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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Characterization and response of three TNT equivalent materials in subsurface explosions

Energetic compositions utilized for inducing seismic responses are often referred to in terms of their TNT equivalent, a metric which is often misused because observations of interest are not often understood with respect to explosive characteristics. Here, in this investigation, we characterize three energetic compositions used to elicit seismic responses in a highly instrumented testbed to further our understanding of subsurface TNT equivalence. Three different energetic sources are prepared and studied for their fidelity to thermochemically predicted detonation behavior. We present effects of subsurface detonation on subsurface rock and seismic emission as a function of energetic source material within the testbed. Field experiments were conducted using a single thermochemical yield of 5 kg using diverse sources consisting of nitromethane, ammonal, and PBXN‐5 (an HMX based plastic bonded explosive) mixtures at the Energetic Materials Research and Testing Center in Socorro, New Mexico. Relative performance of energy density‐related detonation parameters, such as detonation velocity and pressure, affect the observed response in the subsurface. Most notable, equal thermochemical yields described in terms of TNT equivalence do not correlate to equal thermochemical effects in the subsurface.

Blue Canyon Dome↗
DOE OSTI2023

Developing a Roadmap for Bio-Derivable and Recyclable Composites: Re-Design and Scale-Up Considerations

Composites, often in the form of fiber reinforced plastics, are used in multiple facets of modern life from snowboards to vehicles, to wind turbines and beyond. Despite their prolific, and often renewable energy related uses, they are currently subject to a linear material economy from emission intensive precursors; thus, there is an opportunity to re-design these materials to be both bio-derivable and recyclable. In the present work, we provide a roadmap of what application considerations must be considered for vacuum assisted resin transfer molding (VARTM) processes for large composites materials at scale (e.g. infusible viscosities, moderate cure times, proper fiber adhesion, low cost, and maximum peak exotherm) when implementing bio-derivable and recyclable materials. We also provide illustrative concepts utilizing polyester covalently adaptable networks, from epoxy-anhydride chemistry, to achieve these goals. We further provide considerations when developing recycling process (e.g. maintenance of fiber sizing and orientation) and demonstrate these practices using low temperature methanolysis. Accompanying technoeconomic and life cycle analysis further illustrate the decarbonization benefits to bio-derivable and recyclable thermosets while informing future research and recycling processes. Finally, we provide a brief introduction to synergistic work within our team exploring how to further decarbonize the manufacturing of these materials.

BIOMASS FUELS,ENERGY CONSERVATION, CONSUMPTION, AN↗
DOE OSTI2025

In-Silico Design of Next Generation Cellulose-Derived Packaging Materials (CRADA Final Report)

Developing sustainable solutions for single-use packaging is an important objective to combat the environmental crisis of plastics pollution. Most embodiments of cellulose-based packaging materials, including CellophaneTM, are completely biodegradable in both terrestrial and marine environments. However, petroleum-derived alternatives offer some performance advantages for metrics such as moisture barriers and mechanical properties. This project leverages molecular dynamics simulation to investigate how molecular modifications to cellulose-based polymer assemblies impact their material properties. An important performance criterion for the modified materials was to retain biodegradability; thus, modifications by naturally occurring, biodegradable additives were the focus of this study. Specifically, we developed models with xylan and lignin of varying monomeric compositions into the cellulose matrix. The mechanical properties were investigated by performing stress-strain simulations, and the water barrier and hydrophobicity were investigated by simulating the water contact angle. Our findings indicate that the incorporation of xylan into the cellulose matrix tends to increase the mechanical properties with an optimal loading of ~27 wt%. We also predict that orienting the nanoscale directionality of the xylan chains such that they are perpendicular to the cellulose fibrils will dramatically increase mechanical strength. In contrast, the incorporation of lignin tends to weaken the composite at all loadings investigated. Simulations of water contact angle predicted that coating polymers on the surface of the cellulose assembly creates a more hydrophobic surface than incorporating them throughout the matrix. Of the coatings investigated, lignin resulted in the most hydrophobic surface, followed by pectin and keratin, which both imparted modest increases in hydrophobicity. Future experimental work done by Futamura will focus on designing material prototypes to capitalize on the predictions of performance enhancement obtained from molecular modeling. While substantial progress was made by the simulations performed in this project, there still exists a vast parameter space that we were unable to investigate, including branching, functional group decoration, and degree of polymerization of polymer additives. However, the methods developed in this initial investigation will facilitate more rapid evaluation of the impact of molecular characteristics on the performance of biopolymer composite materials and thereby accelerate future materials discovery efforts in this area.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Element differentiation with a Hartmann- based X-ray phase imaging system

Significant efforts are currently ongoing in X-ray imaging to provide multimodal imaging systems, targeting better sensitivity and specificity for both biomedical or non-destructive testing applications. Knowing the elemental composition of specific structures, such as breast microcalcifications in mammography, would help to differentiate malign and benign tumours. Standard X-ray Phase Contrast Imaging techniques provide only qualitative information on elements with similar absorption properties. However, their chemical composition can be determined from the measurement of the phase as it is directly related to the optical index of elemental materials. We will show new experimental results obtained with an X-ray phase imaging system based on a Hartmann mask. Early data treatment succeeded in retrieving both the real and imaginary parts of the refractive index. The system demonstrates the capability to discriminate materials based on elemental composition.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine learning approaches for intentional materials engineering

In this article, the development of nanoporous metals and metallic composites through dealloying processes presents significant opportunities in materials engineering. However, designing multicomponent precursor alloys and establishing corresponding processing methods that yield predictable compositions and nanostructures remain a complex challenge. This article explores how machine learning (ML)-augmented computational and experimental methodologies can tackle these challenges by predicting precursor alloy compositions, final nanoporous structures, and mechanical properties, while integrating ML-enabled autonomous experimentation for material design and quantification. We highlight recent advancements in applying ML to nanostructured materials design via dealloying and discuss how techniques from other nanomaterial designs can be adapted for improved control over morphological and compositional outcomes in nanoporous and nanocomposite materials. Furthermore, we explore the role of ML in autonomous synchrotron x-ray experimentation, enabling real-time feedback between modeling and experimental setups. ML-driven approaches to microstructure characterization and mechanical property prediction are also examined, with a focus on modeling and advanced imaging techniques such as three-dimensional nanotomography. Finally, this article outlines future directions for ML-enhanced materials science, emphasizing the exploration of high-dimensional parameter spaces and the incorporation of materials kinetics into processing and property evaluation, ultimately advancing the design of nanoporous structures and materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Using phase boundary mapping to resolve discrepancies in the Mg 2 Si–Mg 2 Sn miscibility gap

Mg 2 Si–Mg 2 Sn compositions within the Mg–Si–Sn materials system have potential as inexpensive, efficient thermoelectrics. These compositions lie specifically along the pseudobinary line with compositions of Mg 2 Si 1-x Sn x . The alloying and possible nanostructuring within the miscibility gap could further increase the thermoelectric figure of merit (zT) for these materials. However, the solubility limits of the miscibility gap differ greatly in the literature. Such a discrepancy could be a result of differing Mg-compositions due to excess magnesium added during sample annealing. To define these limits better and explain the change in proposed solubility limits based on magnesium content, the three-phase regions on either side of the pseudobinary phase region are phase boundary mapped and defect energy calculations are performed. This study presents a new understanding of the Mg–Si–Sn ternary phase diagram around the pseudobinary phase region. The solubility limits on either side of the pseudobinary should be essentially identical between the Mg-rich and Mg-poor three-phase regions unless the system temperature is brought above about 565 °C, at which eutectic liquid Mg 0.9 Sn 0.1 forms. This creates a second Mg-rich three-phase region which intersects the pseudobinary with a lower Sn solubility. Thus, samples prepared along the pseudobinary line are not well-defined thermodynamically when excess magnesium is added. Excess Mg can push the system into a new three phase region with Mg 2 Si 1-x Sn x composition different from that of the true miscibility gap. This understanding presents new guidelines for evaluating the miscibility gap and assists strategies for microstructure engineering and thermoelectric material processing.

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

Cathode Upcycling for Direct Recycling of Lithium‐Ion Batteries Using a Precipitation Approach

With the increased production of electric vehicles to reduce carbon emissions, the lithium-ion battery market to supply those vehicles has grown dramatically. To enhance battery sustainability and circularity, direct recycling methods aim to recover intact cathode materials. However, end-of-life cathode materials are typically 15–20 years old and often have lower energy density compared to current cathode materials. To address this challenge, a rapid precipitation process is developed to boost energy density by converting low Ni-compositions, LiNi 0.33 Co 0.33 Mn 0.33 O 2 (NMC111), into higher Ni-compositions (NMC622). This process forms a Ni-rich coating on cathode particles that diffuses into the core upon high-temperature relithiation, increasing compositional homogeneity. The upcycling process leverages existing infrastructure, offering low capital cost and minimal additional chemical input. Through ex situ tomographic transmission X-ray microscopy (TXM), 3D Ni:Co elemental mixing is quantified, confirming that elemental content evens at the secondary particle level with a mean NMC622 composition upon relithiation. However, elemental gradients remain in the single crystalline primary particles. Ex situ high-resolution and in situ wide-angle X-ray diffraction reveals concurrent structural changes during the relithiation process. These findings provide key insights into the structural and chemical mechanisms of elemental diffusion to obtain further improvements of increased capacity and retention through compositional conversion of cathode materials.

Cathode Upcycling↗
DOE OSTI2020

A step forward from high-entropy ceramics to compositionally complex ceramics: a new perspective

High-entropy ceramics (HECs) have quickly gained attention since 2015. To date, nearly all work has focused on five-component, equimolar compositions. This perspective article briefly reviews different families of HECs and selected properties. Following a couple of our most recent studies, we propose a step forward to expand HECs to compositionally-complex ceramics (CCCs) to include medium-entropy and/or non-equimolar compositions. Here, using defective fluorite and ordered pyrochlore oxides as two primary examples, we further consider the complexities of aliovalent cations and anion vacancies as well as ordered structures with two cation sublattices. Better thermally-insulating yet stiff CCCs have been found in non-equimolar compositions with optimal amounts of oxygen vacancies and in ordered pyrochlores with large size disorder; it is demonstrated that medium-entropy ceramics (MECs) can prevail over their high-entropy counterparts. The diversifying classes of CCCs provide even more possibilities than HECs to tailor the composition, defects, disorder/order, and consequently various properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electrode Mesoscale as a Collection of Particles: Coupled Electrochemical and Mechanical Analysis of NMC Cathodes

Battery electrodes are composed of polydisperse particles and a porous, composite binder domain. These materials are arranged into a complex mesostructure whose morphology impacts both electrochemical performance and mechanical response. We present image-based, particle-resolved, mesoscale finite element model simulations of coupled electrochemical-mechanical performance on a representative NMC electrode domain. Beyond predicting macroscale quantities such as half-cell voltage and evolving electrical conductivity, studying behaviors on a per-particle and per-surface basis enables performance and material design insights previously unachievable. Voltage losses are primarily attributable to a complex interplay between interfacial charge transfer kinetics, lithium diffusion, and, locally, electrical conductivity. Mesoscale heterogeneities arise from particle polydispersity and lead to material underutilization at high current densities. Particle-particle contacts, however, reduce heterogeneities by enabling lithium diffusion between connected particle groups. While the porous composite binder domain (CBD) may have slower ionic transport and less available area for electrochemical reactions, its high electrical conductivity makes it the preferred reaction site late in electrode discharge. Mesoscale results are favorably compared to both experimental data and macrohomogeneous models. This work enables improvements in materials design by providing a tool for optimization of particle sizes, CBD morphology, and manufacturing conditions.

42 ENGINEERING↗
DOE OSTI2024

Mixed Enthalpy–Entropy Descriptor for the Rational Design of Synthesizable High-Entropy Materials Over Vast Chemical Spaces

The practically unlimited high-dimensional composition space of high-entropy materials (HEMs) has emerged as an exciting platform for functional material design and discovery. However, the identification of stable and synthesizable HEMs and robust design rules remains a daunting challenge. Here, we propose a mixed enthalpy–entropy descriptor (MEED) that enables highly efficient, robust, high-throughput prediction of synthesizable HEMs across vast chemical spaces from first-principles. The MEED is based on two parameters: the relative formation enthalpy with respect to the most stable competing compound and the spread of the point-defect formation energy spectrum. The former measures the relative synthesizability of an HEM to its most stable competing phase, going beyond the conventional thermodynamic understanding. Further, the latter gauges the relative entropy forming ability of an HEM, entailing no sampling over numerous alloy configurations. By applying the MEED to two structurally distinct representative material systems (i.e., 3D rocksalt carbides and 2D layered sulfides), we not only successfully identify all experimentally reported HEMs within these systems but also reveal a cutoff criterion for assessing their relative synthesizability within each system. By the MEED, tens of new high-entropy carbides and 2D high-entropy sulfides are also predicted, which have the potential for a wide variety of applications such as coating in aerospace devices, energy conversion and storage, and flexible electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Hybrid Ceramic-CMC Vane with EBC for Future Coal Derived Syngas Fired 65% Efficient Turbine Combined Cycle

The efficiency of both simple cycle and combined cycle power generation systems scale with the peak temperature at which the gas exits the combustor to drive the turbine. In conventional systems, a substantial fraction of the total turbine core flow exiting the compressor is diverted downstream to cool metallic turbine hardware rather than power the turbine, much of which is used to cool the first-stage turbine vane. The use of coal derived syngas fuels provides an additional challenge to the lifetime of materials utilized in the turbine, as particulate byproducts created in the coal gasification process melt in the combustion gas, and can subsequently deposit and interact with the turbine hardware. The development of durable hot-section materials capable of operating at temperature well above that of single crystal superalloy airfoil/zirconia based thermal barrier coatings is critical to realizing 65% efficient coal derived syngas fired gas turbine based power systems. To enable higher turbine inlet temperatures while lowering cooling air requirements, United Technologies Research Center (UTRC), the central R&D laboratory supporting UT Pratt & Whitney, led the conceptual design of a new type of ceramic composite turbine hot section materials system. The design focused on a novel hybrid monolithic ceramic-fiber reinforced ceramic matrix composite (CMC) first stage turbine vane having an environmental barrier coating. By utilizing ceramic construction in the turbine hot-section, the core flow normally used to cool metallic components will be substantially reduced, increasing efficiency and reducing emissions. To provide the framework for future demonstration testing, UTRC partnered with University of North Dakota Energy and Environmental Research Center (UNDEERC) to provide a conceptual design for a gasified coal fed high-pressure turbine combustor system designed to mimic the conditions expected in a future 65% fuel to busbar efficient syngas fueled gas turbine based combined cycle. The UNDEERC and UTRC collaborated on characterizing dusts from coal gasifier filtration systems.

10 SYNTHETIC FUELS↗
DOE OSTI2024

Machine Learning for Additive Manufacturing of Functionally Graded Materials

Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-by-layer from 3D modeling data. Among AM applications, the fabrication of Functionally Graded Materials (FGMs) has significant importance due to the potential to enhance component performance across several industries. FGMs are manufactured with a gradient composition transition between dissimilar materials, enabling the design of new materials with location-dependent mechanical and physical properties. This study presents a comprehensive review of published literature pertaining to the implementation of Machine Learning (ML) techniques in AM, with an emphasis on ML-based methods for optimizing FGMs fabrication processes. Through an extensive survey of the literature, this review article explores the role of ML in addressing the inherent challenges in FGMs fabrication and encompasses parameter optimization, defect detection, and real-time monitoring. The article also provides a discussion of future research directions and challenges in employing ML-based methods in the AM fabrication of FGMs.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Nanocomposite additives based on graphene sheets and silica nanofibers

A method for producing a composite polymeric article, an additive for a polymeric article, and a composite polymeric article are provided. The method generally includes providing a plurality of graphene nanoplatelets, providing a plurality of silica nanofibers, providing a polymeric material, and distributing the plurality of silica nanofibers and the plurality of graphene nanoplatelets within the polymeric material to achieve a composite article. The additive for a polymeric article includes a plurality of graphene nanoplatelets and a plurality of silica nanofibers. The composite polymeric article includes a plurality of graphene nanoplatelets, a plurality of silica nanofibers, and a polymeric matrix. The plurality of graphene nanoplatelets and the plurality of silica nanofibers are distributed within the polymeric matrix. The silica nanofibers have a mean cross sectional diameter of not more than 100 nm.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Autonomous Polycrystalline Material Decomposition For Hyperspectral Neutron Tomography

Hyperspectral neutron tomography is an effective method for analyzing crystalline material samples with complex compositions in a non-destructive manner. Since the counts in the hyperspectral neutron radiographs directly depend on the neutron cross-sections, materials may exhibit contrasting neutron responses across wavelengths. Therefore, it is possible to extract the unique signatures associated with each material and use them to separate the crystalline phases simultaneously.We introduce an autonomous material decomposition (AMD) algorithm to automatically characterize and localize polycrystalline structures using Bragg edges with contrasting neutron responses from hyperspectral data. The algorithm estimates the linear attenuation coefficient spectra from the measured radiographs and then uses these spectra to perform polycrystalline material decomposition and reconstructs 3D material volumes to localize materials in the spatial domain. Our results demonstrate that the method can accurately estimate both the linear attenuation coefficient spectra and associated reconstructions on both simulated and experimental neutron data.

Samin nur chowdhury, Mohammad↗
DOE OSTI2022

Compression Analysis of Materials via in situ X-ray Computed Tomography

X-ray computed tomography (X-ray CT) is an analytical technique used in materials science to non– destructively characterize features in a variety of materials like polymers, metals, composites, and explosives. The non-destructive imaging allows for the analysis of features (voids and cracks), which give a fundamental understanding of material characteristics.This is more effective when combinedwith a load cell to expose the material to realworld stimuli to understand material characteristics and morphological behavior in situ. This study focused on using in situ X-ray CT to understand the material characteristics and morphological changes of sugar prills and a lattice under a compressive load. Sugar prills are used as a surrogate to analyze explosives in a safer and less expensiveway. The sugar prills were found to be brittle and shattered when compressed via the CT renderings and the stress/strain information. The lattices are used as both the basis and ground truth comparison for the development of models to predict the morphological and material characteristic changes that occur as a result of loading. The lattice was found to have weak regions due to low polymer interlayer fusion in these regions during the printing process. It was also found that under the initial compression the lattice demonstrated elastic behavior as its cellular structure was intact until the cellular structure started to collapse causing yielding in the lattice. Additionally, the analysis of the sugar prills and lattice demonstrate the information that can be gleaned from in situ X-ray CT experiments that would be lost in traditional pre- and post-mortem X-rayCT analysis.

36 MATERIALS SCIENCE↗