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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Hanford Waste Treatment Plant Effluent Management Facility Stack Effluent Monitoring: Sampling Probe Location Qualification Evaluation

The Hanford Tank Waste Treatment and Immobilization Plant Effluent Management facility (EMF) stack monitor location was qualified using the LV-S1 scale model stack as a baseline, augmented by the LB-S1 and LV-S2 scale model stacks to address the Direct Feed Low Activity Waste Effluent Management Facility Vessel Vent Process (DVP) injection into the main Active Confinement Ventilation (ACV) system duct. As required by the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-1999 standard, the scale models and its sampling locations were geometrically similar to the actual stack and the Reynolds numbers for both the actual and model stacks were >10,000. An additional criterion is that the product of the hydraulic diameter and mean velocity (DV) of the full-scale stack must be between 1/6 DV and 6 DV of the scale model stack tests. Verification tests of the EMF stack was performed at normal operating conditions. The minimum 1/6 DV value, along with the maximum 6 DV value from the scale model testing determines the range of stack flow rates for which the full-scale stack may be operated and remain in compliance with the stack verification criterion. Based on the LV-S1 scale model test DV values, the corresponding stack flow rates for the EMF stack are as listed in Table S1. Table S1. Effluent Management Facility Stack Qualified Flow Range. Stack Parameter EM-1 Minimum Qualified Stack Flow (scfm) 781 Maximum Qualified Stack Flow (scfm) 53,432 The remaining criteria for the stack verification to be considered valid involve the flow angle and velocity uniformity results. First, the flow angle at the full-scale stack must be =20°. Second, the velocity uniformity at the full-scale stack must be =20% coefficient of variance (COV). Finally, the velocity uniformity results for the actual and scale model stack tests must agree within 5% COV. These criteria were met through the full-scale stack test at the EMF. Flow angle results were less than 5°; all flow angle results were within the =20° criterion. The velocity uniformity results for each test condition ranged between 2.2% COV and 4.3% COV, which were all within the range of the target % COV values from the scale model tests on the LV-S1, LB-S1, and LV S2 scale models. Based on these stack verification test results, the EMF filtered exhaust stack sampling location meets the qualification criteria provided in the ANSI/HPS N13.1-1999 standard for all fan operating configurations. This includes each combination of ACV fan with the DVP exhausters. Further changes to the system configuration or operating conditions that are outside the qualified flow rates described in this report may require additional tests or analyses to determine compliance with the standard.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

A Comparative Study of Deep Learning Models for Fracture and Pore Space Segmentation in Synthetic Fractured Digital Rocks

This study focuses on the comparative study of deep learning (DL) models for pore space and discrete fracture networks (DFNs) segmentation in synthetic fractured digital rocks, specifically targeting low-permeability rock formations, such as shale and tight sandstones. Accurate characterization of pore space and DFNs is critical for subsequent property analysis and fluid flow modeling. Four DL models, SegNet, U-Net, U-Net-wide, and nested U-Net (i.e., U-Net++), were trained, validated, and tested using synthetic datasets, including input and label image pairs with varying properties. The model performance was assessed regarding pixel-wise metrics, including the F1 score and pixel-wise difference maps. In addition, the physics-based metrics were considered for further analysis, including sample porosity and absolute permeability. Particularly, We first simulated the permeability of porous media containing only pore space and then simulated the permeability of porous media with DFNs added. The difference between these two values is used to quantify the connectivity of segmented DFNs, which is an important parameter for low-permeability rocks. The pixel-wise metrics showed that the nested U-Net model outperformed the rest of the DL models in pore space and DFNs segmentation, with the SegNet model exhibiting the second-best performance. Particularly, nested U-Net enhanced segmentation accuracy for challenging boundary pixels affected by partial volume effects. The U-Net-wide model achieved improved accuracy compared to the U-Net model, which indicated the influence of parameter numbers. Similarly, nested U-Net has the closest match to the ground truth of physics-based metrics, including the porosity of pore space and DFNs, and the permeability difference quantifying the connectivity of DFNs. The findings highlight the effectiveness of DL models, especially the U-Net++ model with nested architecture and redesigned skip connections, in accurately segmenting pore spaces and DFNs, which are crucial for pore-scale fluid flow and transport simulation in low-permeability rocks.

Wang, Hongsheng↗
DOE OSTI2024

Evidence of gas phase nucleation of nanodiamond in microwave plasma assisted chemical vapor deposition

The mechanism of ballas-like nanodiamond formation still remains elusive, and this work attempts to analyze its formation in the framework of activation energy (Ea) of nanodiamond films grown from a H2/CH4 plasma in a 2.45 GHz chemical vapor deposition system. The Ea was calculated from the Arrhenius equation corresponding to the thickness growth rate using substrate temperature (∼1000−1300 K) in all the calculations. While the calculated values matched with the Ea for nanodiamond formation throughout the literature, these values of ∼10 kcal/mol were lower compared to ∼15–25 kcal/mol for standard single crystal diamond (SCD) formation, concluding thus far that the energetics and processes involved were different. Further, the substrate preparation and sample collection method were modified while keeping the growth parameters constant. Unseeded Si substrate was physically separated from the plasma discharge by a molybdenum disk with a pinhole drilled in it. Small quantity of a sample substance was collected on the substrate. The sample was characterized by electron microscopy and Raman spectroscopy, confirming it to be nanodiamond, thus suggesting that nanodiamond self-nucleated in the plasma and flowed to the substrate that acted as a mere collection plate. It is hypothesized then, if nanodiamond nucleates in gas phase, gas temperature has to be used in the Arrhenius analysis. The Ea values for all the nanodiamond films were re-calculated using the simulated gas temperature (∼1500−2000 K) obtained from a simple H2/CH4 plasma model, giving new values within the range characteristic to SCD formation. Based on these findings, a unified growth mechanism for nanodiamond and SCD is proposed, concluding that the rate-limiting reactions for nanodiamond and SCD formation are the same.

Materials Science↗
DOE OSTI2025

Light, High Performance and Scalable Coal-Derived Composites for Construction: Precast and Cast-in-Place Applications

The overall objective of this project was to produce a coal-based construction material that has up to ~95 weight percent (wt. %) coal with physical, chemical, and thermal properties exceeding those of ordinary Portland cement (OPC)-based construction materials. Additionally, the project aimed to minimize external binders by implementing novel mixing techniques, while exceeding the performance/cost ratio of OPC. Finally, the project was to demonstrate production of precast products via the design and fabrication of products via a bench scale process. Consistent with some of these objectives, the project successfully fabricated samples of coal-based composite materials with >80 wt% coal with physical, chemical and thermal properties on par with cement-based concrete. Select samples demonstrated compressive strengths with >7,000 psi and flexural strength of >420 psi. The composite materials minimized external binders and also demonstrated durability, as evidenced by resistance to acidic and basic solutions. Finally, larger slab and beam type samples were produced using a process developed by the Recipient, although, the process was not semicontinuous in nature. Taken together, the results of this project suggest that domestic coal has potential to serve as a replacement for cementitious materials utilized in incumbent construction technologies, which could significantly reduce the energy and emissions of the construction industry

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Initial development of a generic fluoride salt-cooled reactor model

Fluoride high-temperature reactors (FHRs) are high-temperature, low-pressure reactor concepts that use tri-structural isotropic (TRISO) fuel and molten fluoride salt coolant. These reactors have the potential to provide both electrical power and high-temperature process heat. We used generic FHR parameters for a pebble-bed FHR to develop an initial model with fresh fuel for a generic FHR (gFHR) in MELCOR and SCALE (NEWT and KENO). In this paper, we present the development of our gFHR models, which will serve as the baseline for a sensitivity and uncertainty analysis to quantify the range of possible source terms for FHRs in severe accidents. We present MELCOR results for fuel and coolant temperatures through the core, a nodalization study for the steady-state thermal hydraulic model, and development of reactor physics models in SCALE. As this work progresses, these models will be used to calculate source terms for a loss-of-forced-flow accident and to conduct a sensitivity study on this accident to establish a range of possible source terms. SCALE will provide reactor physics parameters like isotopic inventory, decay heat generation, and temperature coefficients of reactivity. Using the uncertainty quantification tools within SCALE, we will generate distributions for those parameters and will use the uncertainty quantification code RAVEN or DAKOTA to sample those distributions in MELCOR to quantify the impact of reactor physics and thermal hydraulic uncertainties on FHR source terms. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Field-level reconstruction from foreground-contaminated 21-cm maps

Current and upcoming 21-cm experiments will soon be able to map 21-cm spatial fluctuations in three dimensions for a wide range of redshifts. However, bright foreground contamination and the nature of radio interferometry create significant challenges, making it difficult to access rich cosmological information from the Fourier modes that lie within the “foreground wedge”. Here, in this work, we introduce two approaches aiming to reconstruct the full 21-cm density field, including the missing modes in the wedge: (a) a field-level inference under an effective field theory (EFT) framework; (b) a diffusion-based deep generative model trained on simulations. Under the EFT framework, we implement a fully differentiable forward model that maps the initial conditions of matter fluctuations to the observed, foreground-filtered 21-cm maps. This enables a gradient-based sampler to simultaneously sample the initial conditions and bias parameters, allowing a physically motivated mode reconstruction. Alternatively, we apply a variational diffusion model to perform 21-cm density reconstruction at the map level. Our model is trained on semi-numerical simulations over a wide range of astrophysical parameters. Our results from both approaches should provide improved cosmological constraints from the field level and also enable cross-correlation between experiments that have little or no overlapping modes.

cosmological perturbation theory↗
DOE OSTI2022

Angle- and polarization-resolved luminescence from suspended and hexagonal boron nitride encapsulated MoSe 2 monolayers

The polarized photoluminescence from atomically thin transition metal dichalcogenides is a frequently applied tool to scrutinize optical selection rules and valley physics, yet it is known to sensibly depend on a variety of internal and external material and sample properties. In this work, we apply combined angle- and polarization-resolved spectroscopy to explore the interplay of excitonic physics and phenomena arising from the commonly utilized encapsulation procedure on the optical properties of atomically thin M o S e 2 . We probe monolayers prepared in both suspended and encapsulated manners. We show that the hBN encapsulation significantly enhances the linear polarization of exciton photoluminescence emission at large emission angles. This degree of linear polarization of excitons can increase up to ∼ <#comment/> 17 % <#comment/> in the hBN encapsulated samples. As we confirm by finite-difference time-domain simulations, it can be directly connected to the optical anisotropy of the hBN layers. In comparison, the linear polarization at finite exciton momenta is significantly reduced in a suspended M o S e 2 monolayer, and becomes notable only in cryogenic conditions. This phenomenon strongly suggests that the effect is rooted in the k-dependent anisotropic exchange coupling inherent in 2D excitons. Our results have strong implications on further studies on valley contrasting selection rules and valley coherence phenomena using standard suspended and encapsulated samples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Investigation of Mass Transfer and Sorption in CO 2 /Brine/Rock Systems via In Situ FT-IR

CO 2 geological storage in deep saline formations is considered a promising method to mitigate anthropogenic CO 2 emissions and, thereby, minimize changes to the Earth’s atmosphere. A fundamental understanding of CO 2 mass transfer and sorption phenomena in brine-saturated reservoir formations is necessary to understand the long-term fate of injected CO 2 as it is subjected to different (physical, dissolution, and mineral) trapping mechanisms. In this work, we investigate CO 2 sorption in brine-saturated and dry Mt. Simon sandstone samples via in-situ Fourier Transform infrared spectroscopy (FT-IR) at elevated pressures, ranging from 0.3 MPa to 8.3 MPa, at a temperature of 50 ⁰C. The FT-IR spectra of bulk-phase CO 2 were simultaneously recorded under the same conditions. For bulk-phase CO 2 , we observed, in agreement with past studies, a doublet peak at 2361 cm -1 and 2336 cm -1 and another peak (ν 2 bending mode) at 667 cm -1 . With increasing pressure, the position of the peak at 667 cm -1 remains invariant, however, when crossing into the supercritical region the doublet peak degenerates onto a single peak at 2336 cm -1 with a barely visible shoulder at 2361 cm -1 . The bulk CO 2 data provide a perfect fit for Beer’s law for the whole range of pressure conditions. For the dry sample, the IR spectrum is experimentally indistinguishable from the bulk CO 2 spectrum, signifying that if physical adsorption occurs to any significant extent, the adsorbed CO 2 molecules are not substantially more rotationally constrained than the dense bulk CO 2 molecules. For the brine-saturated sample, we observe a strong band centered at 2342 cm -1 and a small companion peak at 2360-2361 cm -1 that degenerates into a barely visible shoulder peak at the higher pressures. The 2342 cm -1 band has been previously observed by other investigators for CO 2 dissolved in bulk water/brine as well during its adsorption on a variety of other wet natural porous media. We observe no peaks corresponding to bicarbonate or carbonate bulk species, which correlates well with the prior literature on similar low-pH aqueous solutions. The integrated peak area for the CO 2 sorbed in the brine-saturated sample correlates linearly with its solubility in the same bulk brine, as measured separately via a PVT-cell approach. Here, this validates the accuracy of both techniques, and the potential of the FT-IR method to be used in the study of mass transfer and adsorption in such systems. To that effect, a simple mathematical model is presented to analyze the FT-IR data to determine the CO 2 effective diffusivity in the brine-saturated sandstone sample.

58 GEOSCIENCES↗
DOE OSTI2020

A partial-volume correction for quantitative spectral x-ray radiography

The technique of spectral radiography has been shown to accurately discriminate a materials elemental composition by using known x-ray physics. This is achieved with a state-of-the-art pixelated spectrometer and a high-fidelity physical model. Similar to other radiographs, the system suffers from partial volume attenuation where the sample projection onto a pixel is only a fraction of the pixel area, leaving the rest unattenuated. This study updates the physical model to account for fractional area which presents new challenges to the existing algorithm. We present how this update is made and explore approaches to stabilize the algorithm through parameter scaling, constrained optimization, and hyperparameter selection.

Gillis, Wesley C.↗
DOE OSTI2021

Hybrid Machine Learning for Scanning Near-Field Optical Spectroscopy

The underlying physics behind an experimental observation often lacks a simple analytical description. This is especially the case for scanning probe microscopy techniques, where the interaction between the probe and the sample is nontrivial. Realistic modeling to include the details of the probe is always exponentially more difficult than its "spherical cow" counterparts. On the other hand, a well-trained artificial neural network based on real data can grasp the hidden correlation between the signal and sample properties. In this work, we show that, via a combination of model calculation and experimental data acquisition, a physics-infused hybrid neural network can predict the tip-sample interaction in the widely used scattering-type scanning near-field optical microscope. This hybrid network provides a long-sought solution for accurate extraction of material properties from tip-specific raw data. The methodology can be extended to other scanning probe microscopy techniques as well as other data-oriented physical problems in general.

36 MATERIALS SCIENCE↗
DOE OSTI2020

GIS-Based Modeling of Contaminated Soil Volumes at Multiple Sites in the Formerly Utilized Sites Remedial Action Program - 20149

The remediation of hazardous, toxic, and radioactive waste (HTRW) sites produces cost-related risks associated with the estimation of contaminated soil or debris volumes. Historical risk-management techniques include cost contingencies to cover volume uncertainties that affect project budgeting and decision-making. The Buffalo District teamed with project partners to lessen volume uncertainty and reduce project risks at multiple HTRW sites managed under the Formerly Utilized Sites Remedial Action Program (FUSRAP). Historical remedial investigations under FUSRAP commonly identified the presence of radiological material in site media, the associated human health risk, and then areas of remediation. To manage remedial execution and reduce risk, pre-design or remediation-phase sampling essentially 'chased' contamination, which was not conducive to efficient predictive budgeting derived from Feasibility Study (FS) cost analyses. The Buffalo District first optimized their approach to better understand volume uncertainty by utilizing the Argonne National Laboratory's Bayesian Approaches for Adaptive Spatial Sampling (BAASS) software [1]. BAASS processed soft data (e.g., gamma walk-over data) and spatial sampling data to estimate the lateral extent of contaminated soil irrespective of depth (i.e., gross contamination extent) and define areas of contaminant uncertainty. The software performed a binary transformation of contaminant concentrations at all sampling points based upon remedial action goals or a sum of ratios approach (i.e., clean, impacted, or range of impacts in soil). The model produced two-dimensional (horizontal) contaminant probability contours and statistical uncertainty in the sampling coverage and resulting contaminant extents. This method was translated vertically by partitioning the sampling data into depth brackets that produced a stacked representation of contaminant extents and uncertainty in the subsurface (i.e., similar to construction lifts). The results commonly led to a better understanding of project uncertainty and the need for sampling strategies that produce high-confidence soil volumes, which control costs. The BAASS-based delineations were eventually replaced by Empirical Bayesian Kriging (EBK) methods available in ArcGIS Spatial or 3D Analysts [2]. The EBK method calculates contaminant probability zones derived from user-controlled semivariograms of the spatial datasets. The resulting probability zones (e.g., 50% or 80% of contaminant probability) represent the two-dimensional surface delineation of the overall horizontal remedial area, similarly to BAASS. However, unlike BAASS, the vertical sampling data within these probability zones became vertical control points to contour a subterranean surface that connects subsurface points to the land-surface delineations of contamination. The resulting representation of horizontal and vertical impacts within an enclosed envelop (volume) of soil included uncertainty distributions that are used to plan uncertainty-reduction sampling. These data-driven and math-based models of three-dimensional sampling results produced well-bounded remedial volumes for project planning and better uncertainty predictions during project budgeting. The EBK method was applied to several FUSRAP sites managed by the Buffalo District and compared to less rigorously modeled sites previously remediated by the District. The comparison of modeled to actual remediated volumes provide a basis for validating the volume-estimation method. This comparison is important to ensure modeled volumes match physical boundaries of site remediation. FUSRAP sites with denser investigative sampling and lesser volume uncertainty proved useful in remedial planning and contracting. The Buffalo District noted that historical sites with sparser sampling arrays had greater disparity between estimated volumes and final remedial volumes. The benefit achieved over the cost of detailed soil sampling appears positive for FUSRAP projects, especially where impacts vary widely and appear unbounded by investigation-phase sampling. The subsequent Empirical Bayesian Kriging of contamination coupled with vertical contouring for soil estimations reduces uncertainty in soil volumes or indicates where sampling is required to reduce uncertainty, which together optimize remedial planning and budgeting. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Hanford Waste Treatment Plant Effluent Management Facility Stack Effluent Monitoring: Sampling Probe Location Qualification Evaluation

The Hanford Tank Waste Treatment and Immobilization Plant Effluent Management Facility (EMF) stack monitor location was qualified using a combination of scale model stacks to mitigate the risk of identifying that the sampling location does not meet the qualification criteria on the full-scale stack. The LV-S1 scale model stack was used as a baseline, augmented by the LB-S1 and LV-S2 scale model stacks to address the Direct Feed Low Activity Waste Effluent Management Facility Vessel Vent Process (DVP) injection into the main Active Confinement Ventilation (ACV) system duct. As required by the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-1999 standard, the scale model and its sampling locations were geometrically similar to the actual stack, and the Reynolds numbers for both the actual and model stacks were >10,000. An additional criterion is that the product of the hydraulic diameter and mean velocity (DV) of the full-scale stack must be between 1/6 DV and 6 DV of the scale model stack tests. The LV-S1, LB-S1, and LV-S2 scale model stack tests have met the criteria of the ANSI/HPS N13.1-1999 standard to demonstrate the stack sampling locations are well mixed. Verification tests of the EMF stack were performed at normal operating conditions. The minimum 1/6 DV value and the maximum 6 DV value from the scale model testing determine the range of stack flow rates for which the full-scale stack may be operated while remaining in compliance with the stack verification criterion. A practical range for the full-scale stack qualification uses the average DV through 6 DV from the scale model tests to compute the corresponding flow rates. Table S1 lists the operating flow rate along with the average and maximum qualified stack flow rate based on the LV-S1 scale model DV values. The operating flow is below the maximum qualified stack flow, which means that the scale model test results are acceptable for stack qualification. The remaining criteria for the stack verification to be considered valid involve the flow angle and velocity uniformity results. First, the flow angle at the full-scale stack must be ≤20°. Second, the velocity uniformity at the full-scale stack must be ≤20% coefficient of variance (COV). Finally, the velocity uniformity results for the actual and scale model stack tests must agree within 5% COV. These criteria were met through the full-scale stack test at the EMF. Flow angle results were <5°; all flow angle results were within the ≤20° criterion. The velocity uniformity results for each test condition ranged between 2.2% COV and 4.3% COV, all of which were within the range of the target % COV values from the scale model tests on the LV-S1, LB-S1, and LV S2 scale models. Based on these stack verification test results, the EMF filtered exhaust stack sampling location meets the qualification criteria provided in the ANSI/HPS N13.1-1999 standard for all planned fan operating configurations. This includes each combination of ACV fans with DVP exhausters. Further changes to the system configuration or operating conditions that are outside the qualified flow rates described in this report may require additional tests or analyses to determine compliance with the standard.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Boson–Boson Interactions at the LHC

Vector boson scattering is a key production process to probe the electroweak symmetry breaking of the Standard Model and is one of the most important topics of the physics program for the HL-LHC since it involves both self-couplings of vector bosons and their coupling with the Higgs boson. If the Higgs mechanism is not the sole source of electroweak symmetry breaking, the scattering amplitude deviates from the Standard Model prediction at high scattering energy. Moreover, deviations may be detectable even if a New Physics scale is higher than the reach of direct searches. In this review, the most recent experimental measurements of the production cross sections of vector boson pairs in association with two jets in proton–proton collisions at $\sqrt{s}$ = 13 TeV at the LHC are reported, using data sets recorded by the ATLAS and CMS detectors. Applications to searches for New Physics, as well as prospects for measuring the electroweak vector boson scattering processes with larger data samples, are also summarized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Efficient sampling of constrained high-dimensional theoretical spaces with machine learning

Abstract Models of physics beyond the Standard Model often contain a large number of parameters. These form a high-dimensional space that is computationally intractable to fully explore. Experimental results project onto a subspace of parameters that are consistent with those observations, but mapping these constraints to the underlying parameters is also typically intractable. Instead, physicists often resort to scanning small subsets of the full parameter space and testing for experimental consistency. We propose an alternative approach that uses generative models to significantly improve the computational efficiency of sampling high-dimensional parameter spaces. To demonstrate this, we sample the constrained and phenomenological Minimal Supersymmetric Standard Models subject to the requirement that the sampled points are consistent with the measured Higgs boson mass. Our method achieves orders of magnitude improvements in sampling efficiency compared to a brute force search.

Hollingsworth, Jacob↗
DOE OSTI2020

New Physics Agnostic Selections For New Physics Searches

We discuss a model-independent strategy for boosting new physics searches with the help of an unsupervised anomaly detection algorithm. Prior to a search, each input event is preprocessed by the algorithm - a variational autoencoder (VAE). Based on the loss assigned to each event, input data can be split into a background control sample and a signal enriched sample. Following this strategy, one can enhance the sensitivity to new physics with no assumption on the underlying new physics signature. Our results show that a typical BSM search on the signal enriched group is more sensitive than an equivalent search on the original dataset.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Quantifying Energetic and Entropic Pathways in Molecular Systems

When examining dynamics occurring at nonzero temperatures, both energy and entropy must be taken into account to describe activated barrier crossing events. Furthermore, good reaction coordinates need to be constructed to describe different metastable states and the transition mechanisms between them. Here we use a physics-based machine learning method called state predictive information bottleneck (SPIB) to find nonlinear reaction coordinates for three systems of varying complexity. SPIB is able to correctly predict an entropic bottleneck for an analytical flat-energy double-well system and identify the entropy- and energy-dominated pathways for an analytical four-well system. Lastly, for a simulation of benzoic acid permeation through a lipid bilayer, SPIB is able to discover the entropic and energetic barriers to the permeation process. Given these results, we thus establish that SPIB is a reasonable and robust method for finding the important entropy, energy, and enthalpy barriers in physical systems, which can then be used to enhance the understanding and sampling of different activated mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Heavy Flavor Physics at the sPHENIX Experiment

The sPHENIX experiment is a state-of-the-art jet and heavy flavor physics detector, which successfully recorded its first Au + Au collision data at 200 GeV at the Relativistic Heavy Ion Collider (RHIC). sPHENIX will provide heavy flavor physics measurements at RHIC, covering an unexplored kinematic region and unprecedented precision, to probe the parton energy loss mechanism, parton transport coefficients in quark–gluon plasma, and the hadronization process under various medium conditions. At the center of sPHENIX, the monolithic active pixel sensor (MAPS)-based VerTeX detector (MVTX) is a high-precision silicon pixel detector. The MVTX provides excellent position resolution and the capability of operating in continuous streaming readout mode, allowing precise vertex determination and recording a large data sample, both of which are particularly crucial for heavy flavor physics measurements. In this work, we will show the general performance of heavy-flavor hadron reconstruction. In addition, we will discuss the commissioning experience with sPHENIX. Finally, we will provide the projection of b-hadron and jet observables and discuss the estimated constraints on theoretical models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Generating synthetic cosmological data with GalSampler

As part of the effort to meet the needs of the Large Synoptic Survey Telescope Dark Energy Science Collaboration (LSST DESC) for accurate, realistically complex mock galaxy catalogues, in this work we have developed galsampler, an open-source python package that assists in generating large volumes of synthetic cosmological data. The key idea behind galsampler is to recast hydrodynamical simulations and semi-analytic models as physically motivated galaxy libraries. galsampler populates a new, larger volume halo catalogue with galaxies drawn from the baseline library; by using weighted sampling guided by empirical modelling techniques, galsampler inherits statistical accuracy from the empirical model and physically motivated complexity from the baseline library. We have recently used galsampler to produce the cosmoDC 2 extragalactic catalogue made for the LSST DESC Data Challenge 2 . Using cosmoDC 2 as a guiding example, we outline how galsampler can continue to support ongoing and near-future galaxy surveys such as the Dark Energy Survey, the Dark Energy Spectroscopic Instrument, WFIRST, and Euclid.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗