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At least 235 records · Page 13

ParChain: a framework for parallel hierarchical agglomerative clustering using nearest-neighbor chain

This paper studies the hierarchical clustering problem, where the goal is to produce a dendrogram that represents clusters at varying scales of a data set. We propose the ParChain framework for designing parallel hierarchical agglomerative clustering (HAC) algorithms, and using the framework we obtain novel parallel algorithms for the complete linkage, average linkage, and Ward's linkage criteria. Compared to most previous parallel HAC algorithms, which require quadratic memory, our new algorithms require only linear memory, and are scalable to large data sets. ParChain is based on our parallelization of the nearest-neighbor chain algorithm, and enables multiple clusters to be merged on every round. We introduce two key optimizations that are critical for efficiency: a range query optimization that reduces the number of distance computations required when finding nearest neighbors of clusters, and a caching optimization that stores a subset of previously computed distances, which are likely to be reused. Experimentally, we show that our highly-optimized implementations using 48 cores with two-way hyper-threading achieve 5.8--110.1x speedup over state-of-the-art parallel HAC algorithms and achieve 13.75--54.23x self-relative speedup. Compared to state-of-the-art algorithms, our algorithms require up to 237.3x less space. Our algorithms are able to scale to data set sizes with tens of millions of points, which existing algorithms are not able to handle.

Computer Science↗

PVDeg: Enhancing Usability and AI-Driven Multi-Mechanism Degradation Modeling

PVDeg version 0.7.0, released in December 2025, introduced major enhancements to improve usability and performance. This update reorganized tutorials and tool notebooks to create a more intuitive experience, enabling users to easily follow and adapt workflows for their specific analyses. In addition to structural improvements, both the notebooks and core logic underwent significant optimization for efficiency, robustness, and style. These refinements were supported by new testing frameworks built on nbval and pytest, adherence to PEP8 standards, and extensive code refactoring, which collectively simplify onboarding for new developers. Looking ahead, version 0.8.0 will deliver advanced AI-driven capabilities. The primary focus is to further develop and automate the degradation workflow, designed to analyze PV module degradation across diverse locations and system configurations. By integrating large language models (LLMs) to scan literature and compile a comprehensive database of materials and degradation rates, this feature will enable modeling of multiple materials and mechanisms within a single, streamlined workflow. Users will be able to evaluate degradation impacts on different system architectures under varying environmental conditions, facilitating informed decisions on bill-of-materials optimization for specific deployment scenarios. These advancements position PVDeg as a powerful, user-friendly tool for accelerating PV reliability research and system design.

14 SOLAR ENERGY↗

F3D Image Processing and Analysis for Many - and Multi-core Platforms

F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expedites any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a "descendent" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.

Source record↗

A BWR Fuel Assembly Concept with Partial Segregation of Fertile Material

Small modular reactors (SMRs) have been a hot topic in recent years due to their own set of advantages over conventional large light water reactors (LWRs). One of the driving forces for SMR development is the significant reduction in the up-front cost and enhanced inherent safety features. The reduced safety concerns are attributed to two main aspects, decay heat and source term. By taking the advantages of the two-phase flow driving head, which allows a much smaller and simpler reactor pressure vessel compared to the integral PWRs, a 50 MWe BWR-based SMR called the Novel Modular Reactor (NMR-50) is currently being developed at Purdue University. For this NMR-50, an optimized long-life core design was developed, which achieves a 10.2-year cycle length under current industrial practices and constraints. Due to the reduced operating power density, however, it was evident that there is a significant room to increase the fuel linear power. Therefore, core designs of partial segregation of fertile material within a fuel assembly (FA) were investigated to extend the fuel cycle length further. A heterogeneous fertile material loading (HFL) within a fuel assembly was developed based on the existing industry UO{sub 2} once-through fuel cycle option for the purpose of near-term deployment and maximum retrofitability. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Perfect narrow-band absorber based on a monolayer of metallodielectric microspheres

We have studied how two-dimensional arrays of metallodielectric core-shell microspheres on a metal substrate can efficiently absorb infrared electromagnetic radiation in a narrow wavelength range under normal incidence. Our simulations indicate that perfect absorption efficiencies can be achieved for resonance wavelengths. The influence of core-shell microspheres geometry and lattice geometry is studied on absorption properties. For wavelength from 1.2 μm to 2.6 μm, an optimal combination of sphere and core radius was obtained to provide perfect absorption which can be wavelength adjusted.

36 MATERIALS SCIENCE↗

Optimization study of B4C filter thickness for shifting to fast spectrum at experimental position in NRAD core

The Japan Atomic Energy Agency (JAEA) has investigated an accelerator-driven system (ADS) to transmute minor actinides (MAs) partitioned from the high level waste. In the nuclear transmutation system such as the ADS, the nuclear data validation of MA is required to reduce the uncertainty caused by the nuclear data of MA. In order to validate the nuclear data, many independent experimental data need to be mutually compared. The Idaho National Laboratory (INL) considers the measurement of fission rate ratio and sample worth with a wide spectral indices by inserting several types of thermal neutron shielding filters in the experimental position in Neutron RADiography (NRAD) which is the thermal neutron reactor. The JAEA has a plan to perform integral experiments with fission chambers in the NRAD because of the expansion of the experimental data contributing to nuclear data validation of MA. In this study, the optimization of the NRAD core configuration, the B4C filter thickness, and the experimental position design was conducted to acquire the high-accuracy and the beneficial experimental data by using MCNP 6.1 and ENDF/B-VII.1. First, by locating the experimental position as close to the center of the core as possible and concentrating the fuel around that position, the neutron flux of the optimized model could be constructed 2.5 times as much as that of the previous model. Second, the optimized B4C filter thickness was determined to be 3mm based on the comprehensive evaluation from the viewpoints of the shielding ability of low energy neutrons, the level of the total neutron flux, and the influence of fabrication accuracy of the B4C filter. Third, we constructed the experimental position model that could further reduce the influence of the low energy neutrons by adopting the aluminum dry box and the bottom filter. Moreover, the neutron energy spectrum of the tentative optimized model constructed by following the above results was compared with that of the fast neutron reactors such as the ADS and the Fast Critical Assembly (FCA). As a result, the tentative optimized model would be able to be obtained the beneficial experimental data for the verification of FCA-IX series data and the validation of MA nuclear data for accuracy improvement of ADS design. Furthermore, the adoption of the tentative optimized model would be acquired the experimental data such as fission reaction rate and sample worth with the wider spectral indices than the previous one because the tentative optimized model would be able to increase the ratio of the fast neutrons by almost completely eliminating the effect of the thermal neutrons.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Prospective estimation of organ dose in CT under tube current modulation

Purpose: Computed tomography (CT) has been widely used worldwide as a tool for medical diagnosis and imaging. However, despite its significant clinical benefits, CT radiation dose at the population level has become a subject of public attention and concern. In this light, optimizing radiation dose has become a core responsibility for the CT community. As a fundamental step to manage and optimize dose, it may be beneficial to have accurate and prospective knowledge about the radiation dose for an individual patient. In this study, the authors developed a framework to prospectively estimate organ dose for chest and abdominopelvic CT exams under tube current modulation (TCM). Methods: The organ dose is mainly dependent on two key factors: patient anatomy and irradiation field. A prediction process was developed to accurately model both factors. To model the anatomical diversity and complexity in the patient population, the authors used a previously developed library of computational phantoms with broad distributions of sizes, ages, and genders. A selected clinical patient, represented by a computational phantom in the study, was optimally matched with another computational phantom in the library to obtain a representation of the patient’s anatomy. To model the irradiation field, a previously validated Monte Carlo program was used to model CT scanner systems. The tube current profiles were modeled using a ray-tracing program as previously reported that theoretically emulated the variability of modulation profiles from major CT machine manufacturers Li et al., [Phys. Med. Biol. 59, 4525–4548 (2014)]. The prediction of organ dose was achieved using the following process: (1) CTDI{sub vol}-normalized-organ dose coefficients (h{sub organ}) for fixed tube current were first estimated as the prediction basis for the computational phantoms; (2) each computation phantom, regarded as a clinical patient, was optimally matched with one computational phantom in the library; (3) to account for the effect of the TCM scheme, a weighted organ-specific CTDI{sub vol} [denoted as (CTDI{sub vol}){sub organ,weighted}] was computed for each organ based on the TCM profile and the anatomy of the “matched” phantom; (4) the organ dose was predicted by multiplying the weighted organ-specific CTDI{sub vol} with the organ dose coefficients (h{sub organ}). To quantify the prediction accuracy, each predicted organ dose was compared with the corresponding organ dose simulated from the Monte Carlo program with the TCM profile explicitly modeled. Results: The predicted organ dose showed good agreements with the simulated organ dose across all organs and modulation profiles. The average percentage error in organ dose estimation was generally within 20% across all organs and modulation profiles, except for organs located in the pelvic and shoulder regions. For an average CTDI{sub vol} of a CT exam of 10 mGy, the average error at full modulation strength (α = 1) across all organs was 0.91 mGy for chest exams, and 0.82 mGy for abdominopelvic exams. Conclusions: This study developed a quantitative model to predict organ dose for clinical chest and abdominopelvic scans. Such information may aid in the design of optimized CT protocols in relation to a targeted level of image quality.

60 APPLIED LIFE SCIENCES↗

Fuel and Core Design Options to Overcome the Heavy Metal Loading Limit and Improve Performance and Safety of Liquid Salt Cooled Reactors

The research performed in this project addressed the issue of low heavy metal loading and the resulting reduced cycle length with increased refueling frequency, inherent to all FHR designs with solid, non-movable fuel based on TRISO particles. Studies performed here focused on AHTR type of reactor design with plate (“plank”) fuel. Proposal to FY12 NEUP entitled “Fuel and Core Design Options to Overcome the Heavy Metal Loading Limit and Improve Performance and Safety of Liquid Salt Cooled Reactors” was selected for award, and the 3-year project started in August 2012. A 4-month NCE was granted and the project completed on December 31, 2015. The project was performed by Georgia Tech (Prof. Bojan Petrovic, PI) and University of Tennessee (Prof. Ivan Maldonado, Co-PI), with a total funding of $758,000 over 3 years. In addition to two Co-PIs, the project directly engaged 6 graduate students (at doctoral or MS level) and 2 postdoctoral researchers. Additionally, through senior design projects and graduate advanced design projects, another 23 undergraduate and 12 graduate students were exposed to and trained in the salt reactor technology. We see this as one of the important indicators of the project’s success and effectiveness. In the process, 1 journal article was published (with 3 journal articles in preparation), together with 8 peer-reviewed full conference papers, 8 peer-reviewed extended abstracts, as well as 1 doctoral dissertation and 2 master theses. The work included both development of models and methodologies needed to adequately analyze this type of reactor, fuel, and its fuel cycle, as well as extensive analyses and optimization of the fuel and core design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Quantum Optimization: Potential, Challenges, and the Path Forward

Recent advances in quantum computers are demonstrating the ability to solve problems at a scale beyond brute force classical simulation. As such, a widespread interest in quantum algorithms has developed in many areas, with optimization being one of the most pronounced domains. Across computer science and physics, there are a number of algorithmic approaches, often with little linkage. This is further complicated by the fragmented nature of the field of mathematical optimization, where major classes of optimization problems, such as combinatorial optimization, convex optimization, non-convex optimization, and stochastic extensions, have devoted communities. With these aspects in mind, this work draws on multiple approaches to study quantum optimization. Provably exact versus heuristic settings are first explained using computational complexity theory — highlighting where quantum advantage is possible in each context. Then, the core building blocks for quantum optimization algorithms are outlined to subsequently define prominent problem classes and identify key open questions that, if answered, will advance the field. The effects of scaling relevant problems on noisy quantum devices are also outlined in detail, alongside meaningful benchmarking problems. We underscore the importance of benchmarking by proposing clear metrics to conduct appropriate comparisons with classical optimization techniques. Lastly, we highlight two domains – finance and sustainability – as rich sources of optimization problems that could be used to benchmark, and eventually validate, the potential real-world impact of quantum optimization.

97 MATHEMATICS AND COMPUTING↗

Experiments to Measure the Effect of Tantalum on Critical Systems

Sandia National Laboratories (SNL) and Oak Ridge National Laboratory (ORNL) collaborated to develop a capability to test the epithermal/intermediate cross sections of materials at the SNL critical experiment facility using the Seven Percent Critical Experiment (7uPCX) fuel. As a result, a new set of critical experiments has been designed to target the epithermal cross sections of tantalum (Ta) and is scheduled to be performed at SNL in 2023. These critical experiments will be evaluated for inclusion in the 2024 edition of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The focus of these critical experiments is to measure the effects of Ta on the critical array size. The critical array size will be determined by an approach-to-critical experiment with the number of fuel rods in the array as a free parameter. The core configurations are designed to optimize the reactivity worth of Ta and the overall percentage of Ta absorption rates in the epithermal/intermediate energy range (0.625 eV – 100 keV). The baseline core configuration includes 7uPCX fuel rods set at a triangular pitch of 1.016 cm and a central dry test region that utilizes a cadmium liner for filtering out thermal neutrons. The central test region has locations for 85 Ta rods set at a triangular pitch of 0.813 cm. The Ta reactivity worth for the case with 85 Ta rods is approximately 2.55%, with the percentage of Ta absorption rates within the intermediate energy range at nearly 90%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Local Power Impact Experiment Design for a New Fuel Type for use in the Advanced Test Reactor

The Advanced Test Reactor (ATR), and complimentary zero-power ATR Critical (ATRC) reactor, located at Idaho National Labs (INL), are undergoing conversion from Highly Enriched Uranium (HEU) to Low Enriched Uranium (LEU). Both have a variety of testing locations that can receive large variations in flux due to its unique serpentine design, consisting of five lobes (see Figure 1). Initial criticality and power distribution throughout the core are controlled by core-external outer shim control cylinders (OSCCs). Distinct test loops allow for testing at specific temperatures, pressures, and irradiation conditions. The ATR is one of the key nuclear engineering research and testing facilities within the DOE National Laboratory Complex, and the ATRC supports its operation [1]. Currently, the Office of Material Management and Minimization (M3) within the National Nuclear Security Administration of the DOE is working to convert the remaining research reactors, including the ATR, from 93% HEU fuel to 19.75% LEU fuel (LEU) to support non-proliferation [2]. Extensive materials testing at INL and internationally has demonstrated that a high-density uranium molybdenum (U 10Mo) alloy can meet the performance requirements of the remaining high powered research reactors. However, there are many technical challenges to address before the conversion to LEU can be successful, including the accurate characterization of the reactor core physics with LEU fuel. Reactor physics safety evaluations currently use Monte Carlo for the 21st Century (MC21), a continuous-energy Monte Carlo radiation transport code [3]. Existing MC21 models of the ATR and ATRC cores have a validation basis for use in neutronics analyses with HEU fuel. The models are used to support safety analyses that include comparisons to the safety requirements for the reactors. However, the use of the LOWE element in the ATR and ATRC is not currently covered by the current model validation basis. To deploy the new fuel type, extensive computational reactor physics support is necessary to support the use of LOWE in the ATR and ATRC. Therefore, LOWE requires a rigorous validation basis, aligned with that of HEU fuel, that takes advantage of the existing software tools and processes currently used for the ATR and ATRC. The experiment to validate of the MC21 models for determining power, the Power Impact Validation Experiment, will consist of two flux runs in the ATRC, one with fully HEU loading and one with a single LOWE element. Both flux runs will be instrumented with 20 sets of azimuthal fission wires and 3 sets of axial fission wires, as shown in Figure 4. Standard flux run methodology will be used [4]. Power Impact Validation Experiment data will be compared against MC21 calculated data, both for absolute fission rate accuracy and to determine the relative change in fission rates between the two runs. The results of the Power Impact Validation Experiment and subsequent evaluations will provide the validation basis for MC21 for use with LOWE elements. Key features of the Power Impact Validation Experiment include: (1) Two flux runs to allow for LOWE perturbed measurements to be compared to already validated measurements taken from a full core of HEU fuel, (2) Optimization of instrumentation to balance analytical needs with practical considerations (e.g., limited time window to count beta particles from fission products), and (3) Standard ATRC core loading, including both driver positions and flux traps, to minimize cost while remaining representative of typical ATR core loading.

42 ENGINEERING↗

High-performance epistasis detection in quantitative trait GWAS

epiSNP is a program for identifying pairwise single nucleotide polymorphism (SNP) interactions (epistasis) in quantitative-trait genome-wide association studies (GWAS). A parallel MPI version (EPISNPmpi) was created in 2008 to address this computationally expensive analysis on large data sets with many quantitative traits and SNP markers. However, the falling cost of genotyping has led to an explosion of large-scale GWAS data sets that challenge EPISNPmpi’s ability to compute results in a reasonable amount of time. Therefore, we optimized epiSNP for modern multi-core and highly parallel many-core processors to efficiently handle these large data sets. This paper describes the serial optimizations, dynamic load balancing using MPI-3 RMA operations, and shared-memory parallelization with OpenMP to further enhance load balancing and allow execution on the Intel Xeon Phi coprocessor (MIC). For a large GWAS data set, our optimizations provided a 38.43× speedup over EPISNPmpi on 126 nodes using 2 MICs on TACC’s Stampede Supercomputer. We also describe a Coarray Fortran (CAF) version that demonstrates the suitability of PGAS languages for problems with this computational pattern. We show that the Coarray version performs competitively with the MPI version on the NERSC Edison Cray XC30 supercomputer. Finally, the performance benefits of hyper-threading for this application on Edison (average 1.35× speedup) are demonstrated.

97 MATHEMATICS AND COMPUTING↗

Data for Characterization of the Ghd8 Flowering Time Gene in a Mini-Core Collection of Miscanthus sinensis

The optimal flowering time for bioenergy crop miscanthus is essential for environmental adaptability and biomass accumulation. However, little is known about how genes controlling flowering in other grasses contribute to flowering regulation in miscanthus. Here, we report on the sequence characterization and gene expression of Miscanthus sinensisGhd8 , a transcription factor encoding a HAP3/NF-YB DNA-binding domain, which has been identified as a major quantitative trait locus in rice, with pleiotropic effects on grain yield, heading date and plant height. In M. sinensis , we identified two homoeologous loci, MsiGhd8A located on chromosome 13 and MsiGhd8B on chromosome 7, with one on each of this paleo-allotetraploid species’ subgenomes. A total of 46 alleles and 28 predicted protein sequence types were identified in 12 wild-collected accessions. Several variants of MsiGhd8 showed a geographic and latitudinal distribution. Quantitative real-time PCR revealed that MsiGhd8 expressed under both long days and short days, and MsiGhd8B showed a significantly higher expression than MsiGhd8A . The comparison between flowering time and gene expression indicated that MsiGhd8B affected flowering time in response to day length for some accessions. This study provides insight into the conserved function of Ghd8 in the Poaceae, and is an important initial step in elucidating the flowering regulatory network of Miscanthus.

Feedstock Production↗

Characterization of the Ghd8 Flowering Time Gene in a Mini-Core Collection of Miscanthus sinensis

The optimal flowering time for bioenergy crop Miscanthus is essential for environmental adaptability and biomass accumulation. However, little is known about how genes controlling flowering in other grasses contribute to flowering regulation in Miscanthus. Here, we report on the sequence characterization and gene expression of Miscanthus sinensisGhd8, a transcription factor encoding a HAP3/NF-YB DNA-binding domain, which has been identified as a major quantitative trait locus in rice, with pleiotropic effects on grain yield, heading date and plant height. In M. sinensis, we identified two homoeologous loci, MsiGhd8A located on chromosome 13 and MsiGhd8B on chromosome 7, with one on each of this paleo-allotetraploid species’ subgenomes. A total of 46 alleles and 28 predicted protein sequence types were identified in 12 wild-collected accessions. Several variants of MsiGhd8 showed a geographic and latitudinal distribution. Quantitative real-time PCR revealed that MsiGhd8 expressed under both long days and short days, and MsiGhd8B showed a significantly higher expression than MsiGhd8A. The comparison between flowering time and gene expression indicated that MsiGhd8B affected flowering time in response to day length for some accessions. This study provides insight into the conserved function of Ghd8 in the Poaceae, and is an important initial step in elucidating the flowering regulatory network of Miscanthus.

geographic distribution↗

Advanced Pt-Based Core–Shell Electrocatalysts for Fuel Cell Cathodes

Proton-exchange membrane fuel cells (PEMFCs) are highly efficient energy storage and conversion devices. Thus, the platinum group metal (PGM)-based catalysts which are the dominant choice for the PEMFCs have received extensive interest during the past couple of decades. However, the drawbacks in the existing PGM-based catalysts (i.e., high cost, slow kinetics, poor stability, etc.) still limit their applications in fuel cells. The Pt-based core–shell catalysts potentially alleviate these issues through the low Pt loading with the associated low cost and the high corrosion resistance and further improve the oxygen reduction reaction’s (ORR’s) activity and stability. This Account focuses on the synthetic strategies, catalytic mechanisms, factors influencing enhanced ORR performance, and applications in PEMFCs for the Pt-based core–shell catalysts. We first highlight the synthetic strategies for Pt-based core–shell catalysts including the galvanic displacement of an underpotentially deposited non-noble metal monolayer, thermal annealing, and dealloying methods, which can be scaled-up to meet the requirements of fuel cell operations. Subsequently, catalytic mechanisms such as the self-healing mechanism in the Pt monolayer on Pd core catalysts, the pinning effect of nitrogen (N) dopants in N-doped PtNi core–shell catalysts, and the ligand effect of the ordered intermetallic structure in L10-Pt/CoPt core–shell catalysts and their synergistic effects in N-doped L10-PtNi catalysts are described in detail. Additionally, the core–shell structure in the Pt-based catalysts have two main effects for enhanced ORR performance: (i) the interaction between Pt shells and core substrates can tune the electronic state of the surface Pt, thus boosting the ORR activity and stability, and (ii) the outer Pt shell with modest thickness can enhance the oxidation and dissolution resistance of the core, resulting in improved durability. We then review the recent attempts to optimize the ORR performance of the Pt-based core–shell catalysts by considering the shape, composition, surface orientation, and shell thickness. The factors influencing the ORR performance can be grouped into two categories: the effect of the core and the effect of the shell. In the former, PtM core–shell catalysts which use different non-PGM element cores (M) are summarized, and in the latter, Pt-based core–shell catalysts with different shell structures and compositions are described. The modifications of the core and/or shell structure can not only optimize the intermediate-binding energetics on the Pt surface through tuning the strain of the surface Pt, which increases the intrinsic activity and stability, but also offer a significantly decreased catalyst cost. Finally, we discuss the membrane electrode assembly performance of Pt-based core–shell catalysts in fuel cell cathodes and evaluate their potential in real PEMFCs for light-duty and heavy-duty vehicle applications. Even though some challenges to the activity and lifetime in the fuel cells remain, the Pt-based core–shell catalysts are expected to be promising for many practical PEMFC applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Magnetostrictive loss reduction through stress relief annealing in an FeNi-based metal amorphous nanocomposite

FeNi-based metal amorphous nanocomposite alloys are emerging soft magnetic materials with promise for high-speed motor applications. Here we demonstrate a technique to optimize magnetic properties in toroidal cores wound from strain annealed (Fe 70 Ni 30 ) 80 Nb 4 Si 2 B 14 amorphous metal ribbon (AMR). In-line strain annealing (SA) of the AMR yields a strip permeability that monotonically decreases with increasing SA tensions. After winding into toroidal cores, dramatic changes in magnetic properties are observed and determined to be of magnetostrictive origin. A procedure to re-anneal wound toroidal cores to reduce hysteresis and reverse magnetostrictive effects is developed inclusive of casting curvature effects. Here, we investigate re-annealing temperatures between 300 – 470 °C for cores produced from each SA condition. Magnetic core loss, W L , coercivity, H c , squareness ratio, K r , and permeability, µ r , are measured as a function of (stress relief) re-annealing temperature to optimally achieve W 1T,400Hz = 0.51 W/kg, H c = 2.42 A/m, K r = 0.22, and µ r = 35,300.

36 MATERIALS SCIENCE↗

Accurate prediction of core-level spectra of radicals at density functional theory cost via square gradient minimization and recoupling of mixed configurations

State-specific orbital optimized approaches are more accurate at predicting core-level spectra than traditional linear-response protocols, but their utility had been restricted due to the risk of "variational collapse" down to the ground state. We employ the recently developed square gradient minimization algorithm to reliably avoid variational collapse and study the effectiveness of orbital optimized density functional theory (DFT) at predicting second period element 1s core-level spectra of open-shell systems. Several density functionals (including SCAN, B3LYP, and ωB97X-D3) are found to predict excitation energies from the core to singly occupied levels with high accuracy (≤0.3 eV RMS error) against available experimental data. Higher excited states are, however, more challenging by virtue of being intrinsically multiconfigurational. We thus present a configuration interaction inspired route to self-consistently recouple single determinant mixed configurations obtained from DFT, in order to obtain approximate doublet states. This recoupling scheme is used to predict the C K-edge spectra of the allyl radical, the O K-edge spectra of CO + , and the N K-edge of NO 2 with high accuracy relative to experiment, indicating substantial promise in using this approach for the computation of core-level spectra for doublet species [vs more traditional time dependent DFT, equation of motion coupled cluster singles and doubles (EOM-CCSD), or using unrecoupled mixed configurations]. Finally, we also present general guidelines for computing core-excited states from orbital optimized DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗