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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Two-Dimensional and Three-Dimensional Tetrel-Arsenide Frameworks Templated by Li and Cs Cations

Two new ternary tetrel pnictide phases, Li 1.08 Ge 4.92 As 7 and Cs 0.11 Zn 0.05 Si 0.95 As, have been synthesized. Both compounds crystallize in new structure types, which demonstrate the flexibility of Ge(Si)–As layers when accommodating electropositive cations of various sizes. Li 1.08 Ge 4.92 As 7 displays a Ge-As layer motif that has not been observed in ternary Ge-As systems, while Cs 0.11 Zn 0.05 Si 0.95 As exhibits a 3D framework composed of fragments of the 2D parent-phase SiAs. For Li 1.08 Ge 4.92 As 7 , a combination of computational modeling and solid-state 7 Li MAS NMR was used to establish the correct crystal structure with one mixed occupied Ge/Li site. The compositions of the phases were confirmed through energy-dispersive X-ray spectroscopy. Transport properties and UV–Vis spectroscopy reveal both reported compounds to be semiconductors. Cs 0.11 Zn 0.05 Si 0.95 As shows high thermal stability with congruent melting at 1300 K and an exceptionally low thermal conductivity of 0.5 W m –1 K –1 at 300 K. Temperature-dependent Li-ion hopping dynamics in Li 1.08 Ge 4.92 As 7 was characterized using 7 Li solid-state NMR.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Investigation of the Solution Chemistry of Hybrid Organic–Inorganic Indium Halides for New Material Discovery

Recently, metal halide perovskites (MHPs) have emerged as a new class of materials for optical and electronic applications such as solar cells and ionizing radiation detectors. Although the solution-processability of MHPs is among their greatest advantages, the solution chemistries of most metal halide systems and their relationship with the observed structural and chemical diversity are poorly understood. In this work, we study the solution chemistry of a model indium halide system, methylammonium (MA)–In–Br, using a combination of the UV–vis spectroscopy, electrospray ionization mass spectrometry (ESI-MS) measurements, small-angle X-ray scattering (SAXS), and density functional theory (DFT) calculations. Our results show that indium could form either octahedral [InBr 6 3– ] or tetrahedral [InBr 4 – ] anions in solution or a combination of both, depending on the loading ratios of MABr and InBr 3 reactants. Understanding the solution chemistry of this system and recognizing the optical fingerprints of these polyanions allow for targeted crystallization of two novel compounds: MAInBr 4 featuring tetrahedral [InBr 4 – ] anions and MA 2 InBr 5 containing both octahedral [InBr 6 3– ] and tetrahedral [InBr 4 – ] anions. Further increase of the MABr content leads to the formation of previously reported MA 4 InBr 7 , containing only octahedral [InBr 6 3– ] anions separated by Br – anions. Furthermore, our results suggest that understanding the solution chemistry of multinary metal halide systems could be a valuable tool for discovering functional materials for practical applications.

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

Intrinsic and induced quantum quenches for enhancing qubit-based quantum noise spectroscopy

Quantum sensing protocols that exploit the dephasing of a probe qubit are powerful and ubiquitous methods for interrogating an unknown environment. They have a variety of applications, ranging from noise mitigation in quantum processors, to the study of correlated electron states. Here, we discuss a simple strategy for enhancing these methods, based on the fact that they often give rise to an inadvertent quench of the probed system: there is an effective sudden change in the environmental Hamiltonian at the start of the sensing protocol. These quenches are extremely sensitive to the initial environmental state, and lead to observable changes in the sensor qubit evolution. We show how these new features give access to environmental response properties. This enables methods for direct measurement of bath temperature, and for detecting non-thermal equilibrium states. We also discuss how to deliberately control and modulate this quench physics, which enables reconstruction of the bath spectral function. Extensions to non-Gaussian quantum baths are also discussed, as is the application of our ideas to a range of sensing platforms (e.g., nitrogen-vacancy (NV) centers in diamond, semiconductor quantum dots, and superconducting circuits).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Linear response of molecular polaritons

In this article, we show that the collective light–matter strong coupling regime where N molecular emitters couple to the photon mode of an optical cavity can be mapped to a quantum impurity model where the photon is the impurity that is coupled to a bath of anharmonic transitions. In the thermodynamic limit where N ≫ 1, we argue that the bath can be replaced with an effective harmonic bath, leading to a dramatic simplification of the problem into one of the coupled harmonic oscillators. We derive simple analytical expressions for linear optical spectra (transmission, reflection, and absorption) where the only molecular input required is the molecular linear susceptibility. This formalism is applied to a series of illustrative examples, showing the role of temperature, disorder, vibronic coupling, and optical saturation of the molecular ensemble, explaining that it is useful even when describing an important class of nonlinear optical experiments. For completeness, we provide Appendixes A–C that include a self-contained derivation of the relevant spectroscopic observables for arbitrary anharmonic systems (for both large and small N) within the rotating-wave approximation. While some of the presented results herein have already been reported in the literature, we provide a unified presentation of the results as well as new interpretations that connect powerful concepts in open quantum systems and linear response theory with molecular polaritonics.

Chemistry↗
DOE OSTI2024

North‐East Peri‐Tethyan Water Column Deoxygenation and Euxinia at the Paleocene Eocene Thermal Maximum

Abstract The Paleocene–Eocene Thermal Maximum (PETM) is associated with climatic change and biological turnover. It shares features with the Oceanic Anoxic Events (OAEs) of the Mesozoic, such as transient global warming and biogeochemical perturbations. However, the PETM experienced a more muted expansion of marine anoxia compared to the Mesozoic OAEs (especially OAE2), with geographically limited evidence for photic zone euxinia (PZE). We explore the extent and drivers of marine deoxygenation during the PETM using biomarkers for water column euxinia and anoxia as well as an intermediate complexity Earth system model (cGEnIE). These reveal that the water column in the North‐East Peri‐Tethys became anoxic, with euxinic conditions reaching the photic zone (PZE) during the PETM. Our model shows that euxinia developed due to a global increase in the ocean nutrient inventory with concomitant oxygen consumption, similar to findings for OAE2. The particularly strong regional response in the NE Peri‐Tethys appears to arise from a combination of global CO 2 ‐weathering forcing, regionally restricted circulation and upwelling of sulphidic thermocline waters. Unlike OAE2, anoxia and PZE do not become widespread in our PETM simulations, consistent with new and existing geochemical and biological proxy data. This globally muted response could result from reduced biogeochemical feedbacks to climate forcing relative to the mid‐Cretaceous climate. Our observations suggest that similar mechanisms operated in response to disparate Cenozoic (PETM) and Mesozoic (OAEs) transient global warming events, while also highlighting that background conditions are crucial in modulating the sensitivity of Earth's system to them.

Behrooz, L.↗
DOE OSTI2025

Ultraviolet Fluorescence Imaging for Photovoltaic Module Metrology: Best Practices and Survey of Features Observed in Fielded Modules

As the photovoltaics (PV) industry grows in sophistication, so must the extent to which systems are characterized. UV Fluorescence (UVF) imaging is a valuable, easy-to-perform, high-throughput, nonintrusive technique for characterizing modules in the field and in the lab. However, UVF is still a relatively new technique, and many in the PV industry are still unaware of its potential. We provide a guideline for obtaining, processing, and interpreting UVF images. We have provided a list of considerations for imaging hardware and settings, a suggested pipeline for image processing, and details on a survey of features shown in UVF images. As a result, a new database with UVF images of 7190 modules and another database curated by BrightSpot Automation are publicly available.

14 SOLAR ENERGY↗
DOE OSTI2020

Plasma Facing Component Characterization and Correlation With Plasma Conditions in Lithium Tokamak Experiment-β

Lithium coatings in the Lithium Tokamak eXperiment (LTX) led to flat temperature profiles. The flat temperature profiles were observed along with a hot, low density edge, implying a broad, collisionless scrape-off layer (SOL). Additionally, in vacuo X-ray photoelectron spectroscopy (XPS) measurements established that lithium coatings evaporatively deposited onto high-Z plasma facing components (PFCs) became oxidized while retaining the ability to achieve good plasma performance long after lithium was applied to the PFCs. Longstanding theory predicted flat temperature profiles with low recycling walls, which was presumed to be due to hydrogen binding with elemental lithium to form lithium hydride. The presence of oxidized lithium, however, raised questions regarding the exact mechanism of hydrogen retention in LTX. To investigate these questions, the upgraded facility LTX- β includes a new sample exposure probe (SEP) for more detailed in vacuo analysis of PFC samples. The SEP is equipped with a vacuum suitcase capable of transporting samples representative of the LTX- β outer midplane PFCs to a stand-alone XPS system while maintaining pressures lower than the LTX- β base vacuum to limit the contamination between sample exposure and analysis. The low-energy resolution XPS system used in past experiments could only enable the determination of elemental percentages on the PFC sample surfaces. Because the new XPS system has higher energy resolution, it is more direct to assign chemical compounds to the measured binding energies. This capability has been confirmed by comparing XPS data from PFC test samples with measurements using a commercial high-resolution XPS system. Quartz crystal microbalances (QCMs) were used to quantify the thickness of the deposited lithium on the LTX- β PFCs. This article describes the application of the SEP to characterize the PFC surfaces using XPS and their relationship to plasma conditions.

Maan, Anurag↗
DOE OSTI2023

ET-AL: Entropy-targeted active learning for bias mitigation in materials data

Growing materials data and data-driven informatics drastically promote the discovery and design of materials. While there are significant advancements in data-driven models, the quality of data resources is less studied despite its huge impact on model performance. In this work, we focus on data bias arising from uneven coverage of materials families in existing knowledge. Observing different diversities among crystal systems in common materials databases, we propose an information entropy-based metric for measuring this bias. To mitigate the bias, we develop an entropy-targeted active learning (ET-AL) framework, which guides the acquisition of new data to improve the diversity of underrepresented crystal systems. We demonstrate the capability of ET-AL for bias mitigation and the resulting improvement in downstream machine learning models. This approach is broadly applicable to data-driven materials discovery, including autonomous data acquisition and dataset trimming to reduce bias, as well as data-driven informatics in other scientific domains.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Soft matter roadmap

Soft materials are usually defined as materials made of mesoscopic entities, often self-organised, sensitive to thermal fluctuations and to weak perturbations. Archetypal examples are colloids, polymers, amphiphiles, liquid crystals, foams. The importance of soft materials in everyday commodity products, as well as in technological applications, is enormous, and controlling or improving their properties is the focus of many efforts. From a fundamental perspective, the possibility of manipulating soft material properties, by tuning interactions between constituents and by applying external perturbations, gives rise to an almost unlimited variety in physical properties. Together with the relative ease to observe and characterise them, this renders soft matter systems powerful model systems to investigate statistical physics phenomena, many of them relevant as well to hard condensed matter systems. Understanding the emerging properties from mesoscale constituents still poses enormous challenges, which have stimulated a wealth of new experimental approaches, including the synthesis of new systems with, e.g. tailored self-assembling properties, or novel experimental techniques in imaging, scattering or rheology. Theoretical and numerical methods, and coarse-grained models, have become central to predict physical properties of soft materials, while computational approaches that also use machine learning tools are playing a progressively major role in many investigations. This Roadmap intends to give a broad overview of recent and possible future activities in the field of soft materials, with experts covering various developments and challenges in material synthesis and characterisation, instrumental, simulation and theoretical methods as well as general concepts.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Observation of quenching-induced magnetic flux trapping using a magnetic field and temperature mapping system

Highly efficient superconducting radio-frequency cavities exhibit low heat loss and are used as components in accelerators and superconducting devices due to their high Q-values. The precise location of magnetic flux trapping in cavities is necessary to identify its effects on the performance of superconducting cavities. In this study, we report a new combined mapping system to measure the temperature and magnetic field on the equator. The proposed system comprehensively maps local magnetic field changes as magnetic flux trapping due to quenching. Our experimental results show that magnetic flux trapping due to quenching increases the local surface resistance of superconducting cavities at 2 K. Thus, the proposed system elucidates the relationship between local flux trapping due to quenching and surface resistance in superconducting cavities and highlights the effect of quenching on the surface resistance. This system can aid in the development of superconducting cavities with higher Q values.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Properties and Controlling Processes of Aerosol and Cloud Condensation Nuclei in Marine Boundary Layer Over Eastern North Atlantic (Final Report)

Remote marine low cloud systems have large spatial and temporal coverages. Because of their relatively low optical thickness and background aerosol concentrations, marine low clouds are particularly susceptible to perturbations in aerosols associated with anthropogenic emissions. Recent studies show that a large fraction of the global aerosol indirect forcing can be attributed to changes in marine low clouds, despite their relatively long distance from most anthropogenic sources. Currently, there remain large uncertainties in the magnitude of the global aerosol indirect radiative forcing. One major contribution to this large uncertainty derives from poor understanding of the aerosols under natural conditions, the perturbation by anthropogenic emissions, and the processes that drive them. In this project, we took advantage of the comprehensive, multi-dimensional characterization of meteorological parameters, trace gases, aerosol, cloud, and drizzle fields during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) and the long-term measurements at the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site on Graciosa Island. By synergistically combining in situ measurements, remote sensing retrievals, and model simulations, we quantified aerosol properties in the ENA, their vertical profiles, and variations with season, synoptic state, and airmass. We investigated key aerosol processes, including entrainment of free troposphere aerosol into marine boundary layer, new particle formation, growth of Aitken mode particles, and the influences of these processes on the cloud condensation nuclei (CCN) population in marine boundary layer. The representation of key aerosol processes in the Energy Exascale Earth System Model (E3SM) was evaluated using the observations. This project has led to 26 publications, which are listed at the end of this report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Smart System for the Contactless Measurement of Energy Expenditure

Energy Expenditure (EE) (kcal/day), a key element to guide obesity treatment, is measured from CO 2 production, VCO 2 (mL/min), and/or O 2 consumption, VO 2 (mL/min). Current technologies are limited due to the requirement of wearable facial accessories. A novel system, the Smart Pad, which measures EE via VCO 2 from a room’s ambient CO 2 concentration transients was evaluated. Resting EE (REE) and exercise VCO 2 measurements were recorded using Smart Pad and a reference instrument to study measurement duration’s influence on accuracy. The Smart Pad displayed 90% accuracy (±1 SD) for 14–19 min of REE measurement and for 4.8–7.0 min of exercise, using known room’s air exchange rate. Additionally, the Smart Pad was validated measuring subjects with a wide range of body mass indexes (BMI = 18.8 to 31.4 kg/m2), successfully validating the system accuracy across REE’s measures of ~1200 to ~3000 kcal/day. Furthermore, high correlation between subjects’ VCO 2 and λ for CO 2 accumulation was observed (p < 0.00001, R = 0.785) in a 14.0 m3 sized room. This finding led to development of a new model for REE measurement from ambient CO 2 without λ calibration using a reference instrument. The model correlated in nearly 100% agreement with reference instrument measures (y = 1.06x, R = 0.937) using an independent dataset (N = 56).

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Pursuit of paired dijet resonances in the Run 2 dataset with ATLAS

New particles with large masses that decay into hadronically interacting particles are predicted by many models of physics beyond the Standard Model. A search for a massive resonance that decays into pairs of dijet resonances is performed using 140 fb –1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS detector during Run 2 of the Large Hadron Collider. Resonances are searched for in the invariant mass of the tetrajet system, and in the average invariant mass of the pair of dijet systems. A data-driven background estimate is obtained by fitting the tetrajet and dijet invariant mass distributions with a four-parameter dijet function and a search for local excesses from resonant production of dijet pairs is performed. No significant excess of events beyond the Standard Model expectation is observed, and upper limits are set on the production cross sections of new physics scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A robust statistical analysis of the role of hydropower on the system electricity price and price volatility

Abstract Hydroelectric power (hydropower) is unique in that it can function as both a conventional source of electricity and as backup storage (pumped hydroelectric storage and large reservoir storage) for providing energy in times of high demand on the grid (S. Rehman, L M Al-Hadhrami, and M M Alam), (2015 Renewable and Sustainable Energy Reviews , 44 , 586–98). This study examines the impact of hydropower on system electricity price and price volatility in the region served by the New England Independent System Operator (ISONE) from 2014-2020 (ISONE, ISO New England Web Services API v1.1 .” https://webservices.iso-ne.com/docs/v1.1/ , 2021. Accessed: 2021-01-10). We perform a robust holistic analysis of the mean and quantile effects, as well as the marginal contributing effects of hydropower in the presence of solar and wind resources. First, the price data is adjusted for deterministic temporal trends, correcting for seasonal, weekend, and diurnal effects that may obscure actual representative trends in the data. Using multiple linear regression and quantile regression, we observe that hydropower contributes to a reduction in the system electricity price and price volatility. While hydropower has a weak impact on decreasing price and volatility at the mean, it has greater impact at extreme quantiles (>70th percentile). At these higher percentiles, we find that hydropower provides a stabilizing effect on price volatility in the presence of volatile resources such as wind. We conclude with a discussion of the observed relationship between hydropower and system electricity price and volatility.

13 HYDRO ENERGY↗
DOE OSTI2023

Improving E3SM Land Model Photosynthesis Parameterization via Satellite SIF, Machine Learning, and Surrogate Modeling

The parameterization of key photosynthesis parameters is one of the key uncertain sources in modeling ecosystem gross primary productivity (GPP). Solar-induced chlorophyll fluorescence (SIF) offers a good proxy for GPP since it marks the actual process of photosynthesis; while machine learning (ML) provides a robust approach to model the GPP-SIF relationship. Here, we trained the boosted regressing tree (BRT) and the Random Forest ML models with Greenhouse Gases Observing Satellite SIF data and in situ GPP observations from 49 eddy covariance towers. These trained ML GPP-SIF models were fed into the Energy Exascale Earth System Model (E3SM) Land Model (ELM) to generate ELM-simulated global SIF estimates, which were then benchmarked against satellite SIF observations with a surrogate modeling approach. Our results indicated good modeling performance of the ML-based GPP-SIF relationship. The ELM model when fed with the ML GPP-SIF models also can well predict the spatial-temporal variations in SIF. We also found high model accuracy for the surrogate modeling. Model parameter sensitivity analysis suggested that the fraction of leaf nitrogen in RuBisCO (flnr) is the most sensitive parameter to the SIF; other sensitive parameters include the Ball-Berry stomatal conductance slope (mbbopt) and the vcmax entropy (vcmaxse). The posterior uncertainty in simulated GPP was greatly reduced after benchmarking, and the model produced improved spatial patterns of mean GPP relative to FLUXCOM GPP. Our integrated approach provides a new avenue for improving land models and using remote-sensing SIF, which can be further improved in the future with more ground- and satellite-based observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Predicting industrial building energy consumption with statistical and machine-learning models informed by physical system parameters

The industrial sector consumes about one-third of global energy, making them a frequent target for energy use reduction. Variation in energy usage is observed with weather conditions, as space conditioning needs to change seasonally, and with production, energy-using equipment is directly tied to production rate. Previous models were based on engineering analyses of equipment and relied on site-specific details. Others consisted of single-variable regressors that did not capture all contributions to energy consumption. Further, new modeling techniques could be applied to rectify these weaknesses. Applying data from 45 different manufacturing plants obtained from industrial energy audits, a supervised machine-learning model is developed to create a general predictor for industrial building energy consumption. The model uses features of air enthalpy, solar radiation, and wind speed to predict weather-dependency; motor, steam, and compressed air system parameters to capture support equipment contributions; and operating schedule, production rate, number of employees, and floor area to determine production-dependency. Results showed that a model that used a linear regressor over a transformed feature space could outperform a support vector machine and utilize features more representative of physical systems. Using informed parameters to build a reliable predictor will more accurately characterize a manufacturing facility's energy savings opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Gallium isotopic constraints for the origin of the Earth-Moon system

Comparatively heavy isotopic compositions of moderately volatile elements (MVE) in lunar rocks have been advocated to reflect the loss of light isotopes during devolatilization processes from the Moon. In this study we present new gallium (Ga) isotope data for lunar highland rocks, with a focus on the Ferroan Anorthosite Suite (FAS). These are commonly thought to be direct crystallization products from the late lunar magma ocean (LMO) and should contain the majority of the Ga inventory of the Moon. As such, FAS rocks are crucial for identifying the processes that drove Ga isotope fractionation as well as for inferring the Ga isotopic composition of the bulk Moon. Our data reveal that FAS samples have a range in δ 71 Ga from -0.27 to 0.22‰ and are generally isotopically light in Ga compared to other lunar lithologies, but straddle values typical of terrestrial rocks. Although Ga is defined as an MVE, these Ga isotope variations do not correspond with concentrations of more volatile elements, indicating that Ga isotope variations in the FAS are not primarily controlled by devolatilization processes. Instead, the Ga isotopic compositions of bulk FAS rocks broadly correlate with the composition of plagioclase, with the calcium content of plagioclase decreasing as Ga becomes isotopically heavier. This suggests that fractionation of Ga isotopes in FAS rocks was caused by the preferential incorporation of isotopically light Ga into plagioclase during the later solidification stages of the LMO. The progressive crystallization and extraction of plagioclase forces the residual melt towards increasingly heavier Ga isotope ratios, corroborating similar conclusions derived from correlations between δ 71 and Eu* in the mare basalt suite. Using Ga isotope partitioning calculations, we demonstrate that an isotope fractionation coefficient between plagioclase and coexisting melt of -0.3 to -0.4‰ could explain the observed range of δ 71 values in FAS, mare basalt suite rocks, and KREEP. These calculations allow for a first order estimate of the Ga isotopic composition of the bulk silicate Moon prior to plagioclase fractionation and suggest it was close to the composition of the bulk silicate Earth. This would imply that the Moon did not lose a substantial fraction of its Ga inventory during accretion, consistent with new constraints from Rb-Sr isotope systematics that indicate the Moon's volatile deficit was primarily inherited from Theia. In conjunction with the overlap in non-mass-dependent isotope ratios, these collective observations could be reconciled if Theia and the proto-Earth formed in similar regions of the inner Solar System that were already volatile-depleted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Brewster angle-cavity ringdown spectroscopy for low temperature plasma measurements in multiphases

Here we report on the development of a Brewster angle-cavity ringdown spectroscopy (BA-CRDS) system for low temperature plasma diagnostics. The system can measure gas species in solutions, with a detection limit (minimum detectable absorbance) of 9.1 × 10 -5 , which is equivalent to a detection limit of 0.04 parts per billion for measuring OH radicals in water at 308 nm. With higher reflectivity ringdown mirrors and improved design of a Brewster angle cell, the detection limit can potentially be up to 10 -6 or lower. In this exploratory study, the absorption cross sections of HgBr 2 and H 2 O 2 in the aqueous phase at 256 nm are measured to be (1.8 ± 0.1) × 10 -18 cm 2 and (5.2 ± 0.5) × 10 -20 cm 2 , respectively. Furthermore, temporal profiles of absorbance from distilled water, HgBr 2 , and H 2 O 2 solutions when interacting with a helium atmospheric plasma jet are individually characterized at different plasma powers, gas flow rates, and/or solute concentrations. The observed linear temporal profiles of absorbance from the plasma-interacted water suggest formation of H 2 O 2 from plasma-generated OH radicals, while the nonlinear temporal profiles from the plasma-treated HgBr 2 solutions reveal possible removal of HgBr 2 by OH radicals. Our results demonstrate that the new BA-CRDS system is a powerful tool for quantification of reactive plasma species in multiphases or other complex settings.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗