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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Ultra-High Vacuum Outgassing Characterization of Thermally Processed Low-Carbon Steel for Advanced Particle Accelerator and Gravitational Wave Detector Applications

This dissertation investigated AISI 1020 low-carbon steel as an alternative vacuum chamber material to conventional stainless steel for ultra-high vacuum (UHV) and extreme-high vacuum (XHV) applications. After a 400 °C/48 h bake, AISI 1020 tube chambers achieved a hydrogen outgassing rate of 2.4 × 10¿¹6 Torr·L·s¿¹·cm¿², approximately 2,300 times lower than the prebaked 316L stainless-steel comparator, among the lowest hydrogen outgassing rates ever reported for an uncoated metallic vacuum chamber. Bare and magnetite-coated AISI 1020 chambers were then compared using throughput and rate-of-rise methods. The magnetite coating yielded 5× lower water outgassing at room temperature, but this advantage disappeared after 80 °C baking. After full thermal conditioning (400 °C/48 h prebake followed by 150 °C/96 h and 200 °C/110 h), bare steel achieved 25× lower hydrogen outgassing than the magnetite-coated chamber (9.6 × 10¿¹6 Torr·L·s¿¹·cm¿²) and >99% H2 purity with carbon species below RGA detection. Monte Carlo molecular flow simulations of a CEBAF photogun beamline (96 scenarios) showed that replacing 304L stainless steel with AISI 1020 reduces equilibrium H2 pressure by a factor of 833; a single 304L electrode contributes 98.8% of the gas load despite occupying only 9.1% of the internal surface area. A 500-m Einstein Telescope beampipe screening showed that corrugated bellows contribute 18% of the gas load from only 0.7% of the surface area. A five-model adsorption isotherm framework applied to 22 pumpdown datasets (164 fits with AR(1)-GLS correction) established that the experimental protocol, not the material, controls isotherm identifiability: Dubinin–Radushkevich wins isothermal pipe pumpdowns; Langmuir wins thermally dominated chamber bakes. Cross-dataset joint fitting of the AISI 1020 pipe pumpdowns yielded an H2 diffusion activation energy Ed = 7.24 ± 1.28 kcal·mol¿¹, consistent with trap dominated diffusion in commercial low-carbon steels. Two companion innovations were developed: a Variable Conductance Device (VCD, patent pending IDF-00723) for XHV outgassing measurement, and VacuumDesignerPro (VDP), a MATLAB-based design tool validated against LIGO benchmarks.

Al-Allaq, Aiman H [Old Dominion University]↗
DOE OSTI2025

Charting the state of GEMs in microalgae: progress, challenges, and innovations

Genome-scale metabolic models (GEMs) provide a systems-level framework for understanding and engineering microalgal metabolism. This review explores the evolution of GEMs in microalgae, highlighting advances in light modeling, automation, and multi-omics integration. Special emphasis is placed on Chlamydomonas reinhardtii as a model species. Limitations of current models, particularly for microalgae, are discussed, alongside promising developments in dynamic modeling and machine learning. Together, these innovations chart a path toward more predictive, adaptable GEMs that can accelerate biotechnological applications of microalgae in sustainable production systems.

Plant Sciences↗
DOE OSTI2021

Progress Towards Goals Outlined in the 2014 Decadal Vision

The Atmospheric Radiation Measurement (ARM) user facility published its first decadal vision document in 2014 (U.S. DOE 2014a). The overarching vision described in that document was to develop an integrated observation-modeling framework to accelerate the application of ARM observations for process studies and model applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

First Detection of 120 GeV Protons with Superconducting Nanowire Detectors

We report the test results for a 120 GeV proton beam incident on superconducting nanowire particle detectors of various wire sizes. NbN devices with the same sensitive area were fabricated with different wire widths and tested at a temperature of 3 K. The relative detection efficiency was extracted from bias current scans for each device. The results demonstrate efficient detection of high energy protons for wire widths less than 400 nm. These results are particularly relevant for novel applications at accelerator facilities, such as the Electron-Ion Collider, where cryogenic cooling is readily available.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Electrospinner Upgrades for Nanofiber Production

Electrospinning is an inexpensive and flexible method for producing nanofibers. Nanofibers are highly adaptable with potential applications in accelerator target systems, air and water filtration, and biomedicine. This project aims to upgrade and test an existing roll-to-roll electrospinner that is more economical for industrial nanofiber production. Varying the diameter of nanofiber can change its functional properties. The current unit cannot adjust spinneret-collector separation, which determines nanofiber diameter. The electro-spinneret channel also does not have lateral adjustment capabilities for precise alignment. Lastly, the viscosities of our polymer solutions have not been quantified. Solution injection into the channel is presently inconsistent because of imperfect nozzle sizing, resulting in waste and decreased efficiency. Modeling was done with Siemens NX CAD software, and viscosity was measured using a Brookfield DVE-LV viscometer. A dual scissor lift design for channel displacement, powered by a dual-shaft DC motor coupled to precision lead screws, was approved and construction was started. Preliminary channel modifications also were initiated. Going forward, the scissor lift system will be integrated and evaluated with our electrospinner, along with further channel modifications. Viscosity measurements of polyvinyldimethylformamide (PVDF) were recorded with inconsistent results due to inadequate testing conditions. Future viscosity trials must be completed in accordance with testing requirements. The optimization and commercialization of roll-to-roll electrospinner units can make nanofiber production more feasible for many new industries and consumer products.

Black, Niko↗
DOE OSTI2020

Design of a multichannel photonic crystal dielectric laser accelerator

To be useful for most scientific and medical applications, compact particle accelerators will require much higher average current than enabled by current architectures. For this purpose, we propose a photonic crystal architecture for a dielectric laser accelerator, referred to as a multi-input multi-output silicon accelerator (MIMOSA), that enables simultaneous acceleration of multiple electron beams, increasing the total electron throughput by at least 1 order of magnitude. To achieve this, we show that the photonic crystal must support a mode at the Γ point in reciprocal space, with a normalized frequency equal to the normalized speed of the phase-matched electron. We show that the figure of merit of the MIMOSA can be inferred from the eigenmodes of the corresponding infinitely periodic structure, which provides a powerful approach to design such devices. Additionally, we extend the MIMOSA architecture to electron deflectors and other electron manipulation functionalities. These additional functionalities, combined with the increased electron throughput of these devices, permit all-optical on-chip manipulation of electron beams in a fully integrated architecture compatible with current fabrication technologies, which opens the way to unconventional electron beam shaping, imaging, and radiation generation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Building an EPA Class VI Permit Application

Summary To accelerate the commercialization of carbon capture and storage (CCS), the US Department of Energy (US DOE) is building on decades of characterization efforts and pilot-scale projects through their CarbonSAFE program. Administered through their National Energy Technology Laboratory, this program seeks to bring fully integrated projects to the sector that can store more than 50 million tonnes of CO2 over a 30-year period. The program, which was enacted before the enhancement of Internal Revenue Code Section 45Q, is in the capture assessment, characterization, and permitting phase. The objectives of this paper are to discuss (a) the injection permitting requirements of the CarbonSAFE projects; (b) information gathering in support of the permit; (c) the timelines of field development and permit-related activities; (d) the major technical components of the field development plan; and (e) early feedback from the regulators toward acceptance of the permit. In Mississippi, more than 30,000 acres have been characterized by six deep characterization wells, a deep groundwater well, and 92 line miles of 2D seismic as part of the CarbonSAFE Project ECO2S. During the acquisition of seismic data, all receiver lines were live, which resulted in the generation of a pseudo-3D seismic design. The incorporation of a 3D seismic survey was not included as part of this project due to logistical difficulties presented by the undulating, wooded surface terrain. A suite of openhole geophysical logs was taken from each well, allowing for a detailed interpretation of prospective storage reservoirs and confining intervals to complement the analysis carried out on the 290 ft of a whole core that was cut through the prospective confining zone and storage reservoir. The detailed geologic and reservoir data were assembled and entered into a 3D model to assess the injection capacity and the area of review (AoR). This information fed into the detailed corrective action, monitoring, testing, and postinjection site care (PISC) modeling. The results have been exceptional. The geologic assessment has revealed three primary storage targets, ranging in depth from 3,500 ft to 6,000 ft. These storage reservoirs net 1,300 ft of sandstone, with mean porosity and permeability of 29% and 3.6 darcies, respectively. Together, these reservoirs have storage capacities that may exceed 20 million tonnes per square mile, making this a gigatonne prospect. Forward modeling of the project resulted in an AoR of 16 sq miles, injecting about 8000 t/d, for 30 years, via two deep injection wells. The excellent confining characteristics of the caprock, relatively simple geologic structure, and lack of historical well drilling activity in this area provide excellent containment of the injected CO2. Based on this work, the project has proposed 20 years of PISC. To date, only two US CO2 injection permits have been granted. These projects relied on a singular capture point feeding a singular sequestration point (source to sink), and considerations have not been made to garner CO2 emissions from other industrial sources. The Kemper County Storage Complex is a first-of-its-kind storage hub concept that looks to develop an area capable of storing significant quantities of CO2 from the region. Also, this work will show how characterization efforts, geological and numerical modeling efforts, and plan development were constructed in support of permit and incentives acceptance.

Energy & Fuels↗
DOE OSTI2023

A Regulatory Approach to Accelerated Deployment for New Material or Applications in Advanced Reactors

New advanced reactor developers may embark on deploying materials in novel and unique environments where a material’s long-term performance may be in question or unknown. In many cases, sufficient test data may not exist for the material in the desired application, or that no prescript or applicable regulatory testing requirements are available to demonstrate the safety of the application explicitly. This study endeavors to develop the framework for a regulatory and technical approach for safe and predictable accelerated materials use in advanced reactors guided by 10 CFR Part 50.43(e)(1), Advanced Reactor Design Criteria contained in Regulatory Guide 1.232, and Reliability Integrity Management Program (RIM) principles.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Perspectives on the generation of electron beams from plasma-based accelerators and their near and long term applications

This article first gives the authors' perspectives on how the field of plasma-based acceleration (PBA) developed and how the current experiments, theory, and simulations are motivated by long term applications of PBA to a future linear collider and an x-ray free electron laser. Here, we then focus on some early applications that will likely emerge from PBA research such as electron beam radiotherapy, directional but incoherent x-ray beams for science and technology, near single cycle continuously tunable infrared pulses for spectroscopy, and non-perturbative quantum electrodynamics enabled by PBA electron beams. In our opinion, these near term applications could be developed within the next decade with a concerted effort by the community.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Simulation of the thermoelectric effect in a multi-metallic superconducting cavity

Superconducting radio-frequency accelerating cavities made with different material layers, such as copper, Nb or Nb₃Sn, are susceptible to thermoelectric effects due to differences in Seebeck coefficients between the metals. A temperature gradient across the surfaces can drive thermoelectric currents, which may impact the cavity performance. A layered Cu/Nb/Nb3Sn single-cell cavity was tested with cryocoolers in 2022. Three heaters were mounted on the cavity surface at different locations and three single-axis cryogenic fluxgate magnetometers were attached close to the cavity equator. A linear increase in the magnetic field was measured while increasing the heaters' power. The cavity setup was analyzed with COMSOL and the results showed a trend similar to that observed in the experiment. This contribution details the approach chosen for the simulation and some of the challenges encountered.

Accelerator Physics↗
DOE OSTI2026

Spin-transparent storage rings for quantum computing

Spin-transparent storage rings, where any spin direction repeats after one full turn, can be used in conjunction with ion traps as a new quantum computing platform [1]. Advantages of spin-transparent rings for quantum computing include: large numbers of stored qubits; long quantum coherence times of up to several hours; long storage lifetimes; and room temperature operation. These exceptional qualities mean rings could provide a scalable way to implement algorithms with deep complexity requiring many quantum operations while simultaneously providing a large number of qubits. This new platform where the qubit has long quantum coherence time can also be used as a quantum sensor or a part of a quantum memory.

Accelerator Physics↗
DOE OSTI2025

Energy recovery proton linear accelerator

High-power proton linear accelerators have important applications in both scientific research and industry. However, the operation of such accelerators with megawatt-level beam power is expensive and limits the broad availability of these facilities. In this Letter, we propose a novel energy recovery proton linear accelerator in which the final GeV-level proton beam is reinjected into the linear accelerator from the accelerator exit and is decelerated in the same accelerator down to about 2 MeV, close to the initial beam energy. This substantially reduces the power consumption of the proton linear accelerator and also avoids the need for a high-power beam dump. We demonstrate this concept through self-consistent simulations and show that the beam-beam effect between the forward-accelerating beam and the backward-decelerating beam would not be a limiting factor for the proposed concept. A potential application of this concept to an electron-ion collider based on energy recovery electron and ion accelerators is discussed.

Energy recovery linacs↗
DOE OSTI2025

Outlook towards deployable continual learning for particle accelerators

Particle accelerators are high power complex machines. To ensure uninterrupted operation of these machines, thousands of pieces of equipment need to be synchronized, which requires addressing many challenges including design, optimization and control, anomaly detection and machine protection. With recent advancements, machine learning (ML) holds promise to assist in more advance prognostics, optimization, and control. While ML based solutions have been developed for several applications in particle accelerators, only few have reached deployment and even fewer to long term usage, due to particle accelerator data distribution drifts caused by changes in both measurable and non-measurable parameters. In this paper, we identify some of the key areas within particle accelerators where continual learning can allow maintenance of ML model performance with distribution drifts. Particularly, we first discuss existing applications of ML in particle accelerators, and their limitations due to distribution drift. Next, we review existing continual learning techniques and investigate their potential applications to address data distribution drifts in accelerators. By identifying the opportunities and challenges in applying continual learning, this paper seeks to open up the new field and inspire more research efforts towards deployable continual learning for particle accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Compiler-Driven FPGA Virtualization with SYNERGY

FPGAs are increasingly common in modern applications, and cloud providers now support on-demand FPGA acceleration in datacenters. Applications in datacenters run on virtual infrastructure, where consolidation, multi-tenancy, and workload migration enable economies of scale that are fundamental to the provider's business. However, a general strategy for virtualizing FPGAs has yet to emerge. While manufacturers struggle with hardware-based approaches, we propose a compiler/runtime-based solution called Synergy. We show a compiler transformation for Verilog programs that produces code able to yield control to software atsub-clock-tickgranularity according to the semantics of the original program. Synergy uses this property to efficiently support core virtualization primitives: suspend and resume, program migration, and spatial/temporal multiplexing, on hardware which is availabletoday.We use Synergy to virtualize FPGA workloads across a cluster of Intel SoCs and Xilinx FPGAs on Amazon F1. The workloads require no modification, run within 3--4x of unvirtualized performance, and incur a modest increase in FPGA fabric usage.

Computer Science↗
DOE OSTI2023

Machine-Learning Assisted Identification of Battery Life Models

Predictive battery life models are commonly utilized to extrapolate degradation trends observed during accelerated aging tests for simulation of degradation in real-world applications. Thus, fitting accelerated aging data as accurately as possible and with low uncertainty is crucial for making believable projections of battery lifetime, but it is challenging to identify algebraic expressions that accurately fit multivariate degradation trends. A review of models published in literature reveal some common expressions for fitting calendar aging data, which is only dependent on temperature and state-of-charge, but no consistency across many models for fitting cycle aging data, indicating the need for a statistically rigorous data driven approach for developing empirical models. This talk will describe a machine-learning assisted method for identification of predictive battery life models utilizing bilevel optimization and symbolic regression. Bilevel optimization with cross-validation is used to statistically determine cell- and stress-dependent model parameters, while symbolic regression identifies both linear and multiplicative candidate expressions to predict stress-dependent degradation rates by selecting low-order subsets of features from a generated feature library. Because model expressions are identified empirically, it is crucial to ensure resulting models behave according to physical expectations, so the stability of models for interpolation or extrapolation is interrogated qualitatively through simulation and quantitatively through cross-validation and uncertainty quantification via bootstrap resampling. This model identification approach substantially improves upon models identified purely using expert judgement in terms of both accuracy and uncertainty. Model simulation and validation is then conducted by deriving a state-equation form of the predictive model, enabling simulation of battery aging under dynamic stresses. This enables validation of the predictive battery model on lab-based tests with varying conditions or on drive-cycle or application-cycle testing protocols. Parameter uncertainty can be carried forward into model simulation, giving lifetime estimates and confidence windows for cell- or system-level lifetime. The financial impact of battery model uncertainty can be estimated by incorporating uncertainty into a technoeconomic model.

battery↗
DOE OSTI2023

High Q SRF cavity-based searches for beyond the standard model physics

The SRF technology developed for accelerators can be successfully applied to new applications, including quantum computing, dark matter searches and beyond the standard model physics. The ultra-high quality factor of SRF cavities can enable unprecedented sensitivity in fields outside of the usual accelerator applications, for examples fundamental and beyond the standard model physics. Applications of SRF cavities for gravitational waves searches are also being investigated. The SQMS Physics and Sensing thrust is working on this effort as it strives to combine SRF cavities with QIS, with a focus on BSM and fundamental physics.

Berlin, A.↗