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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Resilient Inverter-Driven Black Start with Collective Parallel Grid-Forming Operation: Preprint

As the modern power systems are experiencing exceptional changes with increasing penetration of inverter-based resources (IBRs), system restoration using IBRs has received attention. Using local grid-forming (GFM) assets near consumers, engineered to establish grid voltages in the absence of a stiff grid, i.e., bottom-up restoration, a distribution system would obtain high system resilience, by not relying on the bulk power system restoration requiring significant human intervention and procedure to restore. This paper studies the technical feasibility of the novel approach with detailed electromagnetic transient (EMT) simulations. To thoroughly evaluate the potential of GFM inverters and technical challenges in IBR-driven black start, a detailed three-phase inverter model is developed, including negative-sequence control for voltage balance and a phase-by-phase current limiter to sustain momentary overloading during the black start. To examine dynamic aspects of the black start process, the EMT simulation also models transformer and motor dynamics to emulate their inrush and start-up behaviors as well as network dynamics. In addition, active involvement of grid-following distributed energy resources (DER) is also studied to facilitate the black start process. It is shown that, by allowing multiple GFM inverters to collectively black start without master-slave coordination, a system can achieve high resilience even with a fraction of assets lost. Two test cases of inverter-driven black start using two and one GFM inverters, respectively, for a heavily unbalanced 2-MVA distribution feeder are demonstrated. Takeaways for further study and field deployment are provided.

grid-forming inverter↗
DOE OSTI2025

Enhancing Unknown Waveform Detection by Learning Intra and Inter-domain Dependencies with Advanced Attention Fusion Mechanisms

Detection of unknown waveforms in mission-critical communications is a crucial area of interest for the Department of Energy (DoE). Traditional methods and recent deep learning-based approaches often assume that the training set includes all possible classes, which is impractical for detecting new waveforms. This limitation gives rise to the problem of open-set recognition (OSR), which involves correctly identifying known classes while detecting and rejecting unknown or unseen classes. To address this limitation, we propose a novel dual-domain complex-valued neural architecture that jointly processes time-domain and frequency-domain signal representations using transformer mechanisms. A transformer model is a deep learning architecture that uses self-attention mechanisms to process and learn relationships in sequential data. Our model employs a cosine similarity loss to extract domain-specific features and incorporates a transformer architecture in the latent space to weigh the importance of different features from the time and frequency domains. The transformer layer includes stacked self-attention and cross-attention modules to learn intra-domain and inter-domain dependencies, creating a more holistic signal representation. An attention-based fusion module intelligently combines the time and frequency-domain features using multi-head attention, enabling the network to learn the optimal feature for each domain in each input signal. Quantitative results demonstrate the impact of these architectural choices on overall performance, showing significant improvement after incorporating self and cross-attention modules and using complex attention fusion over simple weighted fusion. Our ongoing work will focus on addressing the limitations of threshold-based OSR methods by developing a novel generative framework that integrates a conditional diffusion probabilistic model (DPM). DPM is a generative framework that learns to synthesize complex data by reversing a gradual noising process using a neural network trained to denoise step-by-step. Our goal is to leverage the inherent strengths of DPMs for identifying unknown signals more robustly. One primary advantage of using a DPM is its ability to provide a more reliable anomaly score based on the model's reconstruction error, rather than relying solely on classifier confidence. Additionally, the iterative denoising process of DPMs makes this approach naturally resilient to low Signal-to-Noise Ratio (SNR) conditions, where traditional methods often fail. By implementing this generative framework, we aim to enhance the model's capability to accurately detect unknown waveforms and maintain performance in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Optical super-resolution microscopy in polymer science

The advent of optical super-resolution microscopy (OSRM) over two decades ago has transformed light-mediated interrogation of systems down to the nanoscale. This innovative set of approaches to optics breaks the so-called diffraction limit of light (~200 nm), allowing for the first time to use optics in the far field to visualize behavior on nanoscopic length scales. While these visualization tools have rapidly found widespread use in biology and related fields, their implementation in materials and, more specifically, in polymer science has been far slower. To overcome possible barriers and highlight possible future directions, we present in this paper an introduction to OSRM for polymer scientists, beginning with an overview of relevant techniques and existing optical probes. We then show and examine the first examples of OSRM adaptation across major areas of polymer science, including: polymerization and structural characterization, self-assembly and solution behavior, bulk structure and behavior, crystallization, gel structure and behavior, phase transitions, and biofunctionality. We hope and anticipate that the discussions provided in this review will draw the attention of the polymer community to the capacities of these hitherto underexplored optical visualization techniques to further transform polymer science.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ultrahigh performance LC/FT-MS non-targeted screening for biomass burning organic aerosol with MZmine2 and MFAssignR

In recent years, ultrahigh performance liquid chromatography Fourier transform mass spectrometry (LC/FT-MS) based non-targeted screening (NTS) methods have become increasingly popular for comprehensive analysis of complex organic mixtures. However, applying these methods for environmental complex mixture analysis is challenging due to the extreme complexity of natural samples and a lack of standard samples or surrogates for environmental complex mixtures. Furthermore, limited molecular markers in the databases and insufficient data processing software workflows make the application of these methods more challenging for environmental complex mixtures. In this work, we implement a new NTS data processing workflow to process data collected from ultrahigh performance liquid chromatography and Fourier transform Orbitrap Elite Mass Spectrometry (LC/FT-MS) by combining MZmine2 and MFAssignR, two opensource data processing tools and commercial Mesquite liquid smoke as a surrogate for biomass burning organic aerosol. MZmine2.53 data extraction followed MFAssignR molecular formula assignment offered noise free and highly accurate 1733 individual molecular formulas presented in liquid smoke with 4906 molecular species, including isomers. The results of this new approach were consistent with the results of direct infusion FT-MS analysis confirming its reliability. Over 90% of the molecular formulas presented in mesquite liquid smoke were matched with the molecular formulas of ambient biomass burning organic aerosol. This suggests the potential use of commercial liquid smoke as a surrogate for biomass burning organic aerosol research. Furthermore, the presented method significantly improves the identification of the molecular composition of biomass burning organic aerosol by successfully addressing some of the limitations related to the data analysis and giving a semi quantitative insight into the analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Insights into the Nanostructure, Solvation, and Dynamics of Liquid Electrolytes through Small-Angle X-Ray Scattering

The fundamental understanding of nanostructures of liquid electrolytes is expected to enable transformative gains in electrochemical energy storage capacities. However, the solvation structures and molecular dynamics in electrolytes are hard to probe, which limits further performance improvements in macroscopic properties such as ionic conductivity, viscosity, and stability. Small-angle X-ray scattering (SAXS), a non-destructive method for nanostructures characterization in liquids, offers a unique perspective on molecular clusters, anion-cation pairs, solvation sheath, percolating network, aggregates, and domain sizes of electrolytes. Notably, the SAXS method has excellent time-resolution, enabling the study of molecular dynamics by operando characterization. This review focuses on the microscopic understanding of liquid electrolytes by SAXS and operando SAXS. The unique capabilities of X-ray scattering for intra- and inter-molecular relationship and nanostructure characterization of electrolytes are highlighted.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Scattering amplitudes and N -body post-Minkowskian Hamiltonians in general relativity and beyond

We present a general framework for calculating post-Minskowskian, classical, conservative Hamiltonians for N non-spinning bodies in general relativity from relativistic scattering amplitudes. Novel features for N > 2 are described including the subtraction of tree-like iteration contributions and the calculation of non-trivial many-body Fourier transform integrals needed to construct position space potentials. A new approach to calculating these integrals as an expansion in the hierarchical limit is described based on the method of regions. As an explicit example, we present the O(G 2 ) 3-body momentum space potential in general relativity as well as for charged bodies in Einstein-Maxwell. The result is shown to be in perfect agreement with previous post-Newtonian calculations in general relativity up to O(G 2 v 4 ). Furthermore, in appropriate limits the result is shown to agree perfectly with relativistic probe scattering in multi-center extremal black hole backgrounds and with the scattering of slowly-moving extremal black holes in the moduli space approximation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Diverse Thaumarchaeota Dominate Subsurface Ammonia-oxidizing Communities in Semi-arid Floodplains in the Western United States

Subsurface microbial communities mediate biogeochemical transformations that drive both local and ecosystem-level cycling of essential elements, including nitrogen. However, their study has been largely limited to the deep ocean, terrestrial mines, caves, and topsoils (< 30 cm). Here, we present regional insights into the microbial ecology of aerobic ammonia oxidation within the terrestrial subsurface of five semi-arid riparian sites spanning a 900-km N-S transect. We sampled sediments, profiled communities to depths of ≤10 m, and compared them to reveal trends regionally within and surrounding the Upper Colorado River Basin (CRB). The diversity and abundance of ammonia-oxidizing microbial communities were evaluated in the context of subsurface geochemistry by applying a combination of amoA (encoding ammonia monooxygenase subunit A) gene sequencing, quantitative PCR, and geochemical techniques. Analysis of 898 amoA sequences from ammonia-oxidizing archaea (AOA) and bacteria (AOB) revealed extensive ecosystem-scale diversity, including archaeal amoA sequences from four of the five major AOA lineages currently found worldwide as well as distinct AOA ecotypes associated with naturally reduced zones (NRZs) and hydrogeochemical zones (unsaturated, capillary fringe, and saturated). Overall, AOA outnumber AOB by 2- to 5000-fold over this regional scale, suggesting that AOA may play a prominent biogeochemical role in nitrification within terrestrial subsurface sediments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Plasma-assisted manipulation of vanadia nanoclusters for efficient selective catalytic reduction of NO x

Supported nanoclusters (SNCs) with distinct geometric and electronic structures have garnered significant attention in the field of heterogeneous catalysis. However, their directed synthesis remains a challenge due to limited efficient approaches. This study presents a plasma-assisted treatment strategy to achieve supported metal oxide nanoclusters from a rapid transformation of monomeric dispersed metal oxides. As a case study, oligomeric vanadia-dominated surface sites were derived from the classic supported V 2 O 5 -WO 3 /TiO 2 (VWT) catalyst and showed nearly an order of magnitude increase in turnover frequency (TOF) value via an H 2 -plasma treatment for selective catalytic reduction of NO with NH 3 . Such oligomeric surface VO x sites were not only successfully observed and firstly distinguished from WO x and TiO 2 by advanced electron microscopy, but also facilitated the generation of surface amide and nitrates intermediates that enable barrier-less steps in the SCR reaction as observed by modulation excitation spectroscopy technologies and predicted DFT calculations.

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

Competing polar phases in 2D ferroelectric transition metal thio- and selenophosphates

The aim of this Perspective is to provide an in-depth discussion of a certain class of 2D ferroelectrics that feature a van der Waals gap where more than one polar phase can exist energetically close to the ground state. Polar phases of interest can include different ferroelectric, antiferroelectric, and paraelectric phases, which can be transformed into each other through external stimuli, offering unprecedented control over polar material properties. With this level of control, important size limitations and integration problems can be overcome, and material platforms with tunable polar properties for multi-functional devices and sensors can be developed for the next generation of information and energy technologies. We highlight the co-existence of polar properties that have been found on local scales using advanced local characterization techniques as well as methods to control polar properties in transition metal thio-/selenophosphates. In conclusion, we give an overview of future challenges and opportunities in this emerging field of energetically close polar phases.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Compatibility of FeCrAlMo in Flowing Pb-Li at 600°C to 700°C

A series of monometallic thermal convection loops (TCLs) has been conducted to determine the maximum temperature where FeCrAl alloys have compatibility with eutectic lead lithium (Pb-Li) for a dual-coolant fusion blanket. Pre-oxidizing commercial alloy APMT (Fe-21Cr-5Al-3Mo) for 2 h at 1000°C to form a surface α-Al 2 O 3 layer was very effective in reducing the mass loss of specimens in the hot and cold legs of the most recent TCL that was operated for 1000 h with a peak temperature of 700°C. However, unlike previous experiments, the postexposure room temperature ductility of many of the APMT specimens was degraded to <10% total elongation, and many of the specimens at the highest temperature (>680°C) were severely damaged or were not recovered. Furthermore, wide-angle X-ray scattering found that the pre-formed α-Al 2 O 3 scale transformed to a mixture of trigonal and tetragonal LiAlO 2 . The overall results suggest that the maximum temperature for FeCrAl is limited to <700°C.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

First experimental study of multiple orientation muon tomography, with image optimization in sparse data environments

Due to the high penetrating power of cosmic ray muons, they can be used to probe very thick and dense objects. As charged particles, they can be tracked by ionization detectors, determining the position and direction of the muons. With detectors on either side of an object, particle direction changes can be used to extract scattering information within an object. This can be used to produce a scattering intensity image within the object related to density and atomic number. Such imaging is typically performed with a single detector-object orientation, taking advantage of the more intense downward flux of muons, producing planar imaging with some depth-of-field information in the third dimension. Several simulation studies have been published with multi-orientation tomography, which can form a three-dimensional representation faster than a single orientation view. In this work we present the first experimental multiple orientation muon tomography study. Experimental muon-scatter based tomography was performed using a concrete filled steel drum with several different metal wedges inside, between detector planes. Data was collected from different detector-object orientations by rotating the steel drum. The data collected from each orientation were then combined using two different tomographic methods. Results showed that using a combination of multiple depth-of-field reconstructions, rather than a traditional inverse Radon transform approach used for CT, resulted in more useful images for sparser data. As cosmic ray muon flux imaging is rate limited, the imaging techniques were compared for sparse data. Using the combined depth-of-field reconstruction technique, fewer detector-object orientations were needed to reconstruct images that could be used to differentiate the metal wedge compositions.

Applied Physics (physics.app-ph)↗
DOE OSTI2020

Active sulfur cycling in the terrestrial deep subsurface

The deep terrestrial subsurface remains an environment where there is limited understanding of the extant microbial metabolisms. At Olkiluoto, Finland, a deep geological repository is under construction for the final storage of spent nuclear fuel. It is therefore critical to evaluate the potential impact microbial metabolism, including sulfide generation, could have upon the safety of the repository. As such, we investigated a deep groundwater where sulfate is present, but groundwater geochemistry suggests limited microbial sulfate-reducing activity. Examination of the microbial community at the genome-level revealed microorganisms with the metabolic capacity for both oxidative and reductive sulfur transformations. Deltaproteobacteria are shown to have the genetic capacity for sulfate reduction and possibly sulfur disproportionation, while Rhizobiaceae, Rhodocyclaceae, Sideroxydans, and Sulfurimonas oxidize reduced sulfur compounds. Further examination of the proteome confirmed an active sulfur cycle, serving for microbial energy generation and growth. Our results reveal that this sulfide-poor groundwater harbors an active microbial community of sulfate-reducing and sulfide-oxidizing bacteria, together mediating a sulfur cycle that remained undetected by geochemical monitoring alone. The ability of sulfide-oxidizing bacteria to limit the accumulation of sulfide was further demonstrated in groundwater incubations and highlights a potential sink for sulfide that could be beneficial for geological repository safety.

58 GEOSCIENCES↗
DOE OSTI2023

Resilient Inverter-Driven Black Start with Collective Parallel Grid-Forming Operation

As modern power systems are experiencing exceptional changes with increasing penetrations of inverter-based resources (IBRs), system restoration using IBRs has received attention. Using local grid-forming (GFM) assets near consumers, engineered to establish grid voltages in the absence of a stiff grid, i.e., bottom-up restoration, a distribution system could obtain high system resilience by not relying on the bulk power system restoration, which requires significant human intervention and procedure. This paper studies the technical feasibility of the novel approach with detailed electromagnetic transient (EMT) simulations. To thoroughly evaluate the potential of GFM inverters and the technical challenges in IBR-driven black start, a detailed three-phase inverter model is developed, including negative-sequence control for voltage balance and a phase-by- phase current limiter to sustain momentary overloading during the black start. To examine dynamic aspects of the black-start process, the EMT simulation also models transformer and motor dynamics to emulate their inrush and startup behaviors as well as network dynamics. In addition, active involvement of grid- following distributed energy resources is also studied to facilitate the black-start process. By allowing multiple GFM inverters to collectively black start without leader-follower coordination, we demonstrate that a system can achieve high resilience even with a fraction of assets lost. Two test cases of inverter-driven black start, using two and one GFM inverters, respectively, for a heavily unbalanced 2-MVA distribution feeder are demonstrated. Takeaways for further study and field deployment are provided.

grid-forming inverter↗
DOE OSTI2025

FY24 Task 5: Leachate Disposition

Directly feeding sludge solids to the high-level waste (HLW) Waste Treatment Plant represents an alternative flowsheet seeking to initiate sludge processing as soon as possible. Key processing functions previously captured during baseline pretreatment operations include leaching and washing prior to solids concentration. These operations should be considered in the potential direct feed flowsheets to maximize waste feed loading, minimize HLW volume, and mitigate corrosion challenges associated with vitrification of high phosphate and fluoride concentrations. Additionally, single-shell tank (SST) retrievals and waste transfers to double-shell tanks (DSTs) in a direct feed flowsheet would likely also benefit from some level of leaching, washing, and solids concentration in order to reduce DST space and mission duration. These operations could occur in a new facility or potentially in available DSTs. If washing and leaching are utilized, an effective disposition pathway for the wash water and leachate solutions are needed. Three target species that benefit significantly from leaching and washing are phosphate, fluoride and aluminum. Phosphate (PO 4 3- ) and fluoride (F - ) can contribute substantially to the amount of carrier fluid needed for dissolution, and the resulting volume of liquid generated. Disposition of this retrieval solution should be evaluated in order to prevent crystallization of these anions throughout system processing. Since there is a high probability that any retrieval solutions will be at or near their PO 4 3- and F - solubility limits, evaporation or blending with a high Na supernate (>3.5 M) is not recommended for the wash water streams without a method to remove precipitants prior to solution disposal. Additionally, aluminum present in the southeast quadrant of the Hanford site represents roughly 60% of the waste solids in the initial processing tanks. These aluminum solids are in the form of gibbsite (Al(OH) 3 ) and can pose significant challenges for processing due to the fast-settling times and high solids loading associated with these materials. Easily remediated by caustic addition to the solids, these wash solutions could be processed through crystalline silicotitanate (CST) ion exchange columns to prepare the supernate solutions for disposition. The current target for feed conditions to the Low Activity Waste (LAW) melter are waste streams that contain nominally 5-6 M Na. Fractions within the tanks contain upwards of 0.2 M phosphate and fluoride in solution at 3.5 M Na. Concentrating these solutions above 5 M Na would result in an exceedance of the solubility limits, and potential for uncontrolled precipitation of the phosphate and fluoride crystal material. The resulting crystalline salt material is typically sodium fluoride phosphate, also referred to as natrophosphate (Na 7 FPO 4 ·19H 2 O). Salt phases are of importance in tank waste due to their chemical reactivity, which can result in precipitation, dissolution, or transformation, impacting any downstream processes (Bolling et al. 2020, Russell, Snow, and Peterson 2010). Salt generation and precipitation could pose challenges by causing system plugging and melter corrosion if left in the supernate stream, or limit sodium molarity of the supernate that would be accepted without incident in waste operations. To understand the impact of this salt generation, the crystallization of natrophosphate in multiple simulant feed matrices was studied to understand the implications of various tank waste supernate chemistries. Three matrices were examined: high PO 4 3- /low F - , low PO 4 3- /high F - , and an average matrix. Subsequent testing was performed with the average matrix with the inclusion of CsNO 3 , and a final run with the average matrix including CsNO 3 and a 137 Cs spike for tracer purposes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Integrable field theories and their CCFT duals

We compute the Mellin transforms of various two-dimensional integrable S-matrices, providing the first explicit, non-perturbative realizations of celestial CFT. In two dimensions, the Mellin transform is simply the Fourier transform in rapidity space, and the “celestial correlator” has no position dependence. The simplified setting allows us to study the analytic properties of CCFT correlators exactly as a function of the conformal dimensions. We find that the correlators exist as real distributions of the conformal weights, with asymptotics controlled by the mass spectrum and three-point couplings of the model. Coupling these models to a flat space limit of JT gravity preserves integrability and dresses the amplitudes by a rapidly varying gravitational phase. We find that the coupling to gravity smooths out certain singular aspects of the Mellin-transformed correlators.

2D Gravity↗
DOE OSTI2022

Enhancing the Reversibility of Lattice Oxygen Redox Through Modulated Transition Metal–Oxygen Covalency for Layered Battery Electrodes

Utilizing reversible lattice oxygen redox (OR) in battery electrodes is an essential strategy to overcome the capacity limitation set by conventional transition metal redox. However, lattice OR reactions are often accompanied with irreversible oxygen oxidation, leading to local structural transformations and voltage/capacity fading. Herein, it is proposed that the reversibility of lattice OR can be remarkably improved through modulating transition metal-oxygen covalency for layered electrode of Na-ion batteries. By developing a novel layered P2-Na 0.6 Mg 0.15 Mn 0.7 Cu 0.15 O 2 electrode, it is demonstrated that the highly electronegative Cu dopants can improve the lattice OR reversibility to 95% compared to 73% for Cu-free counterpart, as directly quantified through high-efficiency mapping of resonant inelastic X-ray scattering. Crucially, the large energetic overlap between Cu 3d and O 2p states dictates the rigidity of oxygen framework, which effectively mitigates the structural distortion of local oxygen environment upon (de)sodiation and leads to the enhanced lattice OR reversibility. The electrode also exhibits a completely solid-solution reaction with an ultralow volume change of only 0.45% and a reversible metal migration upon cycling, which together ensure the improved electrochemical performance. Finally, these results emphasize the critical role of transition metal-oxygen covalency for enhancing the reversibility of lattice OR toward high-capacity electrodes employing OR chemistry.

25 ENERGY STORAGE↗
DOE OSTI2025

A systematic review of machine learning in groundwater monitoring

With increasing concerns about water scarcity, groundwater has become crucial since this resource provides most of the freshwater needs. However, various human and natural activities often contaminate the groundwater, making it unsuitable for use. Over the years, scientists and engineers have used many methods to predict and track groundwater contamination as part of environmental monitoring. Consequently, there is an urgent need for improved methods, particularly in the face of increasing contamination. Machine learning has sometimes been used to monitor groundwater, air quality, and climate. Traditional methods must be improved due to the complexity and large amount of environmental data. This includes using hybrid models that combine traditional and new techniques. Despite the use of machine learning in many scientific areas, there is a lack of comprehensive reviews focusing on its use in environmental monitoring, especially groundwater monitoring. We aim to fill this gap by exploring machine-learning applications in groundwater monitoring. We discuss relevant methods, their limitations, and future potential. We summarize research on automating data processing and model training using groundwater sensor data. Our research underscores the transformative potential of machine learning to revolutionize long-term groundwater monitoring and contamination detection, providing valuable insights for future research and practical applications.

AI/ML↗
DOE OSTI2020

Effect of Al substitution on the magnetocaloric properties of Ni-Co-Mn-Sn multifunctional alloys

Ni-Mn-based metamagnetic shape memory alloys have been extensively studied due to their multifunctional properties including magnetocaloric effect (MCE), magnetoresistance effect, and magnetic-field-induced strain. However, the large intrinsic thermal hysteresis of these alloys sets a limit on further development for practical applications. Here, with a few atomic percent Al substitution, we greatly reduced the thermal hysteresis and transformation temperature interval while maintaining the large magnetization difference (ΔM) between austenite and martensite. The simultaneous achievement of a large ΔM and low thermal hysteresis leads to a remarkable enhancement in MCE upon Al substitution, and a maximum magnetic entropy change of 31.6 J/kg K is achieved under a field of 5 T in Ni 39 Co 11 Mn 40 Sn 8 Al 2 . Furthermore, our in situ high-energy X-ray diffraction experiments show that the Ni 39 Co 11 Mn 40 Sn 8 Al 2 has good geometric compatibility between austenite and martensite, which accounts for the reduced thermal hysteresis in this alloy. This study is instructive for the development of high-performance magnetocaloric materials in the metamagnetic shape memory alloys.

36 MATERIALS SCIENCE↗