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DOE OSTI2020

Machine Learning-Based Upscaling of Finite-Size Molecular Dynamics Diffusion Simulations for Binary Fluids

Molecular diffusion coefficients calculated using molecular dynamics (MD) simulations suffer from finite-size (i.e., finite box size and finite particle number) effects. Results from finite-sized MD simulations can be upscaled to infinite simulation size by applying a correction factor. For self-diffusion of single-component fluids, this correction has been well-studied by many researchers including Yeh and Hummer (YH); for binary fluid mixtures, a modified YH correction was recently proposed for correcting MD-predicted Maxwell–Stephan (MS) diffusion rates. In this study we use both empirical and machine learning methods to identify improvements to the finite-size correction factors for both self-diffusion and MS diffusion of binary Lennard-Jones (LJ) fluid mixtures. Using artificial neural networks (ANNs), the error in the corrected LJ fluid diffusion is reduced by an order of magnitude versus existing YH corrections, and the ANN models perform well for mixtures with large dissimilarities in size and interaction energies where the YH correction proves insufficient.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

In Situ and Operando Morphology Study of Germanium-Selenium Alloy Anode for Li-ion Batteries

Selenium-doped germanium (GeSe) micrometersized particles have been reported with good cycling performance and rate capability due to a Li-Se-Ge network formed during the first lithiation that provides a Li-ion fast pathway. To understand the effect of the Li-Se-Ge network at a high cycling rate, we monitored the morphology change of both pure Ge and GeSe particles during cycling with an in situ/operando focused-ion beam-scanning electron microscope method. Our results showed that the proposed inactive Li-Se-Ge network can provide fast Li-ion transport and also buffer volume variation, resulting in homogeneous volume change and uniform microstructural evolution.

germanium↗

DOE OSTI2018

Swellable Organically Modified Silica (SOMS) as a Catalyst Scaffold for Catalytic Treatment of Water Contaminated with Trichloroethylene

The properties of a swellable organically modified silica (SOMS) scaffold allowed us to synthesize “smart” catalysts with tunable accessibility of the active sites induced by organic swelling agents. Pd nanoparticles (NPs) deposited inside the swollen matrix of SOMS were shown to be selectively located on the interior surface, a surface which is only available through swelling. Techniques such as near ambient-pressure X-ray photoelectron spectroscopy (NAP–XPS) and cryogenic scanning electron microscopy (SEM) were employed to characterize Pd/SOMS in its swollen as well as unswollen state because their conventional counterparts do not preserve the swollen state of Pd/SOMS during spectral acquisition. The results obtained depicted significant differences between the unswollen and swollen state of Pd/SOMS. The most important difference is that Pd NPs became accessible on the surface after exposure to an organic compound. This indicates that the accessibility of the active sites can be controlled by changing the reaction environment, hence allowing a tunable accessibility induced by organic swelling agents. The effects of the extent of swelling on the catalytic activity were investigated by performing catalytic activity experiments in the presence of an organic swelling agent. Hydrodechlorination (HDC) of trichloroethylene (TCE), an important method of catalytic water abatement, was chosen as a model reaction. The catalytic performance was found to be proportional to the concentration of the organic swelling agent, indicating that the accessibility of active sites is related to the concentration of organic compounds. While the unavoidable reaction product HCl inhibited the commonly used HDC catalyst 1%Pd/Al 2 O 3 , 1%Pd/SOMS was able to maintain its rate throughout the reaction under the same conditions, indicating its resistance to the inhibition. Overall, a silica-based catalyst with tunable accessibility of the active sites induced by changes in the reaction environment can have significant implications for heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Direct measurements for the kinetics of C–C bond fission in the high temperature decomposition of isopropanol

The thermal decomposition of isopropanol was studied experimentally and theoretically with a view to isolate and directly measure rate coefficients for the dominant radical channel in this multi-channel process. Two complementary shock tube methods, laser schlieren densitomtery and H-atom atomic resonance absorption spectroscopy, were used to obtain rate coefficents for the C–C bond fission channel. The experimental ranges span temperatures from 1200–2100 K and pressures between 30–690 torr. These are the most direct measurements of this rate coefficent in the fall-off regime of relevance to high-temperature reacting systems. Theoretical studies also performed in this work confirm that the title reaction and a molecular elimination involving dehydration were the sole unimolecular processes at high temperatures. A master equation analysis yielded k ( T, P ) for the C–C fission and these are shown to be in good agreement with the present experimental measurements. Comparisons with prior experimental and theoretical studies in the literature indicate branching ratios as well as absolute k ( T, P ) for C–C bond-fission have been under-predicted for this decomposition reaction. Consequently, results from the present studies place an increased emphasis on radical-driven secondary processes in high-temperature pyrolysis of this simplest secondary alcohol.

Kim, John H. [Univ. of Michigan, Ann Arbor, MI (Un↗

DOE OSTI2017

Structural characteristics of a gas–liquid flow in a microchannel with a T-shaped mixer

The results of experimental studies of the structural characteristics of a nitrogen–water mixture flow in a horizontal microchannel provided with a T-shaped mixer are presented. The experiments are performed in a channel with a rectangular cross section of 250 × 315 μm under the conditions of a dominating influence of capillary forces. Structural characteristics of the flow are determined using the two-beam laser scanning and high-speed video capture at a distance of 500 calibers from the inlet in a wide range of reduced gas- and liquid-flow rates. A new method for the identification of flow regimes is proposed based on the statistical treatment of the laser-scanning data, and a map of flow patterns is constructed.

42 ENGINEERING↗

DOE OSTI2018

Experimental Detection of Resonant Tunneling in the Doped Structure with a Single Quantum Well by the Admittance Spectroscopy Method

The admittance measurements of heterostructures with quantum wells (QW) In{sub x}Ga{sub 1 – x}As/GaAs (0.19 ≤ x ≤ 0.3) precisely grown by the MOCVD method were carried out. By means of the admittance spectroscopy method, the resonant tunneling emission was for the first time registered as the determining mechanism inducing high-frequency conductance of doped heterostructures with QW, the separation of tunnel and resonant tunneling contributions was carried out, and the influence of tunnel component on the total rate of carrier emission from QW was analyzed. The self-consistent simulation of capacitance–voltage characteristics of the structures was performed, and the transmittance of the system formed by the Hartree potential around QW was calculated. Experimentally and by numerical calculations, it is shown that the probability of resonant tunneling emission decreases with increasing reverse bias due to the broken symmetry of the barriers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2017

Substrate-insensitive atomic layer deposition of plasmonic titanium nitride films

The plasmonic properties of titanium nitride (TiN) films depend on the type of substrate when using typical deposition methods such as sputtering. We show atomic layer deposition (ALD) of TiN films with very weak dependence of plasmonic properties on the substrate, which also suggests the prediction and evaluation of plasmonic performance of TiN nanostructures on arbitrary substrates under a given deposition condition. Our results also observe that substrates with more nitrogen-terminated (N-terminated) surfaces will have significant impact on the deposition rate as well as the film plasmonic properties. Furthermore, we illustrate that the plasmonic properties of ALD TiN films can be tailored by simply adjusting the deposition and/or post-deposition annealing temperatures. These characteristics and the capability of conformal coating make ALD TiN films on templates ideal for applications that require the fabrication of complex 3D plasmonic nanostructures.

36 MATERIALS SCIENCE↗

DOE OSTI2018

A Minimum Variance Algorithm for Overdetermined TOA Equations with an Altitude Constraint.

We present a direct (non-iterative) method for solving for the location of a radio frequency (RF) emitter, or an RF navigation receiver, using four or more time of arrival (TOA) measurements and an assumed altitude above an ellipsoidal earth. Both the emitter tracking problem and the navigation application are governed by the same equations, but with slightly different interpreta- tions of several variables. We treat the assumed altitude as a soft constraint, with a specified noise level, just as the TOA measurements are handled, with their respective noise levels. With 4 or more TOA measurements and the assumed altitude, the problem is overdetermined and is solved in the weighted least squares sense for the 4 unknowns, the 3-dimensional position and time. We call the new technique the TAQMV (TOA Altitude Quartic Minimum Variance) algorithm, and it achieves the minimum possible error variance for given levels of TOA and altitude estimate noise. The method algebraically produces four solutions, the least-squares solution, and potentially three other low residual solutions, if they exist. In the lightly overdermined cases where multiple local minima in the residual error surface are more likely to occur, this algebraic approach can produce all of the minima even when an iterative approach fails to converge. Algorithm performance in terms of solution error variance and divergence rate for bas eline (iterative) and proposed approach are given in tables.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Performance of b Jet Identification at $\sqrt{s}$ = 13 TeV with the ATLAS Detector at CERN [Slides]

The efficient identification of jets from bottom quarks (b-jets) is one of the most important techniques for many physics analyses at the Large Hadron Collider, including studies of the Higgs boson, the top quark, and searches beyond the Standard Model. The performance is characterized by b-tagging efficiency (probability to identify a b-jet as such) and the mistag rate (probability to mistakenly accept a non-b-jet).The mistag occurs as a result of finite detector resolution, presence of long-lived particles, and material interactions. As these effects can be different between the experimental data and Monte Carlo (MC) simulation, it is important to measure the b-tagging performance in data and derive the MC correction factors. I will describe various methods to measure the performance of b jet identification in pp collisions at √s = 13 TeV with the ATLAS detector and will report on Direct Tag method which is recently developed in the ATLAS collaboration for Light jet calibration.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Wall Upgrades for Energy Retrofits: A Techno-Economic Study

Homes built before 1992, when the U.S. Department of Energy’s (DOE) Building Energy Codes Program was established, represent approximately 68% of the residential building stock in the country. Up to 43% of these homes have little to no insulation in the walls and have very high air leakage rates of 10 or more air changes per hour at 50 pascals of pressure (ACH50). These issues can represent a substantial portion of unnecessary money spent on utility bills for homeowners, especially in the colder climates. There is a significant need for cost-effective, reliable retrofit methods for these homes that include air, moisture, and vapor controls which are considered best practices for high-performance new home construction. Well-tested and documented wall retrofit systems can help to achieve substantial energy savings and also improve durability, comfort, health, and resilience. In 2018, DOE’s Building Technologies Office awarded Pacific Northwest National Laboratory, Oak Ridge National Laboratory, and the University of Minnesota funding to complete a 3-year project to compare a range of residential wall retrofit systems that prioritized affordability, durability and energy savings potential. In addition to these core criteria, the ease-of-construction and the wide-scale applicability of the solutions also were considered. In this project, the research team identified, constructed, tested, simulated, and analyzed the feasibility and economics of 16 wall retrofit assemblies (14 test configurations and two baseline configurations).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Explainable and Differentiable Reinforcement Learning for Multi-objective Optimization in Particle Accelerators

Operating particle accelerators involves optimizing multiple goals simultaneously, which can be challenging due to trade-offs among objectives. While evolutionary algorithms like the genetic algorithm (GA) have been used for various Multi-Objective Optimization (MOO) tasks, they are not inherently suited for complex control problems. This talk highlights two variations of Reinforcement Learning (RL) for concurrently optimizing heat load and trip rates at the Continuous Electron Beam Accelerator Facility (CEBAF). The problem involves strict constraints on individual states, actions, and overall energy requirements of the beam. First, this talk highlights how differentiability can be harnessed through a Deep Differentiable Reinforcement Learning (DDRL) approach to address MOO issues within particle accelerators. We examine the DDRL method alongside Model Free Reinforcement Learning (MFRL), GA, and Bayesian Optimization (BO). The performance of these methods is assessed by generating a Pareto-front for two objectives. Our findings indicate that DDRL excels in handling high-dimensional problems more effectively than MFRL, BO, and GA. Next, we will show integration of explainable physics-based constraints into RL algorithms to enhance trans- parency and trust in decision-making processes by enabling users to verify that agents adhere to established physical principles. This surrogate function can be modeled using neural networks or sparse dictionary mod- els. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment provided but the surrogate model. In addi- tion, we find that the introduction of a mathematical functional dictionary based surrogate model enables our reinforcement learning algorithms to reliably converge for difficult high-dimensional accelerator controls environments.

Rajput, Kishansingh [Thomas Jefferson National Acc↗

DOE OSTI2018

Robotic Underwater Decontamination Services for Nuclear Applications-18464

Successful Underwater Robotic Decontamination Demonstrates Dose-Saving And Outage-Shortening Technology Diakont successfully provided underwater robotic decontamination services on a North American nuclear power plant's refueling cavity and dryer-separator pool in Spring 2017 using a new tool system. Historically, nuclear plant operators have conducted cleaning and decontamination of these surfaces manually, after draining water from the space. However manual decontamination is slow, and can result in excessive personnel dose exposure. The underwater robotic decontamination services present a vast improvement over manual decontamination because it reduces personnel dose exposure, reduces radwaste, doesn't impact plant chemistry, and doesn't risk inadvertently spreading contamination. Also the new decontamination method avoids the risk of personnel injury and component damage associated with hydrolasing. And by performing the decontamination robotically while the cavities are flooded, in many cases the critical path outage schedule can be shortened. Able to decontaminate horizontal, vertical, and curved surfaces, the decontamination tools easily navigate to areas within flooded cavities that are inaccessible to previous solutions, performing decontamination in parallel to other activities including fuel movement. Also, unlike other legacy solutions, the new tools do not require continuous use of an overhead crane or other method of suspension while performing the decontamination activities. The ROV-type decontamination tool attaches and drives along the cavity and component surfaces using a high-force, no-flow vortex generator, even in the presence of Residual Heat Removal (RHR) or shutdown cooling flow. Efficient, effective cleaning is performed using a rugged brushing action to detach the crud, while vacuuming it away at high flow rates to a submerged filter. At the Spring 2017 refueling outage, the decontamination services with the new methodology were so effective that no additional manual cavity decontamination was required after drain-down. Using the tool's ability to swim, attach, and crawl, field technicians decontaminated the majority of the surfaces designated by the plant operator. Preliminary surveys indicated that all contamination levels were reduced to <50 K dpm/100 cm{sup 2}, helping the utility meet their INPO/Industry collective radiation exposure goals. The new cleaning and decontamination services are ideal for servicing various underwater areas within nuclear power plants such as refueling cavities, BWR-6 drywell heads, spent fuel pools, cask loading pools and fuel transfer canals. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Comparing the extraction performance of cyclodextrin-containing supramolecular deep eutectic solvents versus conventional deep eutectic solvents by headspace single drop microextraction

A headspace single drop microextraction (HS-SDME) method coupled with high performance liquid chromatography was developed to compare the extraction of eighteen aromatic organic pollutants from aqueous solutions using cyclodextrin-based supramolecular deep eutectic solvents (SUPRADESs) and alkylammonium halide-based conventional deep eutectic solvents (DESs). Different derivatives of beta-cyclodextrin (β-CD) were employed as hydrogen bond acceptors (HBA) in SUPRADESs and the extraction performance investigated. SUPRADES comprised of the 20 wt% native β-CD HBA provided the highest enrichment factors of analytes compared to SUPRADESs comprised of other derivatives of β-CD (random methylated β-cyclodextrin, heptakis(2,3,6-tri-O-methyl)-β-cyclodextrin, and 2-hydroxypropyl β-cyclodextrin). In addition, native β-CD and its derivatives were dissolved in the neat DESs and their effect on the extraction of analytes examined. Dissolution of 20 wt% native β-CD in the choline chloride ([Ch + ][Cl - ]):2Urea DES resulted in a significant increase in the extraction efficiencies of target analytes compared to the neat [Ch + ][Cl - ]:2Urea DES. Under optimum conditions, the extraction method required a solvent microdroplet of 6.5 μL, 1000 rpm stir rate, 30% (w/v) salt concentration, and a temperature of 40 °C. The tetrabutylammonium chloride: 2 lactic acid DES resulted in the highest enrichment factors while the [Ch + ][Cl - ]:2Urea DES had the lowest for most of the analytes among the evaluated solvents. The method provided limits of detection (LODs) down to 35 μg L -1 . Finally, the developed method was applied for the analysis of spiked tap and lake water, where relative recoveries ranging from 83.7% -119.7% and relative standard deviations lower than 19.2% were achieved.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Impacts of intentional mycoplasma contamination on CHO cell bioreactor cultures

Mycoplasma contamination events in biomanufacturing facilities can result in loss of production and costly cleanups. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and may penetrate the 0.2 µm filters often used in the primary clarification of harvested cell culture fluid. Culture cell-based and indicator cell-based assays that are used to detect mycoplasma are highly sensitive but can take up to 28 days to complete and cannot be used for real-time decision making during the biomanufacturing process. To support real-time measurements of mycoplasma contamination, there is a push to explore nucleic acid testing. However, cell-based methods measure growth or colony forming units and nucleic acid testing measures genome copy number; this has led to ambiguity regarding how to compare the sensitivity of the methods. In addition, the high risk of conducting experiments wherein one deliberately spikes mycoplasma into bioreactors has dissuaded commercial groups from performing studies to explore the multiple variables associated with the upstream effects of a mycoplasma contamination in a manufacturing setting. Here we studied the ability of Mycoplasma arginini to persist in a single-use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G1 (IgG1) antibody. We examined M. arginini growth and detection by culture methods, as well as the effects of M. arginini on mammalian cell health, metabolism, and productivity. We compared process parameters and controls normally measured in bioreactors including dissolved oxygen, gas mix, and base addition to maintain pH, to examine parameter changes as potential indicators of contamination. Our work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Importantly, how the M. arginini contamination impacts the CHO cells is influenced by the concentration of CHO cells and rate of perfusion at the time of M. arginini spike. Careful evaluation of dissolved oxygen, pH control parameters, ammonia, and arginine over time may be used to indicate Mycoplasma contamination events in biomanufacturing facilities can result in loss of production and costly cleanups. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and may penetrate the 0.2 µm filters often used in the primary clarification of harvested cell culture fluid. Culture cell-based and indicator cell-based assays that are used to detect mycoplasma are highly sensitive but can take up to 28 days to complete and cannot be used for real-time decision making during the biomanufacturing process. To support real-time measurements of mycoplasma contamination, there is a push to explore nucleic acid testing. However, cell-based methods measure growth or colony forming units and nucleic acid testing measures genome copy number; this has led to ambiguity regarding how to compare the sensitivity of the methods. In addition, the high risk of conducting experiments wherein one deliberately spikes mycoplasma into bioreactors has dissuaded commercial groups from performing studies to explore the multiple variables associated with the upstream effects of a mycoplasma contamination in a manufacturing setting. Here we studied the ability of Mycoplasma arginini to persist in a single-use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G1 (IgG1) antibody. We examined M. arginini growth and detection by culture methods, as well as the effects of M. arginini on mammalian cell health, metabolism, and productivity. We compared process parameters and controls normally measured in bioreactors including dissolved oxygen, gas mix, and base addition to maintain pH, to examine parameter changes as potential indicators of contamination. Our work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Importantly, how the M. arginini contamination impacts the CHO cells is influenced by the concentration of CHO cells and rate of perfusion at the time of M. arginini spike. Careful evaluation of dissolved oxygen, pH control parameters, ammonia, and arginine over time may be used to indicate Mycoplasma contamination events in biomanufacturing facilities can result in loss of production and costly cleanups. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and may penetrate the 0.2 µm filters often used in the primary clarification of harvested cell culture fluid. Culture cell-based and indicator cell-based assays that are used to detect mycoplasma are highly sensitive but can take up to 28 days to complete and cannot be used for real-time decision making during the biomanufacturing process. To support real-time measurements of mycoplasma contamination, there is a push to explore nucleic acid testing. However, cell-based methods measure growth or colony forming units and nucleic acid testing measures genome copy number; this has led to ambiguity regarding how to compare the sensitivity of the methods. In addition, the high risk of conducting experiments wherein one deliberately spikes mycoplasma into bioreactors has dissuaded commercial groups from performing studies to explore the multiple variables associated with the upstream effects of a mycoplasma contamination in a manufacturing setting. Here we studied the ability of Mycoplasma arginini to persist in a single-use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G1 (IgG1) antibody. We examined M. arginini growth and detection by culture methods, as well as the effects of M. arginini on mammalian cell health, metabolism, and productivity. We compared process parameters and controls normally measured in bioreactors including dissolved oxygen, gas mix, and base addition to maintain pH, to examine parameter changes as potential indicators of contamination. Our work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Importantly, how the M. arginini contamination impacts the CHO cells is influenced by the concentration of CHO cells and rate of perfusion at the time of M. arginini spike. Careful evaluation of dissolved oxygen, pH control parameters, ammonia, and arginine over time may be used to indicate mycoplasma contamination in CHO cell cultures in a bioreactor before a read-out from a traditional method.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Intrepid MCMC: Metropolis-Hastings with exploration

In engineering examples, one often encounters the need to sample from unnormalized distributions with complex shapes that may also be implicitly defined through a physical or numerical simulation model, making it computationally expensive to evaluate the associated density function. For such cases, MCMC has proven to be an invaluable tool. Random-walk Metropolis Methods (also known as Metropolis-Hastings (MH)), in particular, are highly popular for their simplicity, flexibility, and ease of implementation. However, most MH algorithms suffer from significant limitations when attempting to sample from distributions with multiple modes (particularly disconnected ones). Here, in this paper, we present Intrepid MCMC - a novel MH scheme that utilizes a simple coordinate transformation to significantly improve the mode-finding ability and convergence rate to the target distribution of random-walk Markov chains while retaining most of the simplicity of the vanilla MH paradigm. Through multiple examples, we showcase the improvement in the performance of Intrepid MCMC over vanilla MH for a wide variety of target distribution shapes. We also provide an analysis of the mixing behavior of the Intrepid Markov chain, as well as the efficiency of our algorithm for increasing dimensions. A thorough discussion is presented on the practical implementation of the Intrepid MCMC algorithm. Finally, its utility is highlighted through a Bayesian parameter inference problem for a two-degree-of-freedom oscillator under free vibration.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2022

How can a diverse set of integral and semi-integral measurements inform identification of discrepant nuclear data? [Slides]

Importance of nuclear data to bias changed significantly when including diverse measurement sets. LLNL pulsed sphere measurements provided information for 9 Be nuclear data above 2 MeV and subcritical benchmarks provided information for 240 Pu nuclear data between 100 keV and 10 MeV. Pulsed sphere leakage spectra and neutron noise observables are differently sensitive to nuclear data compared to critical benchmarks. Leakage spectra are sensitive to nuclear data above 5 MeV. Count rate and Feynman Y are more sensitive to nuclear data. A change in bias can help evaluators identify discrepant nuclear data. In the future, EUCLID plans to perform RAFIEKI analysis with additional benchmark and measurement sets.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Thermonuclear Reaction Rates and Primordial Nucleosynthesis

Assuming the best numerical value for the cosmic baryonic density and the existence of three neutrino flavors, standard Big Bang nucleosynthesis is a parameter-free model. It is important to assess if the observed primordial abundances can be reproduced by simulations. Numerous studies have shown that the simulations overpredict the primordial 7 Li abundance by a factor of ≈3 compared to the observations. The discrepancy may be caused by unknown systematics in 7 Li observations, poorly understood depletion of lithium in stars, errors in thermonuclear rates that take part in the lithium and beryllium synthesis, or physics beyond the standard model. Here, we focus on the likelihood of a nuclear physics solution. The status of the key nuclear reaction rates is summarized. Big Bang nucleosynthesis simulations are performed with the most recent reaction rates, and the uncertainties of the predicted abundances are established using a Monte Carlo technique. Correlations between abundances and reaction rates are investigated based on the metric of mutual information. The rates of four reactions impact the primordial 7 Li abundance: 3 He(α,γ) 7 Be, d(p,γ) 3 He, 7 Be(d,p)2α, and 7 Be(n,p) 7 Li. We employ a genetic algorithm to search for simultaneous rate changes in these four reactions that may account for all observed primordial abundances. Furthermore, when the search is performed for reaction rate ranges that are much wider than recently reported uncertainties, no acceptable solutions are found. Based on the currently available evidence, we conclude that it is highly unlikely for the cosmological lithium problem to have a nuclear physics solution.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Active Interrogation using Photofission Technique for Nuclear Materials Control and Accountability

Innovative systems with increased sensitivity and resolution are in great demand to detect diversion and to prevent misuse in support of nuclear materials management for the U.S. fuel cycle. Nuclear fission is the most important multiplicative process involved in non-destructive active interrogation. This process produces the most easily recognizable signature for nuclear materials. In addition to thermal or high-energy neutrons, high-energy gamma rays can also excite a nucleus and cause fission through a process known as photofission. Electron linear accelerators (linacs) are widely used as the interrogating photon sources for inspection methods involving photofission technique. After photofission reactions, prompt signals are much stronger than the delayed signals, but it is difficult to quantify them in practical measurements. Delayed signals are easily distinguishable from the interrogating radiation. Linac-based, advanced inspection techniques utilizing the delayed signals after photofission have been extensively studied for homeland security applications. Previous research also showed that a unique delayed gamma ray energy spectrum exists for each fissionable isotope. In this work, high-energy delayed γ-rays were demonstrated to be signatures for detection, identification, and quantification of special nuclear materials. Such γ-rays were measured in between linac pulses using independent data acquisition systems. A list-mode system was developed to measure low-energy delayed γ-rays after irradiation. Photofission product yields of 238 U and 239 Pu were determined based on the measured delayed γ-ray spectra. The differential yields of delayed γ-rays were also proven to be able to discriminate nuclear from non-nuclear materials. The measurement outcomes were compared with Monte Carlo simulation results. It was demonstrated that the current available codes have capabilities and limitations in the simulation of photofission process. A two-fold approach was used to address the high-rate challenge in used nuclear fuel assay based on photofission technique. First, a standard HPGe preamplifier was modified to improve its capabilities in high-rate pulsed photofission environment. Second, advanced pulse processing algorithms were shown to greatly improve throughput rate without large sacrifice in energy resolution at ultra-high input count rate. Two customized gamma spectroscopy systems were also developed in real-time on FPGAs. They were shown to have promising performance matching available commercial units.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗