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At least 541 records · Page 30

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DOE OSTI2020

Drive-pressure optimization in ramp-wave compression experiments through differential evolution

Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. Furthermore, we solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closely reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

A linked-scale coupled model of mass erosion and redistribution in plasma-exposed micro-foam surfaces

Surface evolution due to exposure to harsh environments is of importance in many scientific and technological applications. In plasma-exposed materials, the surface receives charged particles from the plasma, leading to a series of processes that drive the system far from equilibrium and may lead to the severe deterioration of the surface properties. Although surface morphological changes are driven by atomic collisions taking place over picoseconds and nanometers, these processes result in mass loss and redistribution of matter over much larger length and time scales. This necessitates a multi-scale approach capable of capturing the range of processes linking primary atomic collision events with engineering-level surface geometry changes. In this paper, we develop a computational model to simulate the morphological evolution and effective erosion rate of micro-architected tungsten foams during low-energy plasma ion bombardment. Furthermore, the model acts on several length scales, with the energy and angular dependence of the sputtering yield of flat tungsten surfaces determined using the SRIM code based on the binary collision approximation. This information is introduced into a low-fluence, short-term Monte Carlo raytracing model, and further into a high-fluence, long-term particle transport model. In the latter, material particles representing billions of atoms are described in a digitized 3-D representation of the foam structure from X-ray tomography data, and are sputtered off and redeposited using the atomistic information. We show that the redeposition of sputtered atoms leads to partial self-healing in the bottom layers with a sharp reduction in the sputtering coefficient of low density foams, roughly 25% of the solid W value. This is in qualitative agreement with recent experiments on low porosity W structures. At high fluence, the foam structure degrades considerably as there are fewer ligaments available to recapture sputtered atoms and, consequently, the sputtering rate increases again.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Anisotropic flow and flow fluctuations of identified hadrons in Pb–Pb collisions at $ \sqrt{s_{\textrm{NN}}}$ = 5.02 TeV

The first measurements of elliptic flow of π ± , K ± , p+$\bar{p}$, K$_{S}^{0}$, Λ+$\bar{Λ}$, $\phi$, Ξ – +$\barΞ$ + , and Ω – +$\barΩ$ + using multiparticle cumulants in Pb–Pb collisions at $\sqrt{s_{NN}}$= 5.02 TeV are resented. Results obtained with two- (v 2 {2}) and four-particle cumulants (v 2 {4}) are shown as a function of transverse momentum, p T , for various collision centrality intervals. Combining the data for both v 2 {2} and v 2 {4} also allows us to report the first measurements of the mean elliptic flow, elliptic flow fluctuations, and relative elliptic flow fluctuations for various hadron species. These observables probe the event-by-event eccentricity fluctuations in the initial state and the contributions from the dynamic evolution of the expanding quark–gluon plasma. The characteristic features observed in previous p T -differential anisotropic flow measurements for identified hadrons with two-particle correlations, namely the mass ordering at low p T and the approximate scaling with the number of constituent quarks at intermediate p T , are similarly present in the four-particle correlations and the combinations of v 2 {2} and v 2 {4}. In addition, a particle species dependence of flow fluctuations is observed that could indicate a significant contribution from final state hadronic interactions. The comparison between experimental measurements and CoLBT model calculations, which combine the various physics processes of hydrodynamics, quark coalescence, and jet fragmentation, illustrates their importance over a wide p T range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Shape‐Evolving Structured Liquids

Migration, division, and reconfiguration - functions essential to living systems - are driven by active processes. Developing synthetic mimics is an outstanding challenge. Lipid bilayers that bound natural systems are locally deformed by active species, e.g., microtubules, but the resulting non-equilibrium shapes relax when active species motion ceases, and the shape changes lack immediate control. A fully synthetic system is described, driven by active particles encapsulated by a reconfigurable nanoparticle-surfactant membrane that undergoes shape fluctuations reminiscent of living cells. These shape changes are preserved after particle activity stops. Surfactant concentration tunes the interfacial tension over three orders of magnitude, making on-demand shape evolution possible. Directional migration, division, and reconfiguration across multiple scales are possible, leading to a new class of biomimetic, reconfigurable, and responsive materials, paving the way for autonomous synthetic machines.

Kim, Paul Y↗

DOE OSTI2023

Molybdenum in basalt-hosted seafloor hydrothermal systems: Experimental, theoretical, and field sampling approaches

Here, seafloor hydrothermal vents represent potential sources of Mo and other biologically relevant transition metals to the global ocean, complementing continental runoff. Here, we use a combination of experimental, theoretical, and field-sampling approaches to investigate the behavior of Mo in basalt-hosted seafloor hydrothermal systems to provide insight into the processes controlling Mo concentrations in hydrothermal fluids and to derive estimates of vent fluid Mo concentrations and fluxes. Results of this study demonstrate that reaction fluids generated from 350°C, 500 bar hydrothermal basalt alteration experiments contain 775–801 nmol/kg Mo and are thus comparable to a recently collected time series of natural seafloor vent fluids that contained 200–220 nmol/kg Mo at 302°C and 29–30 nmol/kg at 281–282°C (Evans et al., 2023). Synchrotron-based analyses of experimentally altered basalt produced in this study and additional natural samples of altered oceanic crust originally collected from Pito Deep Rift reveal the presence of Mo-rich particles consistent with trace molybdenite. Comparisons of Mo:Cu ratios in natural vent fluids and near-vent sediment trap samples from Main Endeavour Field indicate that vent fluid Mo is readily incorporated into buoyant plume particles and advected out of the near-vent field, analogous to previous mass balance studies of Cu in this region. Thermodynamic calculations of molybdenite solubility in the context of mineral-buffered hydrothermal fluids and comparisons with natural and experimental hydrothermal fluids suggest that high-temperature vent fluids contain 30–1500 nmol/kg Mo. While a minor component of the modern Mo budget, hydrothermal Mo fluxes are estimated to have constituted 0.3–200× the contemporaneous continental weathering fluxes prior to the ~2.4 Ga ago “Great Oxidation Event” and widespread oxidative continental weathering. Overall, identification of hydrothermal vents as a source of Mo-rich plume particles with potential for dispersal into the wider marine environment has significant implications for hypotheses regarding the co-evolution of Life and Earth’s environments, specifically the form and availability of Mo in anoxic Archean-Eon oceans, where Mo-dependent enzymatic pathways are thought to have emerged and subsequently evolved.

58 GEOSCIENCES↗

DOE OSTI2023

Material flow behavior and microstructural refinement of AA6061 alloy during friction extrusion

In this work we used friction extrusion (FE), a solid phase processing technique, to produce dense, fully consolidated 5?mm rods of aluminum alloy 6061 (AA6061). The combination of large shear stresses and high temperatures at the tool-billet interface during extrusion produced equiaxed, dynamically recrystallized grains and finely distributed precipitates. Texture and microstructure evolution during extrusion was investigated in detail using scanning electron microscopy, electron backscatter diffraction, and transmission electron microscopy. Smoothed particle hydrodynamics simulation was performed to study complex material flow during extrusion. Simulation results suggest spiral material flow during extrusion which corroborated experimental results. Advantages of friction extruded microstructure over conventionally extruded counterparts are also explored using flash annealing for solution treatment followed by artificial aging. Mechanical properties of the as-friction extruded, and the artificially aged specimens were evaluated using tensile testing and compared with conventional extruded material properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Physicochemical Heterogeneity in Silicon Anodes from Cycled Lithium-Ion Cells

The severe capacity fade of lithium-ion cells with silicon-dominant anodes has hindered their widescale commercialization. In this work, we link cell capacity fade to the heterogeneous physicochemical evolution of silicon anodes during battery cycling. Through a multi-length scale characterization approach, we demonstrate that silicon particles near the anode surface react differently than those near the copper current collector. In particular, near the anode surface we find an amorphized wispy silicon encased in a highly fluorinated matrix of electrolyte-reduction products. In contrast, closer to the current collector, the silicon retains more of its initial morphology and structure, suggesting the presence of isolated particles. Here, the results show that accessibility of active silicon to lithium-ions varies across the anode matrix. Material and cell designs, which minimize electrode expansion resulting from the in-filling of pores with the solid electrolyte interphase (SEI), are needed to enhance anode homogeneity during the electrochemical cycling.

25 ENERGY STORAGE↗

DOE OSTI2024

Transfer functions for Q A /Q B international regulatory limits for the safe transport of radioactive materials

This paper presents a proposed revision of the International Atomic Energy Agency transport regulations, related to the A 1 and A 2 limit values used to determine the radioactive transport classification. Based on the 'Q system', a novel methodology was introduced to derive Q A and Q B values related to scenarios involving external exposure from a distant source. These values are key parameters that respectively represent the total effective dose and total equivalent dose to the skin, from all primary and secondary particles contributing to radiation exposure. The International Working Group (WG A 1 /A 2 ) is established and associated with the TRANSSC Technical Expert Group on Radiation Protection. A review of the A 1 and A 2 values is performed in response to identified limitations within the existing Q system. The followed approach is based on Monte Carlo simulations that enabled the development of transfer functions aimed at reducing computational time and increasing the flexibility of dose evaluations for any radionuclide with known particle emission spectra. This method allows updating the Q A and Q B values to account for future data evolutions (decay data, fluence-to-dose conversion coefficients) and standardizing the calculation of regulation limits across all referenced radionuclides and scenarios related to external exposure. The transfer functions are established using three Monte Carlo simulation codes—FLUKA, Geant4, and MCNP—and address the previous limitations of the 'Q system', reflecting the latest International Commission for Radiation Protection recommendations and improvements in calculation techniques. The results of the WG show consistent agreement across the codes, with minor discrepancies observed at low primary energies due to statistical uncertainties and different handling of stopping power for electrons/positrons in the codes. This revised approach aligns with current standards and recommendations, ensuring that the radiological consequences of transport accidents are acceptable for the new A 1 and A 2 limits from a radiological protection perspective.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2020

Code package for calculating modified cosmic ionization and thermal histories with dark matter and other exotic energy injections

Here we present a new public Python package, DarkHistory, for computing the effects of dark matter annihilation and decay on the temperature and ionization history of the early universe. DarkHistory simultaneously solves for the evolution of the free electron fraction and gas temperature, and for the cooling of annihilation/decay products and the secondary particles produced in the process. Consequently, we can self-consistently include the effects of both astrophysical and exotic sources of heating and ionization, and automatically take into account backreaction, where modifications to the ionization/temperature history in turn modify the energy-loss processes for injected particles. We introduce a number of worked examples, demonstrating how to use the code in a range of different configurations, in particular for arbitrary dark matter masses and annihilation/decay final states. Possible applications of DarkHistory include mapping out the effects of dark matter annihilation/decay on the global 21 cm signal and the epoch of reionization, as well as the effects of exotic energy injections other than dark matter annihilation/decay. The code is available at https://github.com/hongwanliu/DarkHistory with documentation at https://darkhistory.readthedocs.io. Data files required to run the code can be downloaded at https://doi.org/10.7910/DVN/DUOUWA.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Phase separation during the direct powder bed fusion of SiC

Powder bed fusion (PBF) is an attractive additive manufacturing option for fabrication of SiC object with complex geometries. However, the density and microstructure controls remain a challenge. This study is aimed at understanding laser–SiC interactions, with emphasis on microstructure-processing relationships, to identify potential solutions for the process improvement. SiC tubes were fabricated by PBF of pure SiC powders without sintering additives. Further, comprehensive analysis by X-ray diffraction, Raman spectroscopy, and electron microscopy indicated that binding of SiC particles was achieved by incongruent melting of SiC to a Si/C mixture containing SiC micro- and nanocrystallites. The phase evolution under laser irradiation of SiC was explained by phase diagrams. This study uncovered the PBF SiC microstructure at different length scales and the relationship between the microstructure and the processing parameters.

36 MATERIALS SCIENCE↗

DOE OSTI2021

2019 Computing Sciences Strategic Plan

Computing has transformed nearly every aspect of scientific inquiry — across disciplines and across scales — from the behavior of subatomic particles to the formation of structures in the early universe, from the assembly of the human genome to the evolution of earth systems. Over the past two decades, computing has become an integral part of how Berkeley Lab is “Bringing Science Solutions to the World.” Advances in computing and mathematics have been key, with new mathematical models of complex physical phenomena, new methods for analyzing complex data, new algorithms for accuracy and scaling and sophisticated software systems that encapsulate these techniques into open, reusable tools. The performance of NERSC computers and the ESnet network have grown by several orders of magnitude, along with our understanding of how to map scientific computations and workflows onto these systems. From research to facility operations, the passion, talent and dedication of the Computing Sciences Area staff has been the cornerstone of our success. The plan outlined in this document describes the next step in a journey to expand the influence and impact of our efforts, building an increasingly connected global enterprise for science that places more powerful instruments in the hands of scientists, along with more powerful methods and tools for modeling, analysis and prediction.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Data-Driven Specification of Earth's Magnetic Field

As our society is increasingly dependent on technologies in space, predicting space weather becomes ever more important. We have come to rely on technologies such as cellphones, GPS, the Internet, and other commercial and military assets. In order to protect these systems a high priority is to develop better understanding of the harmful conditions of space weather encountered in the near-Earth radiation environment which are mostly dictated by the dynamics of energetic charged particles. The main objective of our proposal was to improve the specification and forecast of the particle distribution in the Earth’s inner magnetosphere using data assimilation together with machine learning (ML) algorithms in our ring current-atmosphere interactions model with self-consistent magnetic and electric fields (RAM-SCBE). Specifically, we explored the application of machine learning algorithms to emulate and improve, through infusion of observational data, the magnetic field (SCBE) of our ring current model. Our work advanced towards the characterization of the RAM-SCBE particle flux field and its potentially different simulation scenarios. We explored how the model behaves in a number of simulation scenarios in order to better understand how the model reacts to perturbations in the solar wind. We were able to capture this behavior through the simulation of an ensemble of RAM-SCB model solutions. The ensemble showed the important correlations between the particle fluxes and the magnetic field. We were able to start the training of a neural network (Autoencoder) to identify the dominant features of the magnetic field, and the main correlations (linear and non-linear) between the particle fluxes and the magnetic field. Our next steps consists of training a neural network to capture the time evolution of the dominant features and obtain a consistent surrogate model for the RAM-SCB.

42 ENGINEERING↗

DOE OSTI2022

Investigating charm production and fragmentation via azimuthal correlations of prompt D mesons with charged particles in pp collisions at $\mathbf {\sqrt{ s} = 13}$ TeV

Angular correlations of heavy-flavour and charged particles in high-energy proton–proton collisions are sensitive to the production mechanisms of heavy quarks and to their fragmentation as well as hadronisation processes. The measurement of the azimuthal-correlation function of prompt D mesons with charged particles in proton–proton collisions at a centre-of-mass energy of $\sqrt{s} = 13$ TeV with the ALICE detector is reported, considering $\mathrm D^{0} $ , $\mathrm D^{+} $ , and $\mathrm D^{*+} $ mesons in the transverse-momentum interval $3< p_{\mathrm{T}} < 36$ GeV/ $c$ at midrapidity ( $|y| < 0.5$ ), and charged particles with $p_{\mathrm{T}} > 0.3$ GeV/ $c$ and pseudorapidity $|\eta | < 0.8$ . This measurement has an improved precision and provides an extended transverse-momentum coverage compared to previous ALICE measurements at lower energies. The study is also performed as a function of the charged-particle multiplicity, showing no modifications of the correlation function with multiplicity within uncertainties. The properties and the transverse-momentum evolution of the near- and away-side correlation peaks are studied and compared with predictions from various Monte Carlo event generators. Among those considered, PYTHIA8 and POWHEG+PYTHIA8 provide the best description of the measured observables. The obtained results can provide guidance on tuning the generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

An Ensemble Score Filter for Tracking High-Dimensional Nonlinear Dynamical Systems

We propose an ensemble score filter (EnSF) for solving high-dimensional nonlinear filtering problems with superior accuracy. A major drawback of existing filtering methods, e.g., particle filters or ensemble Kalman filters, is the low accuracy in handling high-dimensional and highly nonlinear problems. EnSF attacks this challenge by exploiting the score-based diffusion model, defined in a pseudo-temporal domain, to characterizing the evolution of the filtering density. EnSF stores the information of the recursively updated filtering density function in the score function, in stead of storing the information in a set of finite Monte Carlo samples (used in particle filters and ensemble Kalman filters). Unlike existing diffusion models that train neural networks to approximate the score function, we develop a training-free score estimation that uses mini-batch-based Monte Carlo estimator to directly approximate the score function at any pseudo-spatial-temporal location, which provides sufficient accuracy in solving high-dimensional nonlinear problems as well as saves tremendous amount of time spent on training neural networks. Another essential aspect of EnSF is its analytical update step, gradually incorporating data information into the score function, which is crucial in mitigating the degeneracy issue faced when dealing with very high-dimensional nonlinear filtering problems. High-dimensional Lorenz systems are used to demonstrate the performance of our method. EnSF provides surprisingly impressive performance in reliably tracking extremely high-dimensional Lorenz systems (up to 1,000,000 dimension) with highly nonlinear observation processes, which is a well-known challenging problem for existing filtering methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020