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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Oxygen Storage Incorporated Into Net Power and the Allam–Fetvedt Oxy-Fuel sCO2 Power Cycle—Techno-Economic Analysis

Abstract With the planned future reliance on variable renewable energy, the ability to store energy for prolonged time periods will be required to reduce the disruption of market fluctuations. This paper presents a method to analyze a hybrid liquid-oxygen (LOx) storage/direct-fired supercritical carbon dioxide (sCO2) power cycle and optimize the economic performance over a diverse range of scenarios. The system utilizes a modified version of the NET Power process to produce energy when energy demand exceeds the supply while displacing much of the cost of the air separation unit (ASU) energy requirements through cryogenic storage of oxygen. The model uses marginal cost of energy data to determine the optimal times to charge and discharge the system over a given scenario. The model then applies ramp rates and other time-dependent factors to generate an economic model for the system without storage considerations. The size of the storage system is then applied to create a realistic model of the plant operation. From the real plant operation model, the amount of energy charged and discharged, the capital expenditures (CAPEX) of each system, energy costs and revenue and other parameters can be calculated. The economic parameters are then combined to calculate the net present value (NPV) of the system for the given scenario. The model was then run through the SMPSO genetic algorithm in Python for a variety of geographic regions and large-scale scenarios (high solar penetration) to maximize the NPV based on multiple parameters for each subsystem. The LOx storage requirements will also be discussed.

Engineering↗
DOE OSTI2022

Fully Distributed Multi-Material Magnetic Sensing Structures for Multiparameter DAS Applications

This dissertation demonstrates the first of its kind distributed magnetic field sensor based on a fiber optic distributed acoustic sensing (DAS) scheme. Ferromagnetic nickel and Metglas® were dispersed internally within a fiber optic preform and then drawn on an in-house fiber optic draw tower to lengths in the kilometers. Due to the close proximity of the ferromagnetic metals and fiber optic core, the magnetostrictive strain response of the ferromagnetic materials when exposed to a magnetic field would perturbate within the fiber cladding and transfer that strain, internally, to the fiber optic core. Strain resulting from the magnetostrictive effect allows the DAS based sensor to accurately translate strain into readable magnetic field data. Due to the high sensitivity seen in this sensor design, multiparameter sources, acoustic and magnetic fields, were tested and validated and a three dimensional magnetic-field vector sensor was proposed. Numerical analysis of the novel sensor design was first implemented using COMSOL Multiphysics, where inputs such as magnetostrictive element shape, size, distance, and number were first investigated. Upon optimizing system constraints, the sensor design was further modified such that single mode operation was consistent across multiple fiber draws while retaining high strain transfer from the ferromagnetic elements to the fiber optic core. Ferromagnetic material selection was evaluated as a function of the saturation magnetostriction constants and a total of 4 modules were used to fully characterize the complex physics involved in this sensor design. All fabrication and testing were performed in-house using a full scale 3-story fiber draw tower and custom environmental testing stations to imitate naturally occurring events such as magnetic or acoustic point sources. A unique stacking method was used to embed ferromagnetic nickel and Metglas® into a fiber optic preform which when combined with a custom fiber draw process resulted in consistent multi-material fibers drawn to lengths of 1-km. In-house testing facilities included different types of electromagnetic generators, in addition to a soil test bed, and an outdoor test bed which allowed 100 meters of fiber to be tested simultaneously. All tested sensors demonstrated high strain transfer capabilities on the order of 0.01-10 μϵ depending on the materials used, ferromagnetic rod number, and core to metal spacing. Due to the sensitivity of the system the difference between AC and DC was distinct, and directional magnetostriction was studied. Transverse and longitudinal magnetic wave propagation was controlled through a solenoid and rectangular Helmholtz coil, both built in-house. A three-dimensional magnetic field vector sensor was proposed due to the success of the magnetic field sensor, and a design was proposed and initially tested to validate direction as a function of field strength and distance. To summarize, this dissertation explores the first fully distributed magnetic field sensor using DAS based techniques and one of the first multi-material fiber draw processes which can produce consistent single mode fiber up to 1-km. Due to extensive FEA modeling, multiple iterations of the magnetic sensor were fully characterized and an equation describing the relationship between sensor design and strain transfer has been created and validated experimentally. Multi-parameter tests including acoustic and magnetic fields were implemented and an algorithm was developed to separate the mixed signals. Finally, a test was performed to demonstrate the feasibility of sensing magnetic fields directionally. Cumulative results demonstrate a high-quality sensor alternative to current designs which may surpass other magnetic sensors due to innate multi-parameter capabilities, in addition to the inexpensive production cost and extremely long operating lengths.

02 PETROLEUM↗
DOE OSTI2019

Optimization of Binning Parameters in the Feynman Variance-to-Mean Method for Delayed Neutron Reinterrogation

The focus of this work is to determine the optimal input parameters for analyzing active interrogation data that utilizes the physics of the delayed neutron re-interrogation technique. This work compares the signature from an active neutron measurement of a highly enriched uranium (HEU) system to an active background measurement (i.e., without the HEU item in place). The item being measured represents a 21.8 kg metal sphere of HEU (93 weight percent) assembled from a subset of the Rocky Flats (RF) uranium hemishells. The detection system consisted of two NoMAD neutron multiplicity detectors, a SNAP III neutron detector, and a Thermo Fisher P211 pulsed 14 MeV neutron source. In addition, varying analyses of the NoMAD list-mode detector data are performed to determine whether it is preferential to use a particular analysis bin size for producing Feynman histograms, selection of pulses to prevent discrepancies from buildup, or window of time during the pulsed neutron interrogation. This work is still currently ongoing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

An Initial Evaluation of the Elevated-Temperature Cyclic Properties of Optimized 316H Stainless Steel Fabricated by Powder Metallurgy Hot Isostatic Pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is a mature advanced manufacturing technology, which can consolidate metallic powder under high temperature and pressure to generate near-net shape components. This process can lower production costs and reduce component lead times for nuclear reactor construction and can be readily deployed in the near term for microreactor components because of their smaller size. The purpose of this work is to continue the evaluation of elevated-temperature cyclic material properties for PM-HIP 316H stainless steel. Prior scoping results have shown that the commercially procured PM-HIP stainless-steel materials have reduced creep-fatigue performance compared to wrought 316 stainless steels. To better understand how PM-HIP processed material properties compare to traditional manufacturing methods, additional billets of PM-HIP 316H stainless steel were procured and tested. This testing is necessary to understand how elevated-temperature properties are influenced by the PM-HIP process and what data are needed for incorporating PM HIP 316H into the American Society of Mechanical Engineers Boiler Pressure Vessel Code, Section III, Division 5 for high temperature reactor construction. Specifically, an additional PM-HIP 316H stainless steel billet with lower oxygen and nitrogen concentrations was fabricated by the Nuclear Advanced Manufacturing Research Centre of the United Kingdom and tested to understand if elevated-temperature cyclic properties can be improved. The creep-fatigue resistance of the material from this new billet did not show appreciable improvement compared to prior testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Optimizing resource allocation in Miscanthus breeding via sparse testing designs for genomic prediction

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in conventional perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse bio-based products. Increasing biomass yield will increase profitability and environmental benefits, so it is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed implementing sparse testing designs. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; G×E interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for G×E interaction consistently presented the highest PA and the lowest MSE: for CNN (PA: ~0.77, MSE: ~0.5) and YDY (PA: ~0.70, MSE: ~1.3) while for TCM and AIL these ranged from ~0.28 to 0.41 and ~1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

Miscanthus sacchariflorus (MSA)↗
DOE OSTI2023

Cost analysis of hydrogen production by high-temperature solid oxide electrolysis

In this study, we estimate construction and operation costs of gigawatt-scale solid oxide electrolysis (SOE) facilities for producing high purity hydrogen gas from water. Manufacturing and assembly costs for two types of SOE cell stacks are estimated using a detailed design for manufacture and assembly (DFMA®) analysis. Modular balance of plant (BOP) process equipment is designed and sized with Aspen®, and cost estimated using equipment vendor quotes. Factory and on-site assembly and installation costs for SOEC stack and BOP equipment integration into modular SOE process units are calculated using a simplified DFMA® method. Total stack costs on a stack input power (SIP) basis reduce to <$100/kW e DC SIP for >500 MW e DC SIP /year production rates with electrode cermet, interconnects, and high-temperature heat treatments dominating the total cost. Integration of stacks with larger BOP equipment operating at higher pressures offers ~36% cost reduction in total facility capital cost due to an economies of physical scale effect since BOP equipment comprises >50% of facility costs. Optimized H 2 prices decrease from ~$\$$4/kgH 2 to ~$\$$2/kgH 2 for 1 GWe DCSIP facilities using $\$$0.025/kWh electricity price. All costs are reported in 2021 US dollars.

08 HYDROGEN↗
DOE OSTI2025

EMPDF : inferring the Milky Way mass with data-driven distribution function in phase space

We introduce the emPDF (empirical distribution function), a novel dynamical modelling method that infers the gravitational potential from kinematic tracers with optimal statistical efficiency under the minimal assumption of steady state. emPDF determines the best-fitting potential by maximizing the similarity between instantaneous kinematics and the time-averaged phase-space distribution function (DF), which is empirically constructed from observation upon the theoretical foundation of oPDF (Han et al. 2016). This approach eliminates the need for presumed functional forms of DFs or orbit libraries required by conventional DF- or orbit-based methods. emPDF stands out for its flexibility, efficiency, and capability in handling observational effects, making it preferable to the popular Jeans equation or other minimal assumption methods, especially for the Milky Way (MW) outer halo where tracers often have limited sample size and poor data quality. We apply emPDF to infer the MW mass profile using Gaia DR3 data of satellite galaxies and globular clusters, obtaining enclosed masses of M (,r) = 26±8, 46±8, 90±13⁠, and 149±40 x 10 10 M ⊙ at r = 30, 50, 100⁠, and 200 kpc, respectively. These are consistent with the updated constraints from simulation-informed DF fitting (Li et al. 2020). While the simulation-informed DF offers superior precision owing to the additional information extracted from simulations, emPDF is independent of such supplementary knowledge and applicable to general tracer populations. emPDF is currently implemented for tracers with complete 6D kinematics within spherical potentials, but it can potentially be extended to address more general problems.

Astrophysics of Galaxies (astro-ph.GA)↗
DOE OSTI2024

Quantum Simulation of the First-Quantized Pauli-Fierz Hamiltonian

We provide an explicit recursive divide-and-conquer approach for simulating quantum dynamics and derive a discrete first-quantized nonrelativistic QED Hamiltonian based on the many-particle Pauli-Fierz Hamiltonian. We apply this recursive divide-and-conquer algorithm to this Hamiltonian and compare it to a concrete simulation algorithm that uses qubitization. Our divide-and-conquer algorithm, using lowest-order Trotterization, scales for fixed grid spacing as O ~ ( Λ N 2 η 2 t 2 / ϵ ) for grid size N , η particles, simulation time t , field cutoff Λ , and error ϵ . Our qubitization algorithm scales as O ~ ( N ( η + N ) ( η + Λ 2 ) t log ( 1 / ϵ ) ) . This shows that even a naive partitioning and low-order splitting formula can yield, through our divide-and-conquer formalism, superior scaling to qubitization for large Λ . We compare the relative costs of these two algorithms on systems that are relevant for applications such as the spontaneous emission of photons and the photoionization of electrons. We observe that for different parameter regimes, one method can be favored over the other. Finally, we give new algorithmic and circuit-level techniques for gate optimization, including a new way of implementing a group of multicontrolled- X gates that can be used for better analysis of circuit cost. Published by the American Physical Society 2024

Mukhopadhyay, Priyanka (ORCID:0000000164639100)↗
DOE OSTI2024

Finding MIDDLE Ground: Scalable and Secure Distributed Learning

Edge computing methods allow devices to efficiently train a high-performing, robust, and personalized model for predictive tasks. However, these methods succumb to privacy and scalability concerns such as adversarial data recovery and expensive model communication. Furthermore, edge computing methods unrealistically assume that all devices train an identical model. In practice, edge devices have varying computational and memory constraints which may not allow certain devices to have the space or speed to train a specific model. To overcome these issues, we propose MIDDLE: a model independent distributed learning algorithm which allows heterogeneous edge devices to assist each other’s training while communicating only non-sensitive information. MIDDLE unlocks the ability for edge devices, regardless of computational or memory constraints, to assist each other even with completely different model architectures. Furthermore, MIDDLE does not require model or gradient communication which greatly reduces communication size and time. We prove that MIDDLE attains the optimal convergence rate O(1/sqrt(TM)) of stochastic gradient descent for convex and non-convex smooth optimization (for total iterations T and batch size M). Finally, our experimental results demonstrate that MIDDLE (even in non-IID data settings) attains robust and high-performing models without model or gradient communication.

Bornstein, Marc I.↗
DOE OSTI2023

Probing Nanocrystal Optical Properties in the Limit of Single Nanocrystals

The Bawendi lab has been at the forefront of the synthesis and characterization of the fundamental photo-physics of quantum confined systems for the past three decades. During this DoE project, our progress has been enabled by both our expertise in single nanocrystal (NC) photoluminescence (PL) spectroscopy as well as our extensive knowledge of the synthetic optimization of various NC semiconductors - all of this forming an efficient feedback loop between characterization and synthesis. Our research in this project has focused on the development and application of novel single emitter optical tools for the characterization of colloidal quantum dots (CQDs) which are semiconducting NCs with size-tunable quantum confined electronic structure. CQDs have had a significant commercial impact as display technologies. They are also commercially available as fluorescent biological markers. CQDs are being investigated as a potential material for photovoltaic or optical sensing applications and as emerging optical quantum materials. We have focused on the fundamental understanding of the optical properties of NCs through the development of novel spectroscopic methods at the single emitter level, including understanding how synthetic and environmental heterogeneities influence NC properties. A major advance in our research has been the development of novel photon resolved correlation spectroscopies that allow us to extract the physics of photo-excited single NCs with unprecedented time and spectral resolution from the photon stream of individual NCs.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Small Fatigue Crack Growth Mechanisms and Interfacial Stability in Cold-Spray 6061 Aluminum Alloys and Coatings

Cold-spray-processed aluminum alloys have static mechanical properties superior to those of aerospace cast alloys, and similar to those of their wrought counterparts, making them good candidates for structural applications. However, their broad and confident use relies upon systematic fatigue crack growth studies to investigate and demonstrate the materials' performance in critical high-integrity components. In this work, the fatigue crack growth behavior in early stages (small crack growth regime) was investigated for cold-spray processed 6061 aluminum alloys and coatings, at stress ratio R = 0.1, in room temperature laboratory air. The effects of the characteristic microstructure and initial flaw size on the fatigue crack growth response were systematically examined, and the crack growth mechanisms at the microstructural scale were established and compared to those of long cracks. The mechanical interfacial stability of coatings was examined in cold-spray 6061-rolled 6061-T6 couples. An original method of quantifying the deposition-substrate interfacial strength, and correlating it to the response under cyclic loading via crack-interface stability maps, was developed. The proposed methodology is based on combined scratch testing and fracture mechanics formulations, and failure at the coating-substrate interface can be predicted for any crack growth scenario under cyclic loading. The method can be broadly used for the design and optimization of cold-spray and other coatings, as well as in structural repair.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Simulation Model of Microsphere Distribution for Selective Internal Radiation Therapy Agrees With Observations

Purpose: To perform a detailed analysis of microsphere distribution in biopsy material from a patient treated with {sup 90}Y-labeled resin spheres and characterize microsphere distribution in the hepatic artery tree, and to construct a novel dichotomous bifurcation model for microsphere deposits and evaluate its accuracy in simulating the observed microsphere deposits. Methods and Materials: Our virtual model consisted of arteries that successively branched into 2 new generations of arteries at 20 nodes. The artery diameter exponentially decreased from the lowest generation to the highest generation. Three variable parameters were optimized to obtain concordance between simulations and measure microsphere distributions: an artery coefficient of variation (ACV) for the diameter of all artery generations and the microsphere flow distribution at the nodes; a hepatic tree distribution volume (HDV) for the artery tree; and an artery diameter reduction (ADR) parameter. The model was tested against previously measured activity concentrations in 84 biopsies from the liver of 1 patient. In 16 of 84 biopsies, the microsphere distribution regarding cluster size and localization in the artery tree was determined via light microscopy of 30-μm sections (mean concentration, 14 microspheres/mg; distributions divided into 3 groups with mean microsphere concentrations of 4.6, 14, and 28 microspheres/mg). Results: Single spheres and small clusters were observed in terminal arterioles, whereas large clusters, up to 450 microspheres, were observed in larger arterioles. For 14 microspheres/mg, the optimized parameter values were ACV=0.35, HDV = 50 cm{sup 3}, and ADR=6 μm. For 4.6 microspheres/mg, ACV and ADR decreased to 0.26 and 0 μm, respectively, whereas HDV increased to 130 cm{sup 3}. The opposite trend was observed for 28 microspheres/mg: ACV = 0.49, HDV = 20 cm{sup 3}, and ADR = 8 μm. Conclusion: Simulations and measurements reveal that microsphere clusters are larger and more common in volumes with high microsphere concentrations and indicate that the spatial distribution of the artery tree must be considered in estimates of microsphere distributions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

High performance porous Si anode enabled by an organic-solvent assisted etching process

Silicon (Si) is a promising anode for the next generation of lithium-ion batteries, but its large volume changes (~300 %) during cycling hindered its practical applications. One method to improve its stability is to etch micron sized Si/SiO 2 particles to form porous Si (p-Si) and accommodate volume changes internally. However, the conventional HF etching method generates excess gas/heat and is difficult to scale up. Herein, we developed an organic-solvent-assisted HF etching process (O-HF) using a mixture of benzene and saturated HF aqueous solution. The organic solvent can be preferentially absorbed on the surface of Si/SiO 2 powder so etching rate of SiO 2 can be controlled to avoid rapid gas/heat generation. This method can also prevent over-etching of Si by minimizing direct contact/react between water and newly exposed Si. Si||NMC622 cells using carbon coated p-Si particles prepared by optimized O-HF etching process demonstrate a capacity retention of 82.0 % after 500 cycles, which is much better than those prepared by conventional HF etching (73.7 %). The thickness of Si anode increases only ~10 % during the initial lithiation, which is comparable with those of graphite anode. In conclusion, the O-HF etching strategy developed in this work can also be applied to the etching of a broad range of materials.

HF etching↗
DOE OSTI2016

SU-G-TeP1-06: Fast GPU Framework for Four-Dimensional Monte Carlo in Adaptive Intensity Modulated Proton Therapy (IMPT) for Mobile Tumors

Purpose: To demonstrate the feasibility of fast Monte Carlo (MC) treatment planning and verification using four-dimensional CT (4DCT) for adaptive IMPT for lung cancer patients. Methods: A validated GPU MC code, gPMC, has been linked to the patient database at our institution and employed to compute the dose-influence matrices (Dij) on the planning CT (pCT). The pCT is an average of the respiratory motion of the patient. The Dijs and patient structures were fed to the optimizer to calculate a treatment plan. To validate the plan against motion, a 4D dose distribution averaged over the possible starting phases is calculated using the 4DCT and a model of the time structure of the delivered spot map. The dose is accumulated using vector maps created by a GPU-accelerated deformable image registration program (DIR) from each phase of the 4DCT to the reference phase using the B-spline method. Calculation of the Dij matrices and the DIR are performed on a cluster, with each field and vector map calculated in parallel. Results: The Dij production takes ∼3.5s per beamlet for 10e6 protons, depending on the energy and the CT size. Generating a plan with 4D simulation of 1000 spots in 4 fields takes approximately 1h. To test the framework, IMPT plans for 10 lung cancer patients were generated for validation. Differences between the planned and the delivered dose of 19% in dose to some organs at risk and 1.4/21.1% in target mean dose/homogeneity with respect to the plan were observed, suggesting potential for improvement if adaptation is considered. Conclusion: A fast MC treatment planning framework has been developed that allows reliable plan design and verification for mobile targets and adaptation of treatment plans. This will significantly impact treatments for lung tumors, as 4D-MC dose calculations can now become part of planning strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations

The method of successive generations used in Monte Carlo simulations of nuclear reactor models is known to suffer from intergenerational correlation between the spatial locations of fission sites. One consequence of the spatial correlation is that the convergence rate of the variance of the mean for a tally becomes worse than O(N–1). In this work, we consider how the true variance can be minimized given a total amount of work available as a function of the number of source particles per generation, the number of active/discarded generations, and the number of independent simulations. We demonstrate through both analysis and simulation that under certain conditions the solution time for highly correlated reactor problems may be significantly reduced either by running an ensemble of multiple independent simulations or simply by increasing the generation size to the extent that it is practical. However, if too many simulations or too large a generation size is used, the large fraction of source particles discarded can result in an increase in variance. We also show that there is a strong incentive to reduce the number of generations discarded through some source convergence acceleration technique. Furthermore, we discuss the efficient execution of large simulations on a parallel computer; we argue that several practical considerations favor using an ensemble of independent simulations over a single simulation with very large generation size.

correlation↗
DOE OSTI2024

Improving I/O-aware Workflow Scheduling via Data Flow Characterization and trade-off Analysis

The scientific computing paradigm has transitioned from compute-intensive to I/O-intensive and memory-intensive in the past decade, especially when data-driven science has become common practice. Numerous empirical I/O-aware scheduling optimizations have been developed by incorporating I/O capacity and bandwidth as constraints into scheduling. Unfortunately, there is a lack of data flow (I/O) characterization tool and an understanding of trade-offs between concurrency, locality, and I/O bandwidth. To bridge the gap, this work 1) presents a set of descriptors to characterize, organize, and visualize I/O profiles, including flow size, I/O bandwidth, and operation count, which group data flows by I/O types, tasks, and files; 2) proposes an I/O Roofline model-based trade-off analysis to find the optimal trade-off between flow operational intensity, concurrency, and flow performance. The I/O descriptors generate useful insights into complicated I/O behaviors, suggesting distinct concurrency, storage, and scheduling to be used by types, tasks, and files. The proposed trade-off analysis guides scheduling decisions that generate resource assignment with the best flow parallelism. We evaluate our I/O-aware scheduling methodology on a highly I/O-intensive workflow–1000 Genomes. The experimental results demonstrate speedups of up to 2.4× compared to the state-of-the- art methods.

Guo, Luanzheng [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2025

Fabrication of a Nb-Ti Superconducting Closed-Loop Coil for the Next-Generation 45 GHz ECR Ion Source MARS-D

Electron Cyclotron Resonance Ion Sources (ECRISs) that utilize Nb-Ti superconducting coils for 28 GHz frequencies have been operating effectively for over twenty years. However, transitioning to higher frequencies demands stronger magnetic fields, and the conventional racetrack-and-solenoid ECRIS structures have reached their maximum capability with Nb-Ti. To address this, a Mixed Axial and Radial field System Demonstrator (MARS-D) is being developed at Lawrence Berkeley National Laboratory (LBNL). This system features an innovative Closed-Loop Coil (CLC) design that optimizes the use of the conductor fields, enabling the application of Nb-Ti in the next-generation 45 GHz ECRISs. The fabrication of the hexagonal CLC is particularly challenging due to its complex winding path and shape, the stiffness of the Nb-Ti superconducting wire, and the small bending radius. Here, to address these challenges, a series of unique fixtures and tools, as well as a pre-over-bending method, were developed for winding the CLC. To validate the winding fixtures, tools, procedures, and materials used in the coil assembly, a 4-layer practice CLC was wound, epoxy-impregnated, and then cold-tested using liquid nitrogen. The full-size MARS-D CLC is in the process of winding. This paper presents the structure of the MARS-D CLC, the winding fixtures and tools, the winding procedures, the quality control, the impregnation, the test results, and the potential future improvements.

ECR ion sources↗
DOE OSTI2021

Additive manufacturing of high-strength multiphase nanostructures in the binary Ni–Nb system for the discovery of new types of superalloys

Abstract Ni-based superalloys have been studied extensively due to their impressive mechanical properties, including strength and creep resistance at high temperatures. Growing interest surrounding additive manufacturing (AM) methods has led to recent investigations of alloys that are traditionally difficult to process, including Ni-based superalloys. Recent work has shown that AM methods enable high-throughput materials discovery and optimization of difficult- or impractical-to-process alloys, including those with high or even majority refractory element compositions. This work focuses on AM-enabled investigations of composition-dependent mechanical and microstructural properties for Ni–Nb binary alloys. Specifically, we report on the mechanical behavior of compositionally-graded Ni x Nb 1− x and uniform composition Ni 59.5 Nb 40.5 specimens made with AM. The AM fabrication process resulted in extraordinarily high strength, attributed to the formation of a dual-phase microstructure consisting of δ-Ni 3 Nb and µ-Ni 6 Nb 7 intermetallic compounds with nanostructured and multimodal grain size and eutectic lamellar spacing. Graphic Abstract

Jones, M. R.↗