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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models

Spectroscopy techniques such as x-ray absorption near edge structure (XANES) provide valuable insights into the atomic structures of materials, yet the inverse prediction of precise structures from spectroscopic data remains a formidable challenge. In this study, we introduce a framework that combines generative artificial intelligence models with XANES spectroscopy to predict three-dimensional atomic structures of disordered systems, using amorphous carbon (a-C) as a model system. In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method, to predict 3D structures of disordered materials from a target property. For demonstration, we apply the model to identify the atomic structures of a-C as a representative material system from the target XANES spectra. We show that conditional generation guided by XANES spectra reproduces key features of the target structures. Furthermore, we show that our model can steer the generative process to tailor atomic arrangements for a specific XANES spectrum. Finally, our generative model exhibits a remarkable scale-agnostic property, thereby enabling generation of realistic, large-scale structures through learning from a small-scale dataset (i.e. with small unit cells). Our work represents a significant stride in bridging the gap between materials characterization and atomic structure determination; in addition, it can be leveraged for materials discovery in exploring various material properties as targeted.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-Strength, High-Ductility, High Entropy Alloys with High-Efficiency Native Oxide Solar Absorbers for Concentrating Solar Power Systems

This EPSCoR Project has been investigating the synergy between the excellent high-temperature mechanical behavior of FeMnNiAlCr high entropy alloys (HEA) and the high solar absorptance of their native oxides for high efficiency concentrated solar thermal power (CSP) systems working at >700°C. While HEAs have attracted substantial interest in recent years, most investigations have focused on their applications as structural materials rather than functional materials. This EPSCoR project discovered that FeMnNiAlCr HEAs can potentially be applied synergistically as both a structural and functional material for high-efficiency concentrating solar thermal power (CSP) systems working at >700°C. The HEA itself would be used in high-temperature tubing to carry molten salts or supercritical CO 2 , while its surface oxide would act as a high-efficiency solar thermal absorber. With Fe and Mn being the major components in these HEAs (adding up to ~70 at.% of the alloy), these materials are much more cost-effective than the Ni-based superalloys currently being investigated for high-temperature CSP systems. Through this research, these Fe-Mn based HEAs have demonstrated yield strengths 2-3x greater than that of stainless steel at 700°C and a creep lifetime >800 h at 700ºC under a typical CSP tubing mechanical load of 35 MPa. Their Mn-rich surface oxides maintain a high optical-to-thermal conversion efficiency of ~87% under 1000x solar concentration ratio for 20 simulated day-night thermal cycles between 750ºC and room temperature. In preliminary corrosion studies, these HEAs have sustained immersion in unpurified bromide molten salts for 14 days at 750°C with <2% weight loss, in contrast to 70% weight loss from a 316 stainless steel reference. The simultaneous achievement of promising mechanical, optical, and thermochemical properties in this FeMnNiAlCr system opens the door to new applications of HEAs in solar energy harvesting. Partnerships with Ames Laboratory and Oak Ridge National Laboratory (ORNL) also advanced our understanding of the fundamental structure-property relationships through atomic scale material characterization and first-principles computational modeling. The key research results in this project can potentially be extended to other HEAs and their native oxides. In terms of applications, the proposed FeMnNiAlCr HEA/native oxide system could potentially exceed the mechanical and the optical performance of existing tubing and solar coating materials under EERE’s CSP program at lower cost, which also aligns well with the EPSCoR Science and Technology strategies of New Hampshire in boosting the deployment of renewable energy.

14 SOLAR ENERGY↗
DOE OSTI2023

Fluctuation cepstral scanning transmission electron microscopy of mixed-phase amorphous materials

Four-dimensional scanning transmission electron microscopy (4D-STEM) is a versatile analytical tool for characterizing materials structural properties. However, extending such analysis to disordered materials is challenging, especially in technologically important samples with mixed ordered and disordered phases. Here, in this work, we present a new 4D-STEM method, called fluctuation cepstral STEM (FC-STEM), based on the fluctuation analysis of cepstral transform of diffraction patterns. The peaks in the associated transformation relate to inter-atomic distances in a thin sample. By varying the real-space range over which fluctuations are calculated, distinct ordered and disordered phases can be mapped in a diffractive image reconstruction. We demonstrate the principles of FC-STEM by characterizing a silicon anode, harvested from a cycled lithium-ion battery. A mixture of amorphous and nanocrystalline silicon, graphitic carbon, and electrolyte by-products is identified and mapped. Comparisons with conventional electron imaging and energy-dispersive X-ray spectroscopy show that FC-STEM is highly effective for the structure determination of mixed-phase amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Irradiation Creep in Materials

A knowledge of the dimensional stability of reactor structural components, under irradiation conditions, is of major importance in the design of thermal, fast, and fusion reactors. When subjected to simultaneous mechanical loading and irradiation, structural materials exhibit a visco-plastic deformation phenomenon, referred to as irradiation creep, which can be more rapid than the deformation occurring out of irradiation. In this article, the phenomenology of this peculiar behavior is described after a short history of its discovery. Then, the theoretical mechanisms proposed in the literature during these past 60 years are presented, with a special focus on mechanisms based on stress induced preferred absorption of point defects by dislocation loops, dislocations and grain boundaries and on mechanisms based on climb-enhanced glide of dislocations. These mechanisms are discussed in the light of experimental evidences. Finally, irradiation creep in various materials, such as zirconium alloys, austenitic stainless steels, nickel-based alloys, ferritic-martensitic steels and graphite, is described.

Onimus, Fabien↗
DOE OSTI2023

Hydrogel-assisted self-healing of biomineralized living building materials

Living building materials (LBMs) are an emergent class of structural materials that leverage the biomineralization capability of microorganisms within sand-hydrogel scaffolds to produce living, load-bearing structures. Here we produced LBMs using a physically crosslinkable sand-hydrogel scaffold and two microorganisms with different biomineralization pathways - Synechococcus sp. PCC 7002 (photosynthetic) and S. pasteurii (ureolytic) - and investigated their self-healing capacity. Our results reveal that both Synechococcus sp. PCC 7002 and S. pasteurii demonstrated exceptional viability within all LBMs for more than 20 days. Damaged LBMs containing Synechococcus sp. PCC 7002 exhibited 103% and 112% of their original compressive and flexural strengths, respectively, after three days of healing at 50% relative humidity (RH) (i.e., ambient conditions). In contrast, LBMs containing S. pasteurii exhibited 71% and 66% of their original compressive and flexural strengths, respectively, after three days of healing at 50% RH. The compressive and flexural strengths of all LBMs rebounded to 93-100% after seven days of healing at 50% RH. Data substantiate that the self-healing ability of the hydrogel plays a critical role in facilitating healing of LBMs, as evidenced by the 82-118% rebounds in compressive and flexural strengths by the sand-hydrogel scaffold alone after three or seven days of healing at 50% RH. Healing was less effective at 100% RH for all LBMs investigated herein.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Turning Natural Herbaceous Fibers into Advanced Materials for Sustainability

Considering the growing concerns about natural resource depletion, energy inequality, and climate crises, biomass-derived materials—the most abundant organic matter on the planet—have received a lot of attention as a potential alternative to petroleum-based plastics. Herbaceous biomasses and extracted cellulose have recently been extensively used in the development of high-performance and multifunctional materials. Herbaceous biomass has sparked interest due to its species diversity, abundance, low cost, lightweight, and sustainability. This review discusses the structure versus property relationships of various sources of herbaceous biomasses (e.g., sugarcane, straw, and bamboo) and their extracted biomaterials, as well as the latest emerging applications from macro- and microscales to nanoscales. We report, high-strength structural materials, porous carbon materials, multichannel materials, and flexible materials are examples of these applications, which include sustainable electronics, environmentally friendly energy harvesting, smart materials, and biodegradable structural buildings.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Coupled effects of electronic and nuclear energy deposition on damage accumulation in ion-irradiated SiC

Coupling between electronic and nuclear energy dissipation in ion-irradiated, single crystal 4H-SiC has been investigated using Si, Ti, and Ni ions over a range of energies at 300 K, and irradiation damage accumulation is characterized using Rutherford backscattering spectroscopy in channeling geometry. The damage production rate from nuclear energy loss (S n ) is observed to decrease with increasing electronic energy loss (S e ) of the incident ions. A dynamic threshold (S e,th ) in electronic energy loss is determined for each ion species, which defines two regions: i) S e > S e,th , where electronic energy dissipation fully suppresses damage production due to nuclear energy loss along incident ion paths, and ii) S e < S e,th , where simultaneous damage recovery due to Se competes with damage production processes. Here, the electronic energy loss threshold (S e,th ) increases sublinearly with incident ion atomic number. Here, the assessment of S e,th and how it affects damage accumulation is important to advance the understanding of complex processes occurring under ion-solid interactions, as well as in the design of functional materials for opto-electronics and novel structural materials and devices tolerant to harsh thermal and radiation environments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Deep learning at the edge enables real-time streaming ptychographic imaging

Abstract Coherent imaging techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the construction of brighter sources and high-rate detectors, coherent imaging methods like ptychography are poised to revolutionize nanoscale materials characterization. However, these advancements are accompanied by significant increase in data and compute needs, which precludes real-time imaging, feedback and decision-making capabilities with conventional approaches. Here, we demonstrate a workflow that leverages artificial intelligence at the edge and high-performance computing to enable real-time inversion on X-ray ptychography data streamed directly from a detector at up to 2 kHz. The proposed AI-enabled workflow eliminates the oversampling constraints, allowing low-dose imaging using orders of magnitude less data than required by traditional methods.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synthesis Methods for Nanoparticle Morphology Control in Energy Applications

Lightweight nano-composite materials, nano-coatings, nanocatalysts, nano-structured materials have demonstrated an ability to reduce emissions and maximize clean energy production. Nanoparticles play an important role in engineering and decarbonization for energy applications, and a wide range of nanoparticle synthesis methods have been developed to include those that enable control over particle morphology. The ability to control nanoparticle morphology allows the tailoring and improvement of material properties that will accelerate efforts towards lowering carbon emissions by developing advanced catalysts for carbon sequestration and will enhance energy efficient processes and technologies. Synthesis methods aimed towards shape control of nanoparticles have demonstrated an ability to form spheres, rods, flower-like shapes, cubes, plates, shells, and chiral geometries. Processing methods used to form these morphologies include microwave assisted synthesis, solvothermal, hydrothermal, and a wide range of capping agents. A discussion of a few of these methods is given along with results and applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-throughput design of high-performance lightweight high-entropy alloys

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Smart material based multilayered microbeam structures for spatial self-deployment and reconfiguration: A residual stress approach

Alleviation of the potentially damaging effects induced by residual stresses was comprehensively investigated in previous research. Here, this paper, however, presents a spatially self-deployable and reconfigurable multilayered microbeam which takes advantage of residual stresses and shape memory effects. Reconfigurable mechanism of a typical four-layered microbeam composed of Pt\Ni 50 Ti 50 \Ni 50 Ti 50 \Pt is introduced, followed by analytical modeling of the maximum distance of the self-deployed gap as functions of variable structural and material parameters, including compressive residual stress in Pt layers and tensile residual stress in Ni 50 Ti 50 layers. Analytical solutions given by the static model agree well with the results obtained via finite element models (FEMs). Fabrication, characterization, and in-situ experiments were carried out to validate the feasibility of deployment of the as-released four-layered microbeam. The maximum distance of the gap was measured to be 41.39 μm at 20 °C, which could be increased to 51.73 μm thanks to controllable reconfiguration driven by shape memory effects. Theoretical analysis of such self-deployment and reconfiguration suggested a tensile residual stress increase by 52 MPa in Ni 50 Ti 50 layers. The multilayered microbeam structure with capabilities of self-deployment and reconfiguration offers great potential for various emerging applications, such as micro robotics, medical drug delivery devices, and intelligent chip scale spacecraft.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Develop a Fast Analysis Solver for Welding Sequence Optimization

During the shipbuilding manufacturing process, materials are exposed to significant stresses, as induced both thermally and mechanically, that alter the intended design and significantly affect the production schedule, labor hours (fitting, welding, rework, etc.), and material structural performance. The type and magnitude of deformation of a given structure depends on many factors such as the material, thickness and quality of components, the process heat input, preheat and inter-pass temperatures, type and size of welds, welding sequence and direction, location, sequence, and degree of fixturing. Numerical simulations using finite element analysis (FEA) have long been used to analyze welding-induced structural distortion. For large assemblies, transient thermal elastic-plastic analysis (TEPA) can take days or weeks to run, and optimization of welding sequence is not feasible. Simplified analysis methods were developed to reduce computational time. However, it is challenging to use these techniques to fully optimize welding sequencing because of their applied simplifications in modeling weld details. A fast analysis solver that could be used by the shipbuilding industry is being developed for optimizing welding sequences by taking full advantage of modern GPU-based HPC hardware and incorporating patented acceleration schemes. The accelerated processing factors are up to 2200 times greater for large, multi-pass welded structures.

Yang, Yu-Ping↗
DOE OSTI2025

High Radiation Resistance in the Binary W‐Ta System Through Small V Additions: A New Paradigm for Nuclear Fusion Materials

Abstract Refractory High‐Entropy Alloys (RHEAs) are promising candidates for structural materials in nuclear fusion reactors, where W‐based alloys are currently leading. Fusion materials must withstand extreme conditions, including i) severe radiation damage from energetic neutrons, ii) embrittlement due to H and He ion implantation, and iii) exposure to high temperatures and thermal gradients. Recent RHEAs, such as WTaCrV and WTaCrVHf, have shown superior radiation tolerance and microstructural stability compared to pure W, but their multi‐element compositions complicate bulk fabrication and limit practical use. In this study, it is demonstrated that reducing alloying elements in RHEAs is feasible without compromising radiation tolerance. Herein, two Highly Concentrated Refractory Alloys (HCRAs) − W 53 Ta 44 V 3 and W 53 Ta 42 V 5 (at.%) − were synthesized and investigated. We found that small V additions significantly influence the radiation response of the binary W–Ta system. Experimental results, supported by ab‐initio Monte Carlo simulations and machine‐learning‐driven molecular dynamics, reveal that minor variations in V content enhance Ta–V chemical short‐range order (CSRO), improving radiation resistance in the W 53 Ta 42 V 5 HCRA. By focusing on reducing chemical complexity and the number of alloying elements, the conventional high‐entropy alloy paradigm is challenged, suggesting a new approach to designing simplified multi‐component alloys with refractory properties for thermonuclear fusion applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Machine Learning Thermodynamics And Kinetics of Defects For Accelerated Materials Discovery

Atomistic defects play a pivotal role in functional and structural materials’ performance across a myriad of technology applications. Quantitative prediction of the thermodynamics and kinetics of defect formation and migration, respectively, typically requires accurate but expensive first-principles approaches, such as density functional theory (DFT). Their computational expense limits the throughput needed to perform high-throughput materials discovery/screening exercises or to perform materials modeling tasks relying on extensive sampling techniques. Therefore, in this Sandia National Laboratories Laboratory Directed Research and Development (LDRD) project (Project #229366), we developed a variety of machine learning techniques, trained on density functional theory calculations, to accelerate the discovery and modeling of materials in which vacancy and interstitial defects primarily dictate material performance. These include applications such as metal oxides for water-splitting or mixed ionic-electronic conduction, metal hydrides for hydrogen storage, and transition metal dichalcogenides for electronics, and the approaches developed herein can further be applied to many other domains that similarly depend on materials’ thermodynamic and kinetic defect properties for their desired functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Epitaxial Metal Electrodeposition Controlled by Graphene Layer Thickness

Control over material structure and morphology during electrodeposition is necessary for material synthesis and energy applications. One approach to guide crystallite formation is to take advantage of epitaxy on a current collector to facilitate crystallographic control. Single-layer graphene on metal foils can promote “remote epitaxy” during Cu and Zn electrodeposition, resulting in growth of metal that is crystallographically aligned to the substrate beneath graphene. However, the substrate–graphene–deposit interactions that allow for epitaxial electrodeposition are not well understood. Here, we investigate how different graphene layer thicknesses (monolayer, bilayer, trilayer, and graphite) influence the electrodeposition of Zn and Cu. Scanning transmission electron microscopy and electron backscatter diffraction are leveraged to understand metal morphology and structure, demonstrating that remote epitaxy occurs on mono- and bilayer graphene but not trilayer or thicker. Density functional theory (DFT) simulations reveal the spatial electronic interactions through thin graphene that promote remote epitaxy. This work advances our understanding of electrochemical remote epitaxy and provides strategies for improving control over electrodeposition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗