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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6

Development of Advanced, Radiation Resistant, Optical-based Detector Technology for Future Experiments.

The primary objective of this project has been to advance the design of high-performance electromagnetic (EM) calorimeters for future particle physics experiments, to identify and measure the timing, position and energy of electrons, positrons and gamma rays, particularly in high-luminosity environments with intense radiation and pileup conditions. To meet such challenges, the proposed research has focused on the development of ultra-compact, radiation-hard calorimeter modules, to provide excellent timing, spatial, and energy resolution. The work aligns with the DOE’s Basic Research Needs (BRN) for High Energy Physics (HEP) Instrumentation and the research team contributes actively to the Coordinating Panel on Advanced Detectors (CPAD) RDC9 calorimetry collaboration in the USA and the European Committee on Future Accelerators (ECFA) DRD-CALO calorimetry collaboration at CERN, the European Laboratory for Particle Physics located in Geneva, Switzerland. The research builds on the RADiCAL (radiation-hard, ultra-compact) modular sampling calorimeter approach, developed by the research team, which employs dense and very bright optical materials such as LYSO:Ce scintillator plates that are interleaved with very dense tungsten plates to minimize detector size while optimizing performance. The modules are comparable in size to a human index finger, dimensionally 14 mm x 14 mm in cross section and 135 mm in length. And despite the small size, the structure is capable of providing excellent timing and energy resolution. This is facilitated through the use of specialized quartz capillaries filled with wavelength-shifting filaments, positioned at various depths along the length of a module, to collect and guide light signals to silicon photomultipliers (SiPMs) which detect and convert the optical signals to electronic signals for analysis. The primary goals of this project have been: (1) Achieve a timing resolution to σ t ≤ 30 ps for high-energy electrons and photons, important for their association with specific events produced in colliding-beam experiments and for the detection of decays-in-flight of long-lived particles. The project has achieved this goal in beam tests of a single RADiCAL module at CERN, during which a timing resolution of σ t = 27 ps was measured for electrons of energy E = 150 GeV. Based upon a mathematical fit to the data measured over a broad energy range from low energy to high energy, a resolution of σ t ≤ 18 ps has been estimated for electrons of very high (TeV) energy. From these measurements and with further expected technical improvements, the timing resolution should reach σ t ≤ 10 ps, important for searches for discovery physics in upcoming and future experiments. (2) Achieve an energy resolution of σ E / E ≤ 10% / $\sqrt{E}$. The project has yet to achieve this goal, but is close to it, having measured a value of σ E / E ≤ 15.9% / $\sqrt{E}$ using a modular array. Ultimately, the resolution goal is expected to be reached by adjustments to material thicknesses within the modules, which will improve the sampling fraction to measure more precisely the shower energy for lower energy particles. The versatility of the modular RADiCAL approach enables the testing of advanced materials, photosensors and electronics, developed in collaboration with CPAD RDC and ECFA DRD-CALO groups. The structure can distinguish electrons, positrons and gamma rays from hadrons and muons and beam-induced backgrounds, making it a valuable tool in a variety of detector environments, including future circular colliders (FCC-ee, FCC-hh) proposed for the European Laboratory for Particle Physics (CERN), the muon-collider proposed for Fermi National Accelerator Laboratory (Fermilab), and searches for new physics in beam-dump, fixed target and forward-physics experiments. And, while designed with particle physics applications in mind, the technologies developed in this project have the potential for application more broadly in particle and nuclear physics, materials science, and medical physics, underscoring the far-reaching potential of this line of instrumentation research and development.

47 OTHER INSTRUMENTATION↗

Stacked Low-Inertia Converter or Solid-State Transformer: Modeling and Model Predictive Priority-Shifting Control for Voltage Balance

This paper presents control challenges of stacked low-inertia converter (SLIC) or cascaded reduced dc-link solid-state transformer (SST) and proposes a novel model predictive priority-shifting (MPPS) control with implicit modulator and a discrete-time large-signal model for voltage balancing and dc-link regulation. Low-inertia converters, featuring small electrolytic capacitor-less dc links, dramatically reduce cost, size, and weight compared to conventional solutions. However, without a large dc-link buffer, the input and output are tightly coupled, leading to significant control challenges. The control becomes even more challenging with these converters stacked input-series output-parallel (ISOP) for medium-voltage (MV) grid, which causes coupling between the modules besides the coupling within each module. This paper analyzes the multi-objective, multi-degree of freedom control problem, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. First, distribution of control efforts under controller saturation is critical because multiple control objectives can be conflicting, especially when the module voltages are unbalanced and are being restored. The MPPS can shift the priorities to address this issue. Second, due to the low inertia and high dc-link ripple, classic space vector pulse-width modulation (SVPWM), average model with small-ripple assumption, and control design based on small-signal model cannot accurately modulate, model, and control the nonlinear reduced dc link. Therefore, a discrete-time large-signal model of the M-S4T is established to derive the predictive control in the MPPS. The MPPS and the PI control are compared in MV simulations to show the issue of applying the PI to the SLIC and the effectiveness of the MPPS for voltage balancing and dc-link regulation in a deadbeat manner. Finally, the proposed control is tested on a 5 kV ISOP SiC SST prototype to verify priority shifting to address controller saturation issue and fast and robust voltage balancing.

14 SOLAR ENERGY↗

Scalable DAQ system operating the CHIPS-5 neutrino detector

The CHIPS R&D project focuses on development of low-cost water Cherenkov neutrino detectors through novel design strategies and resourceful engineering. This work presents an end-to-end DAQ solution intended for a recent 5 kt CHIPS prototype, which is largely based on affordable mass-produced components. Much like the detector itself, the presented instrumentation is composed of modular arrays that can be scaled up and easily serviced. A single such array can carry up to 30 photomultiplier tubes (PMTs) accompanied by electronics that generate high voltage in-situ and deliver time resolution of up to 0.69 ns. In addition, the technology is compatible with the White Rabbit timing system, which can synchronize its elements to within 100 ps. While deployment issues did not permit the presented DAQ system to operate beyond initial evaluation, the presented hardware and software successfully passed numerous commissioning tests that demonstrated their viability for use in a large-scale neutrino detector, instrumented with thousands of PMTs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multi-Modal Characterization of Nuclear Fuels and Materials at the Idaho National Laboratory Materials & Fuels Complex

The Idaho National Laboratory (INL) leads cutting-edge research pertaining to the advancement of nuclear reactor technologies, including nuclear fuels and materials. The INL Irradiated Materials Characterization Laboratory (IMCL), Electron Microscopy Laboratory (EML), and future Sample Preparation Laboratory (SPL) are available to the nuclear research community to assess the behavior of nuclear fuels and materials, efficiently and comprehensively characterizing from the engineering to atomistic scale. The IMCL is a unique, 12,000-square-foot facility located at the INL Materials and Fuels Complex designed for analysis of irradiated materials. The facility operates advanced characterization instruments that are sensitive to vibration, temperature, and electromagnetic interference in modular radiological shielding and confinement systems, granting researchers the ability to assess the microstructural, chemical, mechanical and thermophysical properties of nuclear materials, especially irradiated fuels. The EML is dedicated to advanced characterization of materials with optical and electron microscopy tools, including scanning electron microscopy/focused-ion beam (SEM/FIB) and transmission electron microscopy (TEM). Upon construction, the SPL will be a 3 story, 49,000 sq. ft facility, that is the most modern reactor structural materials testing and analysis facility in the world, designed to investigate reactor structural materials in support of life-extension programs and development of advanced reactor concepts, including mechanical testing and advanced characterization capabilities. This presentation will showcase some of the main capabilities available at both IMCL, EML, and SPL, specifically illustrating how these characterization techniques are incorporated into multi-modal characterization work scopes to elucidate the degradation of nuclear structural materials and irradiated fuels.

36 MATERIALS SCIENCE↗

Qubit Control System (QubiC) v1.0

We design a modular FPGA (field-programmable gate array) based system called QubiC to control and measure a superconducting quantum processing unit. The system includes room temperature electronics hardware, FPGA gateware, and engineering software.

Huang, Gang↗

TAMM: Tensor algebra for many-body methods

Tensor algebra operations such as contractions in computational chemistry consume a significant fraction of the computing time on large-scale computing platforms. The widespread use of tensor contractions between large multi-dimensional tensors in describing electronic structure theory has motivated the development of multiple tensor algebra frameworks targeting heterogeneous computing platforms. In this paper, we present Tensor Algebra for Many-body Methods (TAMM), a framework for productive and performance-portable development of scalable computational chemistry methods. TAMM decouples the specification of the computation from the execution of these operations on available high-performance computing systems. With this design choice, the scientific application developers (domain scientists) can focus on the algorithmic requirements using the tensor algebra interface provided by TAMM, whereas high-performance computing developers can direct their attention to various optimizations on the underlying constructs, such as efficient data distribution, optimized scheduling algorithms, and efficient use of intra-node resources (e.g., graphics processing units). The modular structure of TAMM allows it to support different hardware architectures and incorporate new algorithmic advances. We describe the TAMM framework and our approach to the sustainable development of scalable ground- and excited-state electronic structure methods. We present case studies highlighting the ease of use, including the performance and productivity gains compared to other frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Near real-time streaming analysis of big fusion data

Experiments on fusion plasmas produce high-dimensional data time series with ever-increasing magnitude and velocity, but turn-around times for analysis of this data have not kept up. For example, many data analysis tasks are often performed in a manual, ad-hoc manner some time after an experiment. In this article, we introduce the Delta framework that facilitates near real-time streaming analysis of big and fast fusion data. By streaming measurement data from fusion experiments to a high-performance compute center, Delta allows computationally expensive data analysis tasks to be performed in between plasma pulses. This article describes the modular and expandable software architecture of Delta and presents performance benchmarks of individual components as well as of an example workflow. Focusing on a streaming analysis workflow where electron cyclotron emission imaging (ECEi) data is measured at KSTAR on the National Energy Research Scientific Computing Center's (NERSC's) supercomputer we routinely observe data transfer rates of about 4 Gigabit per second. In NERSC, a demanding turbulence analysis workflow effectively utilizes multiple nodes and graphical processing units and executes them in under 5 min. We further discuss how Delta uses modern database systems and container orchestration services to provide web-based real-time data visualization. For the case of ECEi data we demonstrate how data visualizations can be augmented with outputs from machine learning models. Here, by providing session leaders and physics operators, results of higher-order data analysis using live visualizations may make more informed decisions on how to configure the machine for the next shot.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electron Linear Accelerator Additive Manufacturing

Superconducting electron linear accelerators open up new opportunities for advanced materials processing. High energy electrons penetrate deeper within materials, increase the processing depth and rate and enables production of far-from-equilibrium materials and selective processing within a material surface and subsurface. With support from the Office of Naval Research, NASA, and DoE, Mainstream Engineering commissioned a superconducting linear electron accelerator to investigate advanced materials processing and additive manufacturing. The goal of Mainstream's Electron Beam Enabled Advanced Manufacturing (EBEAM) center is to develop unique, far-from-equilibrium materials and alleviate significant technological deficiencies. We will present results of irradiating various metals and their unique material properties. Monte Carlo simulations electron beam and sample interaction were used to optimize the processing parameters and study far-from-equilibrium processing conditions. Applications include stainless steel additive manufacturing for small modular nuclear reactors and dissimilar metal bonding of corrosion-resistant cladding for next-generation molten salt reactors.

36 MATERIALS SCIENCE↗

GPU acceleration of hybrid functional calculations in the SPARC electronic structure code

We present a Graphics Processing Unit (GPU)-accelerated version of the real-space SPARC electronic structure code for performing hybrid functional calculations in generalized Kohn–Sham density functional theory. In particular, we develop a batch variant of the recently formulated Kronecker product-based linear solver for the simultaneous solution of multiple linear systems. We then develop a modular, math kernel based implementation for hybrid functionals on NVIDIA architectures, where computationally intensive operations are offloaded to the GPUs, while the remaining workload is handled by the central processing units (CPUs). Considering bulk and slab examples, we demonstrate that GPUs enable up to 8× speedup in node-hours and 80× in core-hours compared to CPU-only execution, reducing the time to solution on V100 GPUs to around 300 s for a metallic system with over 6000 electrons, and significantly reducing the computational resources required for a given wall time.

Kohn-Sham density functional theory↗

Engineering phase-frustration-induced flat bands in an aza-triangulene covalent kagome lattice

π-Conjugated covalent organic frameworks provide a versatile molecular scaffold for the realization of designer quantum nanomaterials. Strong electron–electron correlation within these artificial lattices can give rise to exotic phases of matter. Their experimental realization, however, requires precise control over orbital symmetry, charge localization and band dispersion, all arising from the effective hybridization between molecular linkers and nodes. Here we present a modular strategy for constructing diatomic kagome lattices from aza-[3]triangulene nodes, in which a D 3h -symmetric ground state is stabilized through resonance contributions from a cumulenic linker. First-principles density functional theory and scanning tunnelling spectroscopy reveal that the hybridization of a sixfold-degenerate set of edge-localized Wannier functions in the unit cell gives rise to orbital-phase-frustration-induced non-trivial flat bands. These results establish a general design principle for engineering orbital interactions in organic lattices and open a pathway towards programmable covalent-organic-framework-based quantum materials with correlated electronic ground states.

conjugated polymers↗

Directed Synthesis of Gold Nanoparticle Superstructures Using Self-Assembling Peptoids Containing Metal-Bonding N-Heterocyclic Carbenes

N-Heterocyclic carbene (NHC) ligands, with strong metal-binding affinity, offer a robust platform for constructing organic–inorganic nanohybrids with high stability and tunable properties. However, achieving precise structural control in a simple manner remains challenging. Here, we report a one-pot synthesis of nanohybrids using self-assembling peptoids functionalized with histidine-2-ylidene, which simultaneously enable peptoid assembly and NHC–metal binding. Histidine-2-ylidene-functionalized peptoids were designed to self-assemble and provide NHC binding sites, while AuNPs served as the inorganic component due to NHCs’ strong affinity for gold surfaces. The resulting peptoid-NHC@AuNPs form well-defined vesicles that are characterized by UV–vis spectroscopy, X-ray photoelectron spectroscopy, and electron microscopy. Importantly, the vesicle size and morphology can be tuned via the peptoid sequence or environmental conditions. Further experiments highlight the crucial role of the NHC sites in the formation and stabilization of these nanohybrids. This modular strategy offers a versatile route to fabricating functional NHC-based nanohybrids for potential applications in sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Massively Parallel Quantum Chemistry: A high-performance research platform for electronic structure

The Massively Parallel Quantum Chemistry (MPQC) program is a 30-year-old project that enables facile development of electronic structure methods for molecules for efficient deployment to massively parallel computing architectures. Here, we describe the historical evolution of MPQC’s design into its latest (fourth) version, the capabilities and modular architecture of today’s MPQC, and how MPQC facilitates rapid composition of new methods as well as its state-of-the-art performance on a variety of commodity and high-end distributed-memory computer platforms.

Peng, Chong↗

Search for neutrinoless β-plus-EC decay of 120 Te with CUORE

The Cryogenic Underground Observatory for Rare Events (CUORE) is a large-scale cryogenic experiment searching for neutrinoless double-beta decay (0νββ) in 130 Te. The CUORE detector is made of natural tellurium, providing the possibility of rare event searches on isotopes other than 130 Te. In this work we describe a search for neutrinoless positron-emitting electron capture (β + EC ) decay in 120 Te with a total TeO 2 exposure of 355.7 kg yr, corresponding to 0.2405 kg yr of 120 Te. Albeit 0νββ with two final-state electrons represents the most promising channel, the emission of a positron and two 511-keV γ 's make 0νβ + EC decay signature extremely clear. To fully exploit the potential offered by the detector modularity we include events with different topology and perform a simultaneous fit of five selected signal signatures. Using blinded data we extract a median exclusion sensitivity of 3.4 × 10 22 yr at 90% credibility interval (C.I.). After unblinding we find no evidence of 0νβ + EC signal and set a 90% C.I. Bayesian lower limit of 2.9 × 10 22 yr on 120 Te half-life. This result improves by an order of magnitude the existing limit from the combined analysis of CUORE-0 and Cuoricino.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Design and validation of a nanosecond short-wave infrared streak camera using gaseous detonation experiments

A custom short-wave infrared (SWIR) galvanometric streak camera was developed to provide nanosecond- scale, time-resolved optical diagnostics. The system was designed as a compact, mechanically driven alternative to traditional tube-based streak cameras, using a galvanometer mirror and multiple-reflection optical path to achieve high temporal resolution while maintaining electronic synchronization for trigger sequencing. Temporal resolution achieved 139.5 ns/px, allowing direct conversion of image-slope gradients to physical wave velocities. The instrument was validated using hydrogen-oxygen-argon detonations within a modular detonation tube, capturing transient emission structures and post-detonation decay behavior with microsecond precision. Although signal levels in filtered configurations were limited by lens transmission and detector sensitivity, the system successfully resolved intensity rise and decay characteristics across 10-60 % argon mixtures. The observed trends demonstrate the feasibility of compact galvanometer-based streak systems for high-speed SWIR imaging in reactive environments!

42 ENGINEERING↗

Ard [SWR-25-18]

A wind farm optimization suite for wind energy that is built for modular, gradient-enabled multi-disciplinary and multi-fidelity optimizations. Dig into wind farm design. An ard is a type of simple and lightweight plow, used through the single-digit centuries to prepare a farm for planting. The intent of Ard is to be a modular, full-stack multi-disciplinary optimization tool for wind farms. The problem with wind farms is that they are complicated, multi-disciplinary objects. They are aerodynamic machines, with complicated control systems, power electronic devices, social and political objects, and the core value (and cost) of complicated financial instruments. Moreover, the design of one of these aspects affects all the rest! Ard seeks to make plant-level design choices that can incorporate these different aspects and their interactions to make wind energy projects more successful.

Frontin, Cory [National Renewable Energy Laborator↗

A decision support tool for e-waste recycling operations using the hen-and-chicks bio-inspired optimization metaheuristic

E-waste from end-of-life electrical and electronic devices is one of the fastest growing waste streams from households and businesses. E-waste recycling yields environmental sustainability and economic benefits. Due to continuous changes in e-waste types and compositions, recycling businesses face challenges to optimize their operational configuration to achieve better economic and environmental performance. To help e-waste recyclers mitigate this problem, we have developed a modular decision support tool called the Comprehensive Manufacturing Assessment Tool (CMAT) that can simulate both e-waste recycling operations and economics. This tool can give valuable insights regarding the profitability of the entire operation and different e-waste types. In addition, a new bio-inspired metaheuristic optimization algorithm, hen-and-chicks optimization (HACO), was developed to assign manpower to different workstations to maximize operational efficiencies. According to the results of our case study, laptops, desktops, and computer peripherals are the three electronic waste products that produce the most profit. Our examination of the sensitivity of material prices shows that the price of steel has the most significant influence on total profit, because it is the most widely used material in the majority of electronic devices. We have released the decision support tool as open-source software under a general public license. It could be customized for other recycling industries beyond e-waste to achieve business sustainability by making their operations more efficient.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Real-time plasma monitoring framework for advanced plasma control and ML-research in DIII-D

Real-time and adaptive plasma control is crucial for robust tokamak operation, requiring sensitivity and tolerance measurements of the plasma state. This paper presents the implementation of an integrated real-time plasma monitoring framework on the DIII-D tokamak to support advanced control approaches, including machine-learning (ML) methods. The system is built on the SHIELD framework, a high-performance modular architecture that provides a unified pipeline for integrating diverse diagnostics. The framework leverages high-bandwidth digitizers, fast numerical processing, and deterministic, low-latency interconnects to stream high-fidelity data from diagnostics such as electron cyclotron emission (ECE), beam emission spectroscopy (BES), CO interferometers, and a visible tangential divertor camera (TangTV). The system’s validity is demonstrated through direct comparisons of real-time and offline data. Furthermore, we present two key applications of the developed plasma monitoring system with ML-based plasma control strategies, including real-time divertor detachment and active Alfvén Eigenmode control. As a result, this work presents a robust and scalable approach for integrating high-frequency, multidimensional diagnostics into advanced control algorithms for future fusion devices.

AI/ML↗

Advances in High-Power Wireless Charging Systems: Overview and Design Considerations

Wireless charging systems are foreseen as an effective solution to improve the convenience and safety of conventional conductive chargers. As this technology has matured, recent broad applications of wireless chargers to electrified transportation have indicated a trend toward higher power, power density, modularity, and scalability of designs. In this article, commercial systems and laboratory prototypes are reviewed, focusing mostly on the advances in high-power wireless charging systems. The recent endeavors in magnetic pad designs, compensation networks, power electronics converters, control strategies, and communication protocols are illustrated. Both stationary and dynamic (in-motion) wireless charging systems are discussed, and critical differences in their designs and applications are emphasized. On that basis, the comparisons among different solutions and design considerations are summarized to present the essential elements and technology roadmap that will be necessary to support large-scale deployment of high-power wireless charging systems. The review is concluded with the discussion of several fundamental challenges and prospects of high-power wireless power transfer (WPT) systems. Foreseen challenges include utilization of advanced materials, electric and electromagnetic field measurement and mitigation, customization, communications, power metering, and cybersecurity.

25 ENERGY STORAGE↗