Synthesis and Thermodynamics of Novel Materials in Advanced Manufacturing
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and nuclear chemistry↗
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Middle-of-line Integration of Atomic Precision Advanced Manufacturing
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Allemang, Christopher Richard [Sandia National Lab↗
Critical feature and seawater testing of cross-flow rotor components fabricated with additive manufacturing
Advanced manufacturing (AM) materials were investigated for their suitability for use in cross-flow turbine rotors. AM materials were categorized into 3 classes – plastics, metals, and ceramics – and reviewed for suitability based on a set of engineering requirements and criteria. Two plastics and two metals were selected to undergo further testing: Essentium CF25, Markforged Onyx, Titanium Ti-6Al-4V, and Inconel 718. Dogbone-shaped specimens were printed from each material in two sets. The first set was tensile tested to get a material baseline. The second set was submerged in the seawater tanks at PNNL-Sequim for 6 months to determine water uptake, corrosion, and biofouling resistance and then subsequently tensile tested. While few macroscopic changes could be observed after seawater testing, the plastic materials degraded significantly as compared to baseline, while the metal material properties remained consistent. Titanium and Inconel are used consistently by industry in extreme conditions, and the materials show promising performance for marine energy use cases.
McVey, James R.↗
Transformational challenge reactor design characteristics
The Transformational Challenge Reactor (TCR) program was conceived with the goal to reduce costs and time frames associated with advanced reactor deployment by leveraging developments in advanced manufacturing, advanced materials, data science, and rapid prototyping and testing. The final deliverable of the TCR program was to be an operational test of a novel reactor design. The TCR core design incorporates a dense tri-structural-isotropic/SiC fuel form and volumetrically efficient yttrium hydride moderator, both of which were manufactured and characterized under the TCR program. The TCR is a 3 MW{sub th} He-cooled experimental nuclear reactor designed to reach a total integrated burnup of less than 24 effective full-power hours to keep the radioactive source term to a very low level. TCR design process revealed a positive moderator coefficient; however, the negative doppler coefficients for the fuel and thermal expansion of fuel, moderator, and core support plate yield an overall negative reactivity coefficient. Calculated fuel element temperatures and stresses are well within safety margins. The maximum hypothetical accident (i.e., de-pressurized loss of forced cooling) yields only a modest increase in reactor temperatures that are all within safety margins. This paper summarizes the high-level TCR design characteristics, which were derived from neutronics, thermohydraulics, thermomechanics, and safety analyses.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
New Directions for Thermoelectrics: A Roadmap from High‐Throughput Materials Discovery to Advanced Device Manufacturing
Thermoelectric materials, which can convert waste heat into electricity or act as solid‐state Peltier coolers, are emerging as key technologies to address global energy shortages and environmental sustainability. However, discovering materials with high thermoelectric conversion efficiency is a complex and slow process. The emerging field of high‐throughput material discovery demonstrates its potential to accelerate the development of new thermoelectric materials combining high efficiency and low cost. The synergistic integration of high‐throughput material processing and characterization techniques with machine learning algorithms can form an efficient closed‐loop process to generate and analyze broad datasets to discover new thermoelectric materials with unprecedented performances. Meanwhile, the recent development of advanced manufacturing methods provides exciting opportunities to realize scalable, low‐cost, and energy‐efficient fabrication of thermoelectric devices. This review provides an overview of recent advances in discovering thermoelectric materials using high‐throughput methods, including processing, characterization, and screening. Advanced manufacturing methods of thermoelectric devices are also introduced to realize the broad impacts of thermoelectric materials in power generation and solid‐state cooling. In the end, this article also discusses the future research prospects and directions.
Song, Kaidong↗
High volume packing fraction TRISO-based fuel in light water reactors
We report that for a decade, fully ceramic microencapsulated (FCM) fuel, containing tri-structural isotropic (TRISO) fuel particles in a silicon carbide (SiC) matrix, has been investigated as an accident-tolerant fuel for light water reactors (LWRs). Other examples exist of TRISO-based concepts for LWR fuels with different matrix materials. Previous studies assumed TRISO particle volume packing of approximately 0.44 in SiC (or another) matrix, the highest realistic packing fractions possible with conventional manufacturing. Recent advances in advanced manufacturing have yielded the development and demonstration of a fuel form that consists of conventionally manufactured TRISO particles in a 3D-printed SiC matrix with significantly higher possible TRISO packing fractions (0.5–0.7). This increased uranium loading enhances the viability of using TRISO-based particle fuel forms in LWRs. The viability of high-packing-fraction TRISO-based particle fuel forms in LWRs is assessed from the perspective of fuel cycle length, achievable fuel burnup, reactivity coefficients, and fuel cycle performance. Higher-packing-fraction TRISO-based fuel enables either longer cycle lengths (by ~25% at a packing fraction of 0.55 relative to 0.44) at a constant enrichment or decreased enrichments (by ~25% at a packing fraction of 0.55 relative to 0.44) at a constant cycle length. Studies of different fuel kernel types (uranium nitride, uranium oxycarbide, and uranium carbide) yield similar results, although the cycle length of uranium oxycarbide is shorter than for uranium nitride or uranium carbide (due to the lower density of uranium oxide). This work also characterized the production of 14 C resulting from neutron absorption in 14 N during operation for uranium mononitride fuel kernels; the ratio of 14 C/N was 1–2 at. % at discharge. For the fuel cycle evaluation, the activity of spent nuclear fuel and high-level waste at 100 and 100,000 years was lower for high-packing-fraction fuels than for conventional LWR fuel. Environmental impact metrics were similar overall, but higher on the front end of the fuel cycle and lower on the back end of the fuel cycle. Reactivity coefficients of higher-packing-fraction TRISO-based fuel were reasonable compared with those of conventional fuels.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Advanced Energy Manufacturing and Recycling Grant Readiness Technical Assistance Program [Slides]
The U.S. Department of Energy's Office of Manufacturing and Energy Supply Chains (MESC) has launched a new technical assistance program, administered by NREL, in support of prospective applicants to the Advanced Energy Manufacturing and Recycling Grant Program. The competitive technical assistance program will help small- and medium-sized manufacturers understand the requirements of the Advanced Energy Manufacturing and Recycling Grant Program and prepare for future applications. Such applications must propose a project to build, retrofit, or expand facilities in coal communities for producing or recycling goods used to support clean energy supply chains. This presentation is for an informational webinar on Wednesday, April 26, 2023.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
The Manufacture of Advanced Key Energy Infrastructure Technologies (MAKE IT) Prize (Final Technical Report)
This is a final technical report for the American-Made Manufacture of Advanced Key Energy Infrastructure Technologies (MAKE IT) Prize, developed by the U.S. Department of Energy (DOE) Office of Technology Commercialization (OTC) in collaboration with the Office of Clean Energy Demonstrations (OCED) and the Office of Energy Efficiency and Renewable Energy (EERE) with support from the National Laboratory of the Rockies (NLR). The MAKE IT Prize aims to catalyze domestic manufacturing of critical energy technology components, moving manufacturing facilities from planning to shovel-ready and enabling strategies for vibrant manufacturing activities in communities. This prize was launched with a prize pool of approximately $30 million spread across two tracks: Facilities and Strategies.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Targeted Adaptive Design
Modern advanced manufacturing and advanced materials design often require searches of relatively high-dimensional process control parameter spaces for settings that result in optimal structure, property, and performance parameters. The mapping from the former to the latter must be determined from noisy experiments or from expensive simulations. Here, we abstract this problem to a mathematical framework in which an unknown function from a control space to a design space must be ascertained by means of expensive noisy measurements, which locate control settings generating desired design features within specified tolerances, with quantified uncertainty. We describe targeted adaptive design (TAD), a new algorithm that performs this sampling task efficiently. TAD creates a Gaussian process surrogate model of the unknown mapping at each iterative stage, proposing a new batch of control settings to sample experimentally and optimizing the updated expected log-predictive probability density of the target design. TAD either stops upon locating a solution with uncertainties that fit inside the tolerance box or uses a measure of expected future information to determine that the search space has been exhausted with no solution. TAD thus embodies the exploration-exploitation tension in a manner that recalls, but is essentially different from, Bayesian optimization and optimal experimental design.
97 MATHEMATICS AND COMPUTING↗
Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss
Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.
Howland, Sylvia↗
Unveiling 3D Morphology of Multiscale Micro-Nanosilver Sintering for Advanced Electronics Manufacturing by Ptychographic X-ray Nanotomography
The sintering processing–structure–property relationship of a multiscale silver materials is investigated: microparticles with nanofeatures, particularly on their three-dimensional (3D) morphology. The target application is to replace conventional lead-based solders in advanced electronic manufacturing. Unlike lead-based solders, silver powders are suited to satisfy increasingly demanding mechanical, electrical, and thermal requirements, meanwhile being free of health effect. Sintering the material at a low temperature and without applied pressure are desirable conditions, which results in a preferred use of silver nanoparticles, as nanofeatures have higher driving force to sinter with the decrease in particle size. However, nanosized powders present potential health/environmental effects. To address the trade-off between the benefits and shortcomings of nano-versus microparticles, this work studies a novel multiscale silver paste, namely micron-sized powders with nanosized features. To get quantitative 3D visualization of micro- and nanoscale features, ptychographic X-ray computed nanotomography is applied. The correlations between conditions (thermal aging, pressure, and substrate metallization), mechanical properties, and morphological parameters are established. Finally, using novel 3D X-ray nanoimaging technique, it is demonstrated that one can design multiscale materials while balancing complex demands required in advanced electronics manufacturing and research directions in materials design and characterization.
36 MATERIALS SCIENCE↗
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↗
Development of Bismuth and Platinum Bi-Metallic Nanoparticles to Enhance Melt Wire Temperature Resolution
Advanced manufacturing (AM) based on direct-write (DW) technologies has emerged as the predominant enabler for the fabrication of active and passive sensors to be deployed in harsh operating environments seen in a nuclear reactor. Recently, Idaho National Laboratory and Boise State University have recently established capabilities to incorporate advanced manufacturing (AM) methods to accelerate, modernize and enhance functionality of nuclear sensors and instrumentation to achieve the goal of enhancing the safety and efficiency of nuclear reactors. A significant thrust of this work includes the development of nuclear relevant feedstock materials compatible with a variety of direct-write processes for the development, fabrication and testing of AM sensors for peak temperature detection and neutron flux monitoring. For this report, bismuth and bismuth/platinum (BiPt) bi-metallic nanoparticles were synthesized using wet chemical approaches to develop bi-metallic feedstock materials to enhance the sensitivity of melt wires for peak temperature detection. Nanoparticle characterization was performed with Transmission Electron Microscopy (TEM) for nanoparticle composition and size, Transmission X-Ray Diffraction Fluorescence (TXRF) for nanoparticle composition, and Differential Scanning Calorimetry to elucidate the melting point of BiPt bi-metallic nanoparticles. Preliminary results indicate bi-metallic BiPt nanoparticles as a viable pathway for fabricating high resolution AM melt wires.
36 MATERIALS SCIENCE↗
Materials Characterization, Prediction, and Control Project: Characterization of 316L Stainless Steel after Solid Phase Processing using Ultrasonic NDE Method
The Pacific Northwest National Laboratory undertook the Materials Characterization, Prediction, and Control Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). A motivation of the Materials Characterization, Prediction, and Control Project was to demonstrate ultrasonic testing as a nondestructive evaluation method to complement traditional destructive methods for characterizing material microstructure with emphasis on grain size determination using a method that may have future applications for real-time inline process monitoring. The objective of the work described in this report is to establish the process and an analysis method for measuring grain sizes of polycrystalline metals with ultrafine grains using ultrasonic shear wave backscattering, building on prior studies on coarser-grained material. The work involves five tasks: Measured ultrasonic backscattering experimentally for a series of 316L stainless steel specimens with various grain sizes made by friction stir processing. Calculated ultrasonic backscattering coefficients from experimental data based on a physical measurement model. Measured ground truth grain sizes of the specimens from electron backscatter diffraction grain boundary images using a generalization of the ASTM E112 (ASTM 2021) intercept method. Built a curve of ultrasonic backscattering coefficients versus the ground truth intercept-based grain sizes to determine the correlation between mean grain sizes and ultrasonic measurements. Demonstrated the ability of using the correlation curve to deduce grain sizes with measured ultrasonic backscattering coefficients for a few 316L stainless steel specimens whose grain sizes were unknown beforehand but were targeted to be an extrapolation to larger grain sizes than used to formulate the correlation curves. Experimental procedures and computational algorithms are developed and validated for these tasks. This work establishes an ultrasonic technique for characterizing material microstructure with ultrafine grains that are often resulted by solid-phase processing. The technique is nondestructive, and it has the potential to be used for real time inline process monitoring. This work successfully demonstrates the viability of an ultrasonic nondestructive evaluation method for microstructural characterization of material having ultrafine grain structure (as small as 1?mm) and produced by an advanced manufacturing method. This includes a demonstration of the method to extrapolate to other conditions. While not demonstrated here, the method is expected to be viable for in-line, or near-inline, process monitoring in advanced manufacturing applications with suitable consideration for access of instrumentation to the material being manufactured.
316 L Stainless Steel↗
Advanced electrode manufacturing to enable low cost PEM electrolysis
A critical challenge for the implementation of proton exchange membrane (PEM)-based water electrolyzers for the H2@Scale vision is the capital cost, which is largely driven by related factors of overdesign and highly manual legacy manufacturing methods. Typical electrolyzer cells have an order of magnitude higher membrane thickness and catalyst loading vs. fuel cells, in part because the manufacturing methods being used are not capable of producing uniform and reliable electrodes on thin membranes with low loading. Advanced electrode manufacturing is therefore the key enabler to reduce the cost of the electrolyzer stack, particularly roll-to-roll (R2R) manufacturing of catalyst coated layers (CCLs) and catalyst coated membranes (CCMs). The electrolyzer manufacturing process still relies on traditional sheet-to-sheet (S2S) processes, which requires intensive labor to make parts to meet the specification requirements. This project leverages fuel cell expertise (GM) with Proton’s knowledge of electrolyzer components to develop the electrocatalyst ink formulations and coating processes using slot die (ORNL) and gravure (NREL) coatings, with proof of concept at the pilot-scale (Kodak).
08 HYDROGEN↗
The Elevated-Temperature Cyclic Properties of Powder Metallurgy-Hot Isostatic Pressed 316H and 316L Stainless Steel
Section III, Division 5 of the American Society of Mechanical Engineers Boiler and Pressure Vessel Code covers construction rules for elevated-temperature nuclear components. Microreactor developers have expressed a need for advanced manufacturing processes to fabricate microreactor components to reduce manufacturing costs. Components fabricated using manufacturing processes other than conventional techniques are not currently qualified in Section III, Division 5. An expeditious approach to qualifying an advanced manufacturing process for alloys whose wrought-product form is already qualified in Division 5 is to demonstrate the resultant properties from the advanced manufacturing process are equivalent or superior to the wrought-product form. Powder metallurgy-hot isostatic pressing (PM-HIP) is a mature technology that offers many advantages that are attractive to the microreactor industry. Preliminary data show that the elevated-temperature creep-fatigue properties of PM-HIP 316H stainless steel (SS) are reduced compared to the Wrought 316H SS, which is qualified in Section III, Division 5. Work is ongoing to identify the mechanisms responsible for the reduced creep-fatigue properties and to establish acceptance criteria to confirm the adequacy of the component for service.
316H stainless steel↗
Advancing Battery Manufacturing: Synchrotron Characterization for Industry
Large-scale battery manufacturing requires understanding the fundamental principles of materials and interfaces and relies on advanced techniques for detailed interrogation. Despite advancements in the industrial scale production and their associated quality control tools, challenges such as electrode heterogeneity, internal defects, and largescale material waste (e.g., scrap) can hamper manufacturing. Synchrotron X-ray characterization techniques offer spatial, temporal, and chemical resolution that can provide diagnostic insights for metrology across various manufacturing steps. This review examines the use of synchrotron tools to advance understanding of key steps in the battery manufacturing process. Recent examples demonstrate how synchrotron methods resolve manufacturing challenges and uncover degradation pathways that are otherwise inaccessible. Future directions for advancing battery manufacturing emphasize collaboration between academia and industry through the use of synchrotron X-ray techniques.
Batteries↗
NNSA Minority Serving Institute Partnership Program (MSIPP)— Advanced Synergistic Program for Indigenous Research in Engineering (ASPIRE) (FY22 Q1 Progress Report)
In 2016, the National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) targeting Tribal Colleges and Universities (TCUs) to offer programs that will prepare students for technical careers in NNSA’s laboratories and production plants. The MSIPP consortium’s approach is as follows: 1) align investments at the college and university level to develop a curriculum and workforce needed to support NNSA’s nuclear weapon enterprise mission, and 2) to enhance research and education at under-represented colleges and universities. The first TCU consortium that MSIPP launched was known as the Advanced Manufacturing Network Initiative (AMNI) whose purpose was to develop additive manufacturing (AM) learning opportunities. The AMNI consortium consisted of Bay Mills Community College, Cankdeska Cikana Community College, Navajo Tech University, Salish Kootenai Community College, Turtle Mountain Community College, and United Tribes Technical College. In 2016, the American Indian Higher Education Consortium (AIHEC), the AMNI consortium and the Southwestern Indian Polytechnic Institute (SIPI), in collaboration with Sandia National Labs, using a grant by NNSA hosted the first TCU Advanced Manufacturing Technology Summer Institute (TCU AMTSI). The AMNI consortium will officially end Sept. 2022. However, building on the successes of AMNI, in FY22 NNSA’s MSIPP launched three additional consortiums: (1) the Indigenous Mutual Partnership to Advanced Cybersecurity Technology (IMPACT), which focuses on STEM and cybersecurity, (2) the Advanced Synergistic Program for Indigenous Research in Engineering (ASPIRE), which focuses on STEM and the electrical and mechanical engineering skills set needed for renewable and distributed energy systems, and (3) the Partnership for Advanced Manufacturing Education and Research (PAMER), which focuses on developing and maintaining a sustainable pathway for a highly trained, next-generation additive manufacturing workforce and a corresponding community of subject matter experts for NNSA enterprises. The following report summarizes the status update during this quarter for the ASPIRE program.
42 ENGINEERING↗