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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unraveling fundamental mechanisms of silicon nitride crystallization in microelectronics manufacturing

This research project investigates the fundamental mechanisms of silicon nitride (SiN) crystallization, aiming to enhance the understanding of this critical material in microelectronics manufacturing. Through a collaborative effort between Sandia National Laboratories, the University of Tennessee, and the University of Florida, we developed a comprehensive framework that integrates experimental techniques, atomistic modeling, meso-scale simulations, and an integrated multi-scale model to capture this physical phenomenon on multiple time and length scales . The project developed a new machine learning based atomistic potential and utilized advanced phase field modeling to capture the complexities of polycrystalline growth and the influence of mechanical stresses on crystallization dynamics. By employing a grain tracker algorithm, the meso-scale model effectively identified and tracked individual crystal grains, enabling the simulation of anisotropic growth behaviors reflective of SiN’s physical properties. The integration of atomistic simulations with meso-scale modeling created a powerful multi-scale framework that validated atomistic inputs and enhanced predictive accuracy for crystallization dynamics at larger scales, validated experimentally. This adaptable modeling capability not only accelerates development times by informing manufacturing processes but also serves as a valuable starting point for understanding crystallization physics in similar materials. The insights gained from this research unlock new opportunities for the development of advanced materials tailored for future microelectronics and photonics applications. Overall, this project represents a significant advancement in understanding of fundamental physics of SiN and establishes a foundation for future research in material science, bridging the gap between atomic-level phenomena and macroscopic material behaviors for practical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

EMSL Community Science Campaign Meeting: Critical Minerals and Materials - Rhizo Critical Campaign Breakout Session Report Summary

The “Critical Minerals Biogeochemistry in the Rhizosphere – Ultramafic Soils (Rhizo Critical)” campaign breakout (BO) session was organized to identify major knowledge gaps and fundamental research needs in rhizosphere microbiology and geochemistry that, if addressed, could transform our ability to recover critical minerals from ultramafic soil systems. We sought to identify significant challenges that must be surmounted in the pursuit of deeper science knowledge. Our ultimate goal is to understand this landscape well enough to identify and prioritize opportunities for EMSL to make the greatest impact with Environmental Transformations and Interactions (ETI) science area research campaigns focused on the biogeochemical processes controlling the behavior of critical minerals and materials in the rhizosphere. The increasing demand for critical materials and minerals (CMM) in the U.S. has heightened interest in low-grade ores with much attention on ultramafic soils, which contain valuable metals such as nickel (Ni), chromium (Cr), manganese, cobalt (Co), and copper (Lee et al., 2025; DOE CMM Report, 2023) used in advanced battery, magnet, wiring and wind turbines, and stainless steel technologies. Metal hyperaccumulating plants grown in ultramafic soils can extract economically valuable concentrations of CMMs through the process of phytomining. This technology has evolved from phytoremediation, which involves using plants to cleanse contaminated environments by removing, detoxifying, or stabilizing pollutants like metals and organic compounds. Hyperaccumulator plants are capable of storing metals in their living tissues at concentrations hundreds to thousands of times higher than those found in 'normal' plants. For instance, while the average concentration of Ni in the dry matter of plants growing in typical soils is usually less than 5 µg g?¹, Ni hyperaccumulation is defined by concentrations exceeding 1,000 µg g?¹ (Corzo Remigio et al., 2020; Reeves et al., 2018). Phytomining research has primarily focused on Ni (Rylott and van der Ent, 2025), for which the U.S. has very limited conventional mines in operation. Most soils typically contain Ni concentrations ranging from 7 to 50 mg kg-1, whereas serpentine soils exhibit significantly higher levels, with Ni content often ranging between 700 and 8,000 mg kg-1 (Sobczyk et al., 2017). While more than 500 plant species in over 50 different families have been identified as Ni hyperaccumulators (Kidd et al., 2018), Ni phytomining (and phytominng in general) remains largely untested because most studies are short-term, small-scale, and conducted under simplified or artificially enriched conditions, so they fail to capture the low metal concentrations, environmental variability, and management constraints that would be needed for a field-scale demonstration. Few hyperaccumulator species have been validated as true “metal crops,” and their biomass production, stress tolerance, and rooting characteristics are usually too poor to yield economically meaningful metal outputs. Critically, the basic mechanisms of metal uptake, transport, and sequestration, especially as shaped by belowground processes such as root exudation, rhizosphere chemistry, and root–microbe interactions that control metal mobility and bioavailability (Montreemuk et al., 2023; Kidd et al., 2018; Durand et al., 2023; Alford et al., 2010), are still only partially understood, and downstream metal recovery from biomass is rarely optimized. Because these limitations stem from gaps in fundamental knowledge rather than from a failure of the concept itself (Rylott and van der Ent, 2025; van der Ent et al., 2015), there is a strong need for basic science that dissects plant metal homeostasis, rhizosphere and microbial processes, and their integration with soil chemistry and process engineering to design more robust, scalable phytomining systems.

Ahkami, Amirhossein↗
DOE OSTI2020

The Earth has humans, so why don’t our climate models?

While climate models have rapidly advanced in sophistication over recent decades, they lack dynamic representation of human behavior and social systems despite strong feedbacks between social processes and climate. The impacts of climate change alter perceptions of risk and emissions behavior that, in turn, influence the rate and magnitude of climate change. Addressing this deficiency in climate models requires a substantial interdisciplinary effort to couple models of climate and human behavior. We suggest a multi-model approach that considers a range of theories and implementations of human behavior and social systems, similar to the multi-model approach that has been used to explore the physical climate system. In this work, we describe the importance of linking social factors with climate processes and identify four priorities essential to advancing the development of coupled social-climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Smart Droplets Stabilized by Designer Surfactants: From Biomimicry to Active Motion to Materials Healing

The science and technologies of emulsion droplets have been a long‐term focus of extensive research endeavors for their practical utility across a breadth of industries, including pharmaceutical products, oil recovery processes, and the food sciences. However, with advances in materials chemistry and characterization tools, new emerging areas are arising with a focus on “smart droplets”. The versatility of emulsion droplets across is based on their ability to partition and create isolated systems with properties defined by the liquid–liquid interface, while preparative routes allow manipulation of droplet size, stability, and encapsulated contents. As described in this article, significant efforts are being devoted to creating new types of droplets by “activating” this interface through the incorporation of reactive structures that trigger droplet response to applied or environmental stimuli (e.g., pH, temperature, salt, or external fields). Moreover, parallels between droplets and live cells inspire efforts to conceive systems that resemble biological motifs or that can produce cellular behaviors that imitate biology (e.g., swarming, communication, or motion). Here, the authors highlight recent advances in smart droplets, with emphasis on organic, polymer, and/or particle surfactants that give rise to inter‐droplet communication (via aggregation, fusion, division, or mass transfer), droplet vehicles for controlled delivery, autonomous droplet motion, and tunable emulsion inversion. Especially emphasized is the macromolecular design to produce reactive and functional surfactants, which are crucial to responsive droplet behavior and their underlying mechanisms. More generally, the exquisite interplay between materials science and biology inspires the review of this research area that provides unique opportunities for insight and inspiration into the capabilities of new droplet designs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effects of size, geometry, and testing temperature on additively manufactured Ti-6Al-4V titanium alloy

This article presents a comprehensive study concerning size and geometry effect on the ambient and high-temperature mechanical behavior of additively manufactured laser powder bed fusion Ti-6Al-4V alloy. Key mechanical property metrics are presented, including strain hardening rate, yield strength, and Young’s modulus as a function of thickness and testing temperature (ambient, 250 °C, and 450 °C). Here, the effect of specimen size on manufacturing-induced microstructural feature formation is demonstrated and discussed. A detailed analysis regarding Young’s modulus, yield strength, and strain hardening rate variation at elevated temperatures is also presented. Size effect and temperature-sensitive deformation mechanisms are linked to the underlying microstructural deformation mechanisms activated at respective temperatures. Counter-intuitively, this study determined that irrespective of the geometry, strain hardening rates increased as temperature increased. An in-depth microstructural examination is presented to explain the stated observation. The texture of Interrupted tensile test samples examined for ambient, 250 °C, and 450 °C post-yield was observed to be unchanged, indicating the strain hardening behavior was not texture dependent. Schmid factor analysis, coupled with experimental findings from previous work, was implemented to generate a hypothesis. This hypothesis suggests that the drop in critical resolved shear stress for basal and pyramidal slip systems, as temperature increases, paired with the high dislocation density of laser powder bed fusion Ti-6Al-4V, leads to dislocation entanglement and results in increased strain hardening at elevated temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dynamic Interconversion of Metal Active Site Ensembles in Zeolite Catalysis

Catalysis science is founded on understanding the structure, number, and reactivity of active sites. Kinetic models that consider active sites to be static and noninteracting entities are routinely successful in describing the behavior of heterogeneous catalysts. Yet, active site ensembles often restructure in response to their external environment and even during steady-state catalytic turnover, sometimes requiring non-mean-field kinetic treatments to describe distance-dependent interactions among sites. Such behavior is being recognized more frequently in modern catalysis research, with the advent of experimental methods to quantify turnover rates with increasing precision, an expanding arsenal of operando characterization tools, and computational descriptions of atomic structure and motion at chemical potentials and timescales increasingly relevant to reaction conditions. This review focuses on dynamic changes to metal active site ensembles on zeolite supports, which are silica-based crystalline materials substituted with Al that generate binding sites for isolated and low-nuclearity metal site ensembles. Metal sites can become solvated and mobilized during reaction, facilitating interactions among sites that change their nuclearity and function. Such intersite communication can be regulated by the zeolite support, resulting in non-single-site and potentially non-mean-field kinetic behavior arising from mechanisms of catalytic action that combine elements of those canonically associated with homogeneous and heterogeneous catalysis. Here, we discuss recent literature examples that document dynamic active site behavior in metal-zeolites and outline methodologies to identify and interpret such behavior. We conclude with our outlook on future research directions to develop this evolving branch of catalysis science and harness it for practical applications.

operando characterization↗
DOE OSTI2020

Selected Negative Linear Compressibilities in the Metal–Organic Framework of [Cu(4,4'-bpy) 2 (H 2 O) 2 ]·SiF 6

Negative linear compressibility (NLC) is a rare high-pressure observation that lattice contraction is accompanied by the structural expansion along a specific direction. Generally, this counterintuitive phenomenon only derives from the intrinsic structural characteristics of materials and cannot be tuned by external perturbations. Searching for an effective method to control NLC effect is still a challenge in both chemical and material science. In this work, we successfully discover and select the NLC behaviors in the metal-organic framework (MOF) of [Cu(4,4'-bpy) 2 (H 2 O) 2 ]·SiF 6 (Cu(bpy)·SiF) through controlling the pressure conditions therein. The NLC effect of Cu(bpy)·SiF originates from the wine-rack mechanism that quasi-square grids transfer to rhombic ones with the structural expansion along the diagonal direction at high pressure. Meanwhile, both of the pressure range and magnitude of the NLC responses are enlarged with optimized pressure conditions. This study not only presents the intriguing selected NLC behaviors of a MOF but also proves the effects of pressure conditions on NLC, which offers promising strategies for further design and applications of NLC materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Mean-field model for the Curie-Weiss temperature dependence of coherence length in metallic liquids

The coherence length of the medium-range order (MRO) in metallic liquids is known to display a Curie-Weiss temperature dependence; its inverse is linearly related to temperature, and when extrapolated from temperatures above the glass transition, the coherence length diverges at a negative temperature with a critical exponent of unity. We propose a mean-field pseudospin model that explains this behavior. Specifically, we model the atoms and their local environment as Ising spins with antiferromagnetic exchange interactions. We further superimpose an exchange interaction between dynamical heterogeneities, or clusters of atoms undergoing cooperative motion. The coherence length in the metallic liquid is thus the correlation length between dynamical heterogeneities. Overall, our results reaffirm the idea that the MRO coherence length is a measure of point-to-set correlations, and that local frustrations in the interatomic interactions are prominent in metallic liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Pandemic, War, and Global Energy Transitions

The COVID-19 pandemic and Russia’s war on Ukraine have impacted the global economy, including the energy sector. The pandemic caused drastic fluctuations in energy demand, oil price shocks, disruptions in energy supply chains, and hampered energy investments, while the war left the world with energy price hikes and energy security challenges. The long-term impacts of these crises on low-carbon energy transitions and mitigation of climate change are still uncertain but are slowly emerging. This paper analyzes the impacts throughout the energy system, including upstream fuel supply, renewable energy investments, demand for energy services, and implications for energy equity, by reviewing recent studies and consulting experts in the field. We find that both crises initially appeared as opportunities for low-carbon energy transitions: the pandemic by showing the extent of lifestyle and behavioral change in a short period and the role of science-based policy advice, and the war by highlighting the need for greater energy diversification and reliance on local, renewable energy sources. However, the early evidence suggests that policymaking worldwide is focused on short-term, seemingly quicker solutions, such as supporting the incumbent energy industry in the post-pandemic era to save the economy and looking for new fossil fuel supply routes for enhancing energy security following the war. As such, the fossil fuel industry may emerge even stronger after these energy crises creating new lock-ins. This implies that the public sentiment against dependency on fossil fuels may end as a lost opportunity to translate into actions toward climate-friendly energy transitions, without ambitious plans for phasing out such fuels altogether. We propose policy recommendations to overcome these challenges toward achieving resilient and sustainable energy systems, mostly driven by energy services.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Modulation of sensory perception by hydrogen peroxide enables Caenorhabditis elegans to find a niche that provides both food and protection from hydrogen peroxide

Hydrogen peroxide (H 2 O 2 ) is the most common chemical threat that organisms face. Here, we show that H 2 O 2 alters the bacterial food preference of Caenorhabditis elegans , enabling the nematodes to find a safe environment with food. H 2 O 2 induces the nematodes to leave food patches of laboratory and microbiome bacteria when those bacterial communities have insufficient H 2 O 2 -degrading capacity. The nematode’s behavior is directed by H 2 O 2 -sensing neurons that promote escape from H 2 O 2 and by bacteria-sensing neurons that promote attraction to bacteria. However, the input for H 2 O 2 -sensing neurons is removed by bacterial H 2 O 2 -degrading enzymes and the bacteria-sensing neurons’ perception of bacteria is prevented by H 2 O 2 . The resulting cross-attenuation provides a general mechanism that ensures the nematode’s behavior is faithful to the lethal threat of hydrogen peroxide, increasing the nematode’s chances of finding a niche that provides both food and protection from hydrogen peroxide.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Unsupervised discovery of extreme weather events using universal representations of emergent organization

Spontaneous self-organization is ubiquitous in systems far from thermodynamic equilibrium. While organized structures that emerge dominate transport properties, universal representations that identify and describe these key objects remain elusive. Here, we introduce a theoretically grounded framework for describing emergent organization that, via data-driven algorithms, is constructive in practice. Its building blocks are spacetime lightcones that embody how information propagates across a system through local interactions. We show that predictive equivalence classes of lightcones—local causal states—capture organized behaviors in complex spatiotemporal systems. Employing an unsupervised physics-informed machine learning algorithm and a high-performance computing implementation, we demonstrate automatically discovering organized structures in two real-world domain science problems. We show that local causal states identify vortices and track their power-law decay behavior in two-dimensional fluid turbulence. We then show how to detect and track familiar extreme weather events—hurricanes and atmospheric rivers—and discover other novel structures associated with precipitation extremes in high-resolution climate data at the grid-cell level.

Rupe, Adam [Pacific Northwest National Laboratory ↗
DOE OSTI2026

Design, characterization and shape recovery behavior of 3D/4D printed shape memory polymers (SMPs)

Shape memory polymers (SMPs) represent a paradigm shift in material science, uniquely capable of undergoing reversible shape transformations triggered by external stimuli, positioning them as pivotal in developing next-generation biomedical devices, aerospace components, and adaptive structures. Extensive research has been done on SMPs with a major focus on high-temperature programming methods, which can limit energy efficiency and applicability with temperature-sensitive materials. Additionally, while various SMP blends have demonstrated great potential, limited work has been done on the suitability for 3D printing these materials, particularly under high-strain and ambient temperature programming conditions. In this study, a three-component optimized SMP composition was evaluated by 3D printing via the Material Extrusion (MEX) technique and investigating its ambient temperature-programming behavior at high strains. The SMP formulation studied was a tailored blend of thermoplastic polyurethane (TPU), polycaprolactone (PCL), and an octadecane diol-based copolymer (OBC) that exhibits robust shape memory behavior, high strain tolerance, and efficient force generation. Rigorous thermal, mechanical, and shape recovery analyses, along with optimized printing parameters and consistent shape recovery rates of up to 90%, were achieved under dynamic mechanical analysis (DMA), even under ambient programming conditions. This work demonstrates the SMP composition’s potential for adaptive, self-deployable systems with 4D printing characteristics ideal for bio-inspired structures and artificial muscle fibers.

Sudan, Kavish [University of Louisville, KY]↗
DOE OSTI2022

Artificial intelligence in computational materials science

In this themed collection we aim to broadly review some of the critical, recent progress in the application of AI/ML to various aspects of computational materials science and materials science more broadly. In this collection spread across two issues, we have assembled a collection of articles from leaders in the broad domain of applying AI/ML, which we collectively refer to as ML, in computational materials science. Together these articles curate the critical, recent progress in the application of ML to various aspects of materials science. Furthermore, these include ML approaches for understanding and driving electron microscopy, designing energy materials and the discovery of principles and materials relevant to the design of materials for the future, studying crystal nucleation and growth, the use of ML to describe force fields governing material and molecular behavior, and other topics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Control of High-Temperature Static and Transient Thermomechanical Behavior of SiMo Ductile Iron by Al Alloying

Abstract Silicon and molybdenum ( SiMo ) ductile iron is commonly used for exhaust manifolds because these components experience thermal cycling in oxidizing environment, which requires resistance to fatigue during transient thermomechanical loads. Previous studies have demonstrated that alloying elements, such as Al , to SiMo ductile iron reduces the amount of surface degradation during static high-temperature exposure. However, deterioration of sphericity of the graphite nodules and a decrease in ductility could affect the tendency of cracking during thermal cycling. In this article, the effect of Al alloying on static and transient thermomechanical behavior of SiMo ductile iron was investigated to optimize the amount of Al alloying. A thermodynamic approach was used to confirm the effect of the Al alloying on the phase transformations in two SiMo cast irons, alloyed by 1.8% Al and 3% Al . These two alloys were cast in a laboratory along with the baseline SiMo ductile iron. Several experimental methods were used to evaluate the dimensional stability, physical properties, static oxidation, and failure resistance during constrained thermal cycling testing to compare their high-temperature capability. Experimental results verified that Al alloying increases the temperature range and decreases volume change during eutectoid transformation, which together with enhancement of oxidation protection improved the dimensional stability. Thermocycling tests showed that the number of cycles to failure depends on the amount of Al alloying and the applied high-temperature exposure during each cycle. SEM/EDX, high-resolution TEM and µCT analysis were used to verify the mechanism resulting from the Al alloying protection. It was shown that an optimal level of Al alloying for balancing oxidation and thermal cracking resistance depends on thermomechanical conditions of application.

36 MATERIALS SCIENCE↗
DOE OSTI2020

29 Si solid state MAS NMR study on leaching behaviors and chemical stability of different Mg-silicate structures for CO 2 sequestration

Silicon is one of the most earth abundant elements, and thus, the fate and reactivity of silicate materials are often important for various energy and environmental technologies including carbon sequestration, where CO 2 is captured and stored as a thermodynamically stable solid carbonate phase. Thus, understanding the structures and chemistries of different silicate phases has become an important research aim. Here in this study, the changes in the silicate structures (Q 0 –Q 4 ) of heat-treated Mg-bearing mineral (serpentine) exposed to a CO 2 -water system (carbonic acid) was investigated using 29 Si MAS NMR, XRPD and ICP-OES and the identified structures were employed to explain complex leaching behaviors of silicate materials. The 29 Si MAS NMR and XRPD analysis indicated that the heat-treated serpentine is a mixture of amorphous (Q 1 : dehydroxylate I, Q 2 : enstatite, Q 4 : silica) and crystalline (Q 0 : forsterite, Q 3 : dehydroxylate II and serpentine) phase, while natural serpentine mineral has single crystalline Q 3 silicate structure. The leaching experiments showed that both Mg and Si in the amorphous silicate structures (Q 1 : dehydroxylate I, Q 2 : enstatite) are more soluble than those in crystalline phase (Q 0 : forsterite, Q 3 : dehydroxylate II and serpentine). Therefore, tuning the silicate structure towards Q 1 and Q 2 would significantly improve carbon sequestration potential of silicate minerals, whereas silicate materials with Q 3 structure would provide great chemical stabilities in acidic conditions. The solubilities of silicate structures were in the order of Q 1 (dehydroxylate I) > Q2 (enstatite) >> Q0 (forsterite) > Q3 (dehydroxylate II) > Q 3 (serpentine) and this finding can be used to better design a wide range of energy and environmental materials and reaction systems.

25 ENERGY STORAGE↗
DOE OSTI2024

Fungal elemental profiling unleashed through rapid laser-induced breakdown spectroscopy (LIBS)

ABSTRACT Elemental profiling of fungal species as a phenotyping tool is an understudied topic and is typically performed to examine plant tissue or non-biological materials. Traditional analytical techniques such as inductively coupled plasma–optical emission spectroscopy (ICP-OES) and inductively coupled plasma–mass spectrometry (ICP-MS) have been used to identify elemental profiles of fungi; however, these techniques can be cumbersome due to the difficulty of preparing samples. Additionally, the instruments used for these techniques can be expensive to procure and operate. Laser-induced breakdown spectroscopy (LIBS) is an alternative elemental analytical technique—one that is sensitive across the periodic table, easy to use on various sample types, and is cost-effective in both procurement and operation. LIBS has not been used on axenic filamentous fungal isolates grown in substrate media. In this work, as a proof of concept, we used LIBS on two genetically distinct fungal species grown on a nutrient-rich and nutrient-poor substrate media to determine whether robust elemental profiles can be detected and whether differences between the fungal isolates can be identified. Our results demonstrate a distinct correlation between fungal species and their elemental profile, regardless of the substrate media, as the same strains shared a similar uptake of carbon, zinc, phosphorus, manganese, and magnesium, which could play a vital role in their survival and propagation. Independently, each fungal species exhibited a unique elemental profile. This work demonstrates a unique and valuable approach to rapidly phenotype fungi through optical spectroscopy, and this approach can be critical in understanding these fungi's behavior and interactions with the environment. IMPORTANCE Historically, ionomics, the elemental profiling of an organism or materials, has been used to understand the elemental composition in waste materials to identify and recycle heavy metals or rare earth elements, identify the soil composition in space exploration on the moon or Mars, or understand human disorders or disease. To our knowledge, ionomic profiling of microbes, particularly fungi, has not been investigated to answer applied and fundamental biological questions. The reason is that current ionomic analytical techniques can be laborious in sample preparation, fail to measure all potential elements accurately, are cost-prohibitive, or provide inconsistent results across replications. In our previous efforts, we explored whether laser-induced breakdown spectroscopy (LIBS) could be used in determining the elemental profiles of poplar tissue, which was successful. In this proof-of-concept endeavor, we undertook a transdisciplinary effort between applied and fundamental mycology and elemental analytical techniques to address the biological question of how LIBS can used for fungi grown axenically in a nutrient-rich and nutrient-poor environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Validation of a Global Geospace Model With a Systems Science Approach Based on Canonical Correlation Analysis

A systems science approach based on canonical correlation analysis (CCA) is applied as a new, behavioral way to validate global geospace models. The biggest novelty of the technique is that it validates models at a system level, whereby a side‐by‐side comparison is performed of CCA applied to a 30‐day observational and the corresponding simulation data sets comprising quiet, moderate and active times. The simulation used the Multiscale Atmosphere‐Geospace Environment (MAGE) model. It is shown that (a) CCA must be combined with sensitivity analysis to be effective, (b) the MAGE model generally reproduces the observed behavior (more so for quieter time intervals), quantified by the intercorrelations between different variables and (c) the technique identifies the SuperMAG SML index as a quantity for which refinements of the model are needed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗