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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Understanding and Tailoring Diffusion and Co-Adsorption Inside the Confined Pores of Metal-Organic Frameworks (Final Scientific/Technical Report for Award DE-SC0019902)

The aim of this program was to gain a fundamental understanding of the behavior of various guest molecules in nano-confined environments, such as metal organic frameworks (MOFs), using a combination of novel synthesis, ab initio modeling, and in situ characterization. Through this project, we developed a concise understanding of the mechanisms that control adsorption/desorption of gaseous molecules and their mixtures, leading to design/synthesis guidelines for MOFs with desired functionality. We further developed methods to disentangle kinetic from thermodynamic effects during adsorption, as well as to characterize the interactions at play. In the first funding cycle, the focus was on the unambiguously characterization of co-adsorption and diffusion of gasses/vapors and their mixtures. In the second funding cycle, the focus was on characterizing the effects of the nano-confinement on the kinetics and thermodynamics of adsorption processes inside MOFs, again with an emphasis on mixtures of gasses and vapors. The nano-confinement can tip the thermodynamic vs. kinetic balance, and current understanding and theory based on single-component analysis can lead to incorrect predictions for mixtures. This is of particular interest in real-world applications, where gasses/vapors are typically mixed, contain impurities, or are often exposed to humid conditions. Our main findings were: (i) within confined environments the adsorption behavior of mixed gasses/vapors can be drastically different from the “sum” of the corresponding single phases; (ii) co-adsorption is often competitive and detrimental to performance, but it can also be cooperative and beneficial; (iii) in some co-adsorbed gasses/vapors, molecules that are strongly bound in the single-component phase can be replaced by molecules that are nominally weaker bound (molecular exchange) due to guest-guest interactions that lower the kinetic barriers and favor the final adsorption state; (iv) kinetic and thermodynamic effects can be precisely controlled through pore-size engineering and synthesis; and, (v) kinetic effects can be identified and disentangled from thermodynamic effects during adsorption through a series of sequential and simultaneous gas loading measurements. The short-term goal of this program was the controlling and understanding of common MOF systems in real-world situations where gasses/vapors are mixed, which will have an important impact on industrial processes and applications from gas storage and sequestration to catalysis and sensors. The long-term goals include the development of theoretical and experimental methods for gaining a fundamental understanding of adsorption/reaction processes within MOFs, as well as new guidelines for synthesizing MOFs with tailored physical and chemical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Carbon Nanotube Formation on Cr-Doped Ferrite Catalyst during Water Gas Shift Membrane Reaction: Mechanistic Implications and Extended Studies on Dry Gas Conversions

A nanocrystalline chromium-doped ferrite (FeCr) catalyst was shown to coproduce H2 and multiwalled carbon nanotubes (MWCNTs) during water gas shift (WGS) reaction in a H2-permselective zeolite membrane reactor (MR) at reaction pressures of ~20 bar. The FeCr catalyst was further demonstrated in the synthesis of highly crystalline and dimensionally uniform MWCNTs from a dry gas mixture of CO and CH4, which were the apparent sources for MWCNT growth in the WGS MR. In both the WGS MR and dry gas reactions, the operating temperature was 500 °C, which is significantly lower than those commonly used in MWCNT production by chemical vapor deposition (CVD) method from CO, CH4, or any other precursor gases. Extensive ex situ characterizations of the reaction products revealed that the FeCr catalyst remained in partially reduced states of Fe3+/Fe2+ and Cr6+/Cr3+ in WGS membrane reaction while further reduction of Fe2+ to Fe0 occurred in the CO/CH4 dry gas environments. The formation of the metallic Fe nanoparticles or catalyst surface dramatically improved the crystallinity and dimensional uniformity of the MWCNTs from dry gas reaction as compared to that from WGS reaction in the MR. Reaction of the CO/CH4 mixture containing 500 ppmv H2S also resulted in high-quality MWCNTs similar to those from the H2S-free feed gas, demonstrating excellent sulfur tolerance of the FeCr catalyst that is practically meaningful for utilization of biogas and cheap coal-derived syngas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Anomalous Behavior in the Atomic Structure of Nb$^{3}$Sn under High Pressure

In the present study, the local atomic structure of a Nb3Sn superconductor sample has been probed by X-ray absorption fine structure (XAFS) as a function of hydrostatic pressure (from ambient up to 26 GPa) using a diamond anvil cell set-up. The analysis of the Nb-K edge extended X-ray absorption fine structure (EXAFS) data was carried out combining standard multi shell structural refinement and reverse Monte Carlo method to provide detailed in situ characterization of the pressure-induced evolution of the Nb local structure in Nb3Sn. The results highlight a complex evolution of Nb chains at the local atomic scale, with a peculiar correlated displacement of Nb–Nb and Nb–Nb–Nb configurations. Such a local effect appears related to anomalies evidenced by X-ray diffraction in other superconductors belonging to the same A15 crystallographic structure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Uncertainties Induced by Processing Parameter Variation in Selective Laser Melting of Ti6Al4V Revealed by In-Situ X-ray Imaging

Selective laser melting (SLM) additive manufacturing (AM) exhibits uncertainties, where variations in build quality are present despite utilizing the same optimized processing parameters. In this work, we identify the sources of uncertainty in SLM process by in-situ characterization of SLM dynamics induced by small variations in processing parameters. We show that variations in the laser beam size, laser power, laser scan speed, and powder layer thickness result in significant variations in the depression zone, melt pool, and spatter behavior. On average, a small deviation of only ~5% from the optimized/reference laser processing parameter resulted in a ~10% or greater change in the depression zone and melt pool geometries. For spatter dynamics, small variation (10 μm, 11%) of the laser beam size could lead to over 40% change in the overall volume of the spatter generated. The responses of the SLM dynamics to small variations of processing parameters revealed in this work are useful for understanding the process uncertainties in the SLM process.

36 MATERIALS SCIENCE↗
DOE OSTI2020

In Situ Study of the Impact of Aberration-Corrected Electron-Beam Lithography on the Electronic Transport of Suspended Graphene Devices

The implementation of aberration-corrected electron beam lithography (AC-EBL) in a 200 keV scanning transmission electron microscope (STEM) is a novel technique that could be used for the fabrication of quantum devices based on 2D atomic crystals with single nanometer critical dimensions, allowing to observe more robust quantum effects. In this work we study electron beam sculpturing of nanostructures on suspended graphene field effect transistors using AC-EBL, focusing on the in situ characterization of the impact of electron beam exposure on device electronic transport quality. When AC-EBL is performed on a graphene channel (local exposure) or on the outside vicinity of a graphene channel (non-local exposure), the charge transport characteristics of graphene can be significantly affected due to charge doping and scattering. While the detrimental effect of non-local exposure can be largely removed by vigorous annealing, local-exposure induced damage is irreversible and cannot be fixed by annealing. We discuss the possible causes of the observed exposure effects. Our results provide guidance to the future development of high-energy electron beam lithography for nanomaterial device fabrication.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Preface

Crystallization via nonclassical pathways is important during the formation of minerals in nature and has become a popular method to synthesize advanced materials on both laboratory and industrial scales. Unlike classical crystal growth pathways via monomer-by-monomer addition, crystallization via nonclassical pathways such as particle-by-particle attachment can form bigger crystals more quickly. Many materials prepared via non-classical crystallization have been applied in various fields such as energy, catalysis, environment, biomedicine, optics, electrics, and magnetics. Understanding nonclassical crystallization pathways could provide new insights on design and synthesize novel materials. This ACS Book series aims to provide updated information on fundamental nonclassical crystallization research, including theory and experiments. It’s also designed for experienced researchers to reinforce their knowledge on the scopes of development of new techniques, especially state-of-the-art in situ characterization tools, to understand mechanisms of crystallization via nonclassical pathways. Topics that would be covered in this book series include: (1) nonclassical nucleation; (2) cluster assembly; (3) particlebased crystallization; (4) crystal formation from amorphous intermedium phases; (5) biomineralization via nonclassical pathways; (6) theoretical developments to simulate nonclassical crystallization; (7) observation of the nonclassical crystallization pathways via various characterization techniques; and (8) the application of nonclassical crystallization. Volume I of the Nonclassical Crystallization Book Series will cover a broad range of topics about nucleation, assembly, observation, and applications of nonclassical crystallization.

Zhang, Xin↗
DOE OSTI2021

Preface

Crystallization via nonclassical pathways is important during the formation of minerals in nature and has become a popular method to synthesize advanced materials on both laboratory and industrial scales. Unlike classical crystal growth pathways via monomer-by-monomer addition, crystallization via nonclassical pathways, such as particle-by-particle attachment, can form larger crystals more quickly. Materials prepared via nonclassical crystallization have been applied in various fields such as energy, catalysis, environment, biomedicine, optics, electrics, and magnetics. Understanding nonclassical crystallization pathways could provide new insights into synthesizing novel materials. This ACS Book series aims to provide updated information on fundamental nonclassical crystallization research, including theory and experiments. It is also intended for experienced researchers, to reinforce their knowledge of the developmental scope of new techniques–especially state-of-the-art in situ characterization tools–to understand mechanisms of crystallization via nonclassical pathways. Topics covered in this book series include: (1) nonclassical nucleation; (2) cluster assembly; (3) particle-based crystallization; (4) crystal formation from amorphous intermedium phases; (5) biomineralization via nonclassical pathways; (6) theoretical developments to simulate nonclassical crystallization; (7) observation of the nonclassical crystallization pathways via various characterization techniques; and (8) the application of nonclassical crystallization. Volume II of the Nonclassical Crystallization Book Series will cover a broad range of topics including particle-based crystallization, biomolecular self-assembly, biomineralization, nanoscale imaging, and applications of nonclassical crystallization.

Zhang, Xin↗
DOE OSTI2021

Integrated transmission electron microscope

An integrated transmission electron microscope comprising multiple electron sources for tuned beams of ultrafast, scanning probe, and parallel illumination in varied beam energies can be alternated within sub-microseconds onto a sample with dynamic ‘transient state’ processes to acquire atomic-scale structural/chemical data with site specificity. The various electron sources and condenser optics enable high-resolution imaging, high-temporal resolution imaging, and chemical imaging, using fast-switching magnets to direct the different electron beams onto a single maneuverable objective pole piece where the sample resides. Such multimodal in situ characterization tools housed in a single microscope have the potential to revolutionize materials science.

Jungjohann, Katherine L.↗
DOE OSTI2020

Development of Acoustic Backscatter for In Situ Monitoring of Nuclear Sludge Wastes During Transfer - 20117

This paper presents an overview into the use of acoustic backscatter systems (ABS) for the in situ characterization of nuclear waste sludge concentration, size and aggregation, highlighting key achievements from the University of Leeds. Previous projects funded through the Engineering and Physical Sciences Research Council (EPSRC) UK and Innovate UK are firstly reviewed and linked to current research within the new TRANSCEND consortium. Detailed are a number of developments at various stages of technology readiness level, from the use of ABS to monitor small-scale sludge settling in columns, to large-scale jet-mixing and waste transfer operations. Current work with Sellafield Ltd will see new technology and world leading analysis methods deployed to measure the consolidation of complex wastes currently undergoing containment, the first time full industrial utilization of these systems has been achieved. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Utah FORGE 2-2439v2: Characterizing In-Situ Stress with Laboratory Modelling and Field Measurements - 2024 Annual Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project by The University of Pittsburgh, presented by Andrew Bunger. The project characterizes the stress in the Utah FORGE EGS reservoir using three methods: Method 1: Demonstrate complimentary laboratory rock-core stress estimation combined with Machine Learning approach for measuring in-situ stress from field sonic log data; Method 2: Complete field based in-situ measurement (mini-frac); and Method 3: Develop a mechanics-based method for connection near wellbore stress measurements to stresses away from the well-bore. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 14, 2024.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Utah FORGE 2439: A Multi-Component Approach to Characterizing In-Situ Stress

Core-based in-situ stress estimation, Triaxial Ultrasonic Velocity (labTUV) data, and Deformation Rate Analysis (DRA) data for Utah FORGE well 16A(78)-32 using triaxial ultrasonic velocity and deformation rate analysis. Report documenting a multi-component approach to characterizing in-situ stress at the U.S. DOE FORGE EGS site: laboratory, modeling and field measurement. Core-based methods for in-situ stress estimation were applied using samples from 5 intervals within the Utah FORGE 16A(78)-32 well. At three of these locations, Triaxial Ultrasonic Velocity (labTUV) tests were performed, resulting in experimentally-determined relationships between wave velocities and stresses. Non-monotonic increase in the velocity-stress relationships are inferred provide evidence of stress history and are therefore used to estimate in-situ stress magnitudes. Additionally, Deformation Rate Analysis (DRA) tests were run on core plugs from various orientations at each of the 5 sampling locations. These, too, provide evidence of stress history based on stress-strain behavior. A novel Weight of Evidence (WoE) method was developed as a means of synthesizing in-situ stress evidence from these two types of tests. Results indicate the minimum horizontal stress gradient ranges from 0.58 psi/ft to 0.69 psi/ft, with 4 of the 5 values between 0.66 psi/ft and 0.69 psi/ft. The vertical stress gradient ranges from 1.05 psi/ft to 1.12 psi/ft, with 4 of the 5 zones given results between 1.09 psi/ft and 1.12 psi/ft. The maximum horizontal stress gradient ranges from 0.98 psi/ft to 1.34 psi/ft, with 4 of the 5 zones falling between 0.98 psi/ft and 1.24 psi/ft. The stress regime thus appears to be on the edge between normal faulting and strike-slip faulting, potentially flipping back and forth between the two regimes due to variability of rock properties, structures such as faults, and/or thermal anomalies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

In situ temperature synthesis and characterization of ferroelectric PZN-4.5PT nanoparticles’ thin films using synchrotron light source

Despite the excellent properties of Pb(Zn 1/3 Nb 2/3 )O 3 -4.5PbTiO 3 (PZN-4.5PT) single crystals, the greatest difficulty for their application on electronic devices is to make them to thin layers related to the difficulty to make them as ceramic materials. In this paper, we use the combined USAXS/SAXS/WAXS instrument at 9ID beamline at APS-ANL for in situ characterization of PZN-4.5PT inorganic perovskite nanoparticles thin films deposited on nanotextured silicon to understand the phase transitions and determine the observed microcrystals' structure. Here, the sample was annealed from ambient to 1000°C. The results revealed structure changes in the nanoparticles' thin films which could be explained by the new phase that can be assigned to the Pb 3 (PO 4 )2-based component. The peak at 31° indicates the presence of the rhombohedral phase perovskites assigned to the nanoparticles. WAXS characterization permitted to identification of many transitions during thermal annealing like dehydration or dihydroxylation of phosphorus gel -OH bonds and internal water.

36 MATERIALS SCIENCE↗