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DOE OSTI2024

In-Silico Analysis of High Refractive Index Materials Through Principles of Materials Design

The intent of the paper is to use specific principles of Materials Design that were developed and applied in the electronics industry for enabling understanding and design of improved high refractive index materials. Further, by combining first-principle based ab-initio, semiempirical interatomic potential methods, and machine learning approaches in conjunction with experimental data, we identified specific determinants of high refractive index materials, which can be critically applied for informing materials design and accelerating discovery. Specifically, it was demonstrated that chalcogenides and perovskites as bulk materials can exhibit higher refractive indices with appropriate engineering of specific aspects of the materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

IRIS-GNN: Leveraging Graph Neural Networks for Scheduling on Truly Heterogeneous Runtime Systems

The diversity of accelerators in computer systems poses significant challenges for software developers, such as managing vendor-specific compiler toolchains, code fragmentation requiring different kernel implementations, and performance portability issues. To address these, the Intelligent Runtime System (IRIS) was developed. IRIS works across various systems, from smartphones to supercomputers, enabling automatic performance scaling based on available accelerators. It introduces abstract tasks for seamless execution transitions between accelerators while ensuring memory consistency and task dependencies. Although IRIS simplifies system details, optimal dynamic scheduling still requires user input to understand workload structures. To address this, we introduce a new scheduling policy for IRIS, termed IRIS-GNN, which is the first IRIS hybrid policy that operates in conjunction with the dynamic policies. This policy employs a Graph-Neural Network (GNN) to conduct Graph Classification of any task graphs submitted to IRIS. This GNN analyzes the structure and attributes of the task graph, categorizing it as either locality, concurrency, or mixed. This classification subsequently guides the selection of the dynamic policy used by IRIS. We provide a comparison of the performance of IRIS-GNN against the complete spectrum of IRIS’s dynamic policies, assess the overhead introduced by the GNN within this scheduling framework, and ultimately explore its practical application in real-world scenarios.

Johnston, Beau↗

DOE OSTI2024

Enabling Low-Overhead HT-HPC Workflows at Extreme Scale using GNU Parallel

GNU Parallel is a versatile and powerful tool for process parallelization widely used in scientific computing. This paper demonstrates its effective application in high-performance computing (HPC) environments, particularly focusing on its scalability and efficiency in executing large-scale high-throughput high-performance computing (HT-HPC) workflows. Through real-world examples, we highlight GNU Parallel’s performance across various HPC workloads, including GPU computing, container-based workloads, and node-local NVMe storage. Our results on two leading supercomputers, OLCF’s Frontier and NERSC’s Perlmutter, showcase GNU Parallel’s rapid process dispatching ability and its capacity to maintain low overhead even at extreme scales. We explore GNU Parallel’s application in massive parallel file transfers using a scheduled Data Transfer Node (DTN) cluster, emphasizing its broad utility in diverse scientific workflows. Beyond its direct application as a viable workflow manager, GNU Parallel can be employed in conjunction with other workflow systems as a "last-mile" parallelizing driver and as a quick prototyping tool to design and extract parallel profiles from application executions. We then argue that the potential for GNU Parallel to transform workflow management at extreme scales is substantial, paving the way for more efficient and effective scientific discoveries.

Maheshwari, Ketan↗

DOE OSTI2025

High Resolution Fission Fragment Spectroscopy with Superconducting Microcalorimeters

Sub-1 AMU mass determination is important for determining fission yields and neutron multiplicity, which are necessary inputs for fission models. Fission models can improve spent nuclear waste stream analysis and nuclear fuel burnup determination. Here, to achieve this goal, we have used superconducting microcalorimeter detectors to directly measure the energy of fission fragments from the spontaneous fission of 252 Cf. With a fiber coupled LED pulser setup we demonstrate that we can reach a relative energy resolution of 0.1% and better for photon pulses with energies above 60 MeV. This instrument, in conjunction with time-of-flight (TOF) measurement, would allow for sub-1 atomic mass unit (AMU) mass determination of fission fragments in a future beamline application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Lossy Compression: An Online Multi-Stage Technology for High-Fidelity Synchro- Waveform Measurements

Effective real-time monitoring and analysis of distributed grids necessitate the use of synchro-waveform measurements, which capture almost all high-frequency disturbances and transient phenomena. However, due to limitations in high-speed measurements and network bandwidth, it is challenging to transfer all high-fidelity synchro-waveforms losslessly and successfully. To cope with these challenges, a hybrid-based online multi-stage compression algorithm is proposed to significantly improve the compression efficiency for synchro-waveform measurements. Initially, the multiple discrete Wavelet transformation is deployed to deconstruct the waveform components. The delta encoding is further developed to decrease the magnitude. In conjunction with the Lempel-Ziv-Markov chain, the hybrid compression algorithm is implemented to achieve real-time compression for the synchro-waveform measurements. Moreover, an innovative error index that synergizes the time and frequency domain error and correlation is formulated to evaluate the waveform distortion. By integrating compression ratio, suitable parameters can be optimally selected. Finally, the simulation, laboratory experiments, as well as field tests across a spectrum of sampling frequencies and time intervals are conducted to substantiate the efficacy of the proposed method. Here, the outcomes demonstrated that a compression ratio of approximately 15.5 and 17.83 can be reached for 0.5 s and 1 s data under both offline and online scenarios, which equates to a substantial 93.5% to 94.39% reduction in data storage requirements.

High-fidelity synchro-waveform measurements↗

DOE OSTI2024

Design of the Electromagnetic Particle Injector (EPI) for Tokamak Deployment

Both predicting and controlling disruptions are critical and urgent issues for ITER as some disruptions with a short warning time may be unavoidable. For these cases, a rapid response disruption mitigation system (DMS) referred to as the electromagnetic particle injector (EPI) is being developed. The primary advantages of the EPI are its fast response time and high velocity, which have been demonstrated in offline experiments (Raman et al., 2021). The EPI is capable of accelerating a metallic sabot electromagnetically using a rail gun to the required velocities ( > 2 km/s) within 2 ms. Two high-field racetrack magnets able to generate fields over 2 T are positioned above and below the rails to permit high velocity at low rail currents, a requirement to minimize electrode erosion. At the end of the acceleration phase, a sabot capture mechanism retains the spent sabot inside the vacuum chamber that houses the EPI. At this point, it releases well-defined microspheres, or a shell pellet, of a radiative payload into the disrupting plasma. A remotely operated sabot loading system positioned behind the injector contains several pre-equipped sabots that can be loaded by an operator from the tokamak control room. The injector is interfaced to the tokamak through a guide tube attached to the front of the EPI vacuum chamber. Finally, the advantages of the EPI system over other DMSs under consideration are described in conjunction with the details of an EPI system designed for near-term test on an existing large tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Resilient Control of Networked Microgrids Using Vertical Federated Reinforcement Learning: Designs and Real-Time Test-Bed Validations

Improving system-level resiliency of networked microgrids against adversarial cyber-attacks is an important aspect in the current regime of increased inverter-based resources (IBRs). To achieve that, this paper contributes in designing a hierarchical control layer, in conjunction with the existing control layers, resilient to adversarial attack signals. Considering model complexities, unknown dynamical behaviors of IBRs, and privacy issues regarding data sharing in multi-party-owned microgrids, designing such a control layer is non-trivial. Here, to tackle these issues, a novel federated reinforcement learning (Fed-RL) method is proposed. To grasp the interconnected dynamics of networked microgrids, the paper develops Federated Soft Actor-Critic (FedSAC) algorithm following the vertical structure of implementing Fed-RL. Next, utilizing the OpenAI Gym interface, we built a custom set-up in GridLAB-D/HELICS co-simulation platform, named Resilient RL Co-simulation (ResRLCoSIM), to train the RL agents with IEEE 123-bus benchmark comprising 3 interconnected microgrids. Finally, the learned policies in the simulation are transferred to the real-time hardware-in-the-loop (HIL) test-bed developed using the high-fidelity Hypersim platform. Finally, experiments show that the simulator-trained RL controllers achieve desirable performance with the test-bed platform, validating the minimization of the sim-to-real gap.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Design by analysis rules for ASME Section III, Division 5, Class B components

The current rules for elevated temperature ASME Section III, Division 5, Class B components, other than piping, were basically adapted from the Design-by-Rule approach for Section VIII, Division 1 vessels. A goal of the proposed new rules is to explicitly account for the design life and cyclic service while recognizing the less-rigorous requirements commensurate with lesser safety consideration. Further goals are to maximize the use of modern computational technology, for example finite element analysis in conjunction with reference stress concepts, and to avoid the need for stress classification. This paper summarizes the work done to address these issues. A summary of the design-by-analysis for primary loads, strain limit evaluation, and creep-fatigue damage assessment is presented. The proposed design-by-analysis creep-fatigue damage calculation approach uses a new elastic follow-up-based Isochronous Stress Strain Curve stress relaxation procedure. A set of sample problems are selected to validate the proposed design-by-analysis rules for creep-fatigue damage assessment. The proposed Class B rules are evaluated against the Class A elastic design rules and the experimental data obtained from a family of a simplified model test-based key-feature test results. The proposed Class B creep-fatigue damage assessment methodology yields conservative design cycles estimates compared to the experimental results.

36 MATERIALS SCIENCE↗

DOE OSTI2024

An under-approximation of entropy for elemental multiconfigurational ground state electronic structures

A combinatorial approach has been applied to the allowable permutations of quantum electronic configurations under the constraints of Hund's rule for established ground state configurations toward an under-approximation of electronic structure entropy. Combined with a previously reported over-approximation, the approximations are used in conjunction in an attempt to bracket the upper and lower entropy limits for multiconfigurational ground state electronic structure entropy and compared to known standard molar entropies for the elements. This formality has been used for the application of a classical statistical mechanics methodology to be applied to the discrete sets of quantum mechanical states of Pu in order to calculate orbital occupancies in Pu's multiconfigurational ground state. Without consideration of the relative energies of various possible electronic configurations contributing to the multiconfigurational ground state, the calculations are performed under a general energy degeneracy assumption weighted to the number of permutations for specific configurations. The number of configurations assumed to significantly contribute is gradually constrained in order to approach a low-order approximation of orbital occupancies in Pu that are then compared to experimental and other calculated results from the literature.

Beaux, II, Miles F. (ORCID:000000032192626X)↗

DOE OSTI2024

Impact of mineral and non-mineral sources of iron and sulfur on the metalloproteome of Methanosarcina barkeri

Methanogens often inhabit sulfidic environments that favor the precipitation of transition metals such as iron (Fe) as metal sulfides, including mackinawite (FeS) and pyrite (FeS 2 ). These metal sulfides have historically been considered biologically unavailable. Nonetheless, methanogens are commonly cultivated with sulfide (HS - ) as a sulfur source, a condition that would be expected to favor metal precipitation and thus limit metal availability. Recent studies have shown that methanogens can access Fe and sulfur (S) from FeS and FeS 2 to sustain growth. As such, medium supplied with FeS 2 should lead to higher availability of transition metals when compared to medium supplied with HS - . Here, we examined how transition metal availability under sulfidic (i.e., cells provided with HS - as sole S source) versus non-sulfidic (cells provided with FeS 2 as sole S source) conditions impact the metalloproteome of Methanosarcina barkeri Fusaro. To achieve this, we employed size exclusion chromatography coupled with inductively coupled plasma mass spectrometry and shotgun proteomics. Significant changes were observed in the composition and abundance of iron, cobalt, nickel, zinc, and molybdenum proteins. Among the differences were alterations in the stoichiometry and abundance of multisubunit protein complexes involved in methanogenesis and electron transport chains. Furthermore, our data suggest that M. barkeri utilizes the minimal iron-sulfur cluster complex and canonical cysteine biosynthesis proteins when grown on FeS 2 but uses the canonical Suf pathway in conjunction with the tRNA-Sep cysteine pathway for iron-sulfur cluster and cysteine biosynthesis under sulfidic growth conditions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Draft assemblies for three geographically distinct isolates of the human-infecting microsporidium Encephalitozoon intestinalis

Encephalitozoon intestinalis is an obligate intracellular parasite that causes enteritis, bronchitis, conjunctivitis, and/or encephalitis in immunosuppressed and immunocompetent individuals. To better assess its genetic diversity, here we report near-chromosome-level draft genome assemblies for three geographically distinct isolates, quadrupling the number of genome assemblies available for the enigmatic fungal pathogen.

Biological and medical sciences↗

DOE OSTI2025

Engineered IL-18 variants with half-life extension and improved stability for cancer immunotherapy

Background The pro-inflammatory cytokine, interleukin-18 (IL-18), plays an instrumental role in bolstering anti-tumor immunity. However, the therapeutic application of IL-18 has been limited due to its susceptibility to neutralization by IL-18 binding protein (IL-18BP), short in vivo half-life, and unfavorable physicochemical properties. Methods In order to overcome the poor drug-like properties of IL-18, we installed an artificial disulfide bond, removed the native, unpaired cysteines, and fused the stabilized cytokine to an IgG Fc domain. The stability, potency, pharmacokinetic and pharmacodynamic properties as well as efficacy of disulfide-stabilized IL-18 Fc-fusion (dsIL-18-Fc) were assessed via in vitro and in vivo studies. Results The stability and mammalian host cell production yields of dsIL-18-Fc were improved, compared to the wild-type (WT) cytokine, while maintaining its biological potency and interactions with IL-18 receptor α (IL-18Rα) and IL-18BP. Recombinant fusion of the cytokine to an IgG Fc domain provided extended half-life. Notably, despite maintaining sensitivity to IL-18BP, dsIL-18-Fc was effective at activating both T and natural killer (NK) cells, and elicited a strong anti-tumor response, either as a single agent, or in conjunction with anti-programmed cell death-ligand 1 (anti-PD-L1) therapy. Conclusions We engineered IL-18 for reinforced stability, extended half-life, and improved manufacturability. The therapeutic benefit of dsIL-18-Fc, coupled with a more favorable manufacturability profile and enhanced drug-like properties, underscores the potential utility of this engineered cytokine in cancer immunotherapy.

Immunology↗

DOE OSTI2025

An Optimization-Based Coupling of Reduced Order Models with an Efficient Reduced Adjoint Basis Generation Approach

Optimization-based coupling (OBC) is an attractive alternative to traditional Lagrange multiplier approaches in multiple modeling and simulation contexts. However, application of OBC to time-dependent problems has been hindered by the computational cost of finding the stationary points of the associated Lagrangian, which requires primal and adjoint solves. This issue can be mitigated by using OBC in conjunction with computationally efficient reduced order models (ROMs). To demonstrate the potential of this combination, in this paper, we develop an optimization-based ROM-ROM coupling for a transient advection-diffusion transmission problem. We pursue the “optimize-then-reduce” path toward solving the minimization problem at each time step and solve reduced space adjoint system of equations, where the main challenge in this formulation is the generation of adjoint snapshots and reduced bases for the adjoint systems required by the optimizer. One of the main contributions of the paper is a new technique for an efficient adjoint snapshot collection for gradient-based optimizers in the context of optimization-based ROM-ROM couplings. In conclusion, we present numerical studies demonstrating the accuracy of the approach along with comparison between various approaches for selecting a reduced order basis for the adjoint systems, including decay of snapshot energy, average iteration counts, and timings.

coupled problems↗

DOE OSTI2024

Single-neutron adding on $^{34}$S

For this work, single-neutron adding data was collected in order to determine the distribution of the single-neutron strength of the 0ƒ 7/2 , 1p 3/2 , 1p 1/2 and 0ƒ 5/2 orbitals outside of Z = 16, N = 18, 34 S. The 34 S(d,p) 35 S reaction has been measured at 8 MeV/u to investigate cross sections to excited states in 35 S. Outgoing proton yields and momenta were analyzed by the Super-Enge Split-Pole Spectrograph in conjunction with the CeBrA demonstrator located at the John D. Fox Laboratory at Florida State University. Angular distributions were compared with Distorted Wave Born Approximation calculations in order to extract single-neutron spectroscopic overlaps. Spectroscopic overlaps and strengths were determined for states in S up through 6 MeV in excitation energy. Each orbital was observed to have fragmented strength where a single level carried the majority. The single-neutron centroids of the 0ƒ 7/2 , 1p 3/2 , 1p 1/2 and 0ƒ 5/2 orbitals were determined to be 2360$^{+90}_{-40}$ keV, 3280$^{+80}_{-50}$ keV, 4780$^{+60}_{-40}$ keV, and ≳7500 keV, respectively. A previous discrepancy in the literature with respect to the distribution of the neutron 1p 1/2 strength was resolved. The integration of the normalized spectroscopic strengths, up to 5.1 MeV in excitation energy, revealed fully-vacant occupancies for the 0ƒ 7/2 , 1p 3/2 , and 1p 1/2 orbitals, as expected. The spacing in the single-neutron energies highlighted a reduction in the traditional N = 28 shell-gap, relative to both the 1p spin-orbit energy difference (N = 32) and the lower limit on the N = 34 shell spacing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Measurement of the background in the CMS muon detector in ${p}{p}$-collisions at $\sqrt{s} = 13$ TeV

The CMS detector, including its muon system, has been operating at the CERN LHC in increasingly challenging conditions for about 15 years. The muon detector was designed to provide excellent triggering and track reconstruction for muons produced in proton–proton collisons at an instantaneous luminosity ($\mathcal{L}$) of 1 x 10 34 cm –2 s –1 . During the Run 2 data-taking period (2015–2018), the LHC achieved an instantaneous luminosity of twice its design value, resulting in larger background rates and making the efficient detection of muons more difficult. While some backgrounds result from natural radioactivity, cosmic rays, and interactions of the circulating protons with residual gas in the beam pipe, the dominant source of background hits in the muon system arises from proton–proton interactions themselves. Charged hadrons leaving the calorimeters produce energy deposits in the muon chambers. In addition, high-energy particles interacting in the hadron calorimeter and forward shielding elements generate thermal neutrons, which leak out of the calorimeter and shielding structures, filling the CMS cavern. We describe the method used to measure the background rates in the various muon subsystems. These rates, in conjunction with simulations, can be used to estimate the expected backgrounds in the High-Luminosity LHC. This machine will run for at least 10 years starting in 2029 reaching an instantaneous luminosity of $\mathcal{L}$ = 5 x 10 34 cm –2 s –1 and increasing ultimately to $\mathcal{L}$ = 7.5 x 10 34 cm –2 s –1 . These background estimates have been a key ingredient for the planning and design of the muon detector upgrade.

Tytgat, M. (ORCID:0000000239902074)↗

DOE OSTI2024

Increasing the Measured Effective Quantum Volume with Zero Noise Extrapolation

Quantum volume is a full-stack benchmark for near-term quantum computers. It quantifies the largest size of a square circuit which can be executed on the target device with reasonable fidelity. Error mitigation is a set of techniques intended to remove the effects of noise present in the computation of noisy quantum computers when computing an expectation value of interest. Effective quantum volume is a proposed metric that applies error mitigation to the quantum volume protocol to evaluate the effectiveness not only of the target device but also of the error mitigation algorithm. Digital zero-noise extrapolation is an error mitigation technique that estimates the noiseless expectation value using circuit folding to amplify errors by known scale factors and then extrapolating computed expectation values to the zero-noise limit. Here we demonstrate that zero-noise extrapolation, with global and local unitary folding with fractional scale factors, in conjunction with dynamical decoupling, can increase the effective quantum volume over the vendor-measured quantum volume. Specifically, we measure the effective quantum volume of four IBM Quantum superconducting processor units, obtaining values that are larger than the vendor-measured quantum volume on each device. This is the first such increase reported.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

PyJMAK: An Open-Source Python Toolkit for Modeling Solid-State Metallurgical Phase Transformations

Accurate prediction of metallurgical phase transformations is an essential basis for autonomous optimization and rapid part qualification. Several methods can be used to estimate the evolution of phase fractions such as JMAK kinetics-based models, phase-field models, thermodynamic models, and data-driven machine learning models. Thermodynamic and phase-field-based methodologies solve multiphysics equations requiring numerous calibration parameters and significant computational resources. As a result, the computation domain is limited to a point or on order of micron-meters. The data-driven models rely on large datasets from experiments and simulations. While the JMAK model only provides information about phase fraction evolution, it can predict this evolution in near real-time using thermal history and thermodynamic data without restriction on the domain. JMAK models have been popularly used by researchers to model phase transformations occuring during additive manufacturing or over arbitrary temperature profiles. Commercial proprietary software such as Abaqus and Ansys or closed-source in-house implementations offer the ability to model JMAK based kinetics to predict phase transformation. However, these software packages are not open-source or freely available for use and development in conjunction with manufacturing machines, sensors, and machine learning algorithms. In addition, the use of the model is restricted by a license token. In contrast, given temperature profiles at multiple points in the domain, this Python-based PyJMAK model can compute phase evolution in parallel due to its stand-alone modular, voxel-based structure, and it can be executed on high-performance computing resources without any license restrictions.

Prabhune, Bhagya [Oak Ridge National Laboratory (O↗

DOE OSTI2026

FAD-Toolset (Floating Array Design Toolset) [SWR-26-056]

The Floating Array Design (FAD) Toolset is a collection of tools for modeling and designing arrays of floating offshore structures. It was originally designed for floating wind systems but has applicability for many offshore applications. A core part of the FAD Toolset is the floating array model, which serves as a high-level library for efficiently modeling a floating array, such as a floating wind array. It combines site condition information and a description of the floating array design, and contains functions for evaluating the array's behavior considering the site conditions. For example, it combines information about site soil conditions, mooring line loads, and an array's anchor characteristics to estimate the holding capacity of each anchor. The library works in conjunction with the tools RAFT, MoorPy, and FLORIS to model floating platforms, wind turbines, mooring systems, power cables, and array wakes respectively. Layered on top of the floating array model is a set of design tools that can be used for algorithmically adjusting or optimizing parts of the a floating array. Specific tools existing for mooring lines, shared mooring systems, dynamic power cables, static power cable routing, and overall array layout. These capabilities work with the design representation and evaluation functions in the floating array model, and they can be applied by users in various combinations to suit different purposes. In addition to standalone uses of the FAD Toolset, a coupling has been made with Ard, (https://github.com/NLRWindSystems/Ard) a sophisticated and flexible wind farm optimization tool. This coupling allows Ard to use certain mooring system capabilities from FAD to perform layout optimization of floating wind farms with Ard's more advanced layout optimization capabilities. The FAD Toolset works with the IEA Wind Task 49 Ontology (https://github.com/IEAWindTask49/Ontology), which provides a standardized format for describing floating wind farm sites and designs. See example use cases in our examples folder (https://github.com/NLRWindSystems/FAD-Toolset/blob/main/examples/README.md) For working with the library, it is important to understand the floating array model structure, which is described more here: https://github.com/NLRWindSystems/FAD-Toolset/blob/main/fad/README.md.

Sirkis, Leah [National Laboratory of the Rockies (↗