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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 OSTI2020

Flue Gas Desulfurization Wastewater Composition and Implications for Regulatory and Treatment Train Design

The U.S. Environmental Protection Agency is currently revising its regulations on trace element discharges from flue gas desulfurization (FGD) wastewater.<br>In this work, we expand a predictive model of trace element behavior at coal-fired power plants (CFPPs) to estimate the trace element concentration of FGD wastewater at the plant level. We demonstrate that variation in trace element concentrations in FGD wastewater can span several orders of magnitude and is a function of both coal rank and installed air pollution control devices. This conclusion suggests that the benefits and costs of FGD wastewater treatment for the median plant will poorly describe the actual benefits and costs over the full range of existing CFPPs.

Mauter, Meagan↗
DOE OSTI2023

Conformer-Dependent Chemistry: Experimental Product Branching of the Vinyl Alcohol + OH + O 2 Reaction

The concentration of formic acid in Earth's tropo-sphere is underestimated by detailed chemical models compared to field observations. Phototautomerization of acetaldehyde to its less stable tautomer vinyl alcohol, followed by the OH-initiated oxidation of vinyl alcohol, has been proposed as a missing source of formic acid that improves the agreement between models and field measurements. Theoretical investigations of the OH + vinyl alcohol reaction in excess O 2 conclude that OH addition to the alpha carbon of vinyl alcohol produces formaldehyde + formic acid + OH, whereas OH addition to the β site leads to glycoaldehyde + HO 2 . Furthermore, these studies predict that the conformeric structure of vinyl alcohol controls the reaction pathway, with the anti-conformer of vinyl alcohol promoting α OH addition, whereas the syn-conformer promotes β addition. However, the two theoretical studies reach different conclusions regarding which set of products dominate. We studied this reaction using time-resolved multiplexed photoionization mass spectrometry to quantify the product branching fractions. Our results, supported by a detailed kinetic model, conclude that the glycoaldehyde product channel (arising mostly from syn-vinyl alcohol) dominates over formic acid production with a 3.6:1.0 branching ratio. Additionally, this result supports the conclusion of Lei et al. that conformer-dependent hydrogen bonding at the transition state for OH-addition controls the reaction outcome. As a result, tropospheric oxidation of vinyl alcohol creates less formic acid than recently thought, increasing again the discrepancy between models and field observations of Earth's formic acid budget.

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

Toward a Machine Learning Approach to Interpreting X-ray Spectra of Trace Impurities by Converting XANES to EXAFS

The fact that the photoabsorption spectrum of a material contains information about the atomic structure, commonly understood in terms of multiple scattering theory, is the basis of the popular extended X-ray absorption spectroscopy (EXAFS) technique. How much of the same structural information is present in other complementary spectroscopic signals is not obvious. Here we use a machine learning approach to demonstrate that within theoretical models that accurately predict the EXAFS signal, the extended near-edge region does indeed contain the EXAFS-accessible structural information. We do this by exhibiting deep operator neural networks (DeepONets) that have learned the relationship between the extended and near edge portions of the X-ray absorption spectrum to predict the former from the latter. We find that we can accurately predict the EXAFS spectrum between 6 and 14 Å –1 from the first 6 Å –1 (≈100 eV) of the absorption spectrum of Cu 2 + substitutional defects in the Fe 3+ mineral hematite (α-Fe 2 O 3 ). This surprising finding implies that theoretical analyses of X-ray absorption spectra could be implemented that extract the same conclusions as high-quality EXAFS studies from spectra collected over a much smaller range of photon energies. This relaxes a host of experimental limitations related to the X-ray source and measurement sample, including collection time, minimum dopant concentration, source brilliance, and energy range. We describe the theoretical data sets and DeepONet construction and show that the resulting DeepONets produce EXAFS that recovers linear combination fits to experimental data with accuracy approaching the original ab initio calculations. We discuss the implications of our findings for minor constituent characterization and for understanding the information content of spectroscopic data more broadly, including how this approach might be applied to measured experimental spectra. In conclusion, to encourage similar efforts, the simulated X-ray spectra, machine learning, and fitting code are publicly available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

INBOUND APPOINTEE PUBLICATION Importance of Substrate-Particle Repulsion for Protein-Templated Assembly of Metal Nanoparticles

We study the protein-directed assembly of colloidal gold nanoparticles on de novo designed protein nanofiber templates. Using sequential assembly on glass substrates, we attach of positively-charged gold nanoparticles to protein nanofibers engineered to have a high density of negatively-charged surface residues. Using a combination of electron and optical microscopy, we measure the density of particle attachment and characterize binding specificity. By varying nanoparticle size and pH of the solution, we explore the importance of charge-dependent particle-fiber and particle-substrate interactions. We find an inverse correlation between particle size and attachment density to the protein nanofibers, attributed to the balance between size-dependent electrostatic particle-fiber attraction and particle-substrate repulsion. We show pH-dependent particle attachment density and binding specificity in relation to the protonation fraction of each assembly layer. Finally, we employ hyperspectral scattering microscopy to draw conclusions about particle density and interparticle spacings of optically-observable particle assemblies.

Guye, Kathryn N.↗
DOE OSTI2025

Coordinated Cation Transport in Ti 3 C 2 T x MXene Membranes

Membrane nanofiltration is an attractive strategy for the selective recovery of high-demand metals from wastewater and brine. Effective sieving of ions in aqueous environments will require precise control over membranes’ nanochannel size and chemistry. Ti 3 C 2 T x MXene is an environmentally stable 2D material that can be processed into laminar membranes containing nanoscale interlayer spaces. The MXene interlayer environment depends on the ion species and amount of water intercalated between MXene sheets, and it is the major factor governing permeation and selectivity through MXene membranes. Coordinated ion–ion and ion-interlayer dynamics in the presence of complex mixtures can impact ion permeability and selectivity. Herein, we observe strong competitive effects between different cations (Li + , Na + , and Ca 2+ ) in binary mixtures, resulting in reduced selectivity when compared with single-salt permeability ratios. X-ray diffraction, molecular dynamics, and density functional theory simulations support the conclusion that cations with stronger attraction to MXene flakes can preferentially occupy the MXene nanochannels and hinder other ions via charge or size exclusion. In conclusion, elucidation of ion transport behavior in MXene under complex conditions will allow for more rational design of efficient ion-sieving membranes.

2D Materials↗
DOE OSTI2026

How to Minimize Faradaic Efficiency Error in Electrochemical CO 2 Reduction for Gas Products

Faradaic efficiency (FE) is an important metric for evaluating electrochemical processes, such as carbon dioxide reduction, that is often used for performance comparisons. Although the equation to calculate FE is well-known, details needed to yield accurate values are often overlooked, potentially leading to errors exceeding 100%. Avoiding any errors is crucial for drawing correct conclusions, especially during a catalysis optimization process. Factors with high potential for FE errors include incorrect mass flow rates and temperature values, imprecise gas chromatography calibrations, and uncorrected gas viscosities, while factors with less potential are also identified. In conclusion, this manuscript presents FE calculation guidelines intended for both newcomers and experts in the field of electrochemical fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Minimal Information Set To Enable Verifiable Theoretical Battery Research

Batteries are an enabling technology for addressing sustainability through the electrification of various forms of transportation (1) and grid storage. (2) Batteries are truly multi-scale, multi-physics devices, and accordingly various theoretical descriptions exist to understand their behavior (3-5) ranging from atomistic details to techno-economic trends. As we explore advanced battery chemistries (6,7) or previously inaccessible aspects of existing ones, (8-10) new theories are required to drive decisions. (11-13) The decisions are influenced by the limitations of the underlying theory. Advanced theories used to understand battery phenomena are complicated and require substantial effort to reproduce. However, such constraints should not limit the insights from these theories. We can strive to make the theoretical research verifiable such that any battery stakeholder can assess the veracity of new theories, sophisticated simulations or elaborate analyses. We distinguish verifiability, which amounts to “Can I trust the results, conclusions and insights and identify the context where they are relevant?”, from reproducibility, which ensures “Would I get the same results if I followed the same steps?” With this motivation, we propose a checklist to guide future reports of theoretical battery research in Table 1. We hereafter discuss our thoughts leading to this and how it helps to consistently document necessary details while allowing complete freedom for creativity of individual researchers. Given the differences between experimental and theoretical studies, the proposed checklist differs from its experimental counterparts. (14,15) This checklist covers all flavors of theoretical battery research, ranging from atomic/molecular calculations (16-19) to mesoscale (20,21) and continuum-scale interactions, (9,22) and techno-economic analysis. (23,24) Finally, as more and more experimental studies analyze raw data, (25) we feel this checklist would be broadly relevant.

25 ENERGY STORAGE↗
DOE OSTI2025

Solvent-Free Melt-Processed Cathode Mitigates Li Anode Instability in Polymer-Based Solid-State Batteries

Solvent-free manufacturing of battery components is a promising alternative to traditional slurry processing for reducing the cost and environmental impact. In this work, we used twin-screw melt extrusion to fabricate a polymer-based high voltage composite cathode. The melt-processed cathode is dense (near zero porosity) and thick (65 μm) and has high active material loading (80 wt %). The active particles are distributed uniformly throughout the melt-processed cathode, unlike the traditional slurry-cast cathode, which exhibits inhomogeneous particle distribution. In the melt-processed cathode, polymer and carbon form separate phases, whereas in the slurry-cast cathode they blend into a single phase. Due to these structural differences, the melt-processed cathode shows smooth charge–discharge profiles, while the slurry-cast cathode shows noisy charging and soft-shorting behavior. In conclusion, this work highlights that twin-screw extrusion as a scalable, solvent-free manufacturing method is advantageous in producing uniform cathodes, which mitigates anode instability.

25 ENERGY STORAGE↗
DOE OSTI2022

Observed Relationships Between Cloud Droplet Effective Radius and Biogenic Gas Concentrations in Summertime Marine Stratocumulus Over the Eastern North Atlantic

Abstract Biogenic gases are a prominent component of the summertime marine boundary layer (MBL) over the Eastern North Atlantic. One of these gases, dimethyl sulfide (DMS), can produce sulfate cloud condensation nuclei (CCN) that, in theory, can brighten clouds through photolysis, and produces a reaction product, methane sulfonic acid (MSA). It is also possible that DMS can interact with sea‐salt or other marine aerosols changing their CCN activation spectrum, which could also modify cloud microphysical structure. Data collected aboard the G1 aircraft during the Aerosol Cloud Experiment Eastern North Atlantic (ACE‐ENA) in well‐mixed and decoupled marine boundary layers (MBLs) were used to examine relationships between the cloud droplet effective radii, , and the concentrations of DMS and MSA in constant cloud liquid water content (LWC) bins. A weak but statistically significant negative correlation was observed between CCN concentration and in most LWC bins, regardless of the source of the CCN, while a weak but statistically significant positive correlation between and DMS was observed. No correlation between the cloud droplet number concentration and DMS was found. The presence of MSA indicated that DMS‐to‐sulfate photolysis was likely occurring, but data sparsity prevented a statistically significant conclusion regarding the relationship between MSA and . Data sparsity in decoupled conditions also prevented statistically significant conclusions. To properly address biogenic gas impacts on cloud microphysics, it is recommended that aircraft data be supplemented by long‐term biogenic gas measurements at the surface in marine locations with appropriate remote and in‐situ cloud sensing capabilities, and the analysis limited to well‐mixed MBL's.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Pyrocumulonimbus Events Over British Columbia in 2017: An Ensemble Model Study of Parameter Sensitivities and Climate Impacts of Wildfire Smoke in the Stratosphere

Abstract The Pyrocumulonimbus (pyroCb) events over British Columbia in 2017 were observed in the lower stratosphere for about 8–10 months after the smoke injections. Several previous studies used global climate models to investigate the physical parameters for the 2017 pyroCb events, but the conclusions show strong model dependency. In this study, we use the Energy Exascale Earth System Model (E3SM) and complete an ensemble of runs exploring three injection parameters: smoke aerosol mass, the percentage of black carbon within the smoke aerosols, and plume injection height. Additionally, we consider the heterogeneous reaction of ozone and primary organic matter. According to the satellite daily observed aerosol optical depth (AOD), we find that the best ensemble member is the simulation with 0.4 Tg of smoke, 3% of which is black carbon, a 13.5 km smoke injection height, and a 10 −5 probability factor of the heterogeneous reaction. Besides AOD, we examine the ensemble score based on the metrics used in previous studies: the metrics of the extinction coefficient at 18 km altitude and the maximum plume height. The conclusion of the best estimate of the injection parameters for 2017 pyroCb events shows strong not only model but also evaluation metric dependency. We use the Random Forest machine learning technique to quantify the relative importance of each parameter in accurately simulating the 2017 pyroCb events and find that the injection height is the most critical feature, no matter which metric is used to score the ensemble members.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Spin-orbit-controlled metal–insulator transition in Sr 2 IrO 4

In the context of correlated insulators, where electron–electron interactions (U) drive the localization of charge carriers, the metal–insulator transition is described as either bandwidth- or filling-controlled. Motivated by the challenge of the insulating phase in Sr 2 IrO 4 , a new class of correlated insulators has been proposed, in which spin–orbit coupling (SOC) is believed to renormalize the bandwidth of the half-filled j eff = 1/2 doublet, allowing a modest U to induce a charge-localized phase. Although this framework has been tacitly assumed, a thorough characterization of the ground state has been elusive. Furthermore, direct evidence for the role of SOC in stabilizing the insulating state has not been established, because previous attempts at revealing the role of SOC have been hindered by concurrently occurring changes to the filling. Here, we overcome this challenge by employing multiple substituents that introduce well-defined changes to the signatures of SOC and carrier concentration in the electronic structure, as well as a new methodology that allows us to monitor SOC directly. Specifically, we study Sr 2 Ir 1-x T x O 4 (T = Ru, Rh) by angle-resolved photoemission spectroscopy, combined with ab initio and supercell tight-binding calculations. This allows us to distinguish relativistic and filling effects, thereby establishing conclusively the central role of SOC in stabilizing the insulating state of Sr 2 IrO 4 . Most importantly, we estimate the critical value for SOC in this system to be λ c = 0.42 ± 0.01 eV, and provide the first demonstration of a spin–orbit-controlled metal–insulator transition.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

The importance of trait selection in ecology

Two recent publications have explored the importance of roots for understanding plant form and function but reached opposite conclusions on the basis of largely overlapping data. Carmona et al. concluded that their results “do not confirm the strong covariation between leaf and fine-root traits predicted by the plant economics spectrum hypothesis”. By contrast, Weigelt et al. concluded that “key leaf and fine-root traits were aligned along the expected [fast–slow] ‘conservation’ gradient of plant economic investment”. Furthermore, here we reflect on the causes for the apparent discrepancies of these studies and show that the rationale behind trait selection is vital for the conclusions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Epidermal growth factor receptor cascade prioritizes the maximization of signal transduction

Many studies have been performed to quantify cell signaling. Cell signaling molecules are phosphorylated in response to extracellular stimuli, with the phosphorylation sequence forming a signal cascade. The information gain during a signal event is given by the logarithm of the phosphorylation molecule ratio. The average information gain can be regarded as the signal transduction quantity (ST), which is identical to the Kullback–Leibler divergence (KLD), a relative entropy. We previously reported that if the total ST value in a given signal cascade is maximized, the ST rate (STR) of each signaling molecule per signal duration (min) approaches a constant value. To experimentally verify this theoretical conclusion, we measured the STR of the epidermal growth factor (EGF)-related cascade in A431 skin cancer cells following stimulation with EGF using antibody microarrays against phosphorylated signal molecules. The results were consistent with those from the theoretical analysis. Thus, signaling transduction systems may adopt a strategy that prioritizes the maximization of ST. Furthermore, signal molecules with similar STRs may form a signal cascade. In conclusion, ST and STR are promising properties for quantitative analysis of signal transduction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Decorrelated singlet and triplet exciton delocalization in acetylene-bridged Zn-porphyrin dimers

The controlled delocalization of molecular excitons remains an important goal towards the application of organic chromophores in processes ranging from light-initiated chemical transformations to classical and quantum information processing. In this study, we present a methodology to couple optical and magnetic spectroscopic techniques and assess the delocalization of singlet and triplet excitons in model molecular chromophores. By comparing the steady-state and time-resolved optical spectra of Zn-porphyrin monomers and weakly coupled dimers, we show that we can use the identity of substituents bound at specific positions of the macromolecules' rings to control the inter-ring delocalization of singlet excitons stemming from their B states through acetylene bridges. While broadened steady-state absorption spectra suggest the presence of delocalized B state excitons in mesityl-substituted Zn-tetraphenyl porphyrin dimers (Zn 2 U-D), we confirm this conclusion by measuring an enhanced ultrafast non-radiative relaxation from these inter-ring excitonic states to lower lying electronic states relative to their monomer. In contrast to the delocalized nature of singlet excitons, we use time-resolved EPR and ENDOR spectroscopies to show that the triplet states of the Zn-porphyrin dimers remain localized on one of the two macrocyclic sub-units. We use the analysis of EPR and ENDOR measurements on unmetallated model porphyrin monomers and dimers to support this conclusion. The results of DFT calculations also support the interpretation of localized triplet states. These results demonstrate researchers cannot conclude triplet excitons delocalize in macromolecular based on the presence of spatially extended singlet excitons, which can help in the design of chromophores for application in spin conversion and information processing technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Large-scale experimental validation of thermochemical water-splitting oxides discovered by defect graph neural networks

Thermochemical water-splitting (TCH) based on 2-step thermal redox cycles in metal oxides is a promising approach to generating H 2 , but state-of-the-art (SOTA) CeO 2 has several practical limitations, which has motivated continued materials discovery efforts in this field. Here, in this study, we improve upon a SOTA defect graph neural network (dGNN) surrogate model's oxygen vacancy predictions and combine them with materials project phase diagrams to down-select and discover structurally diverse, experimentally known metal oxides whose TCH performance was previously unknown. Amongst twelve candidates selected based on our high-throughput screening and down-selection criteria, we achieved ∼80% accuracy in identifying materials with stable redox cycling and hydrogen production in stagnation flow reactor water-splitting experiments. Closer to 100% accuracy can be achieved if higher-accuracy, hybrid DFT-predicted vacancy formation energies were computed and used in lieu of the most uncertain dGNN-based screening predictions, as they correct false positives to true negatives. Notably, two discovered candidates, Sr 3 PrMn 2 O 8 and Ba 2 Fe 2 O 5 , display hydrogen yields greater than CeO 2 under specific redox conditions. In conclusion, these results demonstrate our ability to computationally predict and experimentally validate promising candidate TCH materials that have the potential to compete with CeO 2 .

08 HYDROGEN↗
DOE OSTI2020

TDCOSMO. I. An exploration of systematic uncertainties in the inference of $H_0$ from time-delay cosmography

Time-delay cosmography of lensed quasars has achieved 2.4% precision on the measurement of the Hubble constant, H0. As part of an ongoing effort to uncover and control systematic uncertainties, we investigate three potential sources: 1- stellar kinematics, 2- line-of-sight effects, and 3- the deflector mass model. To meet this goal in a quantitative way, we reproduced the H0LiCOW/SHARP/STRIDES (hereafter TDCOSMO) procedures on a set of real and simulated data, and we find the following. First, stellar kinematics cannot be a dominant source of error or bias since we find that a systematic change of 10% of measured velocity dispersion leads to only a 0.7% shift on H0 from the seven lenses analyzed by TDCOSMO. Second, we find no bias to arise from incorrect estimation of the line-of-sight effects. Third, we show that elliptical composite (stars + dark matter halo), power-law, and cored power-law mass profiles have the flexibility to yield a broad range in H0 values. However, the TDCOSMO procedures that model the data with both composite and power-law mass profiles are informative. If the models agree, as we observe in real systems owing to the “bulge-halo” conspiracy, H0 is recovered precisely and accurately by both models. If the two models disagree, as in the case of some pathological models illustrated here, the TDCOSMO procedure either discriminates between them through the goodness of fit, or it accounts for the discrepancy in the final error bars provided by the analysis. This conclusion is consistent with a reanalysis of six of the TDCOSMO (real) lenses: the composite model yields H0 = 74.0−1.8+1.7 km s−1 Mpc−1, while the power-law model yields 74.2−1.6+1.6 km s−1 Mpc−1. In conclusion, we find no evidence of bias or errors larger than the current statistical uncertainties reported by TDCOSMO.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Substructure in the stellar halo near the Sun: I. Data-driven clustering in integrals-of-motion space

Context. Merger debris is expected to populate the stellar haloes of galaxies. In the case of the Milky Way, this debris should be apparent as clumps in a space defined by the orbital integrals of motion of the stars. Aims. Our aim is to develop a data-driven and statistics-based method for finding these clumps in integrals-of-motion space for nearby halo stars and to evaluate their significance robustly. Methods. We used data from Gaia EDR3, extended with radial velocities from ground-based spectroscopic surveys, to construct a sample of halo stars within 2.5 kpc from the Sun. We applied a hierarchical clustering method that makes exhaustive use of the single linkage algorithm in three-dimensional space defined by the commonly used integrals of motion energy E, together with two components of the angular momentum, L z and L ⊥ . To evaluate the statistical significance of the clusters, we compared the density within an ellipsoidal region centred on the cluster to that of random sets with similar global dynamical properties. By selecting the signal at the location of their maximum statistical significance in the hierarchical tree, we extracted a set of significant unique clusters. By describing these clusters with ellipsoids, we estimated the proximity of a star to the cluster centre using the Mahalanobis distance. Additionally, we applied the HDBSCAN clustering algorithm in velocity space to each cluster to extract subgroups representing debris with different orbital phases. Results. Our procedure identifies 67 highly significant clusters (> 3σ), containing 12% of the sources in our halo set, and 232 subgroups or individual streams in velocity space. In total, 13.8% of the stars in our data set can be confidently associated with a significant cluster based on their Mahalanobis distance. Inspection of the hierarchical tree describing our data set reveals a complex web of relations between the significant clusters, suggesting that they can be tentatively grouped into at least six main large structures, many of which can be associated with previously identified halo substructures, and a number of independent substructures. This preliminary conclusion is further explored in a companion paper, in which we also characterise the substructures in terms of their stellar populations. Conclusions. Our method allows us to systematically detect kinematic substructures in the Galactic stellar halo with a data-driven and interpretable algorithm. The list of the clusters and the associated star catalogue are provided in two tables available at the CDS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Further modeling of q 95 windows for the suppression of edge localized modes by resonant magnetic perturbations in the DIII-D tokamak

An improved resonant plasma response model that more accurately captures the physics of the interaction between a tokamak plasma and a resonant magnetic perturbation (RMP) is developed. The model interpolates between the linear and the nonlinear response regimes and takes into account the fact that the slip-frequency is non-zero in the nonlinear regime. The improved model is incorporated into the extended perturbed equilibrium code (EPEC) toroidal asymptotic matching code. The modified EPEC code is used to investigate RMP-induced edge-localized-mode (ELM) suppression in DIII-D H-mode discharge #145380. Somewhat surprisingly, allowing for a finite slip-frequency (i.e., relaxing the so-called no-slip constraint) is found to only slightly facilitate the locking of driven magnetic island chains to the RMP, and, hence, to only slightly facilitate RMP-induced ELM suppression. This is true despite the fact that the nature of non-locked island solutions is radically different when the no-slip constraint is imposed compared to when it is relaxed (in the first case, the widths of the island chains driven at the rational surfaces pulsate, and in the second case, they remain steady). The previously obtained conclusion that the response of a typical H-mode tokamak plasma to an RMP cannot be accurately modeled by linear theory is confirmed. Here, the previously obtained conclusion that the best agreement between theory and observations is achieved by assuming that the natural frequencies of tearing modes, in the absence of the RMP, are determined by the local equilibrium E × B velocity is also confirmed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗