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

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At least 397 records · Page 22

Designing alloys with process-mapping AI pre-trained on empirical knowledge

<span style="font-family: Calibri, sans-serif; font-size: 12pt;">Accelerated materials design should match the recent trends in the product development cycles. Materials data analytics can be used to significantly shorten development time of specialized alloys needed for next generation energy applications. However, it faces a challenge of scarce data available for training ML models. Incorporation of the domain knowledge into deep-learning graph structure via fuzzy pre-training and causal process imitation presents a viable approach to developing accurate data-driven models and reliable alloy design tools, with limited datasets. Artificial Intelligence (AI) was used in this study to incorporate such knowledge in the domain-specific computational tool, pyroMind. The tool provides not only novel design ideas but also their interpretation via physics and engineering concepts.</span>

Romanov, Vyacheslav↗

Advanced Materials & Manufacturing Technology (AMMT): Development of Additive Manufacturing Agnostic Process Parameter Procedure, 316H Stainless Steel Readiness Level Data Sets, and Machine Maintenance Plan

The University of California, Davis is involved in a project to deploy and enhance an artificial intelligence (AI) system for predicting and preventing plasma disruptions on the DIII D tokamak, under the funding from Department of Energy DE-SC0023500 (title: AI/Deep Learning FRNN Software for Prediction & Real-Time Control of DIII-D Plasma Control System (PCS)). The overarching goal is to demonstrate that real-time, AI-guided intervention can proactively modify the plasma state to avoid or mitigate disruptions—a critical challenge for the future of fusion energy.

36 MATERIALS SCIENCE↗

Recent developments on 2D magnetic materials: challenges and opportunities

The emergence of two-dimensional (2D) magnetic materials exhibiting strong magnetization at ultrathin limits above room temperature are promising for miniaturization of devices beyond Moore’s law for future energy efficient nano-electronic devices. Here, the current status, different mechanisms for the existence of magnetism, spin current injection and other magnetic properties of monolayer to few-layers of various 2D magnetic materials are reviewed. Some of the promising applications of these materials are spintronics devices such as spin valves, spin tunnel field-effect transistors, and spin filtering magnetic tunnel junctions. Due to the tunable electronic properties of these 2D materials, it's quite interesting to inject the spin current with suitable ferromagnetic contacts. For instance,black phosphorus is a layered material with a small Schottky barrier height capable of injecting spin current. This review includes many recently explored 2D magnetic materials ranging from exfoliated 2D crystals to CVD grown materials from single to several layers, demonstrating tunable layer dependent magnetic properties. We also explore some of the promising theoretical study based on 2D magnetic compounds such as 2D alkali-based chromium chalcogenides, which shows ferromagnetic as well as semiconducting behavior. The layer-dependent magnetic ordering has been observed in layered compounds like 1T-CrTe 2 , VSe 2 , CrI 3 , and Fe 3 GeTe 2 , which have great potential for the future applications in magnetic based electronic devices. Finally, we emphasize the challenges, opportunities and future directions of the 2D magnetic materials, where new discoveries might have outstanding impact in transformational scientific breakthroughs towards memory, spintronics, optoelectronics and other multifunctional device applications.

36 MATERIALS SCIENCE↗

Thermo-chemo-mechanical understanding of damage development in porous cementitious materials exposed to sodium chloride under thermal cycling

Interactions between sodium chloride (NaCl) and cementitious materials have shown to facilitate premature deteriorations of concrete in cold environments. NaCl chemically interacts with tri‑calcium aluminate (C{sub 3}A) and monosulfate (AF{sub m}) resulting in a chemical phase change during thermal cycling. The chemical phase change can create damage in porous cementitious materials. Experimental and thermodynamic modeling were conducted in this study to understand the thermo-chemo-physical interactions between NaCl and cementitious materials and identify the source of the chemical phase change. Results indicates that the destructive chemical phase change is the formation of mirabilite (Na{sub 2}SO{sub 4}.10H{sub 2}O). It was found that the phase change temperature of mirabilite is strongly influenced by the concentration of NaCl in the solution. At high concentration NaCl solutions (>10% by mass), mirabilite is formed due to the release of a small amount of sulfate ions from the concrete matrix.

36 MATERIALS SCIENCE↗

Development of metallic nuclear material purification process via simultaneous chlorination and volatilization

Here, a purification process involving simultaneous chlorination and volatilization is reported using aluminum, iron, gallium, and uranium separation from cerium metal as the demonstration system. Anhydrous Cl 2 gas was reacted with the metal after it had been converted to small particles of hydride at temperatures ranging from 523 to 973 K. Each of the impurities should form chlorides with relatively high saturated vapor pressures. The objective of the process was to volatilize these chlorides after first achieving near-complete conversion of the metals to hydride and then chlorides. Complete conversion of hydrides to chlorides could not be achieved using relatively low-grade (99.5%) Cl 2 . High decontamination factors for all of the metal impurities required near complete conversion to chloride. It was concluded that oxygen contamination of the feed gas stream likely limits the conversion to chlorides by forming oxides instead, which then limits the volatilization of contaminants. Uranium was particularly challenging to remove in experiments suspected of having high oxygen contamination in the feed gas stream. After switching to ultra-high purity (99.999%) Cl 2 , complete conversion to chlorides within the measurement error was possible for the entire temperature range studied. Decontamination factors for aluminum, iron, gallium, and uranium were found to have average values of 1.9, 9.8, 14, and 5, respectively, at 973 K. While the process was most extensively studied using a once-through gas flow, recycling unreacted Cl 2 gas succeeded at minimizing waste while still maintaining complete conversion and similar decontamination factors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of Porous Crystalline Materials for Selective Binding of O 2 from Air

Porous materials that take advantage of different chemisorptive behaviors of O 2 and N 2 could be an effective alternative to approaches based on physisorption for this important separation. Recently, the tetra-nuclear cobalt complex [(Co(III) 2 (bpbp)O 2 ) 2 bdc](PF 6 ) 4 (CSD code: GAMVIB; bpbp – = 2,6-bis(N,N-bis(2-pyridylmethyl)aminomethyl)-4-tert-butylphenolato; bdc 2– = 1,4-benzenedicarboxylato) was shown to have potential for O 2 /N 2 separations based on this concept. This observation raises the question of what other known materials have similar properties. Here, we combine structure screening with a high-throughput periodic density functional theory (DFT) workflow to investigate O 2 and N 2 adsorption in materials from validated crystal structure databases (e.g., CoRE-MOF database and CSD database). These calculations identify multiple materials that have similar di-Co clusters to GAMVIB that are predicted to selectively bind O 2 over N 2 , and suggest design rules that can be used to tune the O 2 and N 2 affinities in materials of this kind.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine-learning for designing nanoarchitectured materials by dealloying

Machine learning-augmented materials design is an emerging method for rapidly developing new materials. It is especially useful for designing new nanoarchitectured materials, whose design parameter space is often large and complex. Metal-agent dealloying, a materials design method for fabricating nanoporous or nanocomposite from a wide range of elements, has attracted significant interest. Here, a machine learning approach is introduced to explore metal-agent dealloying, leading to the prediction of 132 plausible ternary dealloying systems. A machine learning-augmented framework is tested, including predicting dealloying systems and characterizing combinatorial thin films via automated and autonomous machine learning-driven synchrotron techniques. This work demonstrates the potential to utilize machine learning-augmented methods for creating nanoarchitectured thin films.

36 MATERIALS SCIENCE↗

Membrane potential sensing: Material design and method development for single particle optical electrophysiology

We review the development of “single” nanoparticle-based inorganic and organic voltage sensors, which can eventually become a viable tool for “non-genetic optogenetics.” The voltage sensing is accomplished with optical imaging at the fast temporal response and high spatial resolutions in a large field of view. Inorganic voltage nanosensors utilize the Quantum Confined Stark Effect (QCSE) to sense local electric fields. Engineered nanoparticles achieve substantial single-particle voltage sensitivity (~2% Δλ spectral Stark shift up to ~30% ΔF/F per 160 mV) at room temperature due to enhanced charge separation. A dedicated home-built fluorescence microscope records spectrally resolved images to measure the QCSE induced spectral shift at the single-particle level. Biomaterial based surface ligands are designed and developed based on theoretical simulations. The hybrid nanobiomaterials satisfy anisotropic facet-selective coating, enabling effective compartmentalization beyond non-specific staining. Self-spiking- and patched-HEK293 cells and cortical neurons, when stained with hybrid nanobiomaterials, show clear photoluminescence intensity changes in response to membrane potential (MP) changes. Organic voltage nanosensors based on polystyrene beads and nanodisk technology utilize Fluorescence (Förster) Resonance Energy Transfer (FRET) to sense local electric fields. Voltage sensing FRET pairs achieve voltage sensitivity up to ~35% ΔF/F per 120 mV in cultures. Non-invasive MP recording from individual targeted sites (synapses and spines) with nanodisks has been realized. However, both of these QCSE- and FRET-based voltage nanosensors yet need to reach the milestone of recording individual action potentials from individual targeted sites.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning Enhanced Development of Functionally Graded Materials Enabled by Directed Energy Deposition

The ability to functionally grade materials provides designers with a new dimension of design flexibility that can be leveraged to improve functionality, reduce cost, or improve efficiency in a wide range of applications. This program was specifically focused on FGMs for hot and harsh gas path environments. These environments are common for the hot sections of jet engines and gas turbines, where parts undergo high temperature and mechanical loads in a corrosive environment. Expensive high γ' strengthened Ni superalloys such as René 41 (R41) and René 80 (R80) are generally used exclusively for a whole part, although only a section of the part demands such superalloys. To minimize cost, low/no γ' strengthened Ni superalloys such as Inconel 718 (INC718) could be used at less-demanding sections of the part could be welded to the high γ' strengthened Ni superalloys. However, the welding typically is a failure site due to the low durability at the welding interface. Functionally grading provides a welding alternative that can allow cost reduction without sacrificing mechanical performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Summary of FY2024 Experimental Results to Support Development of New Inelastic Material Models and Validation of Section III, Division 5, Class A Design Rules

To address the data gap crucial for updating existing viscoplastic constitutive material models for the Class A materials in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code, Section III, Division 5, High Temperature Reactors (ASME, 2023) for inelastic design analysis, Oak Ridge National Laboratory (ORNL) conducted experimental studies on Alloy 800H and Alloy 617 across a range of temperatures up to their maximum temperature limits in Section III, Division 5. The studies aim to characterize the materials' deformation behavior under both strain-controlled mechanical cyclic loading and thermal cycling conditions. This report summarizes ORNL's FY 2024 experimental findings on Alloy 800H and Alloy 617, focusing on pure fatigue tests, cyclic stress-strain curves, thermomechanical fatigue experiments, and verification of the high temperature cyclic damage summation design rules.

36 MATERIALS SCIENCE↗

Development Results on Replacement Materials for Current Scarce or High Supply Chain Risk Materials

In September 2020, the U.S. government issued an executive order to address the threat to the domestic supply chain from its reliance on critical minerals (CMs) from foreign competitors and to support the domestic mining and processing industry. The Advanced Materials and Manufacturing Technology (AMMT) program is addressing this executive order by evaluating advanced manufacturing (AM) and its impact on the demands of CMs for energy production in general and how the deployment of AM in nuclear energy will support the projected goals of the Paris Accord and further a net-zero carbon economy (NZE) by 2050. Three strategic reports were previously prepared by the AMMT program to date and identified two areas for more detailed exploration: (1) the replacement of high-risk CMs such as cobalt and niobium by more abundant minerals and (2) the minimization and utilization of CM waste streams. The design of nuclear materials without critical elements as alloying elements, is a part of the nuclear materials strategy to overcome the critical minerals scarcity. In this report, two approaches are evaluated namely (1) replacement of critical elements as alloying elements in nuclear materials, and (2) the design of a new alloys that does not contain critical minerals as an alloying element.

36 MATERIALS SCIENCE↗

Application of the Continuum Damage Mechanics Wilshire-Cano-Stewart (WCS) Model

In this study, the applications of the continuum damage mechanics-based Wilshire-Cano-Stewart (WCS) model are explored to predict rupture time, minimum-creep-strain-rate (MCSR), damage, damage evolution, and creep deformation. Increase knowledge in manufacturing methods has pushed the limit of material science and the development of new materials. Conventional testing is required to qualify materials against creep which according to the ASME B&PV III code, 10,000+ hours of experiments are necessary for each heat before materials are put into service. This process is costly and not feasible for new materials. As an alternative, models have been employed to predict creep behaviors and reduce the amount of time necessary for material qualification. Many models have been developed to predict distinct creep behaviors and the question of which model is best remains. Amongst current models, the WCS model has emerge with the ability to predict multiple behaviors using an explicit analytical approach with the ability to predict long-term creep. In this study the novel continuum damage mechanics WCS is employed in multiple applications. The goals of the study are (a) to discuss and determine the framework of the WCS model and validated it mathematically and using parametric simulations, (b) applied the model to accelerated creep data to show the capabilities of the model with non-conventional data, and (c) applied a novel numerical method, the datum temperature method (DTM) to show the model extrapolations and interpolations capabilities with limited and reduce data sets. To accomplish these goals, data is gathered for alloy P91 and Inconel 718 to develop and post-audit validate the model. The benefits of using the WCS model is that it provides an explicit stress and temperature dependency ideal for extrapolations, the coupled equations are suitable for finite element analysis (FEA) implementation, and it follows an explicit calibration approach. The model also proves that it can be applied to accelerated testing data and using the DTM.

Cano, Jaime A↗

Development of Lightweight Structural Materials with Improved Properties for Fission Batteries

Fission batteries require lightweight structural materials that demonstrate structural resilience when subjected to repeated shutdown, transportation, startup cycles, and certain external conditions, including rare events such as seismic vibrations and tsunamis. The objectives of this project are (1) to produce lightweight structural materials whose strength-to-weight ratios and fatigue resistance exceed those of current widely used structural materials such as 316 stainless steels (SS316), and (2) to enhance radiation tolerance of structural materials over a suitable service temperature range. To achieve these, (1) a lattice structure will be produced, (2) advanced modeling and simulation tools will be employed to design lattice structures (e.g., a gyroid structure) that reduce stress concentrations and thus increase fatigue resistance, and (3) one-dimensional (1-D) carbon nanotubes will be added to enhance radiation resistance. To validate our solution, high-temperature tensile and fatigue testing, in combination with microstructure characterization, will be conducted on wrought materials, additively manufactured solid materials, and the designed lightweight lattice structure material. Ion irradiation, microstructure characterization, and nanoindentation will be carried out to investigate the effect of 1-D carbon nanotubes on radiation tolerance. Successful completion of this project will deliver a material to serve as a substitute for current SS316 using the same chemistry but with lighter weight and improved mechanical properties. In addition, a material with carbon nanotubes can be designed for improved radiation tolerance over a suitable service temperature range. This project will establish new techniques in innovative materials/lattice design, advanced macroscale properties prediction, and the application of state-of-the-art processes.

36 MATERIALS SCIENCE↗