics. The Wei–Norman approach is applied using unitary transformations defined in terms of generators of the associated Lie groups, here the semi-direct product of the Heisenberg group and the symplectic group. A new explicit relation for the unitary transformations is given in terms of a finite product of elementary transformations. The sequential application of adequate sets of unitary transformations leads naturally to a new separation of variables method for time dependent Hamiltonians, which is shown to be related to the Inönü–Wigner contraction of Lie groups. The new method allows also a better understanding of interacting particles or coupled modes and opens an alternative way to analyze topological phases in driven systems. - Highlights: • Exact unitary transformation reducing time dependent quadratic quantum Hamiltonian to zero. • New separation of variables method and simultaneous uncoupling of modes. • Explicit examples of transformations for one to four dimensional problems. • New general evolution equation for quadratic form in the action, respectively Green’s function.
Highlights: • Dynamics in tilted lattices with harmonic confinement is reviewed. • Both spinless and spinful fermions are analyzed. • Local effective tilt is the relevant parameter for nonergodicity. • Neel or domain wall initial states are studied. • Domains with similar spin orientation act as transport and communication barriers. We review the dynamics of interacting particles in disorder-free potentials concentrating on a combination of a harmonic binding with a constant tilt. We show that a simple picture of an effective local tilt describes a variety of cases. Our examples include spinless fermions (as modeled by Heisenberg spin chain in a magnetic field), spinful fermions as well as bosons that enjoy a larger local on-site Hilbert space. We also discuss the domain-wall dynamics that reveals nonergodic features even for a relatively weak tilt as suggested by Doggen et al. (2020). By adding a harmonic potential on top of the static field we confirm that the surprising regular dynamics is not entirely due to Hilbert space shuttering. It seems better explained by the inhibited transport within the domains of identically oriented spins. Once the spin-1/2 restrictions are lifted as, e.g., for bosons, the dynamics involve stronger entanglement generation. Again for domain wall melting, the effect of the harmonic potential is shown to lead mainly to an effective local tilt.
Here, we report results from experiments where we characterize the surface properties of soot particles interacting with high-pressure methane. We also found considerable differences in behavior of the soot material between static and dynamic pressure conditions that can be explained by multiscale correlations in the dynamics, from the micro to macro of the porous fractal-like carbon matrix. The measurements were possible utilizing cold neutron imaging of methane mixed with combustion generated carbon (soot) inside steel cells. The studies were performed under static and dynamic pressure conditions in the range 10-90 bar, and are of interest for applications of energy storage of hydrogenous fuels. The very high cross sections for neutrons compared to hard X-ray photons, enabled us to find considerable amounts of native hydrogen in the soot and to see and quantify the presence of hydrogen atoms in the carbon soot matrix under different pressure conditions. Our work lays the base for more detailed in-situ investigations on the interaction of porous carbon materials with hydrogen in practical environments for hydrogen and methane storage.
Monte Carlo (MC) simulations are widely used for medical applications and nuclear reaction models are fundamental for the simulation of the particle interactions with patients in ion therapy. Therefore, it is of utmost importance to have reliable models in MC simulations for such interactions. Geant4 is one of the most used toolkits for MC simulation. However, its models showed severe limitations in reproducing the yields measured in the interaction of ion beams below 100 MeV/u with thin targets. For this reason, we interfaced two models, SMF (“Stochastic Mean Field”) and BLOB (“Boltzmann-Langevin One Body”), dedicated to simulate such reactions, with Geant4.
The morphological evolution of tin particles with different sizes during the first lithiation and delithiation processes has been visualized by an in operando synchrotron transmission X-ray microscope (TXM). Here, the in operando lithium ion battery cell was operated at constant current condition during TXM imaging. Two-dimensional projection images with 40 nm resolution showing morphological evolution were obtained and analyzed. The analysis of relative area change shows that the morphology of tin particles with different sizes changed simultaneously. This phenomenon is mainly because of a negative feedback mechanism among tin particles in the battery electrode at a constant current operating condition. For irregular-shaped tin particles, the contour analysis demonstrates that the regions with higher curvature started volume expansion first, and then the entire particle expanded almost homogeneously. This study provides insights for understanding the dynamic morphological change and the particle-particle interactions in high capacity lithium ion battery electrodes.
Controlling nanoparticles (NPs) aggregation in cellulose/NPs composites allows to optimise NPs driven properties and their applications. Polyelectrolytes are used to control NPs aggregation and their retention within the fibrous matrix. Here in this study, we aim at evaluating how a polyelectrolyte (Cationic Polyacrylamide; CPAM, molecular weight: 13 MDa, charge: 50%, Radius of gyration: 30–36 nm) adsorbs and re-conforms onto the surface of silica(SiO 2 ) NPs differing in diameter (8, 22 and 74 nm) and to investigate the respective NPs aggregation in cellulose matrices. SEM shows the local area distribution of NPs in composites. Ultra-SAXS (USAXS) allows to evaluate the average NPs size distribution and the inter-particle interactions at length scale ranging from 1 to 1000 nm. USAXS data analysis reveals that CPAM covers multiple NPs of the smaller diameter (8 nm), presumably with a single chain to form large size NPs aggregates. As the NPs diameter is increased to 22 nm, CPAM re-conforms over NP surface forming a large shell of thickness 5.5 nm. For the composites with NPs of diameter 74 nm, the CPAM chain re-conforms further onto NP surface and the surrounding shell thickness decreases to 2.2 nm. Lastly, structure factor analysis reveals higher structural ordering for NPs as increases their diameter, which is caused by different conformations adopted by CPAM onto NPs surface.
One popular technique for the numerical time advance of charged particles interacting with electric and magnetic fields according to the Lorentz force law [1], [2], [3] and [4] is the Boris algorithm. Its popularity stems from simple implementation, rapid iteration, and excellent long-term numerical fidelity [1] and [5]. Excellent long-term behavior strongly suggests the numerical dynamics exhibit conservation laws analogous to those governing the continuous Lorentz force system [6]. Moreover, without conserved quantities to constrain the numerical dynamics, algorithms typically dissipate or accumulate important observables such as energy and momentum over long periods of simulated time [6]. Identification of the conservative properties of an algorithm is important for establishing rigorous expectations on the long-term behavior; energy-preserving, symplectic, and volume-preserving methods each have particular implications for the qualitative numerical behavior [6], [7], [8], [9], [10] and [11].
In this paper we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular simulations. The latter are ubiquitous in physicochemical and biological applications, where they are typically associated with coupling mechanisms, multi-physics and/or boundary conditions. In general the non-equilibrium steady states are not known explicitly as they do not necessarily have a Gibbs structure. The presented approach can compare microscopic behavior of molecular systems to parametric and non-parametric coarse-grained models using the relative entropy between distributions on the path space and setting up a corresponding path-space variational inference problem. The methods can become entirely data-driven when the microscopic dynamics are replaced with corresponding correlated data in the form of time series. Furthermore, we present connections and generalizations of force matching methods in coarse-graining with path-space information methods. We demonstrate the enhanced transferability of information-based parameterizations to different observables, at a specific thermodynamic point, due to information inequalities. We discuss methodological connections between information-based coarse-graining of molecular systems and variational inference methods primarily developed in the machine learning community. However, we note that the work presented here addresses variational inference for correlated time series due to the focus on dynamics. The applicability of the proposed methods is demonstrated on high-dimensional stochastic processes given by overdamped and driven Langevin dynamics of interacting particles.
The ‘Restricted Collision List’ (RCL) method for speeding up the calculation of DSMC Variable Soft Sphere collisions, with Borgnakke–Larsen (BL) energy exchange, is presented. The method cuts down considerably on the number of random collision parameters which must be calculated (deflection and azimuthal angles, and the BL energy exchange factors). A relatively short list of these parameters is generated and the parameters required in any cell are selected from this list. The list is regenerated at intervals approximately equal to the smallest mean collision time in the flow, and the chance of any particle re-using the same collision parameters in two successive collisions is negligible. The results using this method are indistinguishable from those obtained with standard DSMC. The CPU time saving depends on how much of a DSMC calculation is devoted to collisions and how much is devoted to other tasks, such as moving particles and calculating particle interactions with flow boundaries. For 1-dimensional calculations of flow in a tube, the new method saves 20% of the CPU time per collision for VSS scattering with no energy exchange. With RCL applied to rotational energy exchange, the CPU saving can be greater; for small values of the rotational collision number, for which most collisions involve some rotational energy exchange, the CPU may be reduced by 50% or more.
Here, we consider neutral particle systems described by moments of a phase-space density and propose a realizability-preserving numerical method to evolve a spectral two-moment model for particles interacting with a background fluid moving with nonrelativistic velocities. The system of nonlinear moment equations, with special relativistic corrections to $\mathscr{O}$($v$/$c$), expresses a balance between phase-space advection and collisions and includes velocity-dependent terms that account for spatial advection, Doppler shift, and angular aberration. The model is conservative for the correct $\mathscr{O}$($v$/$c$) Eulerian-frame number density and is consistent, to $\mathscr{O}$($v$/$c$), with Eulerian-frame energy and momentum conservation. This model is closely related to the one promoted by Lowrie et al. and similar to models currently used to study transport phenomena in large-scale simulations of astrophysical environments. The proposed numerical method is designed to preserve moment realizability, which guarantees that the moments correspond to a nonnegative phase-space density. The realizability-preserving scheme consists of the following key components: (i) a strong stability-preserving implicit-explicit (IMEX) time-integration method; (ii) a discontinuous Galerkin (DG) phase-space discretization with carefully constructed numerical uxes; (iii) a realizability-preserving implicit collision update; and(iv) a realizability-enforcing limiter. In time integration, nonlinearity of the moment model necessitates solution of nonlinear equations, which we formulate as fixed-point problems and solve with tailored iterative solvers that preserve moment realizability with guaranteed global convergence. We also analyze the simultaneous Eulerian-frame number and energy conservation properties of the semi-discrete DG scheme and propose a "spectral redistribution" scheme that promotes Eulerian-frame energy conservation. Through numerical experiments, we demonstrate the accuracy and robustness of this DG-IMEX method and investigate its Eulerian-frame energy conservation properties.
The stress evolution occurring in UMo/Al dispersion fuel is important since it affects the fuel performance during irradiation. In this study, a new analytical model was developed to predict the local stresses in UMo/Al dispersion fuel. In the model, a hypothetical unit sphere composed of a UMo fuel particle, interaction layer (IL), and Al matrix was considered, and the governing equations for the stress-strain relationship, strain-displacement, and mechanical equilibrium were established using a spherical coordinate system. The mathematical derivations were obtained for local stresses in the radial and circumferential direction using a thick-walled sphere model. Furthermore, this analytical model employed the stress distribution as the boundary condition, which is calculated using a finite element model with homogenized fuel meat. The developed model’s solution scheme was verified against Abaqus solutions obtained for two irradiated plates with heterogeneous meat. The model calculated consistent results for interfacial stresses in the IL and Al matrix, indicating that the newly developed model was reliable when simultaneously calculating fission gas pressurization on the UMo/IL/Al composite, and the use of the stress distribution in the homogenized fuel meat as the boundary condition for the analytical model was acceptable
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Most of the Pu separated from irradiated commercial nuclear fuel is stored as PuO 2 . The primary quantitative nondestructive measurement technique used to verify the amount of Pu in storage containers is passive neutron correlation counting. An important physical property of the oxide material is the ratio, α, of the rate of (α, n) neutrons produced inside the item to the rate of neutrons produced by spontaneous fission. This ratio influences the precision of the correlated counting method and affects the interpretation of the data because of how it changes both the primary total neutron production rate and the rate of induced fission events taking place inside the item. In addition to the main O(α, n) contribution, additional contributions come from α-particle interactions with light element impurities that are inevitably present. In this work, we calculate specific (α, n) yield coefficients, expressed in units of neutrons per second per gram of α-emitting nuclide per part per million by mass of the specified impurity element distributed in a pure PuO 2 matrix, for some key α-emitting actinides commonly present in reprocessed Pu ( 238–242 Pu+ 241 Am). These coefficients are directly applicable to nuclear safeguards verification work in which the α ratio is often calculated from the Pu-isotopic composition and chemical information obtained by other means. Further, they also provide a convenient up-to-date reference set against which values generated by other methods can be compared. Results are presented for impurities with atomic number from 3 to 17 inclusive, plus K and Fe. In most cases, these coefficients are not expected to change by more than 5%–10% at any time in the future. However, as new data become available, changes as large as 20% may be needed for some targets (e.g., F). The present yield calculations are limited by the general shortage of quality experimental total (α, n) reaction cross section data, which, together with unexplained variation between determinations, means that an objective and coherent evaluation is not possible. The situation is even less satisfactory for the partial differential cross section needed to calculate neutron spectra.
The study of neutron unbound systems via the invariant mass technique is the primary focus of the MoNA Collaboration, which built and operates the Modular Neutron Array (MoNA) and the Large multi-Institutional Scintillator Array (LISA) at FRIB. Advancements in nuclear structure from theory and experiment along the neutron dripline have presented opportunities to understand the nature of unbound systems in higher mass nuclei. The GEometry ANd Tracking (Geant4) platform has been used in high-energy and nuclear physics to simulate particle interactions with as much detail as the user desires. Geant4 currently does not have a physics class to simulate neutron unbound systems. Given the advancement of accelerator facilities and active searches along the neutron dripline, detailed simulations to study the breakup of neutron unbound systems, are necessary. Furthermore, the implementation of the breakup of neutron unbound systems in Geant4 will be presented.
In this review, we present the current state of the art of our understanding of the spectrum of excited strongly interacting particles and discuss methods that allow for a systematic and model-independent calculation of the hadron spectrum. These are lattice QCD and effective field theories. Synergies between both approaches can be exploited allowing for a deeper understanding of the hadron spectrum. Results based on effective field theories and hadron–hadron scattering in lattice QCD or combinations thereof are presented and discussed. We also show that the often used Breit–Wigner parametrization is at odds with chiral symmetry and should not be used in case of strongly coupled channels.