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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Promising Method of Sm–Co Magnet Reprocessing in Alkali Chloride Melts

Developing new, efficient methods for samarium and cobalt recovery from scraps/rejects and swarf at Sm–Co magnet manufacturing sites during shaping and finishing is an important task in terms of meeting their growing demand. In this work, the reaction of oxygen with a solution of samarium and cobalt chlorides in a LiCl–KCl eutectic melt was studied at 400–600 °C to explore possible methods for the separation and recovery of samarium and cobalt from these waste products. The pyrochemical reaction resulted in the formation and precipitation of samarium oxychloride, while the cobalt remained in the melt in a soluble chloride form. The effect of temperature and the amount of oxygen passed through the melt (oxygen-to-samarium molar ratio) on the course of the reaction were studied. Kinetic parameters of the oxygen with samarium chloride reaction were determined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Ultrafast dense DNA functionalization of quantum dots and rods for scalable 2D array fabrication with nanoscale precision

Scalable fabrication of two-dimensional (2D) arrays of quantum dots (QDs) and quantum rods (QRs) with nanoscale precision is required for numerous device applications. However, self-assembly–based fabrication of such arrays using DNA origami typically suffers from low yield due to inefficient QD and QR DNA functionalization. In addition, it is challenging to organize solution-assembled DNA origami arrays on 2D device substrates while maintaining their structural fidelity. Here, we reduced manufacturing time from a few days to a few minutes by preparing high-density DNA-conjugated QDs/QRs from organic solution using a dehydration and rehydration process. We used a surface-assisted large-scale assembly (SALSA) method to construct 2D origami lattices directly on solid substrates to template QD and QR 2D arrays with orientational control, with overall loading yields exceeding 90%. Our fabrication approach enables the scalable, high fidelity manufacturing of 2D addressable QDs and QRs with nanoscale orientational and spacing control for functional 2D photonic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Dynamic Beam Shape Sensing and Control in an Open Architecture Metal AM System for Microstructure Manipulation

Most commercially available metal additive manufacturing (AM) systems are closed-architecture, meaning that the system manufacturer limits the ability of the user to directly control the process conditions and can modify the specified inputs using proprietary methods. Unfortunately, this approach severely limits or confounds the ability for users to perform research on fundamental aspects of additive manufacturing. ARCTOS Technology Solutions (ARCTOS) produces an open-architecture laser powder bed fusion (PBF) additive manufacturing system that allows the user to fully control all aspects of the process control and monitoring. The purpose of this project is to help develop beam shaping capabilities and controls within the ARCTOS open-architecture system for control of microstructure evolution during metal AM.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Verification Suite of Test Cases for the Barotropic Solver of Ocean Models

Abstract The development of any atmosphere or ocean model warrants a suite of test cases (TCs) to verify its spatial and temporal discretizations, order of accuracy, stability, reproducibility, portability, scalability, etc. In this paper, we present a suite of shallow water TCs designed to verify the barotropic solver of atmosphere and ocean models. These include the non‐dispersive coastal Kelvin wave; the dispersive inertia‐gravity wave; the dispersive planetary and topographic Rossby waves; the barotropic tide; and a non‐linear manufactured solution. These TCs check the implementation of the linear pressure gradient term; the linear constant or variable‐coefficient Coriolis and bathymetry terms; and the non‐linear advection terms. Simulation results are presented for a variety of time‐stepping methods as well as two spatial discretizations: a mimetic finite volume method based on the TRiSK scheme, and a high‐order discontinuous Galerkin spectral element method. The experimental procedure for conducting these numerical experiments is detailed. It underscores several key considerations that vary depending on the chosen spatial discretization method. Finally, convergence studies of every TC are conducted with refinement in both space and time, only in space, and only in time. The convergence slopes match the expected theoretical predictions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Channel Wall Nozzle Manufacturing Technology Advancements for Liquid Rocket Engines

A regeneratively-cooled nozzle is a critical component for expansion of the hot gases to enable high temperature and performance liquid rocket engines systems. Channel wall nozzles are a design solution used across the propulsion industry as a simplified method to fabricate the nozzle structure with internal coolant passages. The scale and complexity of the channel wall nozzle (CWN) design is challenging to fabricate leading to extended lead times and higher costs. Some of these challenges include: 1) unique and high temperature materials, 2) Tight tolerances during manufacturing and assembly to contain high pressure propellants, 3) thin-walled features to maintain adequate wall temperatures, and 4) Unique manufacturing process operations and tooling. The United States (U.S.) National Aeronautics and Space Administration (NASA) along with U.S. specialty manufacturing vendors are maturing modern fabrication techniques to reduce complexity and decrease costs associated with channel wall nozzle manufacturing technology. Additive Manufacturing (AM) is one of the key technology advancements being evaluated for channel wall nozzles. Much of additive manufacturing for propulsion components has focused on powder bed fusion, but the scale is not yet feasible for application to large scale nozzles. NASA is evolving directed energy deposition (DED) techniques for nozzles including arc-based deposition, blown powder deposition, and Laser Wire Direct Closeout (LWDC). There are different approaches being considered for fabrication of the nozzle and each of these DED processes offer unique process steps for rapid fabrication. The arc-based and blown powder deposition techniques are being used for the forming of the CWN liner. A variety of materials are being demonstrated including Inconel 625, Haynes 230, JBK-75, and NASA HR-1. The blown powder DED process is also being demonstrated for forming an integral channel nozzle in a single operation in similar materials. The LWDC process is a method for closing out the channels within the liner and forming the structural jacket using a localized laser wire deposition technique. Identical materials mentioned above have been used for this process in addition to bimetallic closeout (C-18150–SS347, and C-18150–Inconel 625). NASA has completed process development, material characterization, and hot-fire testing on a variety of these channel wall nozzle fabrication techniques. This paper will present an overview of the various processes and materials being evaluated and the results from the hot-fire testing. Future development and technology focus areas will also be discussed relative to channel wall nozzle manufacturing.

Gradl, Paul R.↗
NASA NTRSDate not supplied

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗
DOE OSTI2025

Challenges in Tracking Waste Reduction Performance Improvement in Manufacturing Plants

The recently released Circularity Gap Report 2023 by the Circle Economy Foundation states that the circularity score for the global economy is declining. The US Environmental Protection Agency (EPA) tracked municipal solid waste from 1960 to 2018 and found that 50% of the waste was destined for landfills. EPA estimates that US industry is responsible for 2.7 Gt of solid nonhazardous waste annually in the US mostly linear economy model. The circular economy framework aims to decouple economic value generation from the extraction of virgin materials from nature. The linear model of material extraction and disposal at the end of life is highly unsustainable. Manufacturing companies are adopting ambitious waste reduction targets to achieve sustainability. Through the Better Plants program, US DOE has established the Waste Reduction Network, which offers technical assistance to partners to achieve their ambitious waste reduction goals. Basic requirements of establishing a target include identifying a baseline, quantifying waste performance, and measuring progress over time. One problem faced by industry is unstandardized metrics for quantifying waste performance that may not be well suited to demonstrate progress. This paper studies traditional methods used to measure waste performance and highlights advantages, disadvantages, and limitations of each method. It also examines the suitability of applying the methods in different manufacturing circumstances. Finally, the paper presents a case study of a large manufacturer that faced inconsistencies in its tracked measurement metric. A solution was proposed and implemented to alter the methodology to enable more accurate waste performance tracking against a baseline.

circular economy↗
DOE OSTI2025

Additive manufacturing for electrocaloric terpolymer thin films

Current heating, venting, and air conditioning (HVAC) systems have drawbacks of high energy consumption, large CO 2 emissions, and low efficiency. Electrocaloric (EC) cycles present an eco-friendly alternative by converting thermal energy to electrical energy. Defect-free thin films with uniform thickness are required to achieve optimal EC performance. A scalable thin film fabrication process is essential for integrating EC cycles into HVAC systems. This study introduces EC thin films prepared by electrospray (ES) processing, a manufacturing method that deposits EC polymer layer by layer using high voltage. The resulting films show superior thickness control, smoother surfaces, and improved thermal and electrical properties compared with solution casting. In addition, post-annealing at 120°C enhances the thermal and EC performance, with films achieving a temperature change (ΔT) of 3.6°C at 100 MV/m when tested near room temperature. With the potential for future scalability, the ES method offers a promising approach for fabricating EC thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Scalable Deep Learning-Based Microarchitecture Simulation on GPUs

Cycle-accurate microarchitecture simulators are essential tools for designers to architect, estimate, optimize, and manufacture new processors that meet specific design expectations. However, conventional simulators based on discrete-event methods often require an exceedingly long time-to-solution for the simulation of applications and architectures at full complexity and scale. Given the excitement around wielding the machine learning (ML) hammer to tackle various architecture problems, there have been attempts to employ ML to perform architecture simulations, such as Ithemal and SimNet. However, the direct application of existing ML approaches to architecture simulation may be even slower due to overwhelming memory traffic and stringent sequential computation logic. This work proposes the first graphics processing unit (GPU)-based microarchitecture simulator that fully unleashes the potential of GPUs to accelerate state-of-the-art ML-based simulators. First, considering the application traces are loaded from central processing unit (CPU) to GPU for simulation, we introduce various designs to reduce the data movement cost between CPUs and GPUs. Second, we propose a parallel simulation paradigm that partitions the application trace into sub-traces to simulate them in parallel with rigorous error analysis and effective error correction mechanisms. Combined, this scalable GPU-based simulator outperforms by orders of magnitude the traditional CPU-based simulators and the state-of-the-art ML-based simulators, i.e., SimNet and Ithemal.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2020

Technology Advancements for Channel Wall Nozzle Manufacturing In Liquid Rocket Engines

A regeneratively-cooled or dump-cooled nozzle is a critical component for expansion of hot gases to enable high temperature and performance in liquid rocket engines systems. Regeneratively-cooled channel wall nozzles are a design solution used across the propulsion industry as a simplified method to fabricate the nozzle structure with internal coolant passages. The scale and complexity of the channel wall nozzle (CWN) design can be challenging to fabricate which results in extended lead times and higher costs. Some of these challenges include: 1) Unique and high temperature materials, 2) Tight tolerances on large parts during manufacturing and assembly to contain high pressure propellants, 3) Thin-walled features to maintain adequate wall temperatures, and 4) Unique manufacturing process operations and complex tooling. The United States (U.S.) National Aeronautics and Space Administration (NASA) and U.S. specialty manufacturing vendors are maturing modern fabrication techniques to reduce complexity and decrease costs associated with channel wall nozzle manufacturing technology. Additive Manufacturing (AM) is one of the key technology advancements under evaluation for channel wall nozzles. Much of additive manufacturing for propulsion components has focused on laser powder bed fusion (L-PBF), but the scale is not yet feasible for application to large scale nozzles. NASA is evolving directed energy deposition (DED) techniques for nozzles including arc-based deposition, blown powder deposition, and Laser Wire Direct Closeout (LWDC). There are different approaches being considered for fabrication of the nozzle, and each of these DED processes offer unique process steps for rapid fabrication. The arc-based and blown powder deposition techniques are used for the forming of the CWN liner. A variety of materials are being demonstrated including Inconel 625, Haynes 230, JBK-75, and NASA HR-1. The blown powder DED process is also being demonstrated for forming an integral channel nozzle in a single operation in similar materials. The LWDC process is a method for closing out the channels within the liner and forming the structural jacket using a localized laser wire deposition technique. Identical materials mentioned above have been used for this process in addition to bimetallic closeout (C-18150–SS347, and C-18150–Inconel 625). NASA has completed process development, material characterization, and hot-fire testing on a variety of these channel wall nozzle fabrication technique. This publication presents an overview of the various channel wall nozzle manufacturing processes and materials under evaluation including results from the hot-fire testing. Future development and technology focus areas is also discussed relative to channel wall nozzle manufacturing.

Additive manufacturing↗
DOE OSTI2021

Comparison of the Mechanical Properties of a Conjugated Polymer Deposited Using Spin Coating, Interfacial Spreading, Solution Shearing, and Spray Coating

The mechanical properties of π-conjugated (semiconducting) polymers are a key determinant of the stability and manufacturability of devices envisioned for applications in energy and healthcare. These properties—including modulus, extensibility, toughness, and strength—are influenced by the morphology of the solid film, which depends on the method of processing. To date, the majority of work done on the mechanical properties of semiconducting polymers has been performed on films deposited by spin coating, a process not amenable to the manufacturing of large-area films. Here, we compare the mechanical properties of thin films of regioregular poly(3-heptylthiophene) (P3HpT) produced by three scalable deposition processes—interfacial spreading, solution shearing, and spray coating—and spin coating (as a reference). Our results lead to four principal conclusions. (1) Spray-coated films have poor mechanical robustness due to defects and inhomogeneous thickness. (2) Sheared films show the highest modulus, strength, and toughness, likely resulting from a decrease in free volume. (3) Interfacially spread films show a lower modulus but greater fracture strain than spin-coated films. (4) The trends observed in the tensile behavior of films cast using different deposition processes held true for both P3HpT and poly(3-butylthiophene) (P3BT), an analogue with a higher glass transition temperature. Grazing incidence X-ray diffraction and ultraviolet–visible spectroscopy reveal many notable differences in the solid structures of P3HpT films generated by all four processes. Herein, while these morphological differences provide possible explanations for differences in the electronic properties (hole mobility), we find that the mechanical properties of the film are dominated by the free volume and surface topography. In field-effect transistors, spread films had mobilities more than 1 magnitude greater than any other films, likely due to a relatively high proportion of edge-on texturing and long coherence length in the crystalline domains. Overall, spread films offer the best combination of deformability and charge-transport properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scalable Synthesis of Pt/SrTiO 3 Hydrogenolysis Catalysts in Pursuit of Manufacturing-Relevant Waste Plastic Solutions

Here, an improved hydrothermal synthesis for shape-controlled, size-controlled 60 nm SrTiO 3 nanocuboid (STO NC) supports, which facilitates the scalable creation of platinum nanoparticles catalyst supported on STO (Pt/STO) for the chemical conversion of waste polyolefins, is reported herein. This synthetic method: 1) produces STO NC supports with average sizes ranging from 25 – 80 nm with narrow size distributions 2) demonstrates how SrCO 3 formation and variation in solution pH prevent the formation of STO NCs, and 3) establishes that STO nucleation prior to the hydrothermal treatment favors nanocuboid formation. The updated hydrothermal synthesis was scaled-up and conducted in a 4L batch reactor, resulting in STO NCs of comparable size and morphology (m = 22.5 g, d avg = 58.6 ± 16.2 nm) to those synthesized under standard hydrothermal conditions in a lab-scale 125 mL autoclave reactor. Size-controlled STO NCs, ranging in roughly 10 nm increments from the 25 nm to 80 nm, were used to support Pt deposited through strong electrostatic adsorption (SEA), a practical and scalable solution-based method. Using SEA techniques and a STO support with an average size of 39.3 ± 6.3 nm, a Pt/STO catalyst with 3.6 wt% Pt was produced and used for high-density polyethylene hydrogenolysis under previously-reported conditions (170 psi H 2 , 300°C, 96h; final product: M w = 2400, Ð = 1.03). As a well-established model system for studying the behavior of heterogeneous catalysts and their supports in reactions, the Pt/STO system detailed in this work presents a unique opportunity to simultaneously convert waste plastic into commercially-viable products while gaining fundamental insight into the mechanism of polyethylene hydrogenolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A time-parallel method for scalable heat transfer simulations of additive manufacturing

Here, a major challenge in simulating the thermal behavior in additive manufacturing processes is the disparate length and time scales between transport phenomena occurring in the melt pool and the component. A common simulation approach relies on spatial decomposition for parallel computing, but due to the nature of heat transfer in AM, where most of the computational expenditure is localized near the melt pool, the computational speedup from spatial parallelization saturates quickly. Therefore, additional parallelism by means of time-domain decomposition is needed to fully take advantage of high-performance computing (HPC) resources. This work introduces a time-parallel method to improve the computational scalability of additive manufacturing simulations on HPC systems, while maintaining high temporal resolution of heat transfer near the melt pool. The method, inspired by the nonlinear paraexp formalism, performs an iterative superposition of nonlinear solutions to the initial value problem, integrating the heat equation across overlapping time-parallel intervals. For a single layer of the NIST AMB2018–01 L7 benchmark problem, the method achieves a 38.51x speedup in wall-clock time with a maximum error in the global temperature solution of 0.99%. This reduces the total solution time from 196.72 min to 5.11 min on 128 nodes of the ORNL Frontier supercomputer. The tradeoff between accuracy and total wall-clock time is investigated and recommendations for time-parallel deployment for AM problems are made.

Additive manufacturing↗
DOE OSTI2022

Scalability Testing Approach for Internet of Things for Manufacturing SQL and NoSQL Database Latency and Throughput

The proliferation of low-cost sensors and industrial data solutions has continued to push the frontier of manufacturing technology. Machine learning and other advanced statistical techniques stand to provide tremendous advantages in production capabilities, optimization, monitoring, and efficiency. The tremendous volume of data gathered continues to grow, and the methods for storing the data are critical underpinnings for advancing manufacturing technology. This work aims to investigate the ramifications and design tradeoffs within a decoupled architecture of two prominent database management systems (DBMS): sql and NoSQL. A representative comparison is carried out with Amazon Web Services (AWS) DynamoDB and AWS Aurora MySQL. The technologies and accompanying design constraints are investigated, and a side-by-side comparison is carried out through high-fidelity industrial data simulated load tests using metrics from a major US manufacturer. The results support the use of simulated client load testing for comparing the latency of database management systems as a system scales up from the prototype stage into production. As a result of complex query support, MySQL is favored for higher-order insights, while NoSQL can reduce system latency for known access patterns at the expense of integrated query flexibility. Here, by reviewing this work, a manufacturer can observe that the use of high-fidelity load testing can reveal tradeoffs in IoTfM write/ingestion performance in terms of latency that are not observable through prototype-scale testing of commercially available cloud DB solutions.

AWS↗
DOE OSTI2026

Compositional Homogeneity in Rapidly Solidified 316L stainless steel produced by laser powder-bed fusion processing

The segregation of alloying elements in rapidly solidified 316L stainless steel produced using additive manufacturing technologies is widely reported throughout literature. The microstructure of thin walls manufactured from 316L stainless steel using laser powder bed fusion are examined for the presence of alloy segregation, i.e. the rejection of solutes to grain boundaries. Metallographic methods including mechanical polishing and chemical etching are used to prepare samples for microanalysis m

Jankowski, Alan F. [Sandia National Laboratories (↗
DOE OSTI2024

Challenges in Tracking Waste Reduction Performance Improvement in Manufacturing Plants

The recently released Circularity Gap Report 2023 by Circle Economy Foundation found that the circularity score for the global economy is declining. This indicates that material extraction from virgin sources is climbing over earlier years. As per data released by US Geological Survey, material use in the US economy has increased exponentially with the expanding US economy over last century. EPA tracked municipal solid waste from 1960 to 2018 and found that 50% of the waste is destined for landfills. EPA estimates that US industry is responsible for 2.7 billion ton of solid non-hazardous waste annually in our mostly linear economy model. The circular economy framework aims at decoupling economic value generation from virgin materials extraction from nature. The linear model of material extraction and disposal at end of life is highly unsustainable. Manufacturing companies have realized this and in their commitments to sustainability are adopting ambitious waste reduction targets. Through Better Plants program US Department of Energy has established Waste Reduction Network where it is offering technical assistance to partners to achieve these ambitious waste reduction goals. Basic requirements of establishing a target include identifying a baseline, quantifying waste performance, and measuring progress over time. One problem faced by industry is the unstandardized metrics to quantify waste performance that may not be well suited to demonstrate progress. In this paper, we research methods traditionally used to measure waste performance and highlight advantages, gaps and limitations of each method. Suitability of the methods applicable to different manufacturing circumstances are also examined. Finally, we present a case study of a large manufacturer that faced inconsistencies in their tracked measurement metric. A solution was proposed to alter the methodology to enable more accurate waste performance tracking against a baseline.

Chaudhari, Subodh↗