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DOE OSTI2023

Microkinetic insights into the role of catalyst and water activity on the nucleation, growth, and dissolution during COF-5 synthesis

The chemical pathway for synthesizing covalent organic frameworks (COFs) involves a complex medley of reaction sequences over a rippling energy landscape that cannot be adequately described using existing theories. Even with the development of state-of-the-art experimental and computational tools, identifying primary mechanisms of nucleation and growth of COFs remains elusive. Other than empirically, little is known about how the catalyst composition and water activity affect the kinetics of the reaction pathway. In this work, for the first time, we employ time-resolved in situ Fourier transform infrared spectroscopy (FT-IR) coupled with a six-parameter microkinetic model consisting of ~10 million reactions and over 20 000 species. The integrated approach elucidates previously unrecognized roles of catalyst pK a on COF yield and water on growth rate and size distribution. COF crystalline yield increases with decreasing pK a of the catalysts, whereas the effect of water is to reduce the growth rate of COF and broaden the size distribution. The microkinetic model reproduces the experimental data and quantitatively predicts the role of synthesis conditions such as temperature, catalyst, and precursor concentration on the nucleation and growth rates. Furthermore, the model also validates the second-order reaction mechanism of COF-5 and predicts the activation barriers for classical and non-classical growth of COF-5 crystals. The microkinetic model developed here is generalizable to different COFs and other multicomponent systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

The precession frequency measurement in the Muon $g - 2$ experiment at Fermilab

The Muon g-2 (E989) experiment aims to reduce the uncertainty on the muon magnetic anomaly value (aμ = g-22 ) by a factor four (0.14 ppm) compared to the previous experiment at Brookhaven National Laboratory (BNL) in order to clarify the difference (now greater than 3 σ) between the experimental value and the Standard Model (SM) prediction. E989 collected a dataset with the same statistical power of the BNL experiment during the Run 1 data taking (2018). The analysis of data is approaching the final stage and the first result should become available in2021. In this paper, I will briefly describe the experimental setup and discuss the measure of the muon’s spin anomalous precession frequency.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Machine Learning Training for HOM reduction and Emittance Preservation in a TESLA-type Cryomodule at FAST

Low emittance electron beams are of high importance at facilities like the LCLS-II at SLAC. Emittance dilution effects due to off-axis beam transport for a TESLA-type cryomodule (CM) have been shown at the Fermilab Accelerator Science and Technology facility. The results showed the correlation between the electron beam-induced cavity high-order modes (HOMs) and submacropulse centroid slewing and oscillation downstream of the CM. Mitigation of emittance dilution can be achieved by reducing the HOM signals and the variances in the submacropulse beam positions downstream of the CM. Here we present a Machine Learning based optimization and model construction for HOM signal level reduction using Neural Networks and Gaussian Processes. To gather training data we performed experiments using single bunch and 50 bunch electron beams with charges up to 125 pC/b. We measured HOM signals of all cavities and beam position with a set of BPMs downstream of the CM. The beam trajectory was changed using V/H125 corrector set located upstream of the CM. The results presented here will inform the LCLS-II injector commissioning and will serve as a prototype for HOM reduction and emittance preservation.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Opportunities for wave energy in bulk power system operations

Wave energy resources have high, yet largely untapped potential as candidate generation technology. In this paper, we perform a data-driven analysis to characterize the impact of wave energy integration on bulk-scale power systems and market operations. Through data-driven sensitivity studies centered on an optimization-based production cost modeling formulation, our work characterizes the inflection point beyond which wave integration starts impacting power system operations, considering present day transmission infrastructure. Furthermore, our analysis also considers the joint effects of wave energy integration and system-wide transmission expansion. Finally, potential resilience scenarios such as wildfire-driven transmission contingencies and heat wave events are investigated, whereby the contributions of grid-integrated wave energy in alleviating the effects of the resilience events are analyzed. As our demonstration test bed, we consider a reduced-order network topology for the U.S. Western Interconnection with wave energy generation integrated at carefully selected sites across the coastal areas of Washington, Oregon, and northern California. Our results indicate that over a representative year of operations, wave energy integration systematically reduces locational marginal prices (LMPs) of energy and price volatility, especially during periods of high wave resource availability (winter months for the U.S. west coast). Average, maximum, and minimum of hourly LMPs over a typical year of operation was reduced by 2.95, 51.28, and 1.13 $\$$/MWh respectively (over a baseline scenario with no wave energy integration), when the selected network model had a total of 5000 MW wave power installed capacity during the representative year of study. The effects of wave energy integration can remain localized with existing transmission infrastructure (identified to be most pronounced in the Pacific Northwest region in the example we studied). However, with concurrent transmission expansion, the impacts of wave energy integration are likely to have a higher geographical spread. Our results also indicate that wave energy may be able to assist power system operations during resilience events such as major transmission contingencies and heat wave events, although such benefits might be dependent on factors such as proximity of affected area to wave resources, availability of adequate resource potential and adequate transmission capacity.

16 TIDAL AND WAVE POWER↗

DOE OSTI2021

Quantifying multipoint ordering in alloys

A central problem in multicomponent lattice systems is to systematically quantify multipoint ordering. Ordering in such systems is often described in terms of pairs, even though this is not sufficient when three-point and higher-order interactions are included in the Hamiltonian. Current models and parameters for multipoint ordering are often only applicable for very specific cases or require approximating a subset of correlated occupational variables on a lattice as being uncorrelated. In this paper, cluster order parameters are introduced to systematically quantify arbitrary multipoint ordering motifs in substitutional systems through direct calculations of normalized cluster probabilities. These parameters can describe multipoint chemical ordering in crystal systems with multiple sublattices, multiple components, and systems with reduced symmetry. These are defined in this paper and applied to quantify four-point chemical ordering motifs in platinum/palladium alloy nanoparticles that are of practical interest to the synthesis of catalytic nanocages. Impacts of chemical ordering on nanocage stability are discussed. It is demonstrated that approximating four-point probabilities from superpositions of lower-order pair probabilities is not sufficient in cases where three- and four-body terms are included in the energy expression. Furthermore, conclusions about the formation mechanisms of nanocages may change significantly when using common pair approximations.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Measured and projected beam backgrounds in the Belle II experiment at the SuperKEKB collider

The Belle II experiment at the SuperKEKB electron–positron collider aims to collect an unprecedented data set of 50 ab -1 to study CP -violation in the B -meson system and to search for Physics beyond the Standard Model. SuperKEKB is already the world’s highest-luminosity collider. In order to collect the planned data set within approximately one decade, the target is to reach a peak luminosity of 6 x 10 35 cm −2 s −1 by further increasing the beam currents and reducing the beam size at the interaction point by squeezing the betatron function down to β $^*_y$ = 0.3 mm. To ensure detector longevity and maintain good reconstruction performance, beam backgrounds must remain well controlled. We report on current background rates in Belle II and compare these against simulation. We find that a number of recent refinements have significantly improved the background simulation accuracy. Finally, we estimate the safety margins going forward. We predict that backgrounds should remain high but acceptable until a luminosity of at least 2.8 x 10 35 cm −2 s −1 is reached for β $^*_y$ = 0.6 mm. At this point, the most vulnerable Belle II detectors, the Time-of-Propagation (TOP) particle identification system and the Central Drift Chamber (CDC), have predicted background hit rates from single-beam and luminosity backgrounds that add up to approximately half of the maximum acceptable rates.

Detector background↗

DOE OSTI2023

Simulation of shell pellet injection strategies for ITER-scale tokamaks

Dispersive shell pellet (DSP) injection is considered as an alternative to shattered pellet injection as a disruption mitigation system for ITER, and strategies for penetration of a shell pellet into ITER are modeled with the 3D MHD code NIMROD. Because the high plasma temperatures lead to rapid ablation of the shell, delivery of the dispersive payload to the core of ITER will be very challenging. Two strategies to increase payload delivery depth are modeled: first, multiple staggered pellets are simulated in DIII-D, to assess the ability for one DSP to "piggy-back" on another to reach deeper into the core; second, DSP injection after pre-dilution-cooling with deuterium is simulated in ITER, in order to reduce the plasma temperature before shell pellet arrival. The DIII-D simulations show that a second, slower pellet can penetrate much deeper once the release of the first payload strongly cools the mid-radius region. When the pellets are staggered, deeper penetration of the second pellet leads to higher radiation fraction and larger runaway electron loss fraction, consistent with single pellet results. However, simultaneously released pellets at mid-radius that do not trigger a large n=1 mode produce an even higher radiation fraction. The ITER simulations show that an inside-out TQ can be produced with a payload release just inside of the q=2 surface, which is achieved at a speed of 800 m/s after pre-dilution cooling. Although stochastization of the core leads to a complete thermal quench, the edge flux surfaces are surprisingly robust in the ITER simulations, regardless of payload release location. As a result, runaway electron losses would not be expected.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Impact of Advection Schemes on Tracer Interrelationships in Large-Eddy Simulations of Deep Convection

This study investigates the preservation of tracer interrelationships during advection in large-eddy simulations of an idealized deep convective cloud, which is particularly relevant to chemistry, aerosol, and cloud microphysics models. Employing the Cloud Model 1, advection is represented using third-, fifth-, and seventh-order weighted essentially non-oscillatory schemes. As a simplified analogy for cloud hydrometeors and aerosols, several inert passive tracers following linear and nonlinear relationships are initialized after the cloud reaches ~6-km depth. Numerical mixing in the simulated turbulent convective clouds leads to significant deviations from the initial nonlinear relationships between tracers. In these simulations, a considerable fraction of the grid points where the tracers’ nonlinear relationships are altered from advection are classified as unrealistic (e.g., ~13% for the environmental tracers on average), including errors from range-preserving unmixing and overshooting. Errors in the sum of three tracers are also relatively large, ranging between ~1% and 16% for 5% of the grid points in and near the cloud. The magnitude of unrealistic mixing and errors in the sum of three tracers generally increase with the order of accuracy of the advection scheme. These results are consistent across model grid spacings ranging from 50 to 200 m, and across three different flow realizations for each combination of grid spacing and advection scheme tested. Tests employing a previously proposed scalar normalization procedure show substantially reduced errors in the sum of three tracers with a relatively small negative impact on other tracer relationships. This analysis, therefore, suggests efficacy of the normalization procedure when applied to turbulent three-dimensional cloud simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Fourier analysis of continuous fractional diffusion synthetic acceleration schemes in slab geometry

We propose two fractional extensions of continuous diffusion synthetic acceleration (DSA) with fractional derivative order α varying over the interval 2 ≥ α ≥ 1 . We investigate the spectral properties of the corresponding continuous families of fractional preconditioners by performing Fourier analysis for a model infinite homogeneous medium problem in slab geometry. The first family results in a fractional acceleration scheme, FrDSAo, that reduces to traditional DSA for .α = 2 and scattering ratio c limiting to a unit value (c → 1) but is otherwise optimized via the Fourier analysis, to obtain the smallest possible spectral radius, for c < 1 and 2 ≥ α ≥ 1. The second family corresponds to a fractional acceleration scheme, FrDSAs, that reduces to traditional DSA for α = 2 for all values of c. The latter scheme is not optimized but has the advantage of lending itself to a more straightforward implementation. For high values of c, the results of the Fourier analysis point to the existence of an interval 2 > α > ∼1.8 where both FrDSAo and FrDSAs can achieve a lower spectral radius than DSA. For example, DSA has a spectral radius of ∼0.2246 for c = 0.9999 while FrDSAo produces a value of ∼0.1616 at α = 1.92 and FrDSAs results in ∼0.2116 at α =1.93. (author)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Parametric Modeling and Economic Analysis of a 2MW th 3-Stream sCO 2 Heat Exchanger

Here, this paper presents the design and cost optimization of a novel 2MW th 3-stream sCO2 plate-fin heat exchanger. This heat exchanger design is unique in that it uses reduced metal oxide particle-to-sCO2 heat exchanger for cost-effective energy storage applications. The design uses low velocity, laminar air as the re-oxidizing reactant to transfer the heat of the re-oxidizing reaction to a sCO2 power loop. The design of the heat exchanger is based on a 2-D, 3-fluid plate/fin heat transfer model. The model parameterizes the size, shape, and number of passages of the heat exchanger to calculate the temperature profile, pressure drop, and fluid velocities of all three fluids. Global heat exchanger parameters such as the effectiveness and total heat transferred to the sCO2 are then calculated for overall performance. Due to the value and increased use of sCO2 heat exchangers in power cycles, a cost model of the system based on the unique high temperature/high pressure operating conditions was created using quotes from reference projects and market analysis. These quoted air-to-sCO2 heat exchangers are then processed using multiple weighting factors pertinent to heat exchanger design, including heat exchanger type, maximum temperature, differential pressures, fluids, duty, and more. These factors are then used in an exponential function in order to generate a parameterized cost curve. The design and cost of the heat exchanger are then optimized using the SMPSO genetic algorithm in Python. The optimization objectives for the system are to maximize the overall system effectiveness, including an air recuperator for preheating, and to minimize unit costs. Additional constraints are added to the system for the sCO2 and air pressure drops, air velocity to reduce particle entrainment, and the length and volume of the heat exchanger.

Cost Model↗

DOE OSTI2022

High-fidelity pool boiling simulations on multiple nucleation sites using interface capturing method

Boiling has proved to be one of the most efficient means for heat transfer and is a very important phenomenon during severe accident scenarios in light water reactors. High-fidelity pool boiling simulations can provide a numerical database for improving mechanistic boiling models by allowing for specific evaluation of interactions among bubbles. Previously published pool boiling simulations investigated two nucleation sites in which bubble growth at one site suppressed nucleation at the other site. Based on previous study results, more complicated interface-capturing simulations on pool boiling were conducted using PHASTA code with locally refined unstructured mesh. First, different boundary conditions (BCs) were assessed to support robustness and reproducibility of the boiling model. Then, a scale study was conducted at a larger domain with nine nucleation sites where either nine or four nucleation sites are activated. Involving more nucleation sites increased the complexity of bubble interactions from surrounding sites. Finally, bubble departure behavior influenced by wall heat flux was investigated. In this work, when heat flux was increased, the order of bubble departure changed, but diagonal bubbles always departed after one another. The departure time interval between the first and second bubble reduced as heat flux increased. The corresponding frequency was almost linearly proportional to the heat flux. In addition, bubble departure behavior was found to be greatly influenced by the nucleation site pattern. Multiple nucleation sites resulted in superimposed inhibitive effects from surrounding sites to each bubble, which extensively delayed the departure. This new observation was not discussed in previously published works. The work presented here provides new insight on the fundamental understanding of boiling phenomena, contributes to the development of a 3D multiphase computational fluid dynamics (M-CFD) model, and provides a more comprehensive database for data-driven pool boiling studies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Lattice Boltzmann model for conjugate heat transfer across thin walls

A lattice Boltzmann (LB) model with an efficient and accurate interface treatment for conjugate heat transfer across a thin wall between two different media is developed. The proposed interface treatment avoids fine meshing and computation within the thin layer; instead, the energy balance within the thin layer and the conjugate conditions on each interface are utilized to construct explicit updating schemes for the microscopic distribution functions of the LB model at the interior lattice nodes of the two media next to the thin layer. The proposed interface schemes reduce to the standard interface scheme for conjugate conditions in the literature in the limit of zero thickness of the thin layer, and thus it can be considered a more general interface treatment. A simplified version of the interface treatment is also proposed when the heat flux variation along the tangential direction of the thin layer is negligible. Three representative numerical tests are conducted to verify the applicability and accuracy of the proposed interface schemes. The results demonstrate that the intrinsic second-order accuracy of the LB model is preserved with the proposed interface schemes for thin layers with constant tangential fluxes, while for general situations with varying tangential fluxes, first-order accuracy is obtained. Finally, this interface treatment within the LB framework is attractive in conjugate heat transfer modeling involving thin layers for its simplicity, accuracy, and significant reduction in computational resources.

42 ENGINEERING↗

DOE OSTI2021

Modelling Nuclear Thermal Propulsion Reactor Startup Transients

The National Aeronautics and Space Administration (NASA) has set the goal of a manned mission to Mars by the year 2030 [1] and charged the national academy of sci- ences "to identify primary technical and programmatic chal- lenges, merits, and risks for maturing space nuclear propulsion technologies of interest to a future human Mars exploration mission" [2]. One relevant technology, nuclear thermal propul- sion (NTP), has notable advantages over traditional chemical rockets; most important among them is the ability to produce larger specific impulse on the order of 900s. The reduction of mission time is crucial for a manned mission to Mars to reduce the risk for the crew. Due to its higher specific impulse, NTP satisfies this need and is pursued as one technology to get humans to Mars [3, 4]. The construction of an NTP sys- tem has to negotiate several challenges laid out in Ref. [2]; one of these challenges is the need to startup the NTP sys- tem from essentially cold conditions to full power within one minute. This paper focuses on studying the neutronics and thermal-hydraulics behavior of a simplified NTP model dur- ing prescribed reactivity insertions and mass flow rate (MFR) ramps. It is the goal of this paper to investigate startup, peak material temperatures, and average specific impulse for a low enriched Uranium (LEU), ceramic and metal material (CER- MET) NTP system when varying reactivity insertion and MFR ramps.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Atomic Origin of the Autocatalytic Reduction of Monoclinic CuO in a Hydrogen Atmosphere

Reducibility is key for the use of bulk metal oxides in chemical transformation involving redox reactions but probing microscopic processes of oxide reduction is challenging. This is because the insulating nature of bulk oxides restricts ion and electron spectroscopic measurements of oxide surfaces. Herein, using a combination of environmental transmission electron microscopy and atomistic modeling, we report direct in-situ atomic-scale observations of the surface and subsurface dynamics and show that the hydrogen induced CuO reduction occurs via the surface decay of Cu-O/Cu bilayer atomic steps, formation of partially reduced CuO superstructure by the self-ordering of O vacancies in the subsurface, and collapse of Cu-O layers in the bulk. In this work, all these substeps can be traced back to the progressively increased concentration and activity of O vacancies in the surface and subsurface of the oxide, thereby leading to the self-accelerated oxide reduction. These results demonstrate the microscopic details that may have broader applicability in modulating various redox processes.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Upscaling Reactive Transport and Clogging in Shale Microcracks by Deep Learning

Fracture networks in shales exhibit multiscale features. A rock system may contain a few main fractures and thousands of microcracks, whose length and aperture are orders of magnitude smaller than the former. It is computationally prohibitive to resolve all the fractures explicitly for such multiscale fracture networks. One traditional approach is to model the small-scale features (e.g., microcracks in shales) as an effective medium. Although this fracture-matrix conceptualization significantly reduces the problem complexity, there are classes of physical processes that cannot be accurately upscaled by effective medium approximations, e.g., microcrack clogging during mineral reactions. Here, we employ deep learning in place of effective medium theory to upscale physical processes in small-scale features. Specifically, we consider reactive transport in a fracture-microcrack network where microcracks can be clogged by precipitation. A deep learning multiscale algorithm is developed, in which the microcracks are upscaled as a wall boundary condition of the main fractures. The wall boundary condition is constructed by recurrent neural networks, which take concentration histories as input and predict the solute transport from main fractures to microcracks. The deep learning multiscale algorithm is firstly employed in specific scenarios, then a general model is developed which can work under various conditions. The new approach is validated against fully resolved simulations and an analytical solution, providing a reliable and efficient solution for problems that cannot be upscaled by effective medium models.

58 GEOSCIENCES↗

DOE OSTI2021

Compositionally graded Ga 1-x In x P buffers grown by static and dynamic hydride vapor phase epitaxy at rates up to 1 μm/min

Here, we demonstrate Ga 1-x In x P compositionally graded buffers (CGBs) grown on GaAs with lattice constants between GaAs and InP by hydride vapor phase epitaxy (HVPE). Growth rates were up to ~1 μm/min and threading dislocation density (TDD) was as low as 1.0 x 10 6 cm -2 . We studied the effect of substrate offcut direction, growth rate, and strain grading rate on CGB defect structure. We compared the effect of a “dynamic grading” style, which creates compositional interfaces via mechanical transfer of a substrate between two growth chambers, vs. “static grading” where the CGB grows in a single chamber. Dynamic grading yielded smoother grades with higher relaxation, but TDD was not significantly different between the two styles. Substrate offcut direction was the most important factor for obtaining CGBs with low defect density. (001) substrates offcut towards (111)B yielded smoother CGBs with lower TDD compared to CGBs grown on substrates offcut towards (111)A. Transmission electron microscopy of static and dynamic CGBs grown on A and B-offcuts only found evidence of phase separation in a static A-offcut CGB, indicating that the B offcut limits phase separation, which in turn keeps TDD low. Reduced growth rate led to the appearance CuPt-type atomic ordering, which affected the distribution of dislocations on the active glide planes but did not alter TDD. Higher growth rates led to smoother CGBs and did not appreciably increase TDD as otherwise predicted by steady-state models of plastic relaxation. These results show HVPE’s promise for lattice-mismatched applications and low-c ost InP virtual substrates on GaAs

36 MATERIALS SCIENCE↗

DOE OSTI2021

Infrared reflection absorption spectroscopy and temperature-programmed desorption studies of CO adsorption on Ni/CeO 2 (111) thin films: The role of the ceria support

Ceria-supported Ni has shown unique catalytic activity due to unique properties of small Ni particles and strong metal-support interaction. Identification of adsorption sites and understanding the chemical interaction over Ni-ceria at the fundamental level provide crucial insights into the reaction pathways of complex catalytic processes. In this study, to probe the surface sites, the adsorption of CO was carried out with model Ni/ceria systems consisting of Ni nanoparticles vapor-deposited on well-ordered CeO x (111) (1.5 < x < 2) thin films using infrared reflection absorption spectroscopy (IRRAS) and temperature-programmed desorption (TPD) under ultrahigh vacuum (UHV) conditions. Fully oxidized CeO 2 (111) (Ce 4+ ) and partially reduced CeO 1.75 (111) (Ce 4+ /Ce 3+ ) thin films were grown on Ru(0001) to examine the role of the ceria support. Additionally, Ni with low coverages (e.g., 0.2 ML) grows forming small two-dimensional particles on ceria at 300 K, which develop into three-dimensional clusters after heating to 700 K. In the absence of Ni, CO adsorption at 1 mTorr at 100 K shows distinct IR bands at 2158 cm -1 on CeO 2 and 2165 cm -1 on CeO 1.75 . Bridging and atop IR bands associated with CO adsorption over metallic Ni were observed on the Ni-CeO 1.75 surface at 300 K under UHV conditions. CO adsorption over Ni 0 was also observed over as-deposited Ni on CeO 2 . However, a new IR band at 2146 cm -1 due to CO adsorption over Ni 2+ species was detected at 100 K over the annealed Ni particles on CeO 2 . CO IRRAS data suggest the oxidation of Ni to Ni 2+ on CeO 2 and the formation of predominant Ni 2+ species with heating, which is further confirmed with CO TPD data and previous x-ray photoelectron spectroscopy results.

36 MATERIALS SCIENCE↗

DOE OSTI2025

QuadTune version 1: a regional tuner for global atmospheric models

When a new, better-formulated physical parameterization is introduced into a global atmospheric model, aspects of the global model solutions are sometimes degraded. Then, in order to use the new global model to address science questions, there is an incentive to restore its accuracy. Oftentimes this restoration is achieved by tuning of model parameter values. Unfortunately, the retuning process is expensive because characterizing the parameter dependence requires numerous time-consuming global simulations. To reduce the cost of tuning, this manuscript introduces a “poor man's” model tuner, “QuadTune”. QuadTune carves the globe into regions and approximates the model parameter dependence through the use of an uncorrelated quadratic emulator (i.e., response surface). The simplicity of the emulator reduces the required number of global model simulations and aids explainability of tuner behavior. Tuning removes parametric error but leaves behind model structural error. Structural error manifests itself as regional residual biases, such as stubborn biases and tuning trade-offs. To visualize these residual biases, QuadTune's software includes a set of diagnostic plots. This paper illustrates the use of the plots for characterizing residual biases with an example tuning problem.

Environmental sciences↗