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At least 379 records · Page 21

Evaluation of Nickel Alloys, Manufactured through Powder Bed Fusion, for Application for Advanced Nuclear Reactors

In collaboration with other laboratories, Idaho National Laboratory has investigated additively manufactured alloys for applications in advanced nuclear reactors. The primary focus has been on nickel alloys, as well as “other” alloys, which are alloys not considered steel nor nickel-based alloys, manufactured by laser powder bed fusion. Suitability of investigated alloys were considered against a matrix of properties of interest, developed jointly with the collaborating laboratories. For the nickel alloys, Alloys 282 and 625 are considered promising due to their properties, existing data, and availability of commercial powder feedstock. Haynes 244 is also of interest for its molten salt corrosion resistance, however there is no current feedstock supply chain, and no experience with this alloy as an additively manufactured material. Iron-chrome-aluminum alloys, titanium alloys, zirconium alloys, ceramics, and ceramic inclusions were all considered within the other alloys category. The results and discussions within this report will be compiled with the investigations from the other collaborating laboratories and compiled into a final report later this year (2023).

36 MATERIALS SCIENCE↗

SCA Tools - SCRM Value Add or Lossy Noise Machines

Software supply chain risk management (SCRM) depends upon accurate information regarding the software components that comprise any given software system. The collection of components included in a software package can be organized within a software bill of materials, or SBOM. SBOMs are ideally generated when the software components are put together, such as at compile time, but for many reasons that has not and is not always possible. For example, legacy or proprietary software packages often do not have SBOMs available to downstream consumers of that software. It’s not just end users that are affected, manufacturers themselves also must deal with this problem. To answer these questions, the market has seen the rise of several commercial software composition analysis (SCA) tools. These tools aim to peer into completed software systems, automatically identifying hidden software dependencies and looking up known vulnerabilities associated with those dependencies to enable end-users to enhance their cyber supply chain risk management processes. These tools are potentially a huge boon to end users of legacy and proprietary software – and a potential bane, depending on how accurate they are. This research asks that question – how accurate are currently available binary SCA tools – and provides answers to several other questions: What does it mean to be “accurate”? What limitations do the tools have in identifying common edge cases that take place in modern software development? Can they help you avoid a devastating supply chain attack, or is it all just noise? After researching SCA tools on the market, we identified three vendors that fit our use case and would provide analysis on compiled binaries. Using these tools, we submitted firmware for critical infrastructure devices for analysis and SBOM generation. The SBOM outputs were then cross referenced with SBOMs generated through manual analysis for comparison. In addition to the firmware samples, we also submitted edge case samples based off a popular open-source library that were specifically crafted to evaluate each tools’ ability to accurately identify components. These samples were customized to be consistent with modifications we have seen in modern software development as well as a couple that are representative of supply chain attacks.

97 MATHEMATICS AND COMPUTING↗

Evaluating Liquid Waste Transfers and their Impacts to the SRS Tank Farm to Support Operations and Closure

The Liquid Waste (LW) contractor at the Savannah River Site, Savannah River Mission Completion (SRMC), supports the storage, processing, and safe disposition of legacy, radioactive liquid waste. The LW Tank Farms contain approximately 127 million liters (33.5 million gallons) of liquid waste within 43 active, underground waste tanks. To meet mission critical milestones for the closure of waste tanks and processing of 34 million liters (9 million gallons) of salt waste per year by the LW Salt Waste Processing Facility (SWPF), an increase in Tank Farm operations, including waste tank transfers, is required. Waste is compiled in salt and sludge batches in the Tank Farms and transferred to SWPF and the Defense Waste Processing Facility (DWPF) for treatment. All waste tank transfers, such as waste removal and batch compilation transfers, must be pre-evaluated to ensure Documented Safety Analysis (DSA) requirements are met via Evaluated Transfer Approval Forms (ETAFs). Facility conditions and configurations may change as a result of a waste transfer. These changes must be reflected in the Tank Farms Emergency Response Datasheet (ERD), which contains data utilized for operation and emergency situations.

Peterson, Shelby R.↗

Universal Jaynes-Cummings Control of an Oscillator

The Jaynes-Cummings (JC) interaction-the coherent exchange of excitations between a two-level system and a harmonic oscillator-is one of the fundamental interactions of quantum optics, realized across platforms such as cavity quantum electrodynamics, trapped ions, mechanical resonators, and superconducting circuits. Although JC interactions and qubit rotations form a universal gate set for oscillator control, practical implementations have not been demonstrated. Here we develop and experimentally demonstrate universal JC-based oscillator control by compiling arbitrary unitary gates into sequences of JC interactions and qubit rotations. In our experiment, the oscillator is realized using a mode of a high quality factor microwave cavity and the ancilla qubit using a superconducting transmon circuit, with the JC interaction implemented by a sideband interaction enabled by the Josephson nonlinearity. The native gates are constructed to be closed below a chosen cutoff photon number, encoding a qudit with suppressed leakage errors, while ancilla relaxation errors are detectable. We further find that the dispersive shift serves as a compilation resource that reduces circuit depths. We demonstrate universal qudit control and implement a single-qutrit gate set with a mean post-selected process fidelity of 96%, as well as ququart and ququint shift gates. These results establish Jaynes-Cummings control as a practical route to universal oscillator control, enabling programmable bosonic processors across a variety of quantum platforms.

Huang, Jordan [Rutgers U., Piscataway]↗

Optimization with the OpenACC-to-FPGA framework on the Arria 10 and Stratix 10 FPGAs

The reconfigurable computing paradigm with field programmable gate arrays (FPGAs) has received renewed interest in the high-performance computing field due to FPGAs’ unique combination of performance and energy efficiency. However, difficulties in programming and optimizing FPGAs have prevented them from being widely accepted as general-purpose computing devices. In accelerator-based heterogeneous computing, portability across diverse heterogeneous devices is also an important issue, but the unique architectural features in FPGAs make this difficult to achieve. To address these issues, a directive-based, high-level FPGA programming and optimization framework was previously developed. In this work, developed optimizations were combined holistically using the directive-based approach to show that each individual benchmark requires a unique set of optimizations to maximize performance. We perform this exploration on Intel Arria 10 and Stratix 10 FPGAs. We also explored the relationships between performance, resource usages, and compilation times, and investigated implications for performance portability. Finally, we present an initial evaluation of a real-world proxy application, LULESH.

97 MATHEMATICS AND COMPUTING↗

Towards Ultra-high-resolution E3SM Land Modeling on Exascale Computers

Here we present an ultra-high-resolution E3SM land model (uELM) for high-fidelity land simulations targeting new Exascale computers. After considering modeling infrastructure compatibility and ELM software features, we designed a parallel model for the uELM development targeting hybrid architectures of new US Exascale computers. We also described a function unit test framework to expedite the piece-wise code porting (with compiler directives), verification, and global variable management. Furthermore, in this study, we report an early uELM model development using OpenACC within a function unit test framework on a pre-Exascale computer, demonstrate the performance of a uLEM submodel with a 3.0-time speedup, and summarize the code porting experience regarding global variable handling, deepcopy, memory reduction, and parallel loop reconstruction.

97 MATHEMATICS AND COMPUTING↗

Automatic Code Generation for High-Performance Graph Algorithms

Graph problems are common across fields of scientific computing and social sciences. However, despite their importance, implementing graph algorithms effectively on modern computing systems is a challenging task that requires significant programming effort and generally results in customized implementations. Current computing and memory hierarchies are not architected for irregular computations resulting in challenges for graph algorithms to achieve high performance on those architectures. In this paper, we present GraphX, a novel compiler framework and DSL designed to simplify the development of efficient graph algorithms and achieve high performance on modern computing systems. GraphX consists of a DSL for efficient implementation of graph algorithms, various optimizations, such as support for sparse linear algebra and workspace transformations, optimized graph primitives, including semiring and masking, and a high-performance code generation engine. Using GraphX, users can implement graph algorithms using a semantically-rich language with graph-oriented operators. GraphX uses these semantics to automatically generate efficient code for target architectures, increasing performance and portability across architectures. The composable nature of GraphX makes it possible to extend the set of optimizations and architectures without modifying the source code. We demonstrate GraphX outperforms state-of-the-art graph libraries, such as LAGraph, up to $3.7 speedup in semiring operations, $2.19 speedup in an important sparse computational kernel, and $9.05 speedup in graph processing algorithms.

compiler, graph algorithms, semiring, masking, wor↗

Numerical gate synthesis for quantum heuristics on bosonic quantum processors

There is a recent surge of interest and insights regarding the interplay of quantum optimal control and variational quantum algorithms. We study the framework in the context of qudits which are, for instance, definable as controllable electromagnetic modes of a superconducting cavity system coupled to a transmon. By employing recent quantum optimal control approaches described in (Petersson and Garcia, 2021), we showcase control of single-qudit operations up to eight states, and two-qutrit operations, mapped respectively onto a single mode and two modes of the resonator. We discuss the results of numerical pulse engineering on the closed system for parametrized gates useful to implement Quantum Approximate Optimization Algorithm (QAOA) for qudits. The results show that high fidelity ( > 0.99) is achievable with sufficient computational effort for most cases under study, and extensions to multiple modes and open, noisy systems are possible. The tailored pulses can be stored and used as calibrated primitives for a future compiler in circuit quantum electrodynamics (cQED) systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A decade of curtailment studies demonstrates a consistent and effective strategy to reduce bat fatalities at wind turbines in North America

Abstract There is a rapid, global push for wind energy installation. However, large numbers of bats are killed by turbines each year, raising concerns about the impacts of wind energy expansion on bat populations. Preventing turbine blades from spinning at low wind speeds, referred to as curtailment, is a method to reduce bat fatalities, but drawing consistent inference across studies has been challenging. We compiled publicly available studies that evaluated curtailment at six wind energy facilities in North America across 10 years. We used meta‐regression of 29 implemented treatments to determine fatality reduction efficacy as well as sources of variation influencing efficacy. We also estimated species‐specific fatality reduction for three species that comprise most fatalities in North America: hoary bat ( Lasiurus cinereus ), eastern red bat ( Lasiurus borealis ) and silver‐haired bat ( Lasionycteris noctivagans ). We found that curtailment reduced total bat fatalities by 33% with every 1.0 ms −1 increase in curtailment wind speed. Estimates of the efficacy for the three target species were similar (hoary bats: 28% per ms −1 , 95% CI: 0.4%–48%, eastern red bats: 32% per ms −1 , 95% CI: 13%–47% and silver‐haired bats: 32% per ms −1 , 95% CI: 3%–53%). Across multiple facilities and years, a 5.0 ms −1 cut‐in speed was estimated to reduce total bat fatalities by an average of 62% (95% CI: 54%–69%). Mortality reductions at individual facilities in any given year were estimated to fall between 33%–79% (95% prediction interval). Inter‐annual differences rather than inter‐site or turbine characteristics accounted for most of the variation in efficacy rates. Species‐specific average mortality reduction at 5.0 ms −1 curtailment wind speed was 48% (95% CI: 24%–64%) for hoary bats, 61% (95% CI: 42%–74%) for eastern red bats and 52% (95% CI: 30%–66%) for silver‐haired bats. Practical implication . curtailment reduced bat mortality at wind turbines in this North American study. Efficacy increased proportionally as curtailment speed is raised, and patterns and rates of efficacy were similar across species. This indicates that curtailment is an effective strategy to reduce bat fatalities at wind energy facilities, but exploration of further refinements could both minimize bat mortality and maximize energy production.

17 WIND ENERGY↗

Research Progress and Perspectives on Pre‐Sodiation Strategies for Sodium‐Ion Batteries

Sodium‐ion batteries (SIBs) with abundant elements have garnered significant attention from researches as a promise compensation to lithium‐ion batteries (LIBs). However, the large‐scale commercial application of SIBs is partially hindered by the limited initial coulombic efficiency (ICE) due to the irreversible formation of solid electrolyte interphase (SEI) and intercalation into the defects in the anode. Similar to pre‐lithiation techniques, pre‐sodiation approaches are considered to be one of the most direct and effective way to compensate for the loss of active sodium at the anode side of SIBs during the initial cycle. In this context, additional sodium ions are pre‐injected to the cathode/anode material by chemical/electrochemical methods, aiming to improve battery span life and energy density. Here, this review delves into the necessity and impact of pre‐sodiation techniques, compiling the latest research progress, for instance, self‐sacrificing cathode additives, over‐sodiated cathode materials, direct contact and solution chemical pre‐sodiation. Notably, the research mechanisms underlying solution chemical pre‐sodiation are highlighted. This comprehensive overview aims to foster a deeper understanding of the pre‐sodiation techniques and expects to provide guidance for realizing the commercial application of high energy density sodium‐ion batteries.

25 ENERGY STORAGE↗

Large–Scale Syntheses of 2D Materials: Flash Joule Heating and Other Methods

In the past 17 years, the larger-scale production of graphene and graphene family materials has proven difficult and costly, thus slowing wider-scale commercial applications. Here, the quality of the graphene that is prepared on larger scales has often been poor, demonstrating a need for improved quality controls. Here, current industrial graphene synthetic and analytical methods, as well as recent academic advancements in larger-scale or sustainable synthesis of graphene, defined here as weights more than 200 mg or films larger than 200 cm 2 , are compiled and reviewed. There is a specific emphasis on recent research in the use of flash Joule heating as a rapid, efficient, and scalable method to produce graphene and other 2D nanomaterials. Reactor design, synthetic strategies, safety considerations, feedstock selection, Raman spectroscopy, and future outlooks for flash Joule heating syntheses are presented. To conclude, the remaining challenges and opportunities in the larger-scale synthesis of graphene and a perspective on the broader use of flash Joule heating for larger-scale 2D materials synthesis are discussed.

01 COAL, LIGNITE, AND PEAT↗

Achieving Stable Molybdenum Oxide Cathodes for Aqueous Zinc-Ion Batteries in Water-in-Salt Electrolyte

A layered MoO 3 material with large interlayer spacing represents a promising cathode for aqueous rechargeable Zn-ion batteries (ARZIBs), but the implementation of this material is limited due to the intrinsically low conductivity and poor structural stability. A 30 m ZnCl 2 water-in-salt electrolyte (WISE) was introduced to a MoO 3 nanobelt cathode for the first time, significantly increasing the stability of MoO 3 cathodes compared to those in 3 M ZnSO 4 and 3 M ZnCl2 electrolyte. The Zn/MoO 3 cell in WISE unambiguously demonstrated significantly improved rate performance delivering 349, 253, and 222 mAh/g at 100, 500, and 1000 mA/g, denoting a 2×, and 12× capacity increase of those achieved in 3 M electrolytes at 500 and 1000 mA/g, respectively. A capacity retention rate of 73% was achieved after (dis)charging at 100 mA/g for 100 cycles, and no obvious capacity fading was observed at higher current densities of 500 mA/g and 2A/g. A compilation of structural and morphological characterization was systematically performed to provide insight into the mechanisms of the improved performance in ZnCl 2 WISE for the MoO3 cathode materials. Specifically, our data collectively suggested that the drastic fading in 3M electrolytes can be attributed to the parasitic surface deposits on Zn originated from Mo dissolution and H 2 formation due to Zn corrosion and hydrogen evolution reaction (HER), which were significantly suppressed in the ZnCl 2 WISE. The direct visualization of these side reactions was achieved for the first time in the Zn-MoO 3 system, using an in situ optoelectrochemical measurement.

25 ENERGY STORAGE↗

X-Ray and Electron Spectroscopy of the CdS/(Ag,Cu)(In,Ga)Se 2 Interface With RbF Treatment

The chemical and electronic structure of the CdS/(Ag,Cu)(In,Ga)Se 2 (CdS/ACIGSe) interface for thin-film solar cells, involving an absorber with a bulk [Ag]/([Ag]+[Cu]) (AAC) ratio of 0.06, a state-of-the-art RbF post-deposition treatment (PDT), and a chemical-bath deposited CdS buffer layer, is studied. To gain a detailed and depth-resolved picture of the CdS/ACIGSe interface, synchrotron- and laboratory-based hard X-ray, soft X-ray, and UV photoelectron spectroscopy, inverse photoemission spectroscopy, and X-ray emission spectroscopy are combined. Compared to the bulk of the absorber, a Cu- and Ga-poor ACIGSe surface is found, with a slightly increased AAC ratio. Strong evidence of a Rb–In–Se species (possibly with some Ag) at the absorber surface is compiled, with a corresponding band gap of 2.79 ± 0.12 eV. This finding is in clear contrast to comparable Ag-free Cu(In,Ga)Se 2 absorbers with RbF-PDT. The Rb–In–Se surface species is not removed by the (wet-chemical) CdS deposition process, while some Se diffuses into the CdS layer and segregates at its surface. The CdS buffer layer shows a band gap of 2.48 ± 0.12 eV, and a cliff (≈ -0.4 eV) is determined in the conduction band alignment at the interface between the Rb–In–Se species and the CdS buffer.

36 MATERIALS SCIENCE↗

Device Performance of Emerging Photovoltaic Materials (Version 1)

Abstract Emerging photovoltaics (PVs) focus on a variety of applications complementing large scale electricity generation. Organic, dye‐sensitized, and some perovskite solar cells are considered in building integration, greenhouses, wearable, and indoor applications, thereby motivating research on flexible, transparent, semitransparent, and multi‐junction PVs. Nevertheless, it can be very time consuming to find or develop an up‐to‐date overview of the state‐of‐the‐art performance for these systems and applications. Two important resources for recording research cells efficiencies are the National Renewable Energy Laboratory chart and the efficiency tables compiled biannually by Martin Green and colleagues. Both publications provide an effective coverage over the established technologies, bridging research and industry. An alternative approach is proposed here summarizing the best reports in the diverse research subjects for emerging PVs. Best performance parameters are provided as a function of the photovoltaic bandgap energy for each technology and application, and are put into perspective using, e.g., the Shockley–Queisser limit. In all cases, the reported data correspond to published and/or properly described certified results, with enough details provided for prospective data reproduction. Additionally, the stability test energy yield is included as an analysis parameter among state‐of‐the‐art emerging PVs.

36 MATERIALS SCIENCE↗

Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data

Understanding rare‐earth element (REE) mineralization mechanisms is essential for developing efficient separation strategies. Although the geochemical pathways that generate REE deposits are qualitatively known, quantitative links between specific conditions and mineralization outcomes remain limited. Herein, the repurpose laboratory REE hydrothermal synthesis data—originally collected for functional‐materials fabrication—as a surrogate for studying mineralization with data‐driven methods. The compiled 1,200+ hydrothermal reaction records and trained three machine‐learning models—K‐nearest neighbors (KNN), random forest (RF), and extreme gradient boosting (XGB)—to predict product elements and phases from precursors, additives, reaction conditions, and engineered features. Validation shows XGB achieves the highest accuracy. Feature importance indicates thermodynamic properties of cations and anions dominate model decisions. Correlations reveal positive relationships among precursor concentration, reaction time, pH, and temperature, consistent with classical crystallization behavior. XGB‐based regressors are built to predict crystallization temperature and pH from precursor/product attributes. Performance is strongest when similar training examples exist, while accuracy declines for underrepresented reactions, notably REE carbonates and heavy‐REE systems. Overall, the study shows that functional‐materials datasets can illuminate REE mineralization and provide priors for exploration and processing. Expanding datasets with less‐studied chemistries and conditions will improve generality and support deposit discovery and more efficient REE recovery.

feature importance analysis↗

Root anatomy helps to reconcile observed root trait syndromes in tropical tree species

Premise Studying the organization of functional traits in plant leaves and stems has revealed notable patterns linking function and form; however, evidence of similarly robust organization in root tissues remains controversial. We posit that anatomical traits in roots can provide insight on the overall organization of the root system. We hypothesized that size variation in the tissue outside the stele is related in a nonlinear fashion with functional traits associated with direct resource uptake, including a negative relationship with root architectural traits, and that similar relationships detected in tropical areas also hold true in other biomes. Methods We addressed our hypotheses using empirical data from 24 tropical tree species in French Guiana, including anatomical measurements in first order roots and functional trait description for the entire fine root system. In addition, we compiled a global meta‐analysis of root traits for 500+ forest species across tropical, subtropical, and temperate forests. Results Our results supported the expected nonlinear relationships between cortical size and morphological traits and a negative linear trend with architectural traits. We confirmed a global negative relationship among specific root length (SRL), diameter, and tissue density, suggesting similar anatomical constraints in root systems across woody plants. However, the importance of factors varies across biomes, possibly related to the unequal phylogenetic representation across latitudes. Conclusions Our findings imply that the rhizocentric hypothesis can be a valuable approach to understand fine root trait syndromes and the evolution of absorptive roots in vascular plants.

Valverde‐Barrantes, Oscar J.↗

Refining T c Prediction in Hydrides via Symbolic‐Regression‐Enhanced Electron‐Localization‐Function‐Based Descriptors

Hydrogen‐based materials are able to possess extremely high superconducting critical temperatures, T c s , due to hydrogen's low atomic mass and strong electron–phonon interaction. Recently, a descriptor based on the Electron Localization Function (ELF) has enabled the rapid estimation of the T c of hydrogen‐containing compounds from electronic networking properties, but its applicability has been limited by the small size and homogeneity of the training dataset used. Herein, the model is re‐examined, compiling a publicly available combined dataset of 244 binary and ternary hydride superconductors. The analysis shows that though ELF‐based networking remains a valuable descriptor, its predictive power declines with increasing compositional complexity. However, by introducing the molecularity index, defined as the highest value of the ELF at which two hydrogen atoms connect, and applying symbolic regression, the accuracy of the predictions can be substantially enhanced. These results establish a more robust framework for assessing superconductivity in hydride materials, facilitating accelerated screening of novel candidates through integration with crystal structure prediction methods or high‐throughput searches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Material Changes in Electrocatalysis: An In Situ/Operando Focus on the Dynamics of Cobalt‐Based Oxygen Reduction and Evolution Catalysts

Abstract The shift towards cheaper, non‐platinum group metal electrocatalyst materials for clean energy technologies is coupled with challenges in maintaining long‐term performance. For practical purposes, electrocatalytic stability typically focuses on catalyst electrochemical performance over time. However, a deeper understanding of catalyst material property changes during operation is needed to enable material‐specific design strategies for long‐term stabilization. In the last several decades, improvements in material characterization techniques have made it possible to probe the composition, structure, and degradation products of catalysts in situ/operando. Herein we review the current understanding of in situ/operando material stability of Co‐based electrocatalysts for the oxygen evolution (OER) and reduction reactions (ORR) in acidic and alkaline environments. We focus on in situ/operando materials characterization of three categories of Co‐based OER/ORR catalysts: oxides and (oxy)hydroxides, mixed‐metal catalysts, and non‐oxide materials. This review aims to compile and compare the results from multiple studies and techniques to provide insight into the role that the starting material, pH, and applied potential have on the active surface and stability of Co‐based materials. We conclude by highlighting directions that have been underexplored with opportunities for continued research including improving in situ/operando characterization, methods to probe long‐term material changes, and the development of operando studies on full‐scale devices. Using Co‐based materials as a case study, this review shows the vital role that in situ/operando characterization must play in the future of improving electrocatalyst stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗