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Results for “Particle properties”
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Influence of Particle-Scale Properties on Fracture Behavior of Silica Sand
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Impact of a New Cloud Microphysics Parameterization on the Simulations of Mesoscale Convective Systems in E3SM
Abstract Mesoscale convective systems (MCSs) are one of the most climatically significant forms of convection because of their large role in water and energy cycles. The mesoscale features associated with MCS are difficult to represent in climate models because the relevant dynamics and physics are absent or poorly represented with coarse model resolution (∼100 km). Using a regionally refined model (RRM) with 0.25° grid spacing embedded in the Energy Exascale Earth System Model (E3SM), we explore the impact of cloud microphysics parameterizations on the simulation of precipitation, particularly MCS precipitation over the contiguous United States. The Predicted Particle Properties (P3) cloud microphysics scheme has been modified and implemented into E3SM to overcome the limitations of the default Morrison and Gettelman (MG2) scheme in which rimed precipitating ice particles (graupel/hail) are absent and frozen particles are artificially partitioned into cloud ice and snow. We show that P3 improves the simulation of precipitation statistics including frequency distribution compared with MG2 with a limited effect on the diurnal cycle. P3 predicts higher hourly rain rates, resulting in 20% more MCSs and a higher total MCS precipitation (4.4%) compared to MG2, agreeing better with observations. The improvements with P3 mainly result from improved representations of ice microphysics, which not only produces higher rain rates through melting but also leads to a stronger large‐scale ascending motion by releasing more latent heating. This study suggests that improving microphysics parameterization is important for simulating MCS precipitation as future climate model resolutions continue to increase.
Conservation laws in coupled cluster dynamics at finite temperature
We extend the finite-temperature Keldysh non-equilibrium coupled cluster theory (Keldysh-CC) [A. F. White and G. K.-L. Chan, J. Chem. Theory Comput. 15, 6137–6253 (2019)] to include a time-dependent orbital basis. When chosen to minimize the action, such a basis restores local and global conservation laws (Ehrenfest’s theorem) for all one-particle properties while remaining energy conserving for time independent Hamiltonians. We present the time-dependent Keldysh orbital-optimized coupled cluster doubles method in analogy with the formalism for zero-temperature dynamics, extended to finite temperatures through the time-dependent action on the Keldysh contour. To demonstrate the conservation property and understand the numerical performance of the method, we apply it to several problems of nonequilibrium finite-temperature dynamics: a 1D Hubbard model with a time-dependent Peierls phase, laser driving of molecular H2, driven dynamics in warm-dense silicon, and transport in the single impurity Anderson model.
Detection of multi-modal Doppler spectra – Part 1: Establishing characteristic signals in radar moment data
Vertically pointing millimeter-wavelength radars provide a wealth of information about cloud and precipitation particle properties. Doppler spectral data can inform on how particles of varying vertical velocities contribute to the total backscattered power observed. It is more computationally cost effective to process moment data instead of spectra data, but doing so leaves valuable information on the cutting room floor. To confidently identify a multi-modal spectra event, in which two or more modes are present within a layer, Doppler spectral data are essential. This means long-term identification of layers featuring multi-modal spectra can be cost prohibitive. To address this, we explore three multi-modal spectra cases from winter precipitation events to determine characteristic signatures of these layers in the moment data averaged over short time periods (∼ 145 s) and explore how these layers differ from the rest of the vertical profiles. We find that the mean spectrum width and the standard deviation of mean Doppler velocity can be used to determine whether or not a layer is multi-modal. In particular, multi-modal layers in mixed-phase and ice clouds feature larger mean spectrum width (exceeding 0.17 m s −1 ) and smaller standard deviation of the mean Doppler velocity (below 0.1 m s −1 ). In Part 1 of this study, the identification criteria and methods are described. In Part 2 (Wugofski and Kumjian, 2025), we perform a verification of the method for three years of vertically pointing radar data, and explore the meteorological conditions associated with identified multi-modal spectral events.
Revisiting GeV-scale annihilating dark matter with the AMS-02 positron fraction
Antimatter cosmic-rays are used to probe new phenomena in physics, including dark matter annihilation. Here, we use the cosmic-ray positron fraction spectrum by the Alpha Magnetic Spectrometer, to search for such an annihilation signal in the Galaxy. We focus on dark matter with mass between 5 and 120 GeV, producing high-energy electrons and positrons. In these cosmic-ray energies the interplay of multiple astrophysical sources and phenomena, makes this search highly sensitive to the underlying astrophysical background assumptions. We use a vast public library of astrophysical models for the cosmic-ray positron fraction background, to derive robust upper limits on the dark matter's annihilation cross section for a number of annihilation channels. This library accounts for different types of cosmic-ray sources and uncertainties on their distribution in space and time. Also, it accounts for uncertainties on those sources' output, their injected into the interstellar medium cosmic-ray spectra and for uncertainties on cosmic-ray propagation. For any given dark matter particle mass and annihilation channel, upper limits on the annihilation cross section are given by bands that stretch a full order of magnitude in its value. Our work provides weaker limits compared to earlier results, that are however robust to all the relevant astrophysical uncertainties. Between 5 and 15 GeV, we find indications for a possible excess flux of cosmic-ray electrons and positrons. That excess is found for most, but not all of our astrophysical background parameter space, and its significance can vary appreciably. Further scrutiny is necessary to improve the understanding of these lower energy cosmic rays. Finally, we note that even if an excess signal is found in these energies, the current background uncertainties do not allow us to accurately deduce its underlying particle properties.
Reconstruction of decays to merged photons using end-to-end deep learning with domain continuation in the CMS detector
A novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz-boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods typically used in high energy physics analyses. It uses minimally processed detector data as input and directly outputs particle properties of interest. The new technique is demonstrated for the reconstruction of the invariant mass of particles decaying in the CMS detector. The decay of a hypothetical scalar particle A into two photons, A → γ γ , is chosen as a benchmark decay. Lorentz boosts γ L = 60 – 600 are considered, ranging from regimes where both photons are resolved to those where the photons are closely merged as one object. A training method using domain continuation is introduced, enabling the invariant mass reconstruction of unresolved photon pairs in a novel way. The new technique is validated using π 0 → γ γ decays in LHC collision data.
Challenges and Advances in Aqueous Processing of Corn Stover Pellets into High Concentration Slurries
Significant progress has occurred in developing combined enzyme hydrolysis and fermentation technologies for transforming lignocellulosic feedstocks into ethanol and other bioproducts. Various routes described in the literature show that low carbon footprint processes efficiently convert the cellulose and hemicellulose fractions of pretreated corn stover, wood chips, and sugarcane bagasse to sugars and to ethanol.Combinations of different pretreatments at high or low pH or in liquid hot water, followed by enzyme hydrolysis and fermentation or direct conversion of cellulose to ethanol (i.e., by consolidated bioprocessing)have been demonstrated. These successes have brought the need to preparing the feedstock – before it enters the biorefinery – into focus. This paper summarizes recent developments in liquefying corn stover,before pretreatment, so that slurries with yield stresses below 200 Pa are obtained and a “pumpable” corn stover slurry results at initial solids loadings of up to 300 g/L. The manner in which corn stover pellets are combined with water and enzyme in an agitated bioreactor is described, and properties that define slurry behavior are presented. Implications on biorefinery operations are explained in terms of particle properties and the preprocessing of corn stover as well as the team approach used to obtain these results.
Overview of symmetric nuclear matter properties from chiral interactions up to fourth order of the chiral expansion
We present and discuss predictions for a cross section of bulk and single-particle properties in symmetric nuclear matter based on recent high-quality nucleon-nucleon potentials at N 3 LO and including all subleading three-nucleon forces. We begin with the equation of state and its saturation properties and proceed to the single-nucleon potential. We also explore short-range correlations as seen through the defect function. The various predictions which we present have a common foundation in an internally consistent ab initio approach.
Particle trapping, size-filtering, and focusing in the nonthermal plasma synthesis of sub-10 nanometer particles
Low-pressure nonthermal flowing plasmas are widely used for the gas-phase synthesis of nanoparticles and quantum dots of materials that are difficult or impractical to synthesize using other techniques. To date, the impact of temporary electrostatic particle trapping in these plasmas has not been recognized, a process that may be leveraged to control particle properties. Furthermore, we present experimental and computational evidence that, during their growth in the plasma, sub-10 nm silicon particles become temporarily confined in an electrostatic trap in radio-frequency excited plasmas until they grow to a size at which the increasing drag force imparted by the flowing gas entrains the particles, carrying them out of the trap. We demonstrate that this trapping enables the size filtering of the synthesized particles, leading to highly monodisperse particle sizes, as well as the electrostatic focusing of the particles onto the reactor centerline. Understanding of the mechanisms and utilization of such particle trapping will enable the design of plasma processes with improved size control and the ability to grow heterostructured nanoparticles.
Particle Dark Matter Across Scales (Final Technical Report)
The research supported by this DOE grant investigated the nature of dark matter, particularly its particle properties and astrophysical manifestations, over the period of 2018 to 2024. The proposal focused on leveraging astrophysical probes, cosmological models, and high-resolution simulations to further our understanding of dark matter, its possible interactions, and the theoretical models that could explain its properties. This research directly contributes to the DOE's mission of exploring the fundamental constituents of the universe, advancing particle physics, and using cosmological and astrophysical observations to detect dark matter.
A point-particle-based hydride shell-shedding model for ejecta particle transport in reactive environments
A shock wave passing over a rough or perturbed metal surface will induce a limiting case of Richtmyer–Meshkov instability and will cause small particles to eject from the surface and transport into the surrounding medium. These particles are known as ejecta and can be either solid or liquid in nature. Recent experiments have shown that liquid cerium ejecta clouds exhibit unexpected non-monotonic acceleration behaviors as well as temperature plateaus after a brief temperature rise if they are transporting in a chemically reactive, hydrogen-based medium while they act as expected in an inert medium. This work details a point-particle model developed for reactive cerium ejecta transport, which attempts to account for these new physics through the behavior of a developing solid hydride shell, which is believed to form as a product of the reaction. The overall model incorporates the effects of the reaction on the particle properties as well as the effects of potential shedding of the shell into sub-micrometer scale flakes and potential phase change of the hydride if the ejecta particles reach the melt point of the hydride layer. The model is tested by performing simulations of the original motivating experiments and comparing quantities, such as ejected mass, velocimetry, and temperature profiles, against the experimental data. While the model is able to capture many general features of the observed anomalies, some inaccuracies still exist. These point to both missing physics in the model (such as a deuterium adsorption mechanism on the hydride layer) as well as a lack of knowledge of certain material properties (such as the strength of cerium hydride to determine dynamic fracture thicknesses) needed to fully reduce the uncertainties in the model by up to an order of magnitude and perform a true attempt at model validation.
Differential emissivity based evaporable particle measurement
A differential emissivity imaging device for measuring evaporable particle properties can include a heated plate, a thermal camera, a memory device, and an output interface. The heated plate can have an upper surface oriented to receive falling evaporable particles. The evaporable particles have a particle emissivity and the upper surface has a plate surface emissivity. The thermal camera can be oriented to produce a thermal image of the upper surface. A memory device can include instructions that cause the imaging device to calculate a mass of the individual evaporable particle via heat conduction using a calculated surface area and an evaporation time.
Introducing the Video In Situ Snowfall Sensor (VISSS)
The open-source Video In Situ Snowfall Sensor (VISSS) is introduced as a novel instrument for the characterization of particle shape and size in snowfall. The VISSS consists of two cameras with LED backlights and telecentric lenses that allow accurate sizing and combine a large observation volume with relatively high pixel resolution and a design that limits wind disturbance. VISSS data products include various particle properties such as maximum extent, cross-sectional area, perimeter, complexity, and sedimentation velocity. Initial analysis shows that the VISSS provides robust statistics based on up to 10 000 unique particle observations per minute. Comparison of the VISSS with the collocated PIP (Precipitation Imaging Package) and Parsivel instruments at Hyytiälä, Finland, shows excellent agreement with the Parsivel but reveals some differences for the PIP that are likely related to PIP data processing and limitations of the PIP with respect to observing smaller particles. The open-source nature of the VISSS hardware plans, data acquisition software, and data processing libraries invites the community to contribute to the development of the instrument, which has many potential applications in atmospheric science and beyond.
Exploring the relationship between solvent-assisted ball milling, particle size, and sintering temperature in garnet-type solid electrolytes
Garnet-type solid electrolytes, such as Li 6.4 La 3 Zr 1.4 Ta 0.6 O 12 (LLZTO), are promising materials for solid-state batteries, but processing remains a challenge, in part due to the high sintering temperature required for densification. Additionally, this temperature can be lowered by decreasing the initial particle size via solvent-assisted ball milling, but the relationship between solvent choice, particle properties, sintering behavior, and ionic conductivity is not well understood. In this work, we systematically explore these parameters, showing that milling in commonly used protic solvents, such as alcohols, effectively decreases the particle size but results in lithium loss (through Li + /H + exchange) that leads to poor sintering. By contrast, milling in aprotic solvents with surfactant reduces the particle size to ~220 nm without lithium loss, enabling the fabrication of dense samples (5.1 g/cm 3 ) with good ionic conductivity (0.43 mS/cm at 25 °C) at a lower sintering temperature (1000 °C). We compare ionic conductivities and activation energies for samples prepared with different particle sizes and sintering temperatures and use multiphase-field simulations to identify the mass transport and microstructural mechanisms responsible for the observed sintering dependence on particle size. These results further clarify the relationship between processing parameters and performance and represent important progress toward overcoming fabrication challenges for these materials.
Vertical Structure and Ice Production Processes of Shallow Convective Postfrontal Clouds over the Southern Ocean in MARCUS. Part II: Modeling Study
Abstract Part I of this series presented a detailed overview of postfrontal mixed-phase clouds observed during the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field campaign. In Part II, we focus on a multiday (23–26 February 2018) case with the aim of understanding ice production as well as model sensitivity to ice process parameterizations using the Weather Research and Forecasting (WRF) Model. The control simulation with the Predicted Particle Properties (P3) microphysics scheme underestimates the ice content and overestimates the supercooled liquid water content, contrary to the bias common in global climate models. The simulations targeted at ice production processes show negligible sensitivity to cloud droplet number concentrations. Further, neither increasing ice nuclei particle (INP) concentrations to an unrealistic level nor adjusting it to MARCUS field estimations alone guarantees more ice production in the model. However, the simulated clouds are found to be highly sensitive to the implementation of immersion freezing, the thresholding of condensation/deposition freezing initiation, and the rime splintering process. By increasing immersion freezing of cloud droplets, relaxing thresholds for condensation/deposition freezing, or removing rime splintering thresholds, the model significantly improves its performance in producing ice. The relaxation of the immersion freezing temperature threshold to the observed cloud-top temperature suggests an in-cloud seeder–feeder mechanism. The results of this work call for an increase in observations of INP, especially over the remote Southern Ocean and at relatively high temperatures, and measurements of ice particle size distributions to better constrain ice nucleating processes in models.
Snowmass2021 CMB-HD White Paper
CMB-HD is a proposed millimeter-wave survey over half the sky that would be ultra-deep (0.5 uK-arcmin) and have unprecedented resolution (15 arcseconds at 150 GHz). Such a survey would answer many outstanding questions about the fundamental physics of the Universe. Major advances would be 1.) the use of gravitational lensing of the primordial microwave background to map the distribution of matter on small scales (k~10 h Mpc^(-1)), which probes dark matter particle properties. It will also allow 2.) measurements of the thermal and kinetic Sunyaev-Zel'dovich effects on small scales to map the gas density and velocity, another probe of cosmic structure. In addition, CMB-HD would allow us to cross critical thresholds: 3.) ruling out or detecting any new, light (< 0.1 eV) particles that were in thermal equilibrium with known particles in the early Universe, 4.) testing a wide class of multi-field models that could explain an epoch of inflation in the early Universe, and 5.) ruling out or detecting inflationary magnetic fields. CMB-HD would also provide world-leading constraints on 6.) axion-like particles, 7.) cosmic birefringence, 8.) the sum of the neutrino masses, and 9.) the dark energy equation of state. The CMB-HD survey would be delivered in 7.5 years of observing 20,000 square degrees of sky, using two new 30-meter-class off-axis crossed Dragone telescopes to be located at Cerro Toco in the Atacama Desert. Each telescope would field 800,000 detectors (200,000 pixels), for a total of 1.6 million detectors.
Optical conductivity of overdoped cuprates from ab initio out-of-plane impurity potentials
Dopant impurity potentials determined by ab initio supercell density functional theory calculations are used to calculate the optical conductivity of overdoped La 2-x Sr x CuO 4 (LSCO) and Tl 2 Ba 2 CuO 6+δ (Tl-2201) in the superconducting and normal states. Vertex corrections are included to account for the effect of forward scattering on two-particle properties. This approach was previously shown to provide good, semiquantitative agreement with measurements of superfluid density in LSCO. Here, in this study, we compare calculations of conductivity with measurements of terahertz conductivity on LSCO using identical impurity, band, and correlation parameters and find similarly good correspondence with experiment. In the process, we delineate the impact of the different disorder mechanisms on single-particle and transport relaxation processes. In particular, we reveal the critical role of apical oxygen vacancies in transport scattering and show that transport relaxation rates in LSCO are significantly reduced when apical oxygen vacancies are annealed out. These considerations are shown to be crucial for understanding the variability of experimental results for overdoped LSCO in samples of nominally identical doping but different types. Finally, we give predictions for Tl-2201 terahertz conductivity experiments.