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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 4

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Continuous optical in-situ pH monitoring during early hydration of cementitious materials

A luminescent sensor technique for pH analyses has been tested in cementitious media. The optical sensors monitor in-situ pH every 5 s during early hydration reactions over a period of 100 h from initial fluid up to consolidated stage. The pH development was analysed in calcium aluminate, calcium sulfoaluminate and OPC/slag cements up to a pH level of 13.3 and directly correlated with the heat of hydration. Thus tracing the dissolution and formation processes of solid phases via pH sensor monitoring is possible. This measurement technique enables the recording of continuous and highly reproducible pH data sets from slurries, pastes, and hardening materials leading to new vistas for individual (trans)formation pathways of solids, hydration and consolidation reactions in high alkaline cementitious systems.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Development of Analytical Protocols For Organics and Isotopes Analysis on the 2009 MARS Science Laboratory.

The Mars Science Laboratory, under development for launch in 2009, is designed explore and quantitatively asses a local region on Mars as a potential habitat for present or past life. Its ambitious goals are to (1) assess the past or present biological potential of the target environment, (2) to characterize the geology and geochemistry at the MSL landing site, and (3) to investigate planetary processes that influence habitability. The planned capabilities of the rover payload will enable a comprehensive search for organic molecules, a determination of definitive mineralogy of sampled rocks and fines, chemical and isotopic analysis of both atmospheric and solid samples, and precision isotope measurements of several volatile elements. A range of contact and remote surface and subsurface survey tools will establish context for these measurements and will facilitate sample identification and selection. The Sample Analysis at Mars (SAM) suite of MSL addresses several of the mission's core measurement goals. It includes a gas chromatograph, a mass spectrometer, and a tunable laser spectrometer. These instruments will be designed to analyze either atmospheric samples or gases extracted from solid phase samples such as rocks and fines. We will describe the range of measurement protocols under development and study by the SAM engineering and science teams for use on the surface of Mars.

Mahaffy, P. R.↗
DOE OSTI2023

Modulating the Mixing Gibbs Free Energy to Enhance Solid–Liquid Phase Separation for High–Performance Organic Solar Cells

Organic solar cells (OSC) feature a hierarchical structure with the electron donor/acceptor layer sandwiched by anode and cathode, which raises the importance of controlling the molecular crystal orientation, domain size, and vertical distribution to facilitate the charge collection at electrodes. However, the similar conjugated backbone of donor/acceptor material and fast film–formation kinetics have led to spinodal–decomposition–orientated phase separation that result in the film presenting an intimately mixed morphology and random molecular orientation. To solve the issue, the mixing Gibbs free energy–triggered solid–liquid phase separation during the film formation process is enhanced by solidifying one component and solvating the other based on a liquid additive. Following the liquid evaporation process, a favorable vertical distribution is obtained. Meanwhile, the prolonged solvation process enlarges the domain size and assists the molecules to diffuse and orient properly, enabling better exciton/charge dynamics during the power conversion processes. As a result, the fabricated devices exhibit a fill factor over 80% and an efficiency of 18.72%, which is one of the top efficiencies for binary OSCs. In conclusion, insights and a methodology is provided here to manipulate the organic donor/acceptor phase separation in terms of mixing Gibbs free energy.

14 SOLAR ENERGY↗
DOE OSTI2020

Phase evolution during lithium–indium halide superionic conductor dehydration

Select rare-earth alkali halides have demonstrated high lithium ion conductivity. The conductivity appears to be related to the stability of the crystal phase, ordering of the lithium sublattice and the amount of residual H 2 O. Li 3 InCl 6 can be synthesized from concentrated aqueous solution through controlled dehydration. In this work, we track Li 3 InCl 6 dehydration using a multimodal approach that combines thermogravimetric, spectroscopic, X-ray diffraction, and neutron scattering techniques. In situ X-ray diffraction suggests a single phase transition caused by dehydration, in disagreement with spectroscopic and thermodynamic measurements. Neutron scattering, being sensitive toward the H 2 O and Li sublattices, reveals multiple phase transitions. We show that the loss of the final trace H 2 O leads to strain and grain boundary formation. Thus, controlled dehydration may be a viable strategy for high-throughput processing for roll-to-roll manufacturing of REAH solid electrolytes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Why would you put a flashlight in a dark matter detector?

Silicon photomultipliers (SiPMs) are solid-state, single-photon sensitive, pixelated sensors whose usage for scintillation detection has rapidly increased over the past decade. It is known that the avalanche process within the device, which renders a single photon detectable, can also generate secondary photons which may be detected by a separate device. This effect, known as external crosstalk, could potentially degrade the science goals of future xenon dark matter experiments. In this article, we measure the effect of external crosstalk in a dual-phase, liquid xenon time projection chamber fully instrumented with SiPMs. We then consider the implications for a future xenon dark matter experiment utilizing SiPMs and discuss possible solutions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Study of scintillation light collection, production and propagation in a 4 tonne dual-phase LArTPC

The 3×1×1 m3 demonstrator is a dual phase liquid argon time projection chamber that has recorded cosmic rays events in 2017 at CERN. The light signal in these detectors is crucial to provide precise timing capabilities. The performance of the photon detection system, composed of five PMTs, are discussed. The collected scintillation and electroluminescence light created by passing particles has been studied in various detector conditions. In particular, the scintillation light production and propagation processes have been analyzed and compared to simulations, improving the understanding of some liquid argon properties.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Abstract for CRADA between NETL and Praxair Surface Technologies, Inc. (AGMT-1288)

The National Energy Technology Laboratory (NETL) and Praxair Surface Technologies (Participant) will collaborate in the design and manufacturing of new high-performance thermal barrier coatings (TBCs) for hydrogen gas turbine applications. High-throughput first-principles density functional theory (DFT) calculations will be performed to accelerate novel TBCs discovery with expanded phase field, increased temperature and erosion capabilities, low thermal conductivity, and significant toughness imparted by ferroelastic toughening for the non-transformable tetragonal oxide phase. Down-selected materials will be manufactured using solid state powder processing techniques. Testing will include isothermal aging followed by Raman and x-ray diffraction (XRD) phase analysis, indentation fracture toughness measurements, erosion testing, and thermal conductivity measurements. The collaboration will facilitate the deployment of hydrogen gas turbine technologies that are a key to the decarburization of power generation in the United States.

08 HYDROGEN↗
DOE OSTI2022

The influence of the processing parameters on the reactive flash sintering of ZrO 2 -CeO 2

Reactive flash sintering (RFS) is a method that was recently developed to produce dense single-phase bulk ceramic parts through solid-state reactions in a single-step that only takes a few minutes. The influence of the RFS parameters on the phase purity of a simple mixed oxide, (Zr 0.8 ,Ce 0.2 )O 2 , was investigated. Parameters such as furnace temperature, furnace atmosphere, electric current density, and alternating current (AC) or direct current (DC) were examined. It was found that (Zr 0.8 ,Ce 0.2 )O 2 pellets with high densities, above 90% of its theoretical density, can be produced by RFS in a few minutes when RFS occurs under oxidizing atmospheres, AC fields with current densities of 100 mA·mm –2 , and at a furnace temperature of 1200°C. Reducing conditions such as Ar-H 2 atmosphere and DC fields, low furnace temperatures, and low current densities resulted in phase impurities and poor reactions between the ZrO 2 and the CeO 2 powders. These results show that RFS is a useful method to produce mixed oxides, but it is very sensitive to the processing parameters. This is the first time that the influence of most of the RFS processing parameters has been studied systematically. Thus, the present work aims to provide guidelines on selecting the right processing parameters when exploring RFS.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Combining synchrotron X-ray diffraction, mechanistic modeling and machine learning for in situ subsurface temperature quantification during laser melting

Laser melting, such as that encountered during additive manufacturing, produces extreme gradients of temperature in both space and time, which in turn influence microstructural development in the material. Qualification and model validation of the process itself and the resulting material necessitate the ability to characterize these temperature fields. However, well established means to directly probe the material temperature below the surface of an alloy while it is being processed are limited. To address this gap in characterization capabilities, a novel means is presented to extract subsurface temperature-distribution metrics, with uncertainty, from in situ synchrotron X-ray diffraction measurements to provide quantitative temperature evolution data during laser melting. Temperature-distribution metrics are determined using Gaussian process regression supervised machine-learning surrogate models trained with a combination of mechanistic modeling (heat transfer and fluid flow) and X-ray diffraction simulation. The trained surrogate model uncertainties are found to range from 5 to 15% depending on the metric and current temperature. The surrogate models are then applied to experimental data to extract temperature metrics from an Inconel 625 nickel superalloy wall specimen during laser melting. The maximum temperatures of the solid phase in the diffraction volume through melting and cooling are found to reach the solidus temperature as expected, with the mean and minimum temperatures found to be several hundred degrees less. The extracted temperature metrics near melting are determined to be more accurate because of the lower relative levels of mechanical elastic strains. However, uncertainties for temperature metrics during cooling are increased due to the effects of thermomechanical stress.

36 MATERIALS SCIENCE↗
DOE OSTI2022

2022 AI Testbed Expeditions Report

By exploiting the coherent properties of a light source, coherent diffraction imaging (CDI) is able to obtain the sample image at a nanoscale resolution using the measured diffraction pattern. Bragg Coherent Diffraction Imaging (BCDI) has become valuable for recovering the displacement and strain field of crystals, providing a valuable tool in material science and solid-state physics. X-ray ptychography is another emerging CDI technique that can produce a high-resolution image of the extended sample and has become popular in many research areas (e.g., materials science, biology, electronics, and optics characterization). CDI including BCDI and ptychography has become an established technique in Synchrotron Facilities including the Advanced Photon Source (APS) and will greatly benefit from the 100x coherent flux increase of the upcoming APS Upgrade (APSU). The current image formation process in CDI employs iterative phase retrieval algorithms, which is a time-consuming and computationally expensive process. Especially after APSU, the traditional iterative methods will not be able to match the experimental data acquisition speed. We employ deep learning (DL) approach to replace the iterative approaches, therefore allowing hundreds of times faster recovery of the object. We developed AutoPhaseNN, a DL-based approach which learns to solve the inverse problem without labeled data. Taking 3D BCDI as a representative technique, AutoPhaseNN has been demonstrated to be one hundred times faster than traditional iterative phase retrieval methods while providing comparable image quality. The current network is trained with 64 x 64 x 64 data size, to achieve higher resolution imaging, we will need to scale the network to input and train/infer 3D arrays of size 256 x 256 x 256 (today) and of size 2560x2560x2560 (APSU). However, the scalability of the network is restricted due to the memory-intensive training process. To perform the training for a 256 x 256 x 256 data size, the required memory exceeds the capacity of the current machine. In this project, we explore using Sambanova system to train the network for the direct data inversion for CDI.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermodynamics-guided alloy and process design for additive manufacturing

In conventional processing, metals go through multiple manufacturing steps including casting, plastic deformation, and heat treatment to achieve the desired property. In additive manufacturing (AM) the same target must be reached in one fabrication process, involving solidification and cyclic remelting. The thermodynamic and kinetic differences between the solid and liquid phases lead to constitutional undercooling, local variations in the solidification interval, and unexpected precipitation of secondary phases. These features may cause many undesired defects, one of which is the so-called hot cracking. The response of the thermodynamic and kinetic nature of these phenomena to high cooling rates provides access to the knowledge-based and tailored design of alloys for AM. Here, we illustrate such an approach by solving the hot cracking problem, using the commercially important IN738LC superalloy as a model material. The same approach could also be applied to adapt other hot-cracking susceptible alloy systems for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Coupling solidification kinetics with phase-behavior computations in hydrodynamic simulations of high-pressure, dynamic-compression processes

In this study, we report a numerical scheme to integrate models for the kinetics of solidification processes together with phase-behavior computations in the context of continuum-scale hydrodynamic simulations. The objective of the phase-behavior computations is to determine the pressure and temperature, given the following three sets of inputs: (1) an appropriate equation of state to describe our system, (2) the phase fraction(s) produced by the kinetic models, (3) and the volume and internal energy obtained by solving the conservation equations that govern the hydrodynamic behavior. The kinetics are assumed to be governed by the Kolmogorov–Johnson–Mehl–Avrami equation, and the nucleation and growth rates that enter into that equation are functions of the pressure and temperature produced by the phase-behavior computations. Our formulation allows for the fluid and solid phases to be at different temperatures (thermal nonequilibrium) and pressures (arising from surface-tension-induced Laplace contributions). The formulation is presented in a fairly general setting that is independent of any particular material, although we demonstrate it in some examples related to high-energy-density science applications where materials are rapidly compressed to pressures exceeding several gigapascals in less than a microsecond. We conclude with a critical evaluation of our approach and provide suggestions for future work to improve the predictive capabilities and generality of the models.

42 ENGINEERING↗
DOE OSTI2020

Chemical Robotics Enabled Exploration of Stability in Multicomponent Lead Halide Perovskites via Machine Learning

Metal halide perovskites have attracted immense interest as a promising material for a variety of optoelectronic and sensing applications. However, issues regarding long-term stability have emerged as the key bottleneck for commercialization. Here, we develop an automated experimental workflow based on combinatorial synthesis and rapid throughput characterization to explore long-term stability of these materials in ambient conditions. We apply it to four model perovskite systems: MA x FA y Cs 1–x–y PbBr 3 , MA x FA y Cs 1–x–y PbI 3 , Cs x FA y MA 1–x–y Pb(Br x+y I 1–x–y ) 3 , and Cs x MA y FA 1–x–y Pb(I x+y Br 1–x–y ) 3 . Non-negative matrix factorization and Gaussian process regression are used to interpolate the photoluminescent behavior of the phase diagram. This interpolative regression analysis helps to distinguish mixtures that form solid solutions from those that segregate into multiple materials, pointing out the most stable regions of the phase diagram. Here, we find stability dependence on composition to be nonuniform within the composition space, suggesting the presence of potential preferential compositional regions. This proposed workflow is universal and can be applied to other solution-processable materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Theory-guided design of duplex-phase multi-principal-element alloys

Density-functional theory (DFT) is used to identify phase-equilibria in multi-principal-element and high-entropy alloys (MPEAs/HEAs), including duplex-phase and eutectic microstructures. Here, a combination of composition-dependent formation energy and electronic-structure-based ordering parameters were used to identify a transition from FCC to BCC favoring mixtures, and these predictions experimentally validated in the Al-Co-Cr-Cu-Fe-Ni system. A sharp crossover in lattice structure and dual-phase stability as a function of composition were predicted via DFT and validated experimentally. The impact of solidification kinetics and thermodynamic stability was explored experimentally using a range of techniques, from slow (castings) to rapid (laser remelting), which showed a decoupling of phase fraction from thermal history, i.e., phase fraction was found to be solidification rate-independent, enabling tuning of a multi-modal cell and grain size ranging from nanoscale through macroscale. Strength and ductility tradeoffs for select processing parameters were investigated via uniaxial tension and small-punch testing on specimens manufactured via powder-based additive manufacturing (directed-energy deposition). This work establishes a pathway for design and optimization of next-generation multiphase superalloys via tailoring of structural and chemical ordering in concentrated solid solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Atmospheric plasma spraying to fabricate metal‐supported solid oxide fuel cells with open‐channel porous metal support

Abstract Metal‐supported solid oxide fuel cells (MS‐SOFCs) have been fabricated by applying phase‐inversion tape‐casting and atmospheric plasma spraying (APS). The effect of the binder amount of the phase‐inversion slurries on the microstructure development of the 430L stainless steel metal support was investigated. The pore structures, the viscosity of the slurry, porosity and permeability of the as‐prepared metal supports are significantly influenced by the amount of the binder. NiO–scandia‐stabilized zirconia (ScSZ) anode, ScSZ electrolyte and La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3−δ (LSCF) cathode layers were consecutively deposited on the metal support with an ideal microstructure by APS process. The effect of plasma power of the APS on the microstructure of the electrolyte and cathode was investigated. A dense electrolyte layer and a porous cathode layer were successfully obtained at 40 and 6 kW of the APS plasma power, respectively. MS‐SOFCs, with a cell configuration of 430L/Ni‐ScSZ/ScSZ/LSCF, achieved a maximum cell power density of 1079 mW cm −2 at 700°C using humidified H 2 as fuel and ambient air as oxidant. The corresponding ohmic resistance and total resistance of MS‐SOFCs was 0.14 and 0.32 Ω cm 2 , respectively. This work demonstrates the feasibility of fabricating high‐performance MS‐SOFCs with economical and scalable techniques.

36 MATERIALS SCIENCE↗
NASA NTRS2001

Software Package Completed for Alloy Design at the Atomic Level

As a result of a multidisciplinary effort involving solid-state physics, quantum mechanics, and materials and surface science, the first version of a software package dedicated to the atomistic analysis of multicomponent systems was recently completed. Based on the BFS (Bozzolo, Ferrante, and Smith) method for the calculation of alloy and surface energetics, this package includes modules devoted to the analysis of many essential features that characterize any given alloy or surface system, including (1) surface structure analysis, (2) surface segregation, (3) surface alloying, (4) bulk crystalline material properties and atomic defect structures, and (5) thermal processes that allow us to perform phase diagram calculations. All the modules of this Alloy Design Workbench 1.0 (ADW 1.0) are designed to run in PC and workstation environments, and their operation and performance are substantially linked to the needs of the user and the specific application.

Bozzolo, Guillermo H.↗
DOE OSTI2023

Using limited neural networks to assess relative mechanistic influence on shock heating in granular solids

The rapid compaction of granular media results in localized heating that can induce chemical reactions, phase transformations, and melting. However, there are numerous mechanisms in play that can be dependent on a variety of microstructural features. Machine learning techniques such as neural networks offer a ubiquitous method to develop models for physical processes. Limiting what kind of microstructural information is used as an input and assessing normalized changes in network error, the relative importance of different mechanisms can be inferred. Here we utilize binned, initial density information as network inputs to predict local shock heating in a granular high explosive trained from large-scale molecular dynamics simulations. In this study, the spatial extent of the density field used in the network is altered to assess the importance and relevant length scales of the physical mechanisms in play, where different microstructural features result in different predictive capabilities.

36 MATERIALS SCIENCE↗