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At least 235 records · Page 13

SUBTASK 1.6 – BASIN ELECTRIC CARBON STORAGE RESEARCH PROJECT: NOVEL MONITORING TECHNIQUES

The Energy & Environmental Research Center (EERC) conducted baseline activities associated with an applied research project at Basin Electric Power Cooperative’s (Basin’s) carbon capture and storage (CCS) site in Beulah, North Dakota, to establish novel carbon storage-monitoring techniques as commercial methods under Cooperative Agreement No. DE-FE0024233, Subtask 1.6. The following report summarizes the baseline activities performed and briefly describes the subsequent (operational monitoring) activities that have been proposed to the U.S. Department of Energy (DOE) as part of the overall project to develop and demonstrate novel monitoring techniques at North America’s largest permitted CCS operation. Dakota Gasification Company (DGC), a wholly owned subsidiary of Basin, owns and operates the Great Plains Synfuels Plant (GPSP) approximately 5 miles northwest of the town of Beulah, North Dakota (Figure 1). In 2023, DGC received approval from the North Dakota Industrial Commission (NDIC) to develop a storage facility on-site for injecting a stream of carbon dioxide (CO2) captured from GPSP. DGC will transport the captured CO2 stream with approximately 6.8 miles of transmission lines that extend north of GPSP and inject >1 million tonnes (MMt) of CO2 annually (>1 MMt/yr) over a 12-year period with up to six underground injection control (UIC) Class VI-compliant injection wells completed in the Broom Creek Formation, a predominantly sandstone reservoir and saline aquifer underlying GPSP. The Broom Creek Formation lies approximately 5900 feet (ft) below ground surface (bgs) at GPSP. The commercial scale (i.e., >1 MMt/yr) of DGC’s permitted carbon storage project is ideal for developing and testing the novel monitoring techniques included within Subtask 1.6. The goals of this project are to demonstrate 1) the cost-effectiveness of novel monitoring technologies included as part of this research, 2) technology capability for tracking the CO2 plume and/or associated pressure response in the subsurface and monitoring out-of-zone migration, and 3) compliance with UIC Class VI program requirements. The research activities proposed for the overall project include 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; 5) advanced wellbore-monitoring methods; 6) deployment of an AIM monitoring network; 7) EM monitoring of CO2 with real-time data processing; 8) continued seasonal drone-based surveillance studies; 9) seismic monitoring with passive and active surveys; and 10) wellbore monitoring with nuclear magnetic resonance (NMR) for near-surface characterization. Completion of Activities 1.0–5.0 (baseline activities) are described in this report. Upon authorization of funding by DOE, the EERC will initiate Activities 6.0– 10.0 (operational monitoring activities). Current state-of-the-art (SOA) carbon storage-monitoring techniques require countless labor hours dedicated to the acquisition of data. Once data are gathered, these SOA techniques often rely on commercial facilities to process raw data from the field. However, it is anticipated that next-generation monitoring techniques, such as those being demonstrated, will lower acquisition footprints, be less operationally intensive, and improve data acquisition efficiencies. These new techniques are more conducive to the application of machine learning, artificial intelligence, and automation, thus providing a pathway for integration into active control systems, informing site operability, and improving the integration of data for future CCS projects across the United States. Additionally, reclaimed and active mining lands are present within the project site, creating a unique opportunity to demonstrate the effectiveness of remote sensing and surface-based geophysics monitoring techniques at similar project sites that may include disturbed, unconsolidated, or actively excavated near-surface environments. The efforts included in the overall project will produce necessary designs, learnings, and data acquired during the baseline and operational monitoring periods that are necessary for time-lapse demonstration and validation of the described monitoring techniques. In addition, it is anticipated that the monitoring technologies included in this study will be compliant with UIC Class VI requirements to enable the potential for implementation at other CCS sites across the United States.

42 ENGINEERING↗

In-Situ Bioleaching of Manganese by Dissimilatory Reduction

This report describes the development of a biological leaching process for recovery of manganese from low-grade ores, with a high degree of selectivity against contaminants such as iron. This results in the production of manganese that is suitable for battery manufacture and other electrical applications. The leaching process makes use of a community of metal reducing organisms that solubilize manganese at a pH of approximately 4.5. These organisms are nourished by simple organic molecules such as acetate that are generated by decomposition of biomass. A series of long-term laboratory experiments were carried out to determine the necessary operating parameters, followed by construction of a small pilot plant processing approximately 100 kg of ore. This pilot unit was operated for two years, demonstrating the ability to consistently produce high-grade manganese at a commercially viable rate.

25 ENERGY STORAGE↗

NLO SMEFT electroweak corrections to Higgs boson decays to four leptons in the narrow width approximation

Some of the most precise measurements of Higgs boson couplings are from the Higgs decays to 4 leptons, where deviations from the Standard Model predictions can be quantified in the framework of the Standard Model effective field theory (SMEFT). In this work, we present a complete next-to-leading order (NLO) SMEFT electroweak calculation of the rate for H → ℓ + ℓ − Z which we combine with the NLO SMEFT result for Z → ℓ + ℓ − to obtain the NLO rate for the H → 4 lepton process in the narrow width approximation. The NLO calculation provides sensitivity to a wide range of SMEFT operators that do not contribute to the rate at lowest order and demonstrates the importance of including correlations between the effects of different operators when extracting limits on SMEFT parameters. We show that the extraction of the Higgs trilinear coupling from the decay H → ℓ + ℓ − Z , Z → ℓ + ℓ − in the narrow width approximation strongly depends on the contributions of other operators that first occur at NLO. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spectral-density estimation with the Gaussian integral transform

The spectral-density operator $\hat{ρ}(ω) = δ(ω–\hat{H})$ plays a central role in linear response theory as its expectation value, the dynamical response function, can be used to compute scattering cross sections. In this work, we describe a near optimal quantum algorithm providing an approximation to the spectral density with energy resolution $\Delta$ and error $\epsilon$ using $O(\sqrt{\text{log}_2 (1/ε)[\text{log}_2 (1 / Δ) + \text{log}_2 (1/ε)]/ Δ)}$ operations. This is achieved without using expensive approximations to the time-evolution operator, but instead exploiting qubitization to implement an approximate Gaussian integral transform of the spectral density. Finally, we also describe appropriate error metrics to assess the quality of the spectral function approximations more generally.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimizing multigrid reduction-in-time and Parareal coarse-grid operators for linear advection

Parallel-in-time methods, such as multigrid reduction-in-time (MGRIT) and Parareal, provide an attractive option for increasing concurrency when simulating time-dependent partial differential equations (PDEs) in modern high-performance computing environments. While these techniques have been very successful for parabolic equations, it has often been observed that their performance suffers dramatically when applied to advection-dominated problems or purely hyperbolic PDEs using standard rediscretization approaches on coarse grids. In this paper, we apply MGRIT or Parareal to the constant-coefficient linear advection equation, appealing to existing convergence theory to provide insight into the typically nonscalable or even divergent behavior of these solvers for this problem. To overcome these failings, we replace rediscretization on coarse grids with improved coarse-grid operators that are computed by applying optimization techniques to approximately minimize error estimates from the convergence theory. Therefore, one of our main findings is that, in order to obtain fast convergence as for parabolic problems, coarse-grid operators should take into account the behavior of the hyperbolic problem by tracking the characteristic curves. Our approach is tested for schemes of various orders using explicit or implicit Runge–Kutta methods combined with upwind-finite-difference spatial discretizations. In all cases, we obtain scalable convergence in just a handful of iterations, with parallel tests also showing significant speed-ups over sequential time-stepping.

97 MATHEMATICS AND COMPUTING↗

Quapprox: A Framework for Benchmarking the Approximability of Variational Quantum Circuit

Most of the existing quantum neural network models, such as variational quantum circuits (VQCs), are limited in their ability to explore the non-linear relationships in input data. This gradually becomes the main obstacle for it to tackle realistic applications, such as natural language processing, medical image processing, and wireless communications. Recently, there have emerged research efforts that enable VQCs to perform non-linear operations. However, it is still unclear on the approximability of a given VQC (i.e., the order of non-linearity that can be handled by a specified design). In response to this issue, we developed an automated tool designed to benchmark the approximation of a given VQC. The proposed tool will generate a set of synthetic datasets with different orders of non-linearity and train the given VQC on these datasets to estimate their approximability. Our experiments benchmark VQCs with different designs, where we know their theoretic approximability. We then show that the proposed tool can precisely estimate the approximability, which is consistent with the theoretic value, indicating that the proposed tool can be used for benchmarking the approximability of a given quantum circuit for learning tasks.

artificial intelligence↗

Godiva IV central cavity neutron environment characterization with threshold neutron detectors

Godiva IV is a cylindrical fast burst reactor comprised of approximately 65 kg of highly enriched uranium that is operated by Los Alamos National Laboratory and sited at the National Criticality Experiments Research Center at the Nevada National Security Site in Nevada in the United States. Godiva IV is typically operated at delayed critical and in the regime spanning from sub-prompt to super-prompt bursts. Godiva IV is used for sample irradiations, criticality safety demonstrations, dosimetry studies, and for studying super-prompt behavior. In preparation for both an upcoming experiment to reduce uncertainties in the prompt fission spectrum for 235U using threshold neutron detectors, and for future research using Godiva IV, it was desired to exercise the process of the selection of threshold neutron detectors/activation foils, radiation metrology, and the subsequent adjustment of the neutron spectrum. For this exercise, nine high purity threshold neutron detectors/activation foils were irradiated in a Godiva IV burst. The foils were then analyzed using a high-purity germanium detector in the NCERC counting laboratory to determine end of irradiation specific activities for available IRDFF-II reactions. This work summarizes the Godiva IV foil irradiation, radiation metrology results, and adjusted neutron spectrum. The results of this exercise ultimately characterized the neutron environment inside the sample irradiation cavity inside Godiva IV to a higher degree than previously performed, informed decisions for the upcoming larger scale experiment, and will inform future neutron spectrum characterizations at NCERC.

Whitman, Nicholas H.↗

Mechanistic and Mitigation-Strategy Insights into NaCl and CaCl 2 Contamination of Proton-Exchange-Membrane Water Electrolysis Using Continuum Modeling

Cationic contaminants are detrimental to proton-exchange-membrane water electrolyzers (PEMWEs). To obtain insight, a 1-D, nonisothermal, multiphase continuum cell model including cationic contamination is developed. Simulations of steady-state cell performance predict decreased performance due to an increase in kinetic overpotential associated with the hydrogen-evolution reaction, which was attributed to decreased protonic-activity within the cathode catalyst layer from proton supplantation with contaminant cations. The accumulation and extent of cation exchange in the cathode catalyst layer depends on the operating current density due to migration. Simulations of cell recovery of potential suggest that a contaminated cell can recover approximately 78% (450 mV) with 24 h of constant current density operation at 2 A cm –2 , with higher current densities accelerating reduced recovery times. Parametric studies show that anode-side acidification at lower current densities inhibit cation contaminant adsorption, and cathode-side acidification at larger current densities facilitate the expulsion of adsorbed cations; for a cathode-side pH of 6 and 5, the cell can recover an additional 10% and 100% performance, respectively. Overall, the model serves as a framework for modeling other aspects of PEMWE systems to address durability and performance aspects, which can assist in improving the viability of the technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

QuadConv: Quadrature-based convolutions with applications to non-uniform PDE data compression

We present a new convolution layer for deep learning architectures which we call QuadConv — an approximation to continuous convolution via quadrature. Our operator is developed explicitly for use on non-uniform, mesh-based data, and accomplishes this by learning a continuous kernel that can be sampled at arbitrary locations. Moreover, the construction of our operator admits an efficient implementation which we detail and construct. As an experimental validation of our operator, we consider the task of compressing partial differential equation (PDE) simulation data from fixed meshes. Here, we show that QuadConv can match the performance of standard discrete convolutions on uniform grid data by comparing a QuadConv autoencoder (QCAE) to a standard convolutional autoencoder (CAE). Further, we show that the QCAE can maintain this accuracy even on non-uniform data. In both cases, QuadConv also outperforms alternative unstructured convolution methods such as graph convolution.

Compression↗

Blending low-carbon hydrogen with natural gas: Impact on energy and life cycle emissions in natural gas pipelines

In this article, hydrogen (H 2 ) is considered an alternative energy carrier to reduce greenhouse gas (GHG) emissions related to power and heat generation. A quantitative analysis was conducted to estimate the energy intensity and GHG emissions associated with the transportation of NG/H 2 mixture in high-pressure transmission pipeline, considering blending ratios up to 100% of low-carbon H 2 . The life cycle emissions were obtained by including upstream supply chain emissions, compression and transportation emissions, and end use combustion emissions of the NG/ H 2 blend. This study accounts for global warming potential of fugitive methane and H 2 emissions associated with pipeline transportation of the blend in the life cycle analysis. A significant reduction in the overall life cycle GHG emissions can be achieved when delivering the same volume throughput but at a reduced energy flow to end users. However, to maintain the nominal energy throughput of the pipeline regardless of the H 2 mole fraction, a maximum reduction of about 6% is obtained as the H 2 mole fraction in the blend will be practically limited to approximately 30% H 2 when the pipeline operates at capacity.

03 NATURAL GAS↗

Dry in-pile fracture test (DRIFT) for separate-effects validation of ceramic fuel fracture models

Fracture is an important component of nuclear fuel behavior, and significant efforts have been invested into developing fuel performance models that are capable of accurately representing fracture. Usable data on the process of fracture propagation in nuclear fuel under realistic service conditions are very limited. To address this need, a series of separate-effects experiments were developed and performed at Idaho National Laboratory's Transient Reactor Test (TREAT) facility. These experiments employ a heat sink to radially remove heat from the fuel in a manner that approximates the effect of coolant in an operating light-water reactor (LWR). The test holder for these experiments is known as the Dry In-pile Fracture Test (DRIFT). A series of experiments employing DRIFT and TREAT were performed to provide data on the extent and nature of fracture in fresh fuel at various points during a ramp to full power. Novel aspects of these experiments include the way they employ a heat sink to replicate steady-state LWR conditions, as well as the use of fiber optic sensors for in-reactor thermal instrumentation. Details on the development of this experiment, experimental conditions, and resulting data (including in situ thermal measurements and post-irradiation imaging of fracture) are provided in this work. LWR-equivalent powers ranging from 10 to 25 kW/m were tested using this apparatus. Cracking was visible at all power levels, with increasing cracking extent as the power level increased, although there was little difference in the cracking between the two highest-power tests, which had LWR-equivalent powers of 20 and 25 kW/m.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A layered Prussian blue analogue as fast-charging negative electrode material for lithium-ion batteries

The simultaneous achievement of fast-charging and high specific capacity remains a critical challenge for lithium-ion battery negative electrodes. Here we report a layered manganese-based Prussian blue analogue, synthesized through vacancy control and subsequent thermal transformation. As a conversion-type negative electrode, this material exhibits high-rate performance, delivering a specific capacity of 510 mAh g −1 at a specific current of 8 A g −1 , and operates at a moderate average voltage of approximately 1.2 V vs. Li/Li + , which mitigates lithium plating risks. This high-rate capability stems from the analogue’s specific linkage configurations, which facilitate a high content of active transition metal and strong Li+ adsorption at nitrogen sites. The high transition metal content enables a high reversible capacity, while strong Li + adsorption promotes an efficient initial crystalline-to-amorphous transformation. This process induces dynamically reversible component migration during subsequent cycling, thereby enhancing conversion reaction kinetics. Our findings provide insights into the application of Prussian blue analogues as fast-charging negative electrode materials. The development of fast-charging and high-capacity negative electrodes is critical for advanced lithium-ion batteries. Here, authors use a vacancy engineering strategy to develop a layered Prussian blue analogue with competitive rate capability, delivering a specific capacity of 510 mAh g −1 at a specific current of 8 A g −1 .

25 ENERGY STORAGE↗

Plasma-arc lamp high heat flux cycling exposure of neutron irradiated tungsten materials

Thick plate, unalloyed W was neutron irradiated in the High Flux Isotope Reactor (HFIR) at 550 °C to a fast fluence of 1.24 × 10 25 n m -2 E > 0.1 MeV (~0.24 dpa). Unirradiated and irradiated specimens of the material were high heat flux (HHF) tested in the Plasma Arc Lamp (PAL) facility. The PAL uses a high-power photon source to provide a broad and even heat distribution on the sample surface. To simulate on/off cycling of normal operating plasma, the samples were exposed to approximately 800 cycles at 4.73 MW m -2 absorbed heat flux (incident heat fluxes of 10.95 MW m -2 ). Additionally, after PAL exposure, slight changes were observed on the surfaces of the samples with SEM. The samples showed some annealing in the near surface polished region, but they were all below the damage threshold for cracking or other destructive features. The PAL has a large parameter space for future testing. The use of the HFIR and PAL to sequentially expose neutron irradiated samples to HHF will be a powerful tool for understanding materials behavior in a fusion-like environment.

36 MATERIALS SCIENCE↗

Biotic Interactions Are More Important than Propagule Pressure in Microbial Community Invasions

ABSTRACT Microbial probiotics are intended to improve functions in diverse ecosystems, yet probiotics often fail to establish in a preexisting microbiome. This is a species invasion problem. The relative importance of the two major factors controlling establishment in this context—propagule pressure (inoculation dose and frequency) and biotic interactions (composition of introduced and resident communities)—is unknown. We tested the effect of these factors in driving microbial composition and functioning following 12 microbial community invasions (e.g., introductions of many microbial invaders) in microcosms. Ecosystem functioning over a 30-day postinvasion period was assessed by measuring activity (respiration) and environment modification (dissolved organic carbon abundance). To test the dependence on environmental context, experiments were performed in two resource environments. In both environments, biotic interactions were more important than propagule pressure in driving microbial composition and community function, but the magnitude of effect varied by environment. Successful invaders comprised approximately 8% of the total number of operational taxonomic units (OTUs). Bacteria were better invaders than fungi, with average relative abundances of 7.4% ± 6.8% and 1.5% ± 1.4% of OTUs, respectively. Common bacterial invaders were associated with stress response traits. The most resilient bacterial and fungal families, in other words, those least impacted by invasions, were linked to antimicrobial resistance or production traits. Illuminating the principles that determine community composition and functioning following microbial invasions is key to efficient community engineering. IMPORTANCE With increasing frequency, humans are introducing new microbes into preexisting microbiomes to alter functioning. Example applications include modification of microflora in human guts for better health and those of soil for food security and/or climate management. Probiotic applications are often approached as trial-and-error endeavors and have mixed outcomes. We propose that increased success in microbiome engineering may be achieved with a better understanding of microbial invasions. We conducted a microbial community invasion experiment to test the relative importance of propagule pressure and biotic interactions in driving microbial community composition and ecosystem functioning in microcosms. We found that biotic interactions were more important than propagule pressure in determining the impact of microbial invasions. Furthermore, the principles for community engineering vary among organismal groups (bacteria versus fungi).

59 BASIC BIOLOGICAL SCIENCES↗

The study of high-frequency pick-ups for electron beam position measurements in the AWAKE common beamline

The common beamline of the AWAKE experiment at CERN involves the co-propagation of two particle beams: protons with 48 nC bunch charge and 250 ps bunch length, and electrons with up to 600 pC bunch charge and approximately 4 ps bunch length. The existing operational beam position monitors at AWAKE cannot measure the electron bunches whilst the more-intense proton bunches are present, due to their low operating frequency. In order to try to address this challenge, two different types of high-frequency pick-ups were studied, a conical-shaped button pick-up and a Cherenkov diffraction radiation-based pick-up designed to operate at around 30 GHz. Both devices were installed at AWAKE and were connected to two identical read-out systems designed by TRIUMF. This contribution presents and discusses the results obtained from beam-based measurements during the current experimental year.

43 PARTICLE ACCELERATORS↗

Transportation analysis and related design optimization of the Fermilab high-beta 650 MHz cryomodule

The Proton Improvement Plan-II (PIP-II) at Fermi National Accelerator Laboratory (FNAL) will create a new and vastly improved accelerator, which will be the source of high-energy particles for the experiments taking place at FNAL. The new linear accelerator (LINAC) contains several types of cryomodules, which are individual particle accelerators. The last cryomodule in the LINAC will be the High-Beta 650 (HB650), which will operate at 650 MHz. Each module is approximately 15 meters in length and 1.5 meters wide, weighs 13 tonnes, and shares many design features with three of the other cryomodules. The HB650 consists of two primary sections, the outer vacuum vessel and the components that reside within it, which will be cooled to cryogenic temperatures – the cold mass. Once assembly is complete at FNAL, it will be transported to one of three places: another location at FNAL, another national laboratory within the continental United States, or to a scientific partner in Europe. Any excitation the module experiences, such as going over rough roads when on a semitrailer, can create high stresses in components and cause failure if severe enough. Additionally, any delicate components with low resonant frequencies that match the excitation spectrum could achieve resonance, potentially causing a fatigue failure by repeated flexing. To ensure the successful transportation of the HB650, a transport analysis utilizing ANSYS simulation software has been performed on major subassemblies, as well as analysis of the subassemblies as a combined system. The optimization of components, design of support structures, and overall increasing of the lowest resonant frequencies have resulted in a cryomodule that will be better equipped to handle transportation and any large impact loads that come with it.

43 PARTICLE ACCELERATORS↗

Reassessing the Market—Computation Interface to Enhance Grid Security and Efficiency

The goal of this project is to reconsider core market and reliability processes that can potentially yield to transformative advances in power grid security, reliability, and efficiency. Current electric power market designs are strongly a function of computing capabilities and limitations that were available in the mid-to-late 1990s, circa deregulation. This includes constructs such as: (1) a 2-tiered day-ahead/real-time market construct; and (2) linearized (“DC”) real power flow approximations in dispatch and pricing. At that time, state-of-the-art computational capabilities could at the limit address deterministic mixed-integer programming formulations of unit commitment (UC) and linear programming formulations of economic dispatch (ED) at limited fidelity and scale. Such constraints forced limited look-ahead time-horizons, crude approximations of AC power flow physics and operations, and artificial partitioning between day-ahead markets, hour(s)-ahead reliability processes, and real-time markets. Consequently, these limitations have resulted in limited security and reliability with increasing out-of-market payments, particularly as uncertainty associated with renewables and distributed energy resources grows.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simulations Supporting the Development of Northstar's Indirect Beam Parameters Monitoring System

NorthStar Medical Radioisotopes, LLC is planning to produce the important medical radioisotope molybdenum-99 (Mo-99), the parent of technetium-99m (Tc-99m), through photonuclear reactions in molybdenum-100 (Mo-100). In this approach, a target comprising multiple thin disks of enriched molybdenum metal is bombarded with a 40-MeV electron beam. Electrons impinged on the molybdenum target produce bremsstrahlung X-rays that cause the nuclear reaction. Because enriched Mo-100 is expensive, there is a desire to utilize as much beam power as possible to achieve maximum production yield and minimize the size of the target. This requirement leads to very high beam power density (and heat deposition in the target), which creates challenging requirements for the cooling of the target. The critical part of the target is the target window. It separates the high-pressure helium cooled target from the vacuum beamline and the subject of structural and thermal stress. The temperature of the target window is proportional to the energy density deposited by the beam, so it is critical to maintain the desired beam profile on the target window. The feasibility of indirectly monitoring the maximum energy density of the beam on the beam window through beam losses at the main collimator (Collimator) before the production target was verified. A model of the NorthStar beam transport line was constructed for this purpose using MAD-X and Tao/Bmad codes. Beam optics were computed for the standard operational scenario, followed by an investigation involving approximately 400 cases with parameter variations in the last tuning quadrupoles. This was done to assess the correlation between losses in the collimator and the peak energy density on the target. We developed a model to explore the potential application of Optical transition radiation (OTR) for controlling beam parameters in the NorthStar beam delivery system. This model was based on a generic formula derived from the fundamental solution of the inhomogeneous wave equation of the vector potential, and allowed us to consider various surfaces, even those with irregular or random features, using numerical integration. We applied the model to OTR generated by relativistic electrons impacting an Inconel® 718 beam window. We examined cases with different levels of the window’s surface roughness, ranging from 0.5 to 3.0 microns of root square mean (RMS) deviation. The results of the OTR simulations provided distributions of OTR photons that can be used to study the limitations of optical systems for controlling beam parameters.

43 PARTICLE ACCELERATORS↗