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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Technoeconomic Analysis of a Novel Microwave Process to Produce Ethylene from Methane

Ethylene is a critical feedstock in industrial processes, serving as a raw material in the petrochemical industry to produce plastics and commodity chemicals. Conventional ethylene production routes are energy-intensive and contribute substantially to the carbon footprint of chemical manufacturing. In this study, an industrial-scale novel microwave process was simulated using ASPEN Plus to assess its economic viability. Technoeconomic analysis confirmed the economic competitiveness of the novel microwave process, with a levelized cost of ethylene of USD 0.51/kg compared to USD 0.56/kg for the conventional base case. Key economic drivers of the process were identified, and sensitivity analyses were conducted to evaluate their impact on project economics. Furthermore, 87.7% of the total utility consumption in the novel microwave process is electricity, highlighting its potential to contribute to the electrification of the chemical industry. The findings of this study confirm the economic feasibility of both industrial-scale microwave reactors and modular plant configurations for the production of ethylene from methane, offering a promising alternative to conventional processes.

electromagnetic radiation↗
DOE OSTI2016

Comparison of observed and simulated spatial patterns of ice microphysical processes in tropical oceanic mesoscale convective systems

To equitably compare the spatial pattern of ice microphysical processes produced by three microphysical parameterizations with each other, observations, and theory, simulations of tropical oceanic mesoscale convective systems (MCSs) in the Weather Research and Forecasting (WRF) model were forced to develop the same mesoscale circulations as observations by assimilating radial velocity data from a Doppler radar. The same general layering of microphysical processes was found in observations and simulations with deposition anywhere above the 0°C level, aggregation at and above the 0°C level, melting at and below the 0°C level, and riming near the 0°C level. Thus, this study is consistent with the layered ice microphysical pattern portrayed in previous conceptual models and indicated by dual-polarization radar data. Spatial variability of riming in the simulations suggests that riming in the midlevel inflow is related to convective-scale vertical velocity perturbations. Lastly, this study sheds light on limitations of current generally available bulk microphysical parameterizations. In each parameterization, the layers in which aggregation and riming took place were generally too thick and the frequency of riming was generally too high compared to the observations and theory. Additionally, none of the parameterizations produced similar details in every microphysical spatial pattern. Discrepancies in the patterns of microphysical processes between parameterizations likely factor into creating substantial differences in model reflectivity patterns. It is concluded that improved parameterizations of ice-phase microphysics will be essential to obtain reliable, consistent model simulations of tropical oceanic MCSs.

58 GEOSCIENCES↗
DOE OSTI2018

Simulation INsight and Analysis

Sina is a tool set for modern scientific data management that provides flexible, light-weight support of non-bulk data capture for retention in and queries against SQL and noSQL data stores. HPC simulations traditionally maintain their data in files. Extracting data of interest for subsequent analysis then requires the time-consuming process of traversing directories and scraping data from files in a variety of formats. Sina facilitates capturing relevant data during execution or post-processing of simulation runs for retention in and queries from a modern data store. The tools are sufficiently general to allow for the inclusion of new fields as scientists learn more about their data. Libraries, currently in C++ and Python, and a command line interface (CLI) are provided. Sina's flexibility starts with a general schema, in JSON, for the collection of non-bulk simulation data. JSON provides a flexible, human-readable representation of the data that of interest. Sina currently has a C++ library for simulations to write data to and read from a schema-compliant file for subsequent ingestion into one of the supported data stores. However, applications are free to write their data directly into a schema-compliant file. Python packages provide data ingestion, management, query, and export capabilities. A command line interface (CLI) provides simplified access to these features. A common application programming interface (API) is used to maintain and query data in any of the supported data stores, which are currently limited to SQL and Apache Cassandra (a column store). Tutorials, demonstrations, and examples illustrate aspects of the process using scripts and Jupyter notebooks.

Pauli, EstebanT↗
DOE OSTI2016

Radiation belt electron acceleration during the 17 March 2015 geomagnetic storm: Observations and simulations

Various physical processes are known to cause acceleration, loss, and transport of energetic electrons in the Earth's radiation belts, but their quantitative roles in different time and space need further investigation. During the largest storm over the past decade (17 March 2015), relativistic electrons experienced fairly rapid acceleration up to ~7 MeV within 2 days after an initial substantial dropout, as observed by Van Allen Probes. In the present paper, we evaluate the relative roles of various physical processes during the recovery phase of this large storm using a 3-D diffusion simulation. By quantitatively comparing the observed and simulated electron evolution, we found that chorus plays a critical role in accelerating electrons up to several MeV near the developing peak location and produces characteristic flat-top pitch angle distributions. By only including radial diffusion, the simulation underestimates the observed electron acceleration, while radial diffusion plays an important role in redistributing electrons and potentially accelerates them to even higher energies. Moreover, plasmaspheric hiss is found to provide efficient pitch angle scattering losses for hundreds of keV electrons, while its scattering effect on > 1 MeV electrons is relatively slow. Although an additional loss process is required to fully explain the overestimated electron fluxes at multi-MeV, the combined physical processes of radial diffusion and pitch angle and energy diffusion by chorus and hiss reproduce the observed electron dynamics remarkably well, suggesting that quasi-linear diffusion theory is reasonable to evaluate radiation belt electron dynamics during this big storm.

58 GEOSCIENCES↗
DOE OSTI2015

Cross-current leaching of indium from end-of-life LCD panels

Graphical abstract: Display Omitted - Highlights: • End-of-life LCD panels represent a source of indium. • Several experimental conditions for indium leaching have been assessed. • Indium is completely extracted with 2 M sulfuric acid at 80 °C for 10 min. • Cross-current leaching improves indium extraction and operating costs are lowered. • Benefits to the environment come from reduction of CO{sub 2} emissions and reagents use. - Abstract: Indium is a critical element mainly produced as a by-product of zinc mining, and it is largely used in the production process of liquid crystal display (LCD) panels. End-of-life LCDs represent a possible source of indium in the field of urban mining. In the present paper, we apply, for the first time, cross-current leaching to mobilize indium from end-of-life LCD panels. We carried out a series of treatments to leach indium. The best leaching conditions for indium were 2 M sulfuric acid at 80 °C for 10 min, which allowed us to completely mobilize indium. Taking into account the low content of indium in end-of-life LCDs, of about 100 ppm, a single step of leaching is not cost-effective. We tested 6 steps of cross-current leaching: in the first step indium leaching was complete, whereas in the second step it was in the range of 85–90%, and with 6 steps it was about 50–55%. Indium concentration in the leachate was about 35 mg/L after the first step of leaching, almost 2-fold at the second step and about 3-fold at the fifth step. Then, we hypothesized to scale up the process of cross-current leaching up to 10 steps, followed by cementation with zinc to recover indium. In this simulation, the process of indium recovery was advantageous from an economic and environmental point of view. Indeed, cross-current leaching allowed to concentrate indium, save reagents, and reduce the emission of CO{sub 2} (with 10 steps we assessed that the emission of about 90 kg CO{sub 2}-Eq. could be avoided) thanks to the recovery of indium. This new strategy represents a useful approach for secondary production of indium from waste LCD panels.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Stochastic representation and conditioning of process-based geological model by deep generative and recognition networks

Accurate and realistic geological modeling is the core of oil and gas development and production. In recent years, process-based methods are developed to produce highly realistic geological models by simulating the physical processes that reproduce the sedimentary events and develop the geometry. However, the complex dynamic processes are extremely expensive to simulate, making process-based models difficult to be conditioned to field data. In this work, we propose a comprehensive generative adversarial network framework as a machine-learning-assisted approach for mimicking the outputs of process-based geological models with fast generation. The main objective of our work is to obtain a continuous parametrization of the highly realistic process-based geological models which enables us to calibrate the models and condition the models to data. Numerical results are presented to illustrate the capability of our proposed methodology.

58 GEOSCIENCES↗
DOE OSTI2024

"Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test"

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. We explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

Jang, Kathy↗
DOE OSTI2025

BCARS Simulated Phantom Dataset for Evaluation of Processing Pipelines

Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy is a powerful label-free biological imaging technique, but the raw signal requires careful processing. The vibrationally resonant (Raman) fingerprint signal is usually small compared with instrumental noise sources and the nonresonant background (NRB) inherent in the BCARS signal. Fortunately, the NRB exhibits a systematic phase relationship with the coherent Raman response, acting as a heterodyne amplifier for the weak fingerprint signal. Due to this heterodyne effect, the Raman response can be recovered quantitatively and invariantly across different instruments, provided the NRB shape is known. Even with heterodyne amplification, the amplitudes of fingerprint signal components are often comparable to system noise. Singular value decomposition (SVD), which utilizes spatial information, is often employed for additional noise filtering. Consequently, finding optimal processing parameters to properly distinguish the NRB and Raman responses and suppress noise in the complex BCARS signal requires a reference system that realistically represents the spectral and spatial properties of BCARS signals obtained from biological samples. We present a digital tissue phantom that meets these criteria as a tool for testing candidate signal processing pipelines. The digital phantom is generated with simulated hyperspectral Raman images having system-specific noise and background characteristics. Here, we analyze phantom datasets with differing background and signal-to-noise conditions to evaluate their impact on the performance of multiple signal processing pipelines. Specifically, we investigate the application of a Butterworth filter-based routine to directly estimate the NRB from the BCARS signal. Additionally, we evaluate a Lorentzian wavelet transform as an alternative to the Hilbert transform for extracting the Raman spectrum from the BCARS signal. While we demonstrate this phantom for BCARS, it can be used for any spectroscopic Raman imaging approach.

Dixon, Jessica Z. [Georgia Institute of Technology↗
DOE OSTI2024

Noble Metals Testing on the DM1200 Pilot Melter System with AZ-101 HLW Simulants, VSL-03R3740-2, Rev. 0

This report documents the results obtained with respect to the behavior of noble metals in tests on the DM1200 HLW Pilot Melter during processing of simulated HLW AZ-101 feed. The principal objective of these tests was to collect data to determine the extent of retention of noble metals in the melter since that is an important uncertainty in determining the expected life of the WTP HLW melter. The present results constitute one part of an integrated testing strategy that has been developed to address this risk.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Large Scale GPU Accelerated PPMLR-MHD Simulations for Space Weather Forecast

PPMLR-MHD is a new magnetohydrodynamics (MHD) model used to simulate the interactions of the solar wind with the magnetosphere, which has been proved to be the key element of the space weather cause-and-effect chain process from the Sun to Earth. Compared to existing MHD methods, PPMLR-MHD achieves the advantage of high order spatial accuracy and low numerical dissipation. However, the accuracy comes at a cost. On one hand, this method requires more intensive computation. On the other hand, more boundary data is subject to be transferred during the process of simulation. In this work, we present a parallel hybrid solution of the PPMLR-MHD model implemented using the computing capabilities of both CPUs and GPUs. We demonstrate that our optimized implementation alleviates the data transfer overhead by using GPU Direct technology and can scale up to 151 processes and achieve significant performance gains by distributing the workload among the CPUs and GPUs on Titan at Oak Ridge National Laboratory. The performance results show that our implementation is fast enough to carry out highly accurate MHD simulations in real time.

Computer Science↗
DOE OSTI2024

On the relationship between precipitation extreme and local temperature over eastern China based on convection permitting simulations: roles of different moisture processes and precipitation types

The Clausius–Clapeyron (CC) scaling, which indicates a roughly 7% increase in saturated water vapor per 1 °C increase in temperature, can serve as a strong constraint linking the intensity of precipitation extremes and local temperature. However, the relationship between precipitation extreme and local temperature (referred to as the PE-T relationship) does not always follow the CC scaling and is highly dependent on climate regimes. In this study, we investigated the impacts of different moisture processes and precipitation types on the PE-T relationship over eastern China during the summertime based on convection-permitting model simulations. Consistent with observations, the simulated intensity of precipitation extremes increases with temperature at a rate close to CC (double-CC) scaling below (above) 20 °C. When the temperature exceeds 25 °C, precipitation intensity starts to drop. Precipitation extremes are mainly contributed by the stratiform, MCS (i.e., mesoscale convective system) convective, and non-MCS convective precipitation at low (< 20 °C), medium (20–25 °C), and high (> 25 °C) temperatures, respectively, suggesting that the double-CC scaling occurs when convective types become dominant, while the negative scaling at high temperatures is attributed to the reduced horizontal scale of convection. Corresponding to the reduced intensity of precipitation at high temperatures, there are stronger divergence and subsidence in the low-level atmosphere, which is probably caused by the net cooling associated with the enhanced melting and evaporation of falling hydrometeors due to the lower relative humidity in the low-level atmosphere. Overall, our findings contribute to a deeper understanding of the temperature dependence of precipitation extremes in eastern China.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Finite Element Simulation and Optimization of Gas-Quenching Process for Tool Steels

Various gas-quenching processes, including marquenching, were investigated to optimize gas-quenching processes in terms of distortion and hardness by means of numerical and experimental analyses. The temperature, microstructure, hardness, and distortion during the various gas-quenching processes of a tool steel block were simulated using a finite element method based on a coupled thermo-metallurgical–mechanical model. The predicted temperature, hardness, and distortion agreed well with the experimental data. The tool steel block (200 × 150 × 70 mm{sup 3}) quenched under 10 bar pressure of nitrogen gas (Case 2) had higher hardness due to the higher martensite fraction and larger distortion owing to the higher thermal stress induced by faster cooling, compared to the block quenched under 2 bar pressure of nitrogen gas (Case 1). The tool steel block marquenched under 10 bar pressure of nitrogen gas interrupted by isothermal holding at 500 °C (Case 3) had 30% smaller distortion with a negligible loss of hardness compared to Case 2. Furthermore, the simulation results could provide an optimized process condition to minimize distortion of the gas-quenched tool steel block while satisfying the hardness requirement.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Guidelines for Publicly Archiving Terrestrial Model Data to Enhance Usability, Intercomparison, and Synthesis

Scientific communities are increasingly publishing data to evaluate, accredit, and build on published research. However, guidelines for curating data for publication are sparse for model-related research, limiting the usability of archived simulation data. In particular, there are no established guidelines for archiving data related to terrestrial models that simulate land processes and their coupled interactions with climate. Terrestrial modelers have a unique set of challenges when publishing data due to the diversity of scientific domains, research questions, and the types and scales of simulations. Researchers in the U.S. Department of Energy’s (DOE) projects use a variety of multiscale models to advance robust predictions of terrestrial and subsurface ecosystem processes. Here, we synthesize archiving needs for data associated with different DOE models, and provide guidelines for publishing terrestrial model data components following FAIR (Findable, Accessible, Interoperable, Reusable) principles. The guidelines recommend archiving model inputs and testing data used in final simulation runs along with associated codes, workflow scripts, and metadata in public repositories. Researchers should consider archiving model outputs if they are within the storage limits of the repository. We also provide considerations for how to bundle files into different data publications with citable digital object identifiers. Finally, we identify repository features and tools that would enable storage and reuse of model data. Given the diversity of DOE terrestrial models, these guidelines are transferable to other model types and will enable efficient reuse of simulation data for purposes such as model intercomparisons, initialization, benchmarking, synthesis, and comparisons with field observations.

58 GEOSCIENCES↗
DOE OSTI2026

Membrane-based solvent extraction for the recovery of rare earths from phosphate mining process streams

This study reports on the capture of rare earth elements (REEs) from phosphate industry process streams, including phosphoric acid (PA) sludge and phosphogypsum (PG), using a membrane solvent extraction (MSX) process. While MSX has been proven effective for a relatively concentrated feed, its effectiveness for dilute REEs solutions remains unexplored. Investigated PA-sludge and PG particles contain total REEs concentrations of ∼1100 and ∼320 ppm, respectively. Acid leaching, implemented to dissolve the REEs, significantly dilutes the REEs concentration to ∼210 ppm for PA-sludge leachate and ∼60 ppm for PG leachate. These low concentrations, compounded by the higher levels of non-REE ions and radioactive species, uranium (U) and thorium (Th), poses challenges to the MSX process. Here, we demonstrated that N,N,N′,N′-tetraoctyl-diglycolamide (TODGA) selectively binds REEs from a >3 M nitric-acid leachate while effectively rejecting U and Th. Concentrations of light REEs in strip solution were doubled compared to the feed, while heavy REEs were preferentially extracted. Furthermore, >99% purity gypsum, free of U and Th, was precipitated during the acid leaching process, aiding separation by removing significant amounts of non-REEs species (e.g., calcium) prior to the MSX process. Molecular simulations support the experimental data, suggesting preferential separation of heavy over light REEs. Based on these results, a cost-effective integrated process including pretreatment, acid leaching, MSX, and wastewater treatment is proposed for the co-recovery of REEs, phosphoric acid, gypsum, and U. This study shows MSX as a technically and economically feasible process for the recovery of REEs from low-concentration process streams, offering advantages over conventional solvent extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Using MARCUS, MICRE, and COMBLE data to improve understanding and modeling of cloud, aerosol, and boundary layer processes at high-latitudes

Because it is believed general circulation (GCM) and numerical weather prediction (NWP) models underestimate shortwave radiation over the Southern Ocean (SO) due to inadequate representations of boundary layer (BL) and cloud processes, it is critical to improve our understanding of key aerosol, cloud, precipitation, and BL processes. Over the north Atlantic Ocean (NA), cold-air outbreaks are common, yet few studies of the aerosol and environmental controls of the associated convective BL clouds exist as needed to develop and evaluate GCM representations. Although processes cannot be observed, cloud and aerosol properties can be measured in-situ or remotely retrieved, which when combined with numerical simulations enable process level understanding required to improve model representations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Implications for Extraterrestrial Hydrocarbon Chemistry: Analysis of Ethylene (C{sub 2}H{sub 4}) and D4-Ethylene (C{sub 2}D{sub 4}) Ices Exposed to Ionizing Radiation via Combined Infrared Spectroscopy and Reflectron Time-of-flight Mass Spectrometry

The processing of the hydrocarbon ice, ethylene (C{sub 2}H{sub 4}/C{sub 2}D{sub 4}), via energetic electrons, thus simulating the processes in the track of galactic cosmic-ray particles, was carried out in an ultrahigh vacuum apparatus. The chemical evolution of the ices was monitored online and in situ utilizing Fourier transform infrared spectroscopy (FTIR) and during temperature programmed desorption, via a quadrupole mass spectrometer utilizing electron impact ionization (EI-QMS) and a reflectron time-of-flight mass spectrometer utilizing a photoionization source (PI-ReTOF-MS). Several previous in situ studies of ethylene ice irradiation using FTIR were substantiated with the detection of six products: [CH{sub 4} (CD{sub 4})], acetylene [C{sub 2}H{sub 2} (C{sub 2}D{sub 2})], the ethyl radical [C{sub 2}H{sub 5} (C{sub 2}D{sub 5})], ethane [C{sub 2}H{sub 6} (C{sub 2}D{sub 6})], 1-butene [C{sub 4}H{sub 8} (C{sub 4}D{sub 8})], and n -butane [C{sub 4}H{sub 10} (C{sub 4}D{sub 10})]. Contrary to previous gas phase studies, the PI-ReTOF-MS detected several groups of hydrocarbon with varying degrees of saturation: C{sub n}H{sub 2n+2} (n = 4–10), C{sub n}H{sub 2n} ( n = 2–12, 14, 16), C{sub n}H{sub 2n−2} ( n = 3–12, 14, 16), C{sub n}H{sub 2n−4} (n = 4–12, 14, 16), C{sub n}H{sub 2n−6} (n = 4–10, 12), C{sub n}H{sub 2n−8} ( n = 6–10), and C{sub n}H{sub 2n−10} ( n = 6–10). Multiple laboratory studies have shown the facile production of ethylene from methane, which is a known ice constituent in the interstellar medium. Various astrophysically interesting molecules can be associated with the groups detected here, such as allene/methylacetylene (C{sub 3}H{sub 4}) or 1, 3-butadiene (C{sub 4}H{sub 6}) and its isomers, which have been shown to lead to polycyclic aromatic hydrocarbons. Finally, several hydrocarbon groups detected here are unique to ethylene ice versus ethane ice and may provide understanding of how complex hydrocarbons form in astrophysical environments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Using Monte Carlo methods to estimate occupational dosage during 225 Ac production

Since alpha emitting isotopes such as 225 Ac, ideal for radiation treatment, are in short supply, the Medical Isotope Research and Production program at Brookhaven National Laboratory (BNL) is devel- oping new pathways for 225 Ac production. One proposed pathway is to resurrect the EBCO cyclotron at BNL to irradiate a 226 Ra target for 40 hours in a 16 MeV proton beam. Using MCNPX and CINDER software to simulate this process, we found that 1.26 Ci of 225 Ac could be produced from 300 mg of 226 Ra. To ensure workplace safety, we modeled the detailed geometry of lab 2-66C in Bldg. 801 and performed Monte Carlo simulations to estimate the radiation outside the lab as the irradiated sample is processed in a hot cell. We found the maximum dose outside the lab to be about 9 x 10 -5 rem/h. To reduce occupational dose, we recommend 200 thick steel shielding covering the sample insertion passage. These 225 Ac production runs could help cover the EBCO cyclotron's operational costs.

43 PARTICLE ACCELERATORS↗