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Mass generation in an Abelian gauge theory with multiple scalar fields and no tree-level dimensionful couplings

We study the Abelian Higgs model with multiple scalar fields, but without mass terms. Solving the model nonperturbatively order-by-order in the number of scalar fields, we find that radiative corrections generate masses for the scalar and gauge boson, without spontaneous symmetry breaking. The mass scales are set by the Λ -parameter of the electroweak running coupling, thereby naturally avoiding the hierarchy problem. No part of our calculation employs a weak-coupling expansion, and we find that the perturbative vacuum is metastable, and hence must decay to the stable nonperturbative vacuum of the theory, which we identify. Although the field content of our Lagrangian is standard, our results predict the existence of two heavy scalar resonances in addition to the Higgs. We believe that these predicted resonances will ultimately allow experimentalists to discriminate between our method and standard solutions of the Higgs model. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multimodal sensor fusion framework for residential building occupancy detection

For several years now, smart building energy systems have been a research area of intensive activity. In light of the increasing need for sustainable buildings and energy systems, this trend motivates an increasing need for a solution to reduce carbon dioxide emissions and improve energy efficiency. This work proposes a high-performing and transferable occupancy detection framework that combines sensor data from different data modalities, including time series environmental data (temperature, humidity, and illuminance), image data, and acoustic energy data using ensemble method. To draw out the best prediction performance in each modality, the proposed framework was developed, including various models that were designed to learn the occupancy patterns reflected in the physical data streams. To tackle the time series environmental data, we designed two variants of an occupancy detection spatiotemporal pattern network (Occ-STPN) that performs both feature level and decision level fusion, respectively. We also propose a new metric; the fading memory mean square error (FMMSE), that provides a fair evaluation and penalization of delayed occupancy predictions. Multiple open-sourced datasets, including the Electricity Consumption and Occupancy and the University of California, Irvine's (UCI) building occupancy detection dataset, along with our own real data collected from six different houses, were used to validate the algorithms' performance. The experimental results presented herein break down the performance for each sensing modality, and a detailed analysis of the performance is also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hematite Crystallization from a Two-Line Ferrihydrite Suspension

Rational design and synthesis of materials, determination of environmental conditions at the time of mineral formation, and definition of mechanisms in biomineralizing systems all require an understanding of the effect of multiple factors on modulating crystallization pathways. In this study, we investigate the influence of temperature, oxalate additive, aging time, and addition of seed crystals on hematite (α-Fe 2 O 3 , Hm) crystallization from a two-line ferrihydrite (Fe 2 O 3 ·xH 2 O, Fh) suspension. We also investigate the effect of temperature on the aging of spindle-shaped Hm mesocrystals, which we synthesize through the addition of sodium oxalate. The results show that Hm mesocrystals form in a temperature window of 45 °C-130 °C. Temperatures ≥ 140 °C favor formation of rhombohedral Hm, suggesting classical monomer-by-monomer growth dominates, whereas crystallization by particle attachment (CPA) is dominant between 45 and 90 °C, while the two processes compete in the intermediate temperature range. Aging of mesocrystals in the original solution at 90 °C or 180 °C leads to a slow morphological evolution towards rhombohedral crystals due to Ostwald ripening. Then, by utilizing rhombohedral Hm and rod-shaped goethite as substrates on which to assemble the mesocrystals, we demonstrate formation of complex heterogeneous structures.

36 MATERIALS SCIENCE↗

22 GeV CEBAF with Novel Fixed Field Alternating Gradient Design

Extending the energy reach of CEBAF up to 22 GeV within the existing tunnel is being explored. Proposed energy upgrade can be achieved by increasing the number of recirculations, while using the existing CEBAF SRF cavity system. Presented scheme is based on an exciting new approach to acceleratie electrons efficiently with multiple passes in a single FFA beam line. Encouraged by recent success of the CBETA Test Accelerator, a proposal was formulated raise CEBAF energy by replacing the highest-energy arcs with Fixed Field Alternating Gradient (FFA) arcs. The new pair of arcs configured with FFA lattice would support simultaneous transport of additional 6 passes with energies spanning a factor of two, using the non-scaling FFA principle implemented with Halbach-derived permanent magnets - a novel magnet technology that significantly saves energy and lowers operating costs. One of the challenges of the multi-pass (11) linac optics is to provide uniform focusing in a vast range of energies, using fixed field lattice. Here, we propose a triplet lattice scaled up with increasing momentum along the linac. This would provide a stable periodic solution covering energy ratio of 1:33. The current CEBAF configured with a 123 MeV injector, makes optical matching in the first linac virtually impossible due to extremely high energy span ratio (1:175). Therefore, we envision replacement of the current injector with a 650 MeV 3-pass recirculating injector based on the existing LERF facility. Finally, the 22 GeV CEBAF would promise to deliver in 10-passes a beam with normalized emittance of 80 mm·mrad and with a relative energy spread of 1.5 × 10-3. Further recirculation beyond 22 GeV is limited by large, 974 MeV per electron, energy loss due to synchrotron radiation.

Bogacz, Slawomir↗

Structural and genetic convergence of HIV-1 neutralizing antibodies in vaccinated non-human primates

A primary goal of HIV-1 vaccine development is the consistent elicitation of protective, neutralizing antibodies. While highly similar neutralizing antibodies (nAbs) have been isolated from multiple HIV-infected individuals, it is unclear whether vaccination can consistently elicit highly similar nAbs in genetically diverse primates. Here, we show in three outbred rhesus macaques that immunization with Env elicits a genotypically and phenotypically conserved nAb response. From these vaccinated macaques, we isolated four antibody lineages that had commonalities in immunoglobulin variable, diversity, and joining gene segment usage. Atomic-level structures of the antigen binding fragments of the two most similar antibodies showed nearly identical paratopes. The Env binding modes of each of the four vaccine-induced nAbs were distinct from previously known monoclonal HIV-1 neutralizing antibodies, but were nearly identical to each other. The similarities of these antibodies show that the immune system in outbred primates can respond to HIV-1 Env vaccination with a similar structural and genotypic solution for recognizing a particular neutralizing epitope. These results support rational vaccine design for HIV-1 that aims to reproducibly elicit, in genetically diverse primates, nAbs with specific paratope structures capable of binding conserved epitopes.

59 BASIC BIOLOGICAL SCIENCES↗

Hindsight logging for model training

In modern Machine Learning, model training is an iterative, experimental process that can consume enormous computation resources and developer time. To aid in that process, experienced model developers log and visualize program variables during training runs. Exhaustive logging of all variables is infeasible, so developers are left to choose between slowing down training via extensive conservative logging, or letting training run fast via minimalist optimistic logging that may omit key information. As a compromise, optimistic logging can be accompanied by program checkpoints; this allows developers to add log statements post-hoc, and "replay" desired log statements from checkpoint---a process we refer to as hindsight logging. Unfortunately, hindsight logging raises tricky problems in data management and software engineering. Done poorly, hindsight logging can waste resources and generate technical debt embodied in multiple variants of training code. In this paper, we present methodologies for efficient and effective logging practices for model training, with a focus on techniques for hindsight logging. Our goal is for experienced model developers to learn and adopt these practices. To make this easier, we provide an open-source suite of tools for Fast Low-Overhead Recovery (flor) that embodies our design across three tasks: (i) efficient background logging in Python, (ii) adaptive periodic checkpointing, and (iii) an instrumentation library that codifies hindsight logging for efficient and automatic record-replay of model-training. Model developers can use each flor tool separately as they see fit, or they can use flor in hands-free mode, entrusting it to instrument their code end-to-end for efficient record-replay. Our solutions leverage techniques from physiological transaction logs and recovery in database systems. Evaluations on modern ML benchmarks demonstrate that flor can produce fast checkpointing with small user-specifiable overheads (e.g. 7%), and still provide hindsight log replay times orders of magnitude faster than restarting training from scratch.

Computer Science↗

Anomalous Stellar Populations in Low-surface-brightness Galaxies

We present new Hubble Space Telescope WFC3 near-IR observations of the color–magnitude diagrams (CMDs) in two low-surface-brightness galaxies, F575-3 and F615-1, notable for having no current star formation based on a lack of Hα emission. Key features of the near-IR CMDs are resolved, such as the red giant branch (RGB), the asymptotic giant branch (AGB) region, and the top of the blue main sequence. F575-3 has the bluest RGB of any CMD in the literature, indicating an extremely low mean metallicity. F615-1 has unusually wide RGB and AGB sequences, suggesting multiple episodes of star formation from metal-poor gas, and possibly infalling material. Both galaxies have an unusual population of stars to the red of the RGB and lower in luminosity than typical AGB stars. These stars have normal optical colors but abnormal near-IR colors. We suggest that this population of stars might be analogous to local peculiar stars like Be stars with strong near-IR excesses owing to a surrounding disk of hot gas.

47 OTHER INSTRUMENTATION↗

Accessing Transient Isomers in the Photoreaction of Metastable‐State Photoacid

The photoreaction of a metastable‐state photoacid (mPAH) generally involves multiple isomers with various connected pathways of photoinduced structural changes during a single reaction cycle. However, only a limited number of isomers have been identified experimentally so far owing to the inherent complexity in combination with the presence of various competing electronic and vibrational processes, as well as the constantly varying interactions between mPAH isomers and solvent molecules. Here, in this work, an optical spectroscopic study on a benzimidazole‐based mPAH, a novel photoacid using benzimidazole as the structural moiety with the active proton, is reported. Through measurements of linear absorption and steady‐state fluorescence in neat solvents and binary mixtures, a pronounced effect of neat water and its binary mixture with glycerol is discovered on the photoreaction of this benzimidazole‐mPAH, manifested by the remarkably distinct spectral responses to irradiation from that observed for an organic solution under identical conditions. Measurements of time‐ and frequency‐resolved fluorescence emission further enable to access transient isomers and the associated spectral characteristics from other competing electronic excited‐state relaxation processes. Spectral deconvolution analysis and time‐dependent density functional theory calculations are applied to separate distinct spectral components and access their potential origin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Verification of Special Nuclear Material (SNM) using Active Well Coincidence Counter (AWCC) and a High Purity Germanium (HPGe) Detector

SNM verification can be accomplished via two methods i.e. destructive analysis (DA) or nondestructive analysis (NDA). The DA modes are much more accurate compared to NDA modes; nevertheless, the sample's physical integrity is destroyed in the process. Techniques such as ICP-MS, ID-ICP-MS, TI-MS are few examples of DA, where a bulk material is ground and mixed with a solution (some form of acid) to acquire a homogenous sample. In contrast, NDA modes utilize signals emitted by the sample such as gamma, neutrons, light, or heat to analyze samples under investigation. HPGe detectors are some of the most frequently used gamma detectors to assay SNM. However, in a high activity scenario it provides a large uncertainty and sometimes becomes unfeasible to measure low energy gamma rays. Meanwhile, neutron detectors are not affected by the gamma background, therefore they can be used in addition to the gamma detectors to verify total fissile mass ({sup 235}U + {sup 239}Pu) of SNM. The AWCC is one of the thermal neutron NDA systems developed at the Los Alamos National Laboratory (LANL). It consists of 42 {sup 3}He detectors to measure gross neutrons (singles), coincidence neutrons (doubles), higher order multiplicity counting (triples, quadruples, etc.). It can effectively operate in both active and passive neutron interrogation modes. It can utilize AmLi, AmBe, or {sup 252}Cf active interrogation neutron sources. It is used to verify declared fissile mass ({sup 235}U or {sup 239}Pu) present in SNM. Objectives: Calibrate HPGe and AWCC for lightly irradiated (with enough {sup 137}Cs gamma background) ∼93% enriched HEU fuels; Verify fissile mass ({sup 235}U +{sup 239}Pu) content using AWCC and HPGe; Model and benchmark AWCC in MCNP6. Neutron coincidence and multiplicity counting: Two or more neutrons are coincident if they are detected by the system within the specified gate window; In AWCC: Gate window is 128 μsec; Induced fission in fissile material such as {sup 235}U and {sup 239}Pu - emission of time correlated neutrons - Singles, Doubles, Triples, or Quadruples; No induced fission in non-fissile materials- no correlated neutrons - only singles. SNM can be verified with high accuracy and precision using gamma and neutron NDA instruments such as HPGe and AWCC. Interaction with thermal neutrons. Non-fissile atoms - do not emit correlated neutrons. Fissile atoms - emit correlated neutrons during induced fission events. The time correlated neutrons can be detected by using coincidence or multiplicity counters such as AWCC. Likewise, {sup 235}U produces 186 keV gamma peak that can be measured by a HPGe gamma detector. Counts under 186 keV gamma peak provide information about {sup 235}U content. Combining AWCC and HPGe results can provide better understanding of special nuclear material under investigation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Probing the Sustainable Reduction of CO 2 , N 2 and NO 3 to Fuels and Chemicals using Non-Traditional Porphyrinoid Catalysts

For the last several decades, numerous strategies have been proposed to be able to interconvert electricity and commodity fuels for transportation and other applications. Even as solar and wind energy become more widely available, these renewable energy sources are not always available where the population is most dense or during peak times of energy demand. One plausible solution to the issue of electricity storage and transport is to use electricity to drive the formation of high-energy compounds and chemical fuels. As a result, the electrochemical conversion of CO 2 into chemical fuels has received major attention as a multi-pronged approach for electricity coversion, storage, and transport. Similar strategies are also attractive for conversion of N 2 and NO x into value added compounds such as ammonia. Metalloporphyrin and metallocorrole complexes are comprised of aromatic tetrapyrrole scaffolds and have been extensively studied as homogeneous catalysts for critical catalytic processes like the electrochemical CO 2 reduction reaction (eCO 2 RR) to generate CO as feedstock for the Fischer–Tropsch process to generate a variety of hydrocarbons as chemical fuels. Despite their significance and impact, efficiently driving such catalytic reduction processes is challenging for multiple reasons. Such processes require multiple-electron transfer events, as opposed to single-electron redox chemistry that forms high-energy singly-reduced intermediates. In addition, these electron transfer events must be coupled to proton-transfer steps and avoid application of high overpotentials where proton (H + ) reduction to generate H 2 (as well as other side-reactions) can lower the selectivity and energy efficiency of the eCO 2 RR process. Certain Fe(III) aromatic tetrapyrroles (e.g., porphyrins and corroles) have been reported to overcome these challenges, but are often difficult to synthesize and modify, and have a tendency to support single-electron redox chemistry at the metal as opposed to multielectron redox involving the ligand and metal in concert. Other families of tetrapyrroles in which all four meso-carbons are reduced (i.e., sp 3 -hybridized) are also known in the literature. These non-aromatic tetrapyrroles are known as porphyrinogens and support multi-electron redox chemistry which has been elaborated by several groups, prompting researchers to consider whether these scaffolds may improve the kinetics and efficiencies of multi-electron steps attendant to activation of thermodynamically stable small-molecule substrates such as CO 2 , N 2 , NO 3 − , and NO 2 − . Although porphyrinogens support multi-electron redox properties, the four sp 3 -hybridized meso-carbons inherent to the tetrapyrrole core completely disrupt π-conjugation between pyrrolic units, which compromises the photochemical properties of porphyrinogens in comparison to that of traditional porphyrinoids. Moreover, the highly reducing nature of porphyrinogens predisposes these platforms to extreme air and water sensitivity. Accordingly, such metalated porphyrinogens are often pyrophoric and/or incompatible with many common organic solvents (CH 2 Cl 2 , CHCl 3 , CH 3 CN, EtOAc, etc.). Hence, reports of efficient small-molecule activation or catalysis supported by porphyrinogens have been limited. To overcome the instability of porphyrinogens while retaining the scaffold’s attractive multi-electron redox properties, we have directed attention to establishing less-well studied groups of non-aromatic tetrapyrroles (i.e., phlorins, biladienes, and isocorroles). These non-traditional tetrapyrroles each contain just a single sp 3 -hybridized meso-carbon, which ablates the platforms aromaticity but still provides an extended π-framework. In addition to developing innovative platforms that may be used to sustainably generate value-added chemicals, fuels, and ammonia via either photo- or electrocatalytic approaches our work also has significantly broadened our understanding of how to prepare and modulate the properties of non-aromatic tetrapyrroles for other applications. Our efforts entailed a synergistic partnership and active collaborations with Drs. David C. Grills and Mehmed Z. Ertem (both of Brookhaven National Lab) to better characterize isocorroles (and related non-aromatic tetrapyrroles) using a variety of advanced spectroscopic and theoretical methods. Our combined efforts have shown that the combination of properties that isocorroles (and related tetrapyrroles) provide results in good chemical stability paired with unique redox and photochemical characteristics that are not typically supported by simple and/or unadorned aromatic tetrapyrroles. Beside redox chemistry, the photochemistry of isocorroles and other non-aromatic tetrapyrroles containing one sp 3 -hybridized meso-carbon is also appealing due to their absorption in the long-visible to near-IR regions, which are essential for photocatalysis and related applications that benefit from direct excitation at these wavelengths. The results reported vastly improve our understanding of non-aromatic tetrapyrrole synthesis, properties and utility for activation of small molecule substrates such as O 2 and CO 2 in the presence of weak cationic organic acids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transforming Windows from Energy Liabilities to Zero-Energy Assets: Next-Generation Solutions for Buildings

Windows have traditionally contributed to a building's HVAC load, but they can also become a source of net energy gain or even operate as zero-energy components. For heating applications, highly insulating windows can harness more solar heat than the energy lost through them, transforming windows from energy liabilities to assets. Dynamic glazings provide further benefits by regulating solar heat gain, reducing cooling loads in summer and heating demands in winter. This simulation study focuses on developing the next generation of zero-energy windows (ZEW) for residential new construction. Through annual energy simulations across climate zones 1-8, ZEW performance benchmarks were established based on current code-level buildings, and we've identified the regions where meeting ZEW standards are most achievable. This work evaluates both static and dynamic window technologies, assessing their effects on annual energy use and cost. Key findings demonstrate that ZEW performance is achievable across diverse climate zones, with specific regional requirements. Most climate zones from 3-8 can achieve ZEW with specific configurations, while some warm climates (1-2) appear challenging for ZEW implementation. Climate zones 4-6 consistently allow for zero energy window implementation, offering multiple pathways through either static or dynamic window technologies. Colder climate zones (7-8) ZEW products allow for higher SHGC values while requiring low U-values.

Yu, Lili↗

Computational Algorithms for Unit Commitment with AC Power Flows (Final Report)

Security-constrained unit commitment (SCUC) is a key component in power system operations. When AC power flow constraints are considered in the SCUC model (AC-SCUC), the problem becomes extremely difficult due to its discrete and non-convex nature, as described in “Grid Optimization Competition Challenge 3 Problem Formulation (GOCC)”. There are four main challenges: (i) Discrete decisions regarding unit online/offline status and start-up/shut-down procedures for every single unit. The number of discrete decision variables increases considerably when a system integrates multiple generators; (ii) Configuration-based combined-cycle formulations, and multi-commodity models that include ramping products, spin/non-spin products, and regulation up/down products. The combined-cycle units introduce additional discrete decision variables and auxiliary service products further complicate the model by connecting multi-commodity products’ continuous and discrete variables; (iii) SCUC models with AC power flow constraints are far more complex due to massive bilinear terms in the large-scale nonlinear power balance equations. The nonlinear power balance equations are further complicated by the discrete step control variables of shunts; (iv) N − 1 contingency analysis. The size of the model increases linearly with the number of contingencies considered, greatly increasing the size of the optimization model. Accordingly, there is an emergent need to develop a robust algorithm capable of deriving a high-quality solution in a short time and passing through contingency tests simultaneously. In this project, we explore innovative techniques to address this challenging problem by integrating advanced polyhedral theory, approximation methods, relaxation strategies, decomposition techniques, and parallel computing. Each technique approaches the problem from a different perspective, leveraging its specific strengths to tackle distinct challenges. Each individual method has demonstrated its effectiveness in the PI’s previous research. Their integration is expected to significantly reduce the computational time required to solve the proposed complex problem. Successful completion of this project has the potential to transform the industry by enhancing optimization solvers capable of handling large-scale day-ahead energy market clearing models within strict time constraints, while incorporating AC power flow constraints. This advancement will lead to reduced overall generation costs and, consequently, increased social welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Sparse matrix‐vector and matrix‐multivector products for the truncated SVD on graphics processors

Summary Many practical algorithms for numerical rank computations implement an iterative procedure that involves repeated multiplications of a vector, or a collection of vectors, with both a sparse matrix and its transpose. Unfortunately, the realization of these sparse products on current high performance libraries often deliver much lower arithmetic throughput when the matrix involved in the product is transposed. In this work, we propose a hybrid sparse matrix layout, named CSRC, that combines the flexibility of some well‐known sparse formats to offer a number of appealing properties: (1) CSRC can be obtained at low cost from the popular CSR (compressed sparse row) format; (2) CSRC has similar storage requirements as CSR; and especially, (3) the implementation of the sparse product kernels delivers high performance for both the direct product and its transposed variant on modern graphics accelerators thanks to a significant reduction of atomic operations compared to a conventional implementation based on CSR. This solution thus renders considerably higher performance when integrated into an iterative algorithm for the truncated singular value decomposition (SVD), such as the randomized SVD or, as demonstrated in the experimental results, the block Golub–Kahan–Lanczos algorithm.

Aliaga, José I.↗

Gold–Thiolate Nanocluster Dynamics and Intercluster Reactions Enabled by a Machine Learned Interatomic Potential

Monolayer protected metal clusters comprise a rich class of molecular systems and are promising candidate materials for a variety of applications. While a growing number of protected nanoclusters have been synthesized and characterized in crystalline forms, their dynamical behavior in solution, including prenucleation cluster formation, is not well understood due to limitations both in characterization and first-principles modeling techniques. Recent advancements in machine-learned interatomic potentials are rapidly enabling the study of complex interactions such as dynamical behavior and reactivity on the nanoscale. Here, we develop an Au-S-C-H atomic cluster expansion (ACE) interatomic potential for efficient and accurate molecular dynamics simulations of thiolate-protected gold nanoclusters (Au n (SCH 3 ) m ). Trained on more than 30,000 density functional theory calculations of gold nanoclusters, the interatomic potential exhibits ab initio level accuracy in energies and forces and replicates nanocluster dynamics including thermal vibration and chiral inversion. Long dynamics simulations (up to 0.1 μs time scale) reveal a mechanism explaining the thermal instability of neutral Au 25 (SR) 18 clusters. Specifically, we observe multiple stages of isomerization of the Au 25 (SR) 18 cluster, including a chiral isomer. Additionally, we simulate coalescence of two Au 25 (SR) 18 clusters and observe series of clusters where the formation mechanisms are critically mediated by ligand exchange in the form of [Au-S] n rings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Residential Façade Upgrades: Market Assessment and Recommendations

In support of DOE’s move toward transformational whole-building upgrades and enclosure solutions, the Pacific Northwest National Laboratory (PNNL) and National Renewable Energy Laboratory (NREL) are partnering and collaborating with leading building science researchers and home-performance entities to identify and characterize technical and economic barriers to façade retrofits in an effort to identify market-viable façade solutions and opportunities for an actionable plan to transform the market. The project includes partnerships with Building Science Corporation (BSC) and a combination of strategic implementation partners with home-performance and retrofit expertise and industry contacts. The project will include expert advisory and review consultation from Lawrence Berkeley National Laboratory’s (LBNL’s) Residential Windows & Attachments team and Oak Ridge National Laboratory’s Building Envelope team. The project consists of three parts: 1. a market analysis that captures the current state of the façade retrofit market and includes housing characteristics and retrofit costs, façade retrofit approaches and materials, contractor business models and workforce requirements to support advanced façade approaches; 2. an economic analysis focused on the viability of advanced façade retrofit approaches and materials; and 3. field demonstration of façade retrofits that include enhanced insulation/air-sealing and window technologies in multiple climate zones. This report represents the market analysis, as outlined in item 1 above. The goal of this analysis is to provide a techno-economic study that supports comprehensive retrofits of residential enclosures that include traditional approaches, and integrated wall assemblies and windows that result in durable, energy efficient, and marketable strategies. This study will provide a better knowledge base regarding the viable market for façade retrofit strategies, identify the barriers to uptake, analyze economic opportunities, and develop documentation specifically aimed to overcome technical and market barriers associated with installation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Simulation, Structural, Thermal and Mechanical Properties of the FeTiTaVW High Entropy Alloy

Developing new materials to be applied in extreme environments is an opportunity and a challenge for the future. High entropy alloys are new materials that seem promising approaches to work in nuclear fusion reactors. In this work, FeTaTiVW high entropy alloys were developed and characterized with Molecular Dynamic and Hybrid Molecular Dynamic Monte Carlo simulations. The simulation results show that phase separation originates a lower potential energy per atom and a high level of segregation compared to those of a uniform solid solution. Moreover, the experimental diffractogram of the milled powder shows the formation of a body-centred cubic-type structure and the presence of TiO2. In addition, the microstructure of the consolidated material evidenced three phases: W-rich, Ti-rich, and a phase with all the elements. This phase separation observed in the microstructure agrees with the Hybrid Molecular Dynamic Monte Carlo simulation. Moreover, the consolidated material’s thermal conductivity and specific heat are almost constant from 25 °C to 1000 °C, and linear expansion increases with increasing temperature. On the other hand, specific heat and thermal expansion values are in between CuCrZr and W values (materials chosen for the reactor walls). The FeTaTiVW high entropy alloy evidences a ductile behaviour at 1000 °C. Therefore, the promising thermal properties of this system can be attributed to the multiple phases and systems with different compositions of the same elements, which is exciting for future developments.

Martins, Ricardo (ORCID:0000000177685704)↗

CRITICAL MINERAL RESOURCE ASSESSMENT OF COALS FROM THE POWDER RIVER BASIN, WYOMING, USA

Coal and associated sediments are potential sources of Rare Earth Elements (REE) and other critical minerals necessary for many consumer and defense-related products and development of energy technologies. For this study, 15 samples were sourced from Dry Fork Mine within the Powder River Basin near Gillette, Wyoming, to determine REE content along with select transition metals (t-metals) of interest in non-combusted coals and associated sediments. An excavator collected samples along a mine highwall, within benched intervals representing a foot to a few feet of coal strata. Homogenized sample subsets were crushed in an aluminum-ceramic vial, then passed through a 106-micron sieve. Sieved samples were pyrolyzed by a LECO TGA-108, which concurrently measured sample moisture, volatile, and ash content. Residual ash was then fused into a glass bead with lithium metaborate at a 6:1 Li-metaborate to sample ratio and then dissolved in 20% nitric acid. The nitric acid solutions containing digested beads were then diluted and passed through a 0.45 micron syringe filter. Filtered samples were analyzed by ICP-MS for REE and select t-metals. Reagent blanks were analyzed to assess for any potential contamination. Total REE plus Y (REE+Y) concentrations across the 15 samples range from 52 ppm to 1015 ppm with an average of 477 ppm on a dry ash basis. When normalized to upper continental crust (UCC; Taylor and McLennan, 1985) values, 13 of the 15 samples show average enrichment factors (EF) for REE+Y greater than 1. EF values indicate M-type enrichment (Sm through Er), as opposed to distinct preferential enrichment of light or heavy REE. T-metals with the highest average concentrations are V, Cu, Ni, and Zr at 215, 243, 123, and 118 ppm, respectively. Multiple t-metals had EF>1; however, Cu, Ge, and Sb have the highest average EF relative to UCC for t-metals, at 9.7, 8.0, and 17.0, respectively.

Copeland, Grant↗

Thread Batching for High-performance Energy-efficient GPU Memory Design

Massive multi-threading in GPU imposes tremendous pressure on memory subsystems. Due to rapid growth in thread-level parallelism of GPU and slowly improved peak memory bandwidth, memory becomes a bottleneck of GPU’s performance and energy efficiency. In this article, we propose an integrated architectural scheme to optimize the memory accesses and therefore boost the performance and energy efficiency of GPU. First, we propose a thread batch enabled memory partitioning (TEMP) to improve GPU memory access parallelism. In particular, TEMP groups multiple thread blocks that share the same set of pages into a thread batch and applies a page coloring mechanism to bound each stream multiprocessor (SM) to the dedicated memory banks. After that, TEMP dispatches the thread batch to an SM to ensure high-parallel memory-access streaming from the different thread blocks. Second, a thread batch-aware scheduling (TBAS) scheme is introduced to improve the GPU memory access locality and to reduce the contention on memory controllers and interconnection networks. Experimental results show that the integration of TEMP and TBAS can achieve up to 10.3% performance improvement and 11.3% DRAM energy reduction across diverse GPU applications. We also evaluate the performance interference of the mixed CPU+GPU workloads when they are run on a heterogeneous system that employs our proposed schemes. Our results show that a simple solution can effectively ensure the efficient execution of both GPU and CPU applications.

Computer Science↗