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At least 199 records · Page 11

Dataset for manuscript "Rotational Memory Function of SPC/E water"

Memory effect are essential for dynamics of condensed materials and are responsible for non-exponential relaxation of correlation functions of dynamic variables through the memory function entering the memory equation. Memory functions of dipole rotations for polar liquids have never been calculated. We present here calculations of memory functions and single-dipole rotations and of the overall system dipole moment for SPC/E water measured by dielectric spectroscopy. The memory functions for single-particle and collective dynamics turn out to be nearly identical. This result validates theories of dielectric spectroscopy in terms of single-particle time correlation function and the connection between the collective and single-particle relaxation times in terms of the Kirkwood factor. The dataset includes single particle and system dipole moments, including their time-dependence.

74 ATOMIC AND MOLECULAR PHYSICS↗

Molecular dynamics analysis of particle number fluctuations in the mixed phase of a first-order phase transition

Molecular dynamics simulations are performed for a finite nonrelativistic system of particles with Lennard-Jones potential. We study the effect of liquid-gas mixed phase on particle number fluctuations in coordinate subspace. A metastable region of the mixed phase, the so-called nucleation region, is analyzed in terms of a noninteracting cluster model. Large fluctuations due to spinodal decomposition are observed. They arise due to the interplay between the size of the acceptance region and that of the liquid phase. These effects are studied with a simple geometric model. The model results for the scaled variance of particle number distribution are compared with those obtained from the direct molecular dynamic simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Techno-Economic Optimization of CSP Plants with Free-Falling Particle Receivers

Particle receivers are one of the candidates for the next generation of CSP plants, whose goal is to reduce the levelized cost of electricity (LCOE) to 0.05 $/kWh. This paper presents a techno-economic analysis to study if a CSP system with free-falling particle receiver can achieve this goal. The plant analyzed integrates two ground-based bins to store the excess energy and a supercritical CO2 cycle to generate electricity. The model used for the analysis presents several upgrades to previous particle systems models in order to increase its fidelity, accuracy, and representativeness of an actual system. The main upgrades are the addition of off-design conditions during the annual simulations in all the components and an improved receiver model validated against CFD simulations. The size of the main components is optimized to obtain the system configuration with minimum LCOE. The results show that particle CSP systems can reduce the LCOE to 0.056 $/kWh if the configuration is composed of 1.61 × 106 m2 of heliostats, a 250 m high tower with a 537 m2 falling particle curtain, and 16 h thermal energy storage.

54 ENVIRONMENTAL SCIENCES↗

Gamma-ray imaging of Np-237 metal using an organic glass imager

Neutron and gamma-ray imaging systems are deployed within the field of nuclear safeguards for the detection and localization of special nuclear materials and other materials of interest. 237 Np is one of these materials of interest due its presence in spent nuclear fuel and potential for use in nuclear weapons when purified. Here, for the first time, a 6 kg neptunium sphere (98.8 wt% 237 Np) was measured using a dual-particle imager, from the University of Michigan, consisting of organic glass and inorganic scintillators. The novel composition of organic glass scintillator was recently developed at Sandia National Labs and has been used in particle imaging systems due to its time resolution and particle discrimination capabilities. Gamma-ray energy spectra from single and coincident events were extracted and the sequencing of Compton scatter and photoelectric absorption gamma-ray events was used to generate images using simple backprojection. The emissions of interest in this work are the 312 keV and 416 keV gamma rays from 233 Pa, a daughter isotope from the neptunium decay series. The results of this work show that there is close agreement between the true source location in angular space and the converged location from the gamma ray images created using the system. The gamma spectroscopy from single and coincident events also identified the characteristic emission from the daughter isotope and could be used to assist with the identification of 237 Np. Furthermore, successful localization of the source with 5 s of data demonstrates the practical application of the imaging system for imaging and detection of material in weapons-useable quantities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Stroboscopic aliasing in long-range interacting quantum systems

We unveil a mechanism for generating oscillations with arbitrary multiplets of the period of a given external drive, in long-range interacting quantum many-particle spin systems. These oscillations break discrete time translation symmetry as in time crystals, but they are understood via two intertwined stroboscopic effects similar to the aliasing resulting from video taping a single fast rotating helicopter blade. The first effect is similar to a single blade appearing as multiple blades due to a frame rate that is in resonance with the frequency of the helicopter blades' rotation; the second is akin to the optical appearance of the helicopter blades moving in reverse direction. Analogously to other dynamically stabilized states in interacting quantum many-body systems, this stroboscopic aliasing is robust to detuning and excursions from a chosen set of driving parameters, and it offers a novel route for engineering dynamical n-tuplets in long-range quantum simulators, with potential applications to spin squeezing generation and entangled state preparation.

Kelly, Shane↗

Discovering exact, gauge-invariant, local energy-momentum conservation laws for the electromagnetic gyrokinetic system by high-order field theory on heterogeneous manifolds

Gyrokinetic theory is arguably the most important tool for numerical studies of transport physics in magnetized plasmas. However, exact local energy-momentum conservation laws for the electromagnetic gyrokinetic system have not been found despite the continuous effort. Without such local conservation laws, energy and momentum can be instantaneously transported across spacetime, which is unphysical and casts doubt on the validity of numerical simulations based on the gyrokinetic theory. The standard Noether procedure for deriving conservation laws from corresponding symmetries does not apply to gyrokinetic systems because the gyrocenters and electromagnetic fields reside on different manifolds. To overcome this difficulty, we develop a high-order field theory on heterogeneous manifolds for classical particle-field systems and apply it to derive exact, local conservation laws, in particular the energy-momentum conservation laws, for the electromagnetic gyrokinetic system. A weak Euler-Lagrange equation is established to replace the standard Euler-Lagrange equation for the particles. It is discovered that an induced weak Euler-Lagrange current enters the local conservation laws. And it is the new physics captured by the high-order field theory on heterogeneous manifolds. A recently developed gauge-symmetrization method for high-order electromagnetic field theories using the electromagnetic displacement-potential tensor is applied to render the derived energy-momentum conservation laws electromagnetic gauge-invariant.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling Tool Development and Validation for Solar Industry Process Heat Using Particle Thermal Energy Storage

U.S. industry sectors used 26.2 quadrillion Btu and accounted for 33% of total energy consumption in 2021 according to the Energy Information Agency. Industrial process heat accounts for 70% of industrial energy use with application temperatures ranging from 60 degrees -1100 degrees C. Industry processes, heavily relying on fossil fuels of cheap coal or natural gas, differ widely in operating conditions and load requirements which makes them difficult to standardize and imposes great challenges in decarbonization. Industry processes require reliable energy supply and vary widely in temperature ranges. Storing energy from renewable sources is necessary to improve reliability and to mitigate renewable intermittency when replacing carbon fuel-based heat supplies to achieve energy savings and reduce emissions. To this end, we have developed a particle-based thermal energy storage (TES) technology using low-cost and highly stable silica sand as a storage medium. The economic and performance-based analysis is key for renewable energy sources to reliably supply industry process heat and ultimately displace fossil fuels for decarbonization. The diversified industrial processes need case-by-case analysis and design. Therefore, an adaptive modeling tool is key for renewable power with energy storage to meet industry demands. Thus, a modeling tool to simulate a solar industry process heat system using the particle TES has been developed using the object-oriented equation-based language Modelica and the commercial platform of Modelon Impact. The Modelica-based software tool provides a general simulation environment for the design of reliable solar energy sources integrated with TES for various industrial process applications at different temperatures for economic competence with fossil fuels such as coal and natural gases. It uses both customized and standard component modeling modules in Modelon libraries for the flexibility to be adapted to a specific energy demand application. The particle TES system establishes a uniform energy supply platform with an efficient heat exchanger and particle thermal energy reservoir integrated with renewable powers. The particle TES system can provide a wide temperature range and can have a large storage temperature difference that increases storage energy density; therefore, it can be an adaptable energy storage system integrated with renewable power to supply 24/7 heat for industry decarbonization.

concentrated solar thermal↗

Collective mode Brownian dynamics: A method for fast relaxation of statistical ensembles

Sampling equilibrium configurations of correlated systems of particles with long relaxation times (e.g., polymeric solutions) using conventional molecular dynamics and Monte Carlo methods can be challenging. This is especially true for systems with complicated, extended bond network topologies and other interactions that make the use and design of specialized relaxation protocols infeasible. We introduce a method based on Brownian dynamics simulations that can reduce the computational time it takes to reach equilibrium and draw decorrelated samples. Importantly, the method is completely agnostic to the particle configuration and the specifics of interparticle forces. In particular, we develop a mobility matrix that excites non-local, collective motion of N particles and can be computed efficiently in $\mathcal{O}(N)$ time. Particle motion in this scheme is computed by integrating the overdamped Langevin equation with an Euler–Maruyama scheme, in which Brownian displacements are drawn efficiently using a low-rank representation of the mobility matrix in position and wave space. We demonstrate the efficacy of the method with various examples from the realm of soft condensed matter and release a massively parallel implementation of the code as a plugin for the open-source package HOOMD-blue [J. A. Anderson et al., J. Comput. Phys. 227, 5342 (2008) and J. Glaser et al., Comput. Phys. Commun. 192, 97 (2015)] which runs on graphics processing units

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stochastic properties of ultralight scalar field gradients

Ultralight axion-like particles are well-motivated dark matter candidates that are the target of numerous direct detection efforts. In the vicinity of the Solar System, such particles can be treated as oscillating scalar fields. The velocity dispersion of the Milky Way determines a coherence time of about 10 6 oscillations, beyond which the amplitude of the axion field fluctuates stochastically. Any analysis of data from an axion direct detection experiment must carefully account for this stochastic behavior to properly interpret the results. This is especially true for experiments sensitive to the gradient of the axion field that are unable to collect data for many coherence times. Indeed, the direction, in addition to the amplitude, of the axion field gradient fluctuates stochastically. We present the first complete stochastic treatment for the gradient of the axion field, including multiple computationally efficient methods for performing likelihood-based data analysis, which can be applied to any axion signal, regardless of coherence time. Additionally, we demonstrate that ignoring the stochastic behavior of the gradient of the axion field can potentially result in failure to discover a true axion signal

79 ASTRONOMY AND ASTROPHYSICS↗

Self-assembly of a triply periodic continuous mesophase with Fddd symmetry in simple one-component liquids

Triply periodic continuous morphologies (networks) arising as a result of the microphase separation in block copolymer melts have so far never been observed self-assembled in systems of particles with spherically symmetric interaction. Here, we report a molecular dynamics simulation where two simple one-component liquids form upon cooling an equilibrium network with the Fddd space group symmetry. This complexity reduction in the liquid network formation in terms of the particle geometry and the number of components evidences the generic nature of this class of phase transition suggesting opportunities for producing these structures in a variety of new systems.

36 MATERIALS SCIENCE↗

Toward an integrated multi-gigahertz ionizing particle diagnostic

Needs arising at both current and future accelerator facilities call for the development of radiation-hardened position-sensing diagnostics that can operate with multi-GHz repetition rates. Such instruments are likely to also have applications in the diagnosis of rapid plasma behavior. Here, building on the recent work of our Advanced Accelerator Diagnostics Collaboration, we are exploring the development of integrated multi-GHz ionizing particle detection systems based on chemical-vapor deposition diamond sensors, with the initial goal of producing a quadrant detector that can determine the intensity and centroid position of a particle beam at a repetition rate between 5 and 10 GHz. Results from our initial high-speed characterization work are presented, including those from a single-channel sensor with a GHz response. Approaches to achieving multi-GHz (5–10 GHz) rate capability, including the design of a dedicated Application Specific Integrated Circuit and the use of 3D RF-solver computer aided design software, are presented and discussed in more detail. 3D RF simulations suggest clean pulses of duration less than 250 ps (FWHM less than 125 ps) can be achieved with the approaches developed by this work.

43 PARTICLE ACCELERATORS↗

Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-informed Deep Generative Models

Here, we propose a new method for inferring the governing stochastic ordinary differential equations (SODEs) by observing particle ensembles at discrete and sparse time instants, i.e., multiple “snapshots.” Particle coordinates at a single time instant, possibly noisy or truncated, are recorded in each snapshot but are unpaired across the snapshots. By training a physics-informed generative model that generates “fake” sample paths, we aim to fit the observed particle ensemble distributions with a curve in the probability measure space, which is induced from the inferred particle dynamics. We employ different metrics to quantify the differences between distributions, e.g., the sliced Wasserstein distances and the adversarial losses in generative adversarial networks. We refer to this method as generative “ensemble-regression” (GER), in analogy to the classic “point-regression,” where we infer the dynamics by performing regression in the Euclidean space. We illustrate the GER by learning the drift and diffusion terms of particle ensembles governed by SODEs with Brownian motions and Lévy processes up to 100 dimensions. We also discuss how to treat cases with noisy or truncated observations. Apart from systems consisting of independent particles, we also tackle nonlocal interacting particle systems with unknown interaction potential parameters by constructing a physics-informed loss function. Finally, we investigate scenarios of paired observations and discuss how to reduce the dimensionality in such cases by proving a convergence theorem that provides theoretical support.

97 MATHEMATICS AND COMPUTING↗

Final Report on Aerosol Pretreatment Technology Performance and Benchmarking

Solvent-based post-combustion CO 2 capture (PCC) technology remains one of the leading methods to combat global CO 2 emissions produced from large-scale coal-fired power production. Advanced solventbased PCC technology has made significant improvements in design and performance that reduce capital and operating costs to enable its commercial use. Key to low cost, manageable logistics, and environmentally safe operation of solvent-based PCC technology are minimal solvent losses from the process through the treated gas stream exiting PCC plant absorbers. High flue gas aerosol particle concentrations (>10 5 particles/cm 3 ) for particles in the range of 70-200 nm have been shown to cause significant amine solvent losses for solvent-based PCC processes through several mechanisms including absorption of solvent and water into growing aerosol particles. Flue gas aerosol pretreatment technology is the only realistic and economically attractive method to reduce very high aerosol particle concentrations (>10 7 particles/cm 3 ) to enable solvent-based PCC for existing power plants lacking sufficient particle removal systems, such as baghouses. The overall goal of this project was to design, construct, independently test, and evaluate three flue gas aerosol pretreatment technologies identified to significantly reduce high aerosol particle concentrations (>10 7 particles/cm 3 ) in the 70-200 nm particle size range: (1) a novel, high-velocity water injection spray concept developed by RWE and tested by Linde, (2) an innovative electrostatic precipitator (ESP) device with optimized operating conditions developed by Washington University in St. Louis (WUSTL), and (3) a non-regenerative sorbent-based filter technology developed by InnoSepra for SO x and NO x removal from coal-fired power plant flue gas. Each technology has been validated with tests on 500-1000 scfm of actual coal-fired flue gas and evaluated in terms of particle removal efficiency (%), cost competitiveness, and environmental impact. Aerosol measurements were performed upstream and downstream of each aerosol reduction unit during independent testing of each technology using advanced instrumentation and analytical methods provided by WUSTL. To perform aerosol measurements, isokinetic probes were inserted into flanged pipes attached to the flue gas piping, and a small suction pump was used to sample gas containing aerosol particles. Aerosol particle number concentrations (# particles/cm 3 ) and size distributions were then measured using a scanning mobility particle sizer (SMPS, TSI Inc.) for very fine particles (<1,000 nm) and a particle counter manufactured by GRIMM for particles larger than 1,000 nm. This report summarizes the aerosol removal performance results from pilot scale testing of each technology. Performance results have been benchmarked against pre-defined targets and other flue gas aerosol pretreatment technologies with documented performance. Linde Gas North America LLC has been the prime contractor to DOE responsible for overall project management and provided the design for the high-velocity water spray-based aerosol removal technology based on a design concept developed by the German utility company RWE.

20 FOSSIL-FUELED POWER PLANTS↗

Identified charged-hadron production in 𝑝+Al, 3 He + Au, and Cu + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV and in U + U collisions at $\sqrt{s_{NN}}$ = 193 GeV

The PHENIX experiment has performed a systematic study of identified charged-hadron (𝜋 ± , 𝐾 ± , 𝑝, $\bar{𝑝}$) production at midrapidity in 𝑝 + Al, 3 He + Au, and Cu + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV and U + U collisions at $\sqrt{s_{NN}}$ = 193 GeV. Identified charged-hadron invariant transverse-momentum (𝑝 𝑇 ) and transverse-mass (𝑚 𝑇 ) spectra are presented and interpreted in terms of radially expanding thermalized systems. The particle ratios of 𝐾/𝜋 and 𝑝/𝜋 have been measured in different centrality ranges of large (Cu + Au and U + U) and small (𝑝 + Al and 3 He + Au) collision systems. The values of 𝐾/𝜋 ratios measured in all considered collision systems were found to be consistent with those measured in 𝑝+𝑝 collisions. However, the values of 𝑝/𝜋 ratios measured in large collision systems reach the values of ≈0.6, which is a factor of ≈2 larger than in 𝑝 + 𝑝 collisions. These results can be qualitatively understood in terms of the baryon enhancement expected from hadronization by recombination. Identified charged-hadron nuclear-modification factors (𝑅 𝐴⁢𝐵 ) are also presented. Enhancement of proton 𝑅 𝐴⁢𝐵 values over meson 𝑅 𝐴⁢𝐵 values was observed in central 3 He + Au, Cu + Au, and U + U collisions. Finally, the proton 𝑅 𝐴⁢𝐵 values measured in the 𝑝 + Al collision system were found to be consistent with 𝑅 𝐴⁢𝐵 values of 𝜙, 𝜋 ± , 𝐾 ± , and 𝜋 0 mesons, which may indicate that the size of the system produced in 𝑝 + Al collisions is too small for recombination to cause a noticeable increase in proton production.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Simulating Southern Ocean Aerosol and Ice Nucleating Particles in the Community Earth System Model Version 2

Southern Ocean (SO) low-level mixed phase clouds have been a long-standing challenge for Earth system models to accurately represent. While improvements to the Community Earth System Model version 2 (CESM2) resulted in increased supercooled liquid in SO clouds and improved model radiative biases, simulated SO clouds in CESM2 now contain too little ice. Previous observational studies have indicated that marine particles are major contributor to SO low-level cloud heterogeneous ice nucleation, a process that initiates a number of cloud processes that govern cloud radiative properties. In this study, we utilize detailed aerosol and ice nucleating particle (INP) measurements from two recent measurement campaigns to assess simulated aerosol abundance, number size distributions, and composition and INP parameterizations for use in CESM2. Our results indicate that CESM2 has a positive bias in simulated surface-level total aerosol surface area at latitudes north of 58°S. Measured INP populations were dominated by marine INPs and we present evidence of refractory INPs present over the SO assumed here to be mineral dust INPs. Results highlight a critical need to assess simulated mineral dust number and size distributions in CESM2 in order to adequately represent SO INP populations and their response to long-term changes in atmospheric transport patterns and land use change. Furthermore, we also discuss important cautions and limitations in applying a commonly used mineral dust INP parameterization to remote regions like the pristine SO.

58 GEOSCIENCES↗

Machine Learning for Mapping Multipactor Susceptibility in RF Systems: Capabilities and Generalization Constraints

Multipactor is a surface-driven electron avalanche phenomenon that degrades the performance and reliability of radio-frequency (RF) systems in particle accelerator and vacuum electronics applications. Multipactor behavior in a given device structure is conventionally assessed through susceptibility charts, which provide a parameter-space characterization of the instability. In this work, we assess the capabilities of machine-learning (ML) models to learn and predict such susceptibility charts and analyze the constraints governing their generalization across materials. Using a simulation-derived dataset spanning six distinct secondary-electron-yield material profiles in a canonical two-surface planar geometry, we train supervised regression models and artificial neural networks to predict the time-averaged electron growth rate, δavg, across the relevant parameter space. Model performance is evaluated using metrics that explicitly probe the structure of susceptibility charts, including Intersection over Union, Structural Similarity Index, and correlation analysis. Tree-based ensemble models outperform neural-network models in reconstructing susceptibility regions and in generalizing across material domains. Principal-component analysis reveals disjoint material feature distributions, indicating that the piecewise mode structure of multipactor susceptibility is difficult to represent with a single global model and that generalization is constrained by data coverage rather than by model complexity. An exhaustive reduced-coverage study further shows that sparse material-space coverage can yield mean performance in the same general range but producing large variability in the susceptibility-region overlap. These results clarify the capabilities of ML-based surrogate models for parameter-space characterization of multipactor discharge. They also provide guidance for their appropriate use in RF system design.

43 PARTICLE ACCELERATORS↗

The CLAS12 Forward Time-of-Flight system

The Forward Time-of-Flight system for the large-acceptance CLAS12 spectrometer in Hall B at the Thomas Jefferson National Accelerator Facility is described. The system is positioned at distances in the range from 6.2 m to 7.2 m from the beam–target interaction point and spans laboratory polar angles from 5 deg → 45 deg and nearly the full azimuth. The system consists of 540 individual scintillation counters with double-ended readout that range in length from 17 cm to 426 cm of discrete widths of 6 cm, 15 cm, and 22 cm, and of discrete thicknesses of 5 cm and 6 cm. We see the effective counter time resolution for passing charged particles varies from 50 ps for the shortest counters at small angles to 200 ps for the longest counters at large angles. The detectors are part of the forward-angle particle identification system for CLAS12 during offline event reconstruction and are a component of the online data acquisition trigger to select final state event topologies with forward-going charged particles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Simulation of Alfvénic avalanche onset in NSTX

In some tokamak discharges, a number of Alfvén eigenmodes (AEs) have been observed to cause a large-scale collapse of the high energy particle distribution, a phenomenon referred to as an avalanche. We examine the necessary conditions for an avalanche using the available experimental information from NSTX on the equilibrium and mode properties for two cases, one with a measurable but benign AE activity and one with an AE activity leading up to an avalanche. To produce an avalanche, the modes present in the discharge must possess resonances that can overlap with a modest increase in instability magnitude, providing a path to global particle stochastic motion. In this paper, we find that the modes present in the avalanche-free discharge do not provide such a path even at a very large amplitude. During the discharge which subsequently produces an avalanche, the high energy population is growing and the Alfvén frequency is dropping due to increasing density, and we find that both these changes, producing a small increased drive or an increased resonance width for the Alfvén modes, can lead in this case to uncontrolled mode growth and large-scale beam particle loss.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗