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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Establishing model credibility for process-microstructure-property relationships in additive manufacturing using exascale computing

Additive Manufacturing (AM) of alloys holds significant promise as a disruptive technology in various industries, yet its adoption is often hindered by challenges in achieving consistent part quality. These issues are primarily due to the complex process-microstructure-property (PSP) relationships inherent to AM. Computational models can greatly aid in understanding these relationships, but their widespread impact and adoption has been limited by a lack of validated, open-source, and computationally efficient PSP modeling frameworks and hardware limitations. Here, this study leverages the ExaAM software suite and data from the AMBench-2018 series of laser powder bed fusion (LPBF) benchmark experiments to perform a comprehensive model assessment, including verification, validation, sensitivity analysis, and uncertainty quantification. The RADICAL-EnTK workflow manager was used to perform an ensemble of heat transport, solidification, and mechanical response simulations on the exascale computer Frontier, considering uncertainties in critical model inputs such as laser spot size and nucleation parameters, and consisting of 125 explicit grain structure simulations and 7875 crystal plasticity simulations. For a selected location within the Inconel 625 AMBench-2018 test artifact, sensitivity analysis and uncertainty quantification were performed using the predicted distributions of grain structure and mechanical properties. Qualitative agreement was found between the predicted grain size and texture and the observed AMBench-2018 microstructure, the mean predicted yield stress was within 5% of the experimental measurement mean, and the mean predicted engineering stress at 5% strain was within 10% of the experimental measurement mean. The insights gained from development and validation of the ExaAM PSP modeling framework will help guide future directions for enhancing the credibility and reliability of PSP models in AM, thereby accelerating the adoption of AM technologies in various industries.

Additive manufacturing↗
DOE OSTI2020

Conditional Generative Adversarial Networks for Solving Heat Transfer Problems

Generative Adversarial Networks (GANs) have been used as a deep learning approach to solving physics and engineering problems. Using deep learning for these problems is attractive in that reasonably accurate models can be inferred from only raw data, eliminating the need to define the exact physical equations governing a problem. We expand on previous work using GANs to generate steady-state solutions to the two-dimensional heat equation. Using a basic conditional GAN (cGAN), we generate accurate solutions for rectangular domains conditioned on four edge boundary conditions (MAE < 0.5%). For finding steady-state solutions over arbitrary two-dimensional domains (not constrained to rectangles), we use a cGAN designed for image-to-image translation. We train this GAN on various types of geometric domains (circles, squares, triangles, shapes with one circular or rectangular hole), achieving accurate results on test data made up of geometries similar to those in training (MAE < 1%). For both of these GANs, we experiment with different loss function terms, showing that a term using the gradients of solution images significantly improves the basic cGAN but not the image-to-image GAN. Lastly, we show that the image-to-image GAN performs poorly when applied to two-dimensional geometries that vary in structure from training data (MAE < 8% for shapes with multiple holes or different shaped holes). This demonstrates the cGAN's lack of generalizability. While the cGAN is an accurate and computationally efficient method when trained and tested on similarly structured data, it is a much less reliable method when applied to data that is slightly different in structure from the training data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Prediction of chlorine and fluorine crystal structures at high pressure using symmetry driven structure search with geometric constraints

The high-pressure properties of fluorine and chlorine are not yet well understood because both are highly reactive and volatile elements, which have made conducting diamond anvil cell and x-ray diffraction experiments a challenge. Here, we use ab initio methods to search for stable crystal structures of both elements at megabar pressures. We demonstrate how symmetry and geometric constraints can be combined to efficiently generate crystal structures that are composed of diatomic molecules. Furthermore, our algorithm extends the symmetry driven structure search method by adding constraints for the bond length and the number of atoms in a molecule while still maintaining generality. As a method of validation, we have tested our approach for dense hydrogen and reproduced the known molecular structures of Cmca-12 and Cmca-4. We apply our algorithm to study chlorine and fluorine in the pressure range of 10 GPa–4000 GPa while considering crystal structures with up to 40 atoms per unit cell. We predict chlorine to follow the same series of phase transformations as elemental iodine from Cmca to Immm to Fm3¯m, but at substantially higher pressures. We predict fluorine to transition from a C2/c to Cmca structure at 70 GPa, to a novel orthorhombic and metallic structure with P42/mmc symmetry at 2500 GPa, and finally to its cubic analog form with Pm3¯n symmetry at 3000 GPa.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Heterogeneous Machine Learning on High Performance Computing for End to End Driving of Autonomous Vehicles

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving. For machines though, this gap is guarded by at least two challenges: 1) machine learning techniques remain brittle and unable to generalize to a wide range of scenarios, and 2) effective training data that enhances generalization and generates the desired driving behavior. Further, each challenge can be computationally intensive on its own thereby exasperating the gap. Moreover, is has not yet been shown that a single form of learning or training is capable of addressing a large range of scenarios. As a result, solving the first challenge does not inherently solve the second and vice versa. The work described here discusses an approach to address the first challenge that would also provide a foundation for solving the second. Our approach utilizes a combination of conditional imitation learning with a static dataset, reinforcement learning with a simulation environment, and high-performance computing to train a neural network. As a result, this reduces the “time to solution” from to the existing techniques for autonomous driving and provides an extensible framework to address the second key challenge.

autonomous vehicles↗
DOE OSTI2019

Crush Strengths of Stainless Steel Honeycomb for Packaging

Honeycomb structures are used as energy absorbers to dissipate kinetic energy. Their low density to high axial strength and inexpensive cost make them ideal for the energy absorption application. Mechanical properties of lightweight materials are well known compared to more dense materials like stainless steel. Determines the viability of using 304 Stainless Steel honeycomb in future SRNL radioactive material packages. Using a combination of the material properties and testing procedures both static and dynamic crush strength of stainless steel honeycomb will be determined. Both static and dynamic crush strengths of stainless steel honeycomb need to be quantified because strain rate plays a role in the material strength. The stainless steel honeycomb being tested will be cut into sections of about 2.0 inches in width, 2.3 inches in length and 2.5 inches in height. The cell size of the material is 0.25 in and the ribbon thickness 0.003 in. The material has a yield strength of 48 ksi and an ultimate strength of 103.2 ksi, with an elastic modulus of 29,300 ksi. Compression testing to determine the static crush strength will use an Instron compression test machine. This Instron machine uses a 20 ksi capacity load cell, while recording data at varying low strain rates. Dynamic impact testing will involve dropping a 43.8 lb impactor from a height around 5 feet onto the stainless steel honeycomb. The honeycomb structure will be on a rigid surface and the impactor will be dropped via a quick release hook. Dynamic crush strength is determined from the weight of the impactor, height of the drop and difference in height of the honeycomb after the drop.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Scaling-Up of Nano-Architected Microstructures: A Mechanical Assessment

Nano– and micro–architected materials generated by ultra–high–resolution 3D printing techniques, such as two–photon polymerization direct laser writing (TPP–DLW) or projection micro–stereolithography (PμSL), have garnered great interest due to their ability to achieve exceptional combinations of material properties. The scalability of these materials, however, remains a crucial challenge as larger high–resolution samples require stitching smaller blocks of the structure of interest together. Herein, scaling techniques and testing methodologies to investigate the effect of stitching on the integrity and mechanical behavior of TPP–DLW parts under tensile load are explored. Specifically, stitched log–pile I–beam specimens with relative densities of 21.5% and 54.7% are tested herein. The micro–tensile tests reveal that the higher–density log–pile samples exhibit brittle behavior with fracture loads at least four times higher than those of lower–density samples. The location of sample failure depends on the type of stitch introduced in the sample, as well as on the relative sample density. Altogether, this study highlights the importance of stitching techniques and relative density for the design of nano– and micro–architected materials.

36 MATERIALS SCIENCE↗
DOE OSTI2019

An Interconnected Channel-Like Framework as Host for Lithium Metal Composite Anodes

Lithium (Li) metal anodes have long been counted on to meet the increasing demand for high energy, high–power rechargeable battery systems but they have been plagued by uncontrollable plating, unstable solid electrolyte interphase (SEI) formation, and the resulting low Coulombic efficiency. These problems are even aggravated under commercial levels of current density and areal capacity testing conditions. In this work, the channel–like structure of a carbonized eggplant (EP) as a stable “host” for Li metal melt infusion, is utilized. With further interphase modification of lithium fluoride (LiF), the as–formed EP–LiF composite anode maintains ≈90% Li metal theoretical capacity and can successfully suppress dendrite growth and volume fluctuation during cycling. EP–LiF offers much improved symmetric cell and full–cell cycling performance with lower and more stable overpotential under various areal capacity and elevated rate capability. Furthermore, carbonized EP serves as a light–weight high–performance current collector, achieving an average Coulombic efficiency ≈99.1% in ether–based electrolytes with 2.2 mAh cm –2 cycling areal capacity. Furthermore, the natural structure of carbonized EP will inspire further artificial designs of electrode frameworks for both Li anode and sulfur cathodes, enabling promising candidates for next–generation high–energy density batteries.

25 ENERGY STORAGE↗
DOE OSTI2019

Singleton portals to the twin sector

The mirror twin Higgs framework allows for a natural Higgs mass while being consistent with collider bounds on colored symmetry partners to standard model quarks. This mechanism relies crucially on a discrete symmetry which relates each standard model field to a mirror partner. These partners are charged under gauge groups identical to, but distinct from, those in the standard model. The minimal twin Higgs scenario provides only one low-energy connection between the visible and twin sectors, the light Higgs boson. We present a new class of portals connecting the two sectors, using fields that have no twin partner under the discrete symmetry. Scalar, fermion, and vector states may provide such singleton portals, each with unique features and experimental signatures. The vector portal, in particular, provides a variety of renormalizable interactions relevant for the LHC. We provide concrete constructions of these portals and determine their phenomenology and opportunities to probe the twin sector at the LHC. We also sketch a scenario in which the structure of the twin sector itself can be tested.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Wavelet-based algorithm for correction of beam-steering artefacts in turbulent flow imaging at elevated pressures

Beam steering by index-of-refraction gradients poses a significant challenge for laser-based imaging measurements in turbulent reacting and non-reacting flows, particularly at elevated pressures. High fidelity imaging and quantitative data interpretation in turbulent flows can be considerably impeded by artefacts generated from beam steering. A wavelet-based filtering scheme has been developed to recover the underlying turbulent flow structures from imaging measurements containing severe beam-steering artefacts. This analysis technique is equally applicable to imaging measurements in reacting and non-reacting flows. It is demonstrated using mixture fraction measurements in a transient turbulent jet flow at 8 bar using Rayleigh scattering imaging at a repetition rate of 100 kHz. In this paper, the corrected images reveal the temporal evolution of flow structures with negligible residual beam-steering artefacts. Tests of the sensitivity of the wavelet-based filtering scheme to noise and spatial resolution indicate that it is a robust analytic tool for correcting severe beam-steering artefacts commonly encountered in laser-based imaging measurements at elevated pressures.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Remanent Magnetic Flux Distribution in Superconducting-Ferromagnetic Layered Heterostructures

Stacks of superconducting tape, made of second-generation coated conductors, present an interesting alternative to bulk superconductors. The layered geometry allows incorporation of other functional, namely ferromagnetic, materials. The ferromagnetic material changes the field configuration within the superconductor and can be used to shape or divert the flux density from its interior. This can be used to optimise the remanent flux density after magnetisation. FEM simulations are employed to test the performance of a variety of superconductor/ferromagnet structures and explain the role of the ferromagnetic material in the composite structure. Cases where trapped field is much higher and lower than remanent magnetisation of the ferromagnetic material are considered, showing that performance can be enhanced or maintained by using ferromagnetic material while reducing the usage of costly superconducting tape.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Subgrains, Texture Evolution, and Dynamic Abnormal Grain Growth in a Mo Rod Material

The roles of subgrains, texture, and surface energy during dynamic abnormal grain growth (DAGG) were examined in a commercial-purity Mo rod material. DAGG was confirmed in this material during tensile deformation at 2023 K (1750 °C). Cooling of specimens after tensile testing was sufficiently rapid to preserve both subgrain structures developed during deformation and several abnormal grains at early stages of growth. These and other microstructural features were characterized to evaluate how subgrains and boundary character influence the early stages of DAGG. Subgrains were observed in the deformed polycrystalline material but were generally absent in newly formed abnormal grains. This was identified as the cause of the sudden drop in flow stress observed at the initiation of DAGG. It is proposed that subgrain intersections with abnormal grain boundaries provide a driving pressure for DAGG. Subgrains within the deformed polycrystals were observed to locally change the boundary curvature at their intersections with abnormal grain boundaries, which likely encouraged growth of the abnormal grains into the deformed polycrystals. Abnormal grains produced by DAGG retained crystallographic orientations and boundary characters that closely resembled those of the polycrystalline material from which they grew. This indicates that neither differences in orientation nor boundary character were important to DAGG in this material.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A Review on Friction Stir Processing of Titanium Alloy: Characterization, Method, Microstructure, Properties

In the past two decades, friction stir processing (FSP) technology has received considerable attention. FSP can be used to adjust and control the microstructure of materials, including eliminating defects, destroying dendrites and controlling fractions in the second stage, and is therefore widely used in titanium and its alloys for biomedical, aerospace and automotive applications. This article comprehensively reviews the methods of studying FSP, the microstructure evolution of materials and the summary of material properties. It begins with the introduction of the FSW system, characterization, structure and elemental analysis, and simulation and performance testing methods, and then introduces the microstructure evolution mechanism of various titanium materials and discusses in detail the material properties of titanium alloy, namely hardness and wear resistance, elasticity and plasticity, corrosion resistance and biocompatibility. Finally, this review presents unresolved issues and outstanding challenges in FSP technology and reveals the direction of this emerging field of research.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Direct Write Assembly of Graphene/Poly(ε-Caprolactone) Composite Scaffolds and Evaluation of Their Biological Performance Using Mouse Bone Marrow Mesenchymal Stem Cells

Scaffold and mesenchymal stem cell–based cartilage tissue engineering offers a favorable way for the repair and regeneration of injured cartilage. In this study, poly (ε-caprolactone) PCL scaffolds with grid-like structure having periodic lattice was manufactured by robocasting method in the presence of graphene nanoplatelets for cartilage tissue engineering applications. For this purpose, a PCL solution (20 wt%) containing pristine graphene nanopowders in the form of platelets was prepared as printing ink and it was dispensed through a nozzle at room temperature to an ethanol bath at 4 °C. The construction of porous scaffolds was made by a layer-by-layer assembly. Results revealed that graphene additions were not detrimental to deposition process and the structure of the resultant scaffolds. In vitro cell tests indicated that the prepared grid-like graphene/PCL composite scaffolds have good cytocompatibility and non-toxicity for mouse bone marrow mesenchymal stem cells. The stem cells attached and proliferated well on the scaffolds and they also demonstrated a chondrogenic differentiation in the absence of transforming growth factors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Accelerated basis adaptation in homogeneous chaos spaces

Polynomial chaos expansions (PCE) provide an efficient approach to uncertainty quantification (UQ) and have been adapted to diverse applications across the spectrum of science and engineering. For situations involving large stochastic parameterizations, the curse of dimensionality renders PCE-based methods computationally prohibitive. A basis adaptation approach for PCE was proposed by Tipireddy and Ghanem (2014) which transforms the input random variables through an isometry such that sufficient probabilistic characterization of specific quantities of interest (QoI) is concentrated in an algebraic manifold embedded in the linear span of the dominant transformed variables. While quite versatile, that original version of the PCE basis adaptation exhibited slow convergence for a number of problems of practical significance. In the present paper, we propose two novel methods to accelerate the convergence of the original basis adaptation approach, thus expanding its reach while also providing insight into its performance. In the first method, information gained from a pilot PCE representation is used to correct the mean and Gaussian coefficients in the adapted space. By taking advantages of probabilistic information in higher dimensional adaptation gleaned from an initial adaptation, the second method updates the rotation matrix used to identify the dominant transformed variables. In this manner, the new rotation matrix concentrates even more probabilistic information in its first few dimensions. These two method can be combined to achieve even better performance, the combined method is referred to as sequentially optimized adaptation method. Here, the methods are demonstrated on an analytical test function and a model of a space structure with several sub-components and a non-smooth quantity of interest representing the maximum acceleration over time. Both methods achieve accelerated convergence of the basis adaptation approach with negligible additional costs.

Accelerated convergence↗
DOE OSTI2026

Long cycle and calendar life of Si-based Li-ion batteries enabled by localized high-concentration electrolytes and their surprising water tolerance

Silicon-based anodes promise an increase in energy density for Li-ion batteries, yet they suffer from a poor calendar life. Researchers have posited that fluorinated lithium salt forms reactive side products that destroy the solid electrolyte interphase (SEI), even without cycling. HF is one such reactive side product formed from trace water contamination in the electrolyte. Some electrolytes, such as localized high concentration electrolytes (LHCEs) may improve cell stability in highly reactive systems, such as Li metal and Si. In the present study, LHCEs containing 200-300 ppm of water retained up to 8% greater capacity (1200-1300 mAh/g Si) in calendar life tests over 200 days compared to dried electrolytes (< 20 ppm water). Calendar aging took place at 100% state of charge. Cells with 200-300 ppm water performed comparably to cells with 20 ppm water in cycle life tests (900-1000 mAh/g Si) . Even adding 1000 ppm water did not lead to rapid capacity fade in cells undergoing cycle life tests. Nano-FTIR spectroscopy revealed chemical and structural differences in the SEI for cells with 1000 ppm water compared to 200-300 ppm water. The SEI differences, including increased Li2O concentration, may have contributed to improved calendar life. This research reveals the capabilities of LHCEs to improve the calendar and cycle life of Si-based Li-ion batteries, despite the presence of a highly reactive contaminant.

25 ENERGY STORAGE↗
DOE OSTI2021

A study on the creep behavior of alloy 709 using in-situ scanning electron microscopy

In this research, an experimental evaluation of creep properties of Alloy 709 in the temperature range of 750–850 °C was undertaken. Alloy 709 is a novel austenitic stainless steel with 20% Cr and 25% Ni by wt% that was developed for application in structural components of nuclear power plants. Creep rupture tests were conducted in an in-situ heating-loading and Scanning Electron Microscope (SEM) unit equipped with Electron Backscatter Diffraction (EBSD) detector and Energy Dispersive Spectroscopy (EDS). “Real-time” creep damage mechanisms of Alloy 709 at various stresses and temperatures using a flat, un-notched sample with continuously reducing cross-section is studied so that the failure and maximum creep damage occurred at the center of the sample where the in-situ SEM imaging could be focused. Accelerated creep tests at temperatures and stresses above service conditions were performed by employing multiple blocks of constant loads where the loads were increased once the sample attained constant creep rate, indicating a secondary creep regime. This technique ensures multiple data points can be obtained from the same test, saves the time required for an otherwise long-term creep test and usage of SEM. Further, Coincident Site Lattice (CSL) boundary maps were collected as control maps before testing, and the grain boundaries were observed during the creep test to understand the effect of grain boundary character on the creep damage mechanism. Void growth, grain boundary separation, and sliding were found to be the main creep mechanisms whose rate is dependent on stress and temperature. Failure mechanisms studied on the fracture surface using SEM fractography were correlated to the sample surface observations to create complementary information to better understand the underline creep mechanism of Alloy 709.

36 MATERIALS SCIENCE↗
DOE OSTI2018

V2O5 nanowires-graphene composite as an outstanding electrode material for high electrochemical performance and long-cycle-life supercapacitor

Highlights: • V{sub 2}O{sub 5} nanowires anchored on the surface of rGO sheets using facile hydrothermal method for energy storage application. • High gravimetric capacitance of 1002 F g{sup −1} has been achieved at the current density of 1 A g{sup −1} in an aqueous electrolyte. • Exceptionally high energy density of 116 Wh kg{sup −1} has been obtained using supercapacitor coin cell. • Composite (V{sub 2}O{sub 5}-NW-G) exhibits excellent cyclic stability with 83.94 % capacitance retention after 5000 GCD cycles. - Abstract: A composite of V{sub 2}O{sub 5} nanowires with reduced graphene oxide (V{sub 2}O{sub 5}-NW-G) has been prepared using facile hydrothermal method and tested for charge storage supercapacitor application. Morphological and structural aspects of as prepared materials has been studied using material characterization techniques like transmission electron microscope (TEM), scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). The nanosized wires like structure of V{sub 2}O{sub 5} anchored on the graphene (rGO) sheets possesses improved electrical conductivity and high surface area. Electrochemical properties of the synthesized materials have been studied using cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS). Composite (V{sub 2}O{sub 5}-NW-G) exhibits exceptional properties like high gravimetric capacitance of 1002 F g{sup −1} along with good cyclic stability of 83.94% capacitance retention after 5000 repetitive GCD cycles. Excellent energy density of 116 Wh kg{sup −1} has been obtained at the power density of 1520 W kg{sup −1}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

New method for level-lifetime measurements with thick scintillators

Level lifetimes provide key insight into the structure of atomic nuclei and serve as stringent tests of theoretical descriptions. Though several methods for determining level lifetimes exist for both reaction measurements and decay studies, here the focus is on techniques involving the direct measurement of time differences between population and subsequent depopulation of excited states. The techniques presented herein are broadly applicable across multiple timing ranges, but the approach is specifically described for the βγ timing method. A multi-step, amplitude-dependent time walk correction was employed to address the data analysis complications that arise from using thick scintillators for electron detection. Further, additional corrections for the depth of the interaction must also be performed when the parent isotope has been implanted into the detector. Techniques are presented for performing these time walk and depth of interaction corrections. Subsequently, a new Monte Carlo method utilizing measured detector responses obtained from the data, coupled with chi-square minimization, is presented for extracting excited state lifetimes ≳ 100 picoseconds. The framework of this Monte Carlo method is developed for the decay of a state in 68 Zn with a known 1.6 ps half life, which is considered prompt given the detection sensitivity of the technique, and then benchmarked using two other excited states in neutron-rich Ni isotopes with 120(34) ps and 1.05(3) ns half lives. Using this new method which takes into account the thick scintillator used, these same half lives were measured to be 135(10) ps and 1.04(24) ns, respectively. The overall good agreement demonstrates the validity of the technique.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗