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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 OSTI2025

Universal method for the optimization of HDC coating uniformity on non-planar, non-stationary substrates for inertial confinement fusion targets

The thickness uniformity of chemical vapor deposited (CVD) diamond coatings on non-planar, non-stationary substrates depends on both the intrinsic instantaneous coating thickness distribution (ICTD) of the coating conditions used and, if applicable, on the frequency of substrate reorientation. While important for many CVD diamond applications, the relative impact of the ICTD and substrate reorientation on the coating thickness uniformity has not been studied. In this work, we systematically investigate the effect of these factors for microwave-plasma chemical vapor deposition (MPCVD) of diamond (referred to as high density carbon (HDC) in the inertial confinement fusion (ICF) community) coatings on spherical, rolling substrates. This coating technique is used to fabricate capsules for ICF experiments, which require extreme coating uniformity with <0.3 % thickness variation (so-called Mode 1 or M1) to ensure symmetric compression of imploding targets. To extract the otherwise unobservable reorientation timescale (Δt), Monte Carlo simulations were performed using experimental ICTD data as input. This combined approach confirms scaling relationships between the substrate reorientation timescale as well as coating thickness and coating uniformity, as expected from a 3D random walk. Simulations confirm that M1 is Rayleigh-distributed and scales as (Δt) 1/2 , consistent with the randomization of two angles that determine orientation of a sphere. We also demonstrate that, under the conditions studied, Δt is the dominant factor in determining thickness uniformity while the intrinsic ICTD has minimal impact. Finally, experiments show that Δt can be affected by total batch size under constant agitation conditions due to space constraints that limit the capsule reorientation kinetics. In conclusion, this study highlights the utility of a combined experiment-simulation approach as a general methodology for understanding and improving coating uniformity on non-planar, non-stationary substrates.

Capsule↗
DOE OSTI2025

An extension of the localized artificial diffusivity method for immiscible and high density ratio flows

The localized artificial diffusivity (LAD) method is widely regarded as the preferred multi-material regularization scheme for the compact finite difference method, because it is conservative, easy to implement, and generally robust for a wide range of multi-material problems. However, traditional LAD methods face significant challenges when applied to flows with large density ratios and when maintaining thermodynamic equilibrium across material interfaces. These limitations arise from the formulation of the artificial diffusivity flux and the reliance on enthalpy diffusion for interface regularization. Additionally, traditional LAD methods struggle to ensure stability under large density ratio conditions, fail to maintain a finite interface thickness, and are therefore unsuitable for modeling immiscible interfaces. Here, in this work, we discuss the origins of these issues in traditional LAD methods and propose modifications which enable the simulation of large density ratio and immiscible flows. The proposed method targets the artificial diffusion fluxes at gradients and ringing in the volume fraction, rather than the mass fraction in traditional methods, to consistently regularize large density ratio interfaces. Furthermore, the proposed method introduces an artificial bulk density diffusion term to enforce equilibrium conditions across interfaces. To address the challenge of modeling immiscible flows, a conservative diffuse interface term is incorporated into the formulation to ensure a finite interface thickness. Specific consideration is taken in the design of the method to ensure that these crucial properties are maintained for N -material flows. The effectiveness of the proposed method is demonstrated through a series of canonical test cases, and its accuracy is validated by comparison with experimental data on micro-bubble collapse in water. These results highlight the method’s robustness and its ability to overcome the limitations of traditional LAD approaches.

Artificial diffusivity↗
DOE OSTI2025

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite↗
DOE OSTI2025

Laser wavelength dependence of laser imprint

In laser direct-drive inertial confinement fusion, laser imprint is one of the major causes of degradation in target performance through its seeding of hydrodynamic instabilities. Early experiments and simulations have shown that laser imprint could be mitigated with a longer laser wavelength because of its lower critical density and longer conduction zone. Building upon this work, we explore a scenario where the laser wavelength during the picket pulse differs from that of the main pulse in order to gain the benefit of reduced imprint, while avoiding losses in drive coupling efficiency or an increase in laser-plasma instabilities. A series of 2D radiation-hydrodynamic simulations, which test three different laser wavelengths for the picket pulse, has been performed, where the intensity of the picket pulse is adjusted in order to maintain the same implosion adiabat. A detailed analysis of the growth of the mass density modulations at the ablation front over a large range of mode numbers confirms that the laser imprint can be mitigated with a picket pulse operating at a longer wavelength than the main pulse because of the longer conduction zone and enhanced thermal smoothing. The amplitude of the ablation front modulations is found to be lower for all mode numbers, which reduces the seeding of the Rayleigh–Taylor instability without affecting the mode growth rates.

Fourier analysis↗
DOE OSTI2025

MLSPICE: Machine Learning based SPICE Modeling Platform for Power Magnetics

Electrical power converters are critical to a wide range of applications ranging from renewable integration to transportation electrification, and can be a key factor determining the size, weight, and efficiency of energy conversion systems. Magnetic components are typically the largest and least efficient components in power electronics. While there have been major strides in the modeling and analysis of power semiconductor devices and circuit simulations, the necessary advances in the design of power magnetics have lagged. In this project, we have transformed the modeling and design of power magnetics with machine learning enabled methods and catalyze simultaneous disruptive improvements for ML-based power electronics design tools. A fully automated open-source machine learning based magnetics modeling platform – the MagNet project - with innovations in full stack have been developed to greatly accelerate the design process and provide new insights to magnetic material and geometry design. The ARPA-E funded MagNet platform contains three major building blocks: 1) a ML-Integrated Data Acquisition System (MIDAS): a highly automated data acquisition testbed which is capable of measuring a large number of magnetic cores with a wide range of electrical circuit excitations; 2) a ML-integrated Core Loss Model (MICLM): a machine-learning trained modeling method for modeling the core loss and saturation effects of magnetic materials for arbitrary excitation waveforms; 3) ML-guided Magnetics SPICE Simulation Tool (PMSPICE): a fully integrated CAD tool which can simulate the magnetics in SPICE. It can help the designers to quickly model the linear and non-linear characteristics of magnetic components and evaluate their behavior in SPICE simulations. The developed MagNet system has fully demonstrated the proposed performance target and has been open sourced to the entire power electronics community to advance the modeling and design of power magnetics from many different angles.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Roughrider Carbon Storage Hub (Final Report)

The Roughrider Carbon Storage Hub was a 2-year project (October 2023 – September 2025) conducted by the Energy & Environmental Research Center (EERC) focused on advancing the feasibility of a commercial-scale carbon dioxide (CO 2 ) geologic storage hub in McKenzie County, North Dakota. The project’s objective was to investigate the potential that stacked storage complexes (multiple deep saline formations) can safely and economically store at least 50 million tonnes of CO 2 within 30 years. The captured CO 2 would be sourced from industrial emitters including project partner ONEOK, Inc.’s gas-processing plants and a planned gas-to-liquids facility. Drilling of the Roughrider 1 stratigraphic test well (14,979-ft total depth) was completed in November 2024. The wellbore intersected four candidate storage formations: Inyan Kara, Broom Creek, Mission Canyon, and Black Island–Deadwood. Operational challenges, including a stuck drill string, were resolved without long-term impact. A comprehensive logging and coring program was conducted, followed by successful well abandonment and site reclamation. Over 660 ft of 4-in. whole core was retrieved. Core plug samples were processed and analyzed for petrophysical and geochemical properties. Results confirmed promising porosity and permeability in the Inyan Kara and Broom Creek Formations and removal of the Mission Canyon and Black Island–Deadwood horizons from further investigation. Data derived from the logging and coring program were used to improve initial geologic models built from legacy data. CO 2 injection simulations showed that the Inyan Kara alone can feasibly store the target mass of CO 2 . Because of subtle differences in geologic structure and porosity trends between the formations, a stacked storage scenario using the Broom Creek and Inyan Kara Formations resulted in a larger overall plume area than using the Inyan Kara alone. Preliminary CO 2 pipeline routes from the industrial sources were mapped utilizing existing rights of way and evaluated for capacity and cost using U.S. Department of Energy Office of Fossil Energy and Carbon Management/National Energy Technology Laboratory models and U.S. Environmental Protection Agency emissions data. Integrating capture, transport, and storage cost estimates with policy incentives (e.g., 45Q credits) provided a total cost-per-ton analysis. Results indicate that the small scale of the volumes to be transported over the cumulative large distances does not support the project’s financial viability. However, the groundwork laid during this project from geological, regulatory, and social perspectives positions the Roughrider hub site as a promising candidate for commercial carbon storage in North Dakota, especially if the economy of scale is introduced for CO 2 transportation to the hub site.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Bridging the length scales in ionic separations via data-driving machine learning

We pursued a data science driven machine learning (ML) approach that blended molecular scale attributes informed from molecular dynamics (MD) simulation and materials properties to the selectivity and energy efficiency in targeted ionic separations using electric fields. The model mixtures investigated for ionic separations are pH sensitive and include organic acids, silica and boron, transition metals, such as copper and chromium. There were two major research thrusts of this project. Firstly, we investigated surrogate models and deep learning that relate material chemistries and structures to selective transport of ionic species under applied electric fields. Secondly we investigated how the bipolar junction interfacial design and water dissociation catalyst in bipolar membranes affect reverse bias polarization behavior and pH modulation in deionization platforms as a function of the platform operating parameters (e.g., cell voltage, residence time, and salt feed concentration). As a result of this work, we also were able to start a new direction, namely ML models for molecular design of surfactants.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Direct Feed High-Level Waste APPS Model Glass Testing (DFHLW APPS) Matrix

This report summarizes the data collected during the batching and melting of the Direct Feed High-Level Waste APPS Model Glass Matrix (DFHLW APPS) to serve as a quality-assured validation of the Aspen Process Performance Simulation (APPS) formulation method. Of 15 glasses tested, 12 satisfied all target property constraints. Two glasses, APPS-05 and -06, formed nepheline on canister centerline cooling heat-treatment and failed the Product Consistency Test response limits. Glass APPS-07-2 formed unacceptably high concentrations of crystals (primarily Na3Nd(PO4)2) when heat treated at 950 °C. All other glasses were found to be satisfactory. The measured property values were compared to predicted values from a set of current models. In many cases the current models were found to be inadequate for design of DFHLW glasses. These models are being adjusted to correct for mispredictions. Other models, e.g., density, toxicity characteristic leaching procedure, and sulfur solubility, are adequate for formulation of DFHLW glasses.

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

Machine Learning‐Augmented Molecular Dynamics Simulations (MD) Reveal Insights Into the Disconnect Between Affinity and Activation of ZTP Riboswitch Ligands

Abstract The challenge of targeting RNA with small molecules necessitates a better understanding of RNA–ligand interaction mechanisms. However, the dynamic nature of nucleic acids, their ligand‐induced stabilization, and how conformational changes influence gene expression pose significant difficulties for experimental investigation. This work employs a combination of computational and experimental methods to address these challenges. By integrating structure‐informed design, crystallography, and machine learning‐augmented all‐atom molecular dynamics simulations (MD), we synthesized, biophysically and biochemically characterized, and studied the dissociation of a library of small molecule activators of the 5‐aminoimidazole–4–carboxamide ribonucleotide triphosphate (ZTP) riboswitch, a ligand‐binding RNA motif that regulates bacterial gene expression. We uncovered key interaction mechanisms, revealing valuable insights into the role of ligand binding kinetics on riboswitch activation. Further, we established that ligand on‐rates determine activation potency as opposed to binding affinity and elucidated RNA structural differences, which provide mechanistic insights into the interplay of RNA structure on riboswitch activation.

Chemistry↗
DOE OSTI2025

Phase-based velocity extraction method for photonic Doppler velocimetry with potential higher time resolution

We present an extension of the [Takeda et al., J. Opt. Soc. Am. 72, 156 (1982)] phase extraction method to heterodyne photonic Doppler velocimetry applications. The method yields results equivalent to those obtained by the short-time Fourier transform (STFT), while offering potential improvements in time resolution. Unlike STFT, which relies on window functions, such as the Hamming window, that emphasize central data points and diminish the influence of edges, the extended Takeda method utilizes all data uniformly. This uniform treatment allows for the derivation of empirical equations that directly relate velocity error to the actual time resolution rather than to the local analysis duration. The established equation provides a useful metric for both optimizing hardware configuration and guiding data analysis. Simulation and experimental results confirm that, for a given dataset, specifying a target time resolution yields consistent velocity errors for both methods. These findings underscore the Takeda method’s advantages, particularly its potential higher time resolution and reduced computational burden, making it a valuable tool for high-throughput applications such as laser dynamic compression experiments.

Computer simulation↗
DOE OSTI2024

Simulation of Direct-Drive Hybrid Using Two Opposed Beams for Inertial Fusion Energy

Xcimer Energy is working to deliver high levels of laser light at the costs required for applications in fusion energy. The architecture of their integrated laser system is unique, in that it naturally supports a target which is illuminated by two opposed beams, and in a manner that can readily complement a reactor. This INFUSE proposal was submitted to investigate a target concept termed the Direct-Drive Hybrid or DDH, and make special use of radiation hydrodynamic simulations and expertise available to the Laboratory for Laser Energetics. The associated capabilities are unique to the field, and take great advantage of investments and advances made by the DOE and DOD over many decades. The primary goals were to stand up the DDH design in calculations for the first time, study and refine the concept, and provide the scientific basis for understanding and projecting proposals by Xcimer Energy. The main accomplishments have been summarized below.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Simulation of Divertor Performance in ST40 Under Dynamic Double-Null Plasmas

A power fraction model was implemented for the simultaneous prediction of 3-D surface temperature evolution at all four divertor targets in near-double-null (DN) tokamak configurations, which is especially important for compact high-field devices that may not have the ability to dissipate large amounts of power on the high-field side. Evaluating the power-sharing between the four divertor strike points in a disconnected DN configuration is important for understanding the overall power balance, as well as for optimizing the power exhaust performance and prolonging the survivability of the plasma facing components (PFCs). This power-sharing is typically evaluated in terms of the separation between the primary and secondary separatrices at the outboard midplane, $\textit {dR}_{\text {sep}}$. The Heat flux Engineering Analysis Toolkit (HEAT) is coupled with Brunner’s power fraction model to simulate the deposited heat flux and resultant temperature change on 3-D divertor targets in a dynamic DN (DDN) pulse operation in ST40, a high-field spherical tokamak. The simulation results showed that with DDN operation, the operation time has significantly increased compared with single-null geometry configurations.

ST40↗
DOE OSTI2026

Synthetic Digital Environments for Training Robots on Earth & Beyond [Poster]

Creating physical replicas of real-world environments to train robots for challenging outdoor tasks, whether constructing energy infrastructure like solar farms on Earth or on the Moon and Mars, is prohibitively expensive. This project will prototype a high-fidelity digital twin framework using NVIDIA IsaacSim to create realistic digital representations of robotic systems and their operating conditions, including varied terrains and environmental factors, allowing robots to learn and adapt in a faster, safer, and more affordable way to tackle unpredictable challenges in terrestrial and extraterrestrial applications. The Robotic Space Exploration (RoSE) Lab at Colorado School of Mines focused on the development and testing of synthetic digital twins to explore multi-physics interactions between robots and unstructured environments, with emphasis on lunar conditions such as deformable regolith, reduced gravity, and terrain-robot contact dynamics. The Industrialized Construction Innovation (ICI) team at National laboratory of the Rockies (NLR), simulated robotic apparatus and construction workflows using synthetic digital twins to inform real-world deployment, targeting application-driven use cases such as robotic construction of a scaled prototype of a photovoltaic energy infrastructure. Joint efforts between RoSE and ICI are continuing to explore how environment-scale multi-physics modeling and application-level robotic system simulation could be integrated to support robotic construction of energy infrastructure in highly unstructured environments, including scenarios relevant to the Lunar South Pole.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Assessment of Physical Security Modeling and Simulation in the Vulnerability Assessment Process

This report provides a comprehensive assessment of physical security modeling and simulation tools available for use in the vulnerability assessment (VA) process for nuclear facilities. It outlines the historical evolution of VA methodologies, emphasizing the transition from traditional layer-based approaches to a more holistic framework that integrates detection probabilities directly into combat simulations. The document details the critical components of the VA process, including the characterization of targets, threats, and protective measures, as well as the development of adversary scenarios that reflect both insider and outsider threats. It highlights the importance of performance assurance programs, emphasizing the need for continuous evaluation and testing of security systems to ensure their effectiveness against evolving threats. Additionally, the report discusses the significance of utilizing accredited modeling and simulation tools in accredited areas to accurately represent adversary actions and the corresponding responses of protective forces. By establishing a systematic approach to VA, this document aims to enhance the overall security posture of nuclear facilities, ensuring compliance with regulatory standards while effectively mitigating risks associated with potential adversarial actions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Clustering analysis of medium-band selected high-redshift galaxies

Next-generation large-scale structure spectroscopic surveys will probe cosmology at high redshifts (2.3 < z < 3.5), relying on abundant galaxy tracers such as Lyα emitters (LAEs) and Lyman break galaxies (LBGs). Medium-band photometry has emerged as a potential technique for efficiently selecting these high-redshift galaxies. In this work, we present clustering analysis of medium-band selected galaxies at high redshift, utilizing photometric data from the Intermediate Band Imaging Survey (IBIS) and spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We interpret the clustering of such samples using both Halo Occupation Distribution (HOD) modeling and a perturbation theory description of large-scale structure. Our modeling indicates that the current target sample is composed from an overlapping mixture of LAEs and LBGs with emission lines. Despite differences in target selection, we find that the clustering properties are consistent with previous studies, with correlation lengths r 0 ≃ 3-4 h -1 Mpc and a linear bias of b ∼ 1.8-2.5. Finally, we discuss the simulation requirements implied by these measurements and demonstrate that the properties of the samples would make them excellent targets to enhance our understanding of the high-z universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Integration of plant and microbial oil processing at oilcane biorefineries for more sustainable biofuel production

Oilcane—an oil-accumulating crop engineered from sugarcane—and microbial oil have the potential to improve renewable oil production and help meet the expected demand for bioderived oleochemicals and fuels. To assess the potential synergies of processing both plant and microbial oils, the economic and environmental implications of integrating microbial oil production at oilcane and sugarcane biorefineries were characterized. Due to decreased crop yields that lead to higher simulated feedstock prices and lower biorefinery capacities, current oilcane prototypes result in higher costs and carbon intensities than microbial oil from sugarcane. To inform oilcane feedstock development, we calculated the required biomass yields (as a function of oil content) for oilcane to achieve financial parity with sugarcane. At 10 dw% oil, oilcane can sustain up to 30% less yield than sugarcane and still be more profitable in all simulated scenarios. Assuming continued improvements in microbial oil production from cane juice, achieving this target results in a minimum biodiesel selling price of 1.34 [0.90, 1.85] USD∙L –1 (presented as median [5th, 95th] percentiles), a carbon intensity of 0.51 [0.47, 0.55] kg CO 2 e L –1 , and a total biodiesel yield of 2140 [1870, 2410] L ha –1 year –1 . Compared to biofuel production from soybean, this outcome is equivalent to 3.0–3.9 as much biofuel per hectare of land and a 57%–63% reduction in carbon intensity. While only 20% of simulated scenarios fell within the market price range of biodiesel (0.45–1.11 USD∙L –1 ), if the oilcane biomass yield would improve to 25.6 DMT∙ha –1 ∙y –1 (an equivalent yield to sugarcane) 87% of evaluated scenarios would have a minimum biodiesel selling price within or below the market price range.

09 BIOMASS FUELS↗
DOE OSTI2025

Generation of strong fields with subcritical density plasmas to study the phase transitions of magnetized warm dense matter

Warm dense matter (WDM) is a regime where Fermi degenerate electrons play an important role in the macroscopic properties of a material. Recent experiments have brought us closer to understanding unmagnetized processes in WDM, but magnetized WDM remains unexplored because kilotesla magnetic fields are required. Although there are examples of field compression generating such fields by imploding pre-magnetized targets, these existing methods give no independent control over the parameters of the magnetized plasma and result in limited laser access for sample creation and diagnosis. In this paper, numerical simulations show that kilotesla magnetic fields can be obtained by shining laser beams onto the inner surface of a cylindrical target, rather than on the outer surface. This approach relies on field compression by a low-density, high-temperature plasma, rather than a high-density, low-temperature plasma, used in the more conventional approach. With this novel configuration, the region of peak magnetic field is mostly free of plasma, hence, other beams can reach a sample placed in the region of the peak field to form WDM and diagnose it.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Measurement of early time outer laser beam reflection inside a cylindrical hohlraum at the National Ignition Facility

In a National Ignition Facility (NIF) cylindrical hohlraum, any specular reflection (“glint”) off the wall from the outer cone (incident angle of 50° and 44° relative to the surface of the wall) laser beam will irradiate the capsule poles. If the glint power is sufficiently large during the picket (early time) of the laser pulse, it may seed high-mode perturbations on the capsule surface that can grow during the implosion. To quantify the glint power on the capsule during the picket by the outer beams, we performed dedicated experiments on NIF using a flat witness foil as a surrogate for the capsule in a half-hohlraum target. We found that the measured glint power is approximately comparable to simulations using a nominal electron conduction flux limiter of f = 0.15, and over an order of magnitude lower than that predicted using f = 0.03 in the wall. Based on our current understanding, we conclude that the glint from the outer beams plays an insignificant role in capsule drive asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗