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At least 649 records · Page 36

Direct Measurement of Cl − Activity in Metal Chloride Molten Salts using a Cl 2 /Cl − Electrode

Molten metal chloride salts are promising candidates for advanced heat transfer fluids in generation IV nuclear reactors and beyond. The activity of the chloride ion in the salt has a large influence on the redox characteristics of the corresponding molten salt. There exists a knowledge gap for the direct measurement of chlorobasicity (Lewis basicity) in molten-salt mixtures. Here, the focus of this work was to develop a Cl 2 /Cl − electrode for the direct measurement of chloride activity in molten metal-chloride salt mixtures. The LiCl–KCl eutectic system was utilized as the reference melt to determine the change in chloride ion activity as increasing concentrations of MgCl 2 are added to the LiCl–KCl eutectic working electrode. The results of the measurements indicated a reduction in chloride ion activity as the concentration of magnesium chloride increased, consistent with the complexation of free chlorides by Lewis acidic magnesium cationic species. The Temkin model was used to estimate the thermodynamic properties of MgCl 4 2− complex.

Chloride↗

HipGISAXS

Implementation of a flexible Grazing Incidence Small-Angle Scattering (GISAXS). Simulation code based on the Distorted Wave Born Approximation (DWBA) theory that effectively utilizes the parallel processing power provided by graphic processors and multicore processors. This constitutes a handy tool for experimentalists facing a massive flux of data, allowing them to accurately simulate the GISAXS process and analyze the produced data. The software computes the diffraction image for any given super position of custom shapes or morphologies in a user-defined region of the reciprocal space for all possible grazing incidence angles and in-plane sample rotations. This flexibility then allows to easily tackle a wide range of possible sample structures such as nanoparticles o top of or embedded in a substrate or a multilayered structure. In cases where the sample displays regions of significant refractive index contrast, an algorithm has been implemented to perform a slicing of the sample along the vertical direction and compute the averaging refractive index profile to be used as the reference geometry of the unpertubed system. Preliminary tests show good agreement with experimental data for a variety of commonly encountered nanostructures.

Xiaoye, Sherry Li↗

OpenStudio-Variability-Gem v1.0

This gem contains methods to introduce variability to extend core OpenStudio SDK. The term "variability" refers to changes in building systems efficiency, operation, or controls, which are non-routine events.

Li, Han↗

WELLS Interactive Application

The Wellbore Exploration and Location Logistic System (WELLS) Interactive Application is an interactive tool to enable easy exploration and visualization of the living national wellbore database (WELLS Database (https://edx.netl.doe.gov/dataset/wells_database)). The tool and underlying database were created and are maintained by the National Energy Technology Laboratory (NETL), providing visualization of the more than six million public wellbore records from more than 65 authoritative state, federal, and tribal resources. The WELLS Interactive Application serves up wellbore data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater, and other types of wells in a single, standardized, unified system. In addition to the surface location of these wells, the underlying database combines select key attributes for features such as well age, depth, and operating status. The system also provides users with references back to the original sources used in this unified platform. The underlying data can be accessed through the WELLS Database: https://edx.netl.doe.gov/dataset/wells_database Additional Information: The WELLS Interactive Application (formerly titled CO2-Locate) enables visualization and access to the public wellbore records through an intuitive web-based mapping tool. The WELLS Interactive Application was designed to help users visualize, query, analyze, and download wellbore records. Public wellbore points are included as a layer in the Map page, called Public Wells. Additionally, a multivariate hexagon grid summarizing well density from proprietary well data, called Well Density, is included to identify data gaps between the public and proprietary well data. Filtering functionalities in the tool allow these two layers to be spatially filtered by state, county, or basin as well as by status, type, true vertical depth, and spud year. The WELLS Interactive Application also contains a Near Me tool can be used to search and explore wellbore data within a user-defined distance of a specified location on the map, which can also be downloaded. The Query tool allows users to query the selected or filtered wells in the Public Wells layer and export the data. For additional information on these tool functionalities, see the help documentation on the About page of the tool. Notes for Consideration: The Well Density layer provided in this application is derived from proprietary wellbore data, the records of which do not always contain values for key features (status, type, true vertical depth, or spud year). Therefore, data might not be available when layers are queried for all filter combinations. Additionally, visualizing layers and applying filters may take additional time to load (i.e., draw on the map) due to the large size of the data.

ccs↗

Utility Sector Impacts of Reduced Electricity Demand

This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Fire-Induced Pressure Response and Failure Characterization of PCV/SCV/3013 Containers - Phase 1

This report discusses the test series performed at Sandia National Laboratories (SNL) to test the response of Primary Containment Vessels (PCVs) under a hypothetical fire scenario. The PCV is the innermost container in a 9975 shipping package (NRC, 2014). This test series was the first of three phases aiming to characterize the PCV/SCV/3013 system, and it will be referred to as Phase 1. The purpose of these tests was to characterize the response of the PCV wall when filled with a bounding payload and exposed to an ASTM-E1529 (ASTM, 2014) standard fire environment. In particular, the goal was to test a working hypothesis for these PCVs: that, during a scenario where the PCV is exposed to an ASTM-E1529 standard fire environment, the accumulated internal pressure (resulting from the expansion of gases and vaporization of moisture/plastics during heat exposure) relieves through the O-ring segment of the PCV before PCV wall failure (rupture). Bounding internal and external conditions were purposefully established for this Phase 1 testing in order to maximize pressurization in the container. Specifically, this Phase 1 test series is designed to determine the worst case thermal stress conditions by exposing five SRNS PCVs with identical payloads to the severe ASTM-E1529 fire conditions in five different configurations with increasing potential to result in a release of the internal contents (i.e. failure). All five tests were successfully executed, and the failure modes were characterized for each test. This report discusses the details of the five tests performed in this phase, their outcomes, and their implications.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Derivation of a Multi-Species Mix Model

Multi-species flow takes place when two or more gases, plasmas or fluids are flowing and interacting with one another through particle collisions, chemical reactions, turbulence, and thermonuclear processes; this list is not exhaustive. It has a wide range of applications in geological, biological and engineering systems. In what follows species refers to different species of atoms or molecules that may or may not be partially or fully ionized. The interactions between these species takes place at an atomic or molecular level. The species are electrically neutral. These are very important points, because the coupling between species that are interacting on a mesoscale level or are immiscible would be very different than what is being considered in this work. In addition, in section 4, we present a heuristic argument to enhance the collisional mean free path to incorporate the effects of turbulent eddies by use of Prandtl’s assumption that the integral scale length of a turbulent boundary layer is proportional to the width of the turbulent layer. This leads to coupling terms that are non-Newtonian, because they are a function of the dynamics of the flow. It is also assumed that the turbulent stress terms are much smaller than the species partial pressures. This may be a good assumption if the species are hot, dense plasmas that exist in ICF targets.

74 ATOMIC AND MOLECULAR PHYSICS↗

Theoretical framework for new magnetic materials for quantum computing and information storage. Final report for the Award No. DE-SC0018910

The focus of this grant was on molecular magnetic materials for information storage and quantum computing. We have been developing robust, first-principle methods for computing relevant electronic and magnetic properties of molecular building blocks (SMMs) of novel magnetic materials and quantum computers. These tools enable theoretical modeling of SMMs’ behavior, facilitating the interpretation of experimental studies and aiding the design of novel magnetic materials. Our strategy is based on the spin-flip (SF) approach, which extends the hierarchy of black-box single-reference methods to strongly correlated systems. Specifically, we developed general scalable algorithms and computer codes for calculating molecular properties, with an emphasis on spin-related properties, such as zero-field splittings, hyperfine couplings, and g-tensors. While our primary focus was on SF wave functions and SF-TDDFT, the underlying theory and computer codes were formulated using reduced density matrices, such that these tools are applicable to a broader class of methods. To extend the scope of applicability of wave-function-based SF methods to larger systems, we developed reduced-scaling approaches for the equation-of-motion coupled-cluster (EOM-CC) methods and continue developing libtensor (our open-source general tensor contraction library for many-body methods). We carried out extensive benchmarks and also carried out several applications.

36 MATERIALS SCIENCE↗

Strong Correlation DMRG and DFT

This project developed new ways to improve computer simulations of materials where electrons interact strongly with each other, a challenge for today’s most widely used method, density functional theory (DFT). We used an exact numerical method, the density matrix renormalization group (DMRG), to create highly accurate reference results for simple model systems, and used these to test DFT, prove when it will converge, and even train machine-learned functionals. We also invented new kinds of localized basis functions (“gausslets” and “multi-sliced gausslets”) and a “sliced-basis” approach that make high-accuracy simulations faster and more practical. These methods were applied to extended hydrogen systems, enabling the direct derivation of accurate low-energy models from first-principles calculations. We also introduced a new formalism, Conditional-Probability DFT, which could bypass traditional approximations. The tools and results from this work, including open-source software releases, will help scientists design and understand complex quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Levelized Cost of Exergy Framework

Exergy is the amount of energy within a substance or within a transfer of energy that can be used to produce work or some other useful output when interacting with some reference environment. Two different energy systems that produce the same output with the same exergetic efficiency must necessarily have the same amount of exergy input, even if the amount of energy input to the two systems is vastly different. For example, a low-grade heat-driven desalination would require far more energy input than a reverse osmosis (RO) plant producing the same amount of water, but if their exergetic efficiencies were the same, they would require the same amount of exergy input. Thus, comparisons between different energy sources on the basis of energy is not always appropriate. Instead, a comparison on a per unit exergy basis provides more insight on the cost-effectiveness of different energy sources and systems. In this presentation, we describe a framework for analyzing the levelized cost of exergy (LCOEx) for both inputs and outputs of various energy systems. Our framework illustrates how the cost per unit exergy of a system's energy source, as well as the exergetic efficiency of the system, greatly affect the cost of the system output. We use the levelized cost of electricity as a benchmark value for LCOEx, due to electricity's ubiquity as an energy source, and because it is relatively inexpensive on a per unit exergy basis. The LCOEx of various heat sources are then compared to the LCOEx of electricity. Medium- and high-grade industrial heat (> 150 degrees C) produced by natural gas tends to have an LCOEx on par with electricity. This is due to the low cost of natural gas, as well as the high exergy content of heat at higher temperatures. Meanwhile, low-grade heat tends to be an expensive exergy source, owing to the low exergy content of the low-grade heat. We first apply our framework to desalination, where RO has come to dominate, due to the low LCOEx of the energy source (electricity) and relatively high exergetic efficiency of RO compared to thermal desalination systems. We then use this framework to highlight an opportunity for dehumidification systems to experience a similar cost improvement as desalination has. If an electrically-driven, high exergetic efficiency dehumidification system were developed (such as the membrane-based dehumidification systems proposed in literature), it would use a low cost exergy source with a high exergetic efficiency and could potentially lower the cost of dehumidification in the way that RO has done for desalination. Finally, we apply our framework to various fuels (natural gas, hydrogen, gasoline, etc.) and energy systems across different sectors (desalination, dehumidification, vehicles, etc.) to understand the variation in the cost of exergy input and exergetic efficiency of different systems and technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Search for Long-Lived Particles with Muon Detector Shower Signature in the CMS Run-3 data

Many beyond standard model theories predict the existence of long-lived particles (LLPs). These LLPs can have sizable lifetimes and decay several meters from their production vertex. In this poster/talk, we present the analysis strategy for searching for LLPs using the Compact Muon Solenoid (CMS) Experiment. The proton-proton collision data used in this analysis were collected from 2022 to 2024 at a center-of-mass energy of 13.6 TeV, corresponding to an integrated luminosity of 170 fb^-1. The LLP decays are reconstructed as a high-multiplicity cluster of detector hits in the cathode strip chambers (CSC) of the muon system endcap. This signature is referred to as the Muon Detector Showers (MDS). This search requires events to contain at least one MDS cluster. The analysis focuses on LLP hadronic decays and LLP masses up to a few tens of GeV. We present the signal properties in MonteCarlo simulation, event selection, background modeling, and evaluation of the expected sensitivity. The results are interpreted under the Twin Higgs model benchmark.

Agyemang-Duah, Andrews [Grambling State U.]↗

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

59 BASIC BIOLOGICAL SCIENCES↗

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

Lindsey, Jack W. (ORCID:0000000309307327)↗

Probing Optimal Reaction Energy for Synthesis of Element 119 from 51 V+ 248 Cm Reaction with Quasielastic Barrier Distribution Measurement

Here, the quasielastic barrier distribution of 51 V+ 248 Cm was extracted by measuring the excitation function of quasielastic backscattering using a gas-filled recoil ion separator, GARIS-III. The obtained barrier distribution is well explained by the coupled-channels calculation, indicating a significant effect of the rotational excitation of deformed 248 Cm. From the measured average Coulomb barrier height and deformation parameters of 248 Cm, the side-collision energy leading to a compact configuration of colliding nuclei was obtained. The relation between the side collision energy and the excitation function of the evaporation-residue cross sections in the 48 Ca+ 248 Cm system was evaluated as a reference for the 51 V+ 248 Cm case. The optimal reaction energy to synthesize a new element 119 at the 51 V+ 248 Cm fusion reaction (3n and 4n channels) was estimated with an aid of these experimental data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Can We Practically Bring Physics-based Modeling Into Operational Analytics Tools?

We present that analytics software is increasingly used to improve and maintain operational efficiency in commercial buildings. Energy managers, owners, and operators are using a diversity of commercial offerings often referred to as Energy Information Systems, Fault Detection and Diagnostic (FDD) systems, or more broadly Energy Management and Information Systems, to cost-effectively enable savings on the order of ten to twenty percent. Most of these systems use data from meters and sensors, with rule-based and/or data-driven models to characterize system and building behavior. In contrast, physics-based modeling uses first-principles and engineering models (e.g., efficiency curves) to characterize system and building behavior. Historically, these physics-based approaches have been used in the design phase of the building life cycle or in retrofit analyses. Researchers have begun exploring the benefits of integrating physics-based models with operational data analytics tools, bridging the gap between design and operations. In this paper, we detail the development and operator use of a software tool that uses hybrid data-driven and physics-based approaches to cooling plant FDD and optimization. Specifically, we describe the system architecture, models, and FDD and optimization algorithms; advantages and disadvantages with respect to purely data-driven approaches; and practical implications for scaling and replicating these techniques. Finally, we conclude with an evaluation of the future potential for such tools and future research opportunities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Response of a Memristive Biomembrane and Demonstration of Potential Use in Online Learning

The pervasive von Neumann architecture uses complex processor cores and sequential computation. In contrast, the brain is massively parallel and highly efficient, owing to the ability of the neurons and synapses to store and process information simultaneously and to adapt according to incoming information. These features have motivated researchers to develop a host of brain-inspired computers, devices, and models, collectively referred to as neuromorphic computing systems. The quest for synaptic materials capable of closely mimicking biological synapses has led to an alamethicin-doped, synthetic biomembrane with volatile memristive properties which can emulate key synaptic functions to facilitate learning and computation. In contrast to its solid-state counterparts, this two-terminal, biomolecular memristor features similar structure, switching mechanisms, and ionic transport modality as biological synapses while consuming considerably lower power. To use the device as a circuit element, it is important to understand its response to different kinds of input signals. Here we develop a simplified closed form analytical solution based on the underlying state equations for pulse and sine wave inputs. A Verilog-A model based on Runge-Kutta method was developed to incorporate the device in a circuit simulator. Finally, the paper demonstrates possible applications for short- and long-term learning using its unique volatile memristive properties.

Hasan, Md Sakib↗

Reference dosimetry for helical tomotherapy: Practical implementation and a multicenter validation

Purpose: The aim of this study was to implement a protocol for reference dosimetry in tomotherapy and to validate the beam output measurements with an independent dosimetry system. Methods: Beam output was measured at the reference depth of 10 cm in water for the following three cases: (1) a 5 x 10 cm{sup 2} static machine specific reference field (MSR), (2) a rotational 5 x 10 cm{sup 2} field without modulation and no tabletop in the beam, (3) a plan class specific reference (PCSR) field defined as a rotational homogeneous dose delivery to a cylindrical shaped target volume: plan with modulation and table-top movement. The formalism for reference dosimetry of small and nonstandard fields [Med.Phys.35: 5179-5186, 2008] and QA recommendations [Med.Phys.37: 4817-4853, 2010] were adopted in the dose measurement protocol. All ionization chamber measurements were verified independently using alanine/EPR dosimetry. As a pilot study, the beam output was measured on tomotherapy Hi-art systems at three other centers and directly compared to the centers specifications and to alanine dosimetry. Results: For the four centers, the mean static output at a depth of 10 cm in water and SAD = 85 cm, measured with an A1SL chamber following the TG-148 report was 6.238 Gy/min {+-} 0.058 (1 SD); the rotational output was 6.255 Gy/min {+-} 0.069 (1 SD). The dose stated by the center was found in good agreement with the measurements of the visiting team: D{sub center}/D{sub visit} = 1.000 {+-} 0.003 (1 SD). The A1SL chamber measurements were all in good agreement with Alanine/EPR dosimetry. Going from the static reference field to the rotational/non modulated field the dose rate remains constant within 0.2% except for one center where a deviation of 1.3% was detected. Conclusions: Following the TG-148 report, beam output measurements in water at the reference depth using a local protocol, as developed at different centers, was verified. The measurements were found in good agreement with alanine/EPR dosimetry. The presented methodology may provide a good concept for reference dosimetry.

61 RADIATION PROTECTION AND DOSIMETRY↗

The Role of Chain-End Association Lifetime in Segmental and Chain Dynamics of Telechelic Polymers

Broadband dielectric spectroscopy, differential scanning calorimetry, and rheology were employed to study the impact of hydrogen (H)-bonding end-groups on segmental and chain dynamics of telechelic polypropylene glycol (PPG) and poly(dimethylsiloxane) (PDMS). Polymer chains with three types of H-bonding end-groups possessing different interaction strengths and a non-H-bonding end-group as reference were compared. The glass transition temperature (Tg) of H-bonding PPG systems with low molecular weight increases compared to the reference, and the Tg difference varies with chain-end interaction strength. In contrast, their shear viscosities (for Tg-scaled temperature, i.e., when the shift in Tg is accounted for) are similar to that one of the reference. This is in strong contrast to the behavior of telechelic PDMS with the same set of end-groups, where the Tg increase of all H-bonding systems is independent of H-bond strengths, while shear viscosity increases significantly only for the strongest H-bonding end-groups. These observations are explained by the difference in lifetime of the end-group associations relative to segmental and chain relaxation times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗