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At least 217 records · Page 12

Summary of SRNL Support Activities to the DOE-ORP Enhanced Waste Glass Program for Fiscal Year 2024

In fiscal year 2024 (FY24) Savannah River National Laboratory (SRNL) continued tasked work for the Office of River Protection (ORP) to expand glass compositional regions accessible for low-activity waste (LAW) and high-activity waste (HLW) vitrification processing. Experimental work continued in four primary technical areas focused on processing and performance of glasses relevant to the Hanford missions. The data and results from this work will be used to expand and validate the glass models being developed at Pacific Northwest National Laboratory (PNNL) for waste processing and acceptance. This report summarizes the activities and deliverables associated with work performed in FY24.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Workshop on Improving Holdup Monitoring in the US

The characterization and quantification of nuclear deposits, or residual nuclear material retained in process equipment, generally referred to as holdup, continues to challenge nuclear processing facilities in DOE program areas such as nuclear criticality safety, material control and accountability, environmental management. The efficiency and effectiveness of nuclear operations in these facilities depends heavily on the results from nondestructive techniques designed to measure nuclear materials in situ. The traditional methods used to measure holdup were established more than 30 years ago and assume unrealistic conditions for most measurement cases. These blind, in situ measurements present unique challenges due to the following attributes: unique, non-ideal geometries; unknown deposit thicknesses; lack of representative calibration standards; large number of holdup deposit locations; and poor accessibility for many measurement locations. These difficulties and the poor assumptions made to handle them have resulted in measurement uncertainties that are often too large for many programs to effectively utilize. In an effort to address and identify solutions to the current holdup challenges facing the US nuclear industry, Oak Ridge National Laboratory hosted the Technical Workshop on Improving Holdup Monitoring in the US. The two-day workshop held August 21–22, 2019, was attended by 35 holdup measurement practitioners, program managers, stakeholders from US Department of Energy sites, the Nuclear Regulatory Commission, and representatives from commercial industry. The primary objectives were to identify critical elements of a successful and defensible holdup measurement program; identify technical challenges, needs, and potential improvements associated with measurement of holdup; and share best practices and lessons learned from recent accumulation events. Fourteen presentations were delivered on holdup topics including necessary elements for effective program management, measurement needs, emerging technologies and other measurement solutions, and lessons learned from recent events. These presentations highlighted best practices related to accumulation monitoring, considerations and proactive steps to facilitate holdup in new facility designs, imaging solutions to improve holdup assumptions, and new software developed in support of holdup measurements. Breakout sessions were also employed to determine additional needs and identify potential solutions to common holdup challenges. The primary discussions focused on causes and prevention of material accumulations, needs for uranium and plutonium measurements, and reduction of measurement uncertainty, all of which were explicitly identified as critical needs during the 2018 Workshop on Technical and Programmatic Needs for a Sustainable NDA Program for the US DOE.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Engineered $\mathrm{Ru}$ on $\mathrm{HY}$ zeolite catalyst for continuous and selective hydrodeoxygenation of lignin phenolics to cycloalkanes under moderate conditions

Here we report a continuous selective hydrodeoxygenation (HDO) process of guaiacol conversion to cycloalkanes under 180 °C/1 MPa, which results in improved HDO chemistry for lignin-based jet fuel production. The incipient wetness impregnation method was modified to prepare an HY zeolite-supported Ru catalyst with better metal dispersion and acid site uniformity, which overcomes the low conversion and selectivity of previous literature. The modified catalyst (Ru-HY-60-MI) was tested in a continuous fixed bed reactor, resulting in increased HDO conversion of guaiacol to cycloalkanes compared to the unmodified catalyst. Pressure, temperature, and weight hourly space velocity-dependent tests validate guaiacol HDO over Ru-HY-60-MI catalyzed ring hydrogenation of guaiacol to 2-methoxycyclohexanol, acid-catalyzed demethoxylation and dehydration to cyclohexene, and further hydrogenation of cyclohexene to cyclohexane. These experiments enable exploring a continuous HDO process, demonstrate effectiveness for other ß-ß and a-O-4 lignin representatives and real lignin bio-oil, and pave the way towards commercialization of lignin-based jet fuel

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FY2021 Status Report on the Computing Systems for the Yucca Mountain Project TSPA-LA Models and Testing of Selected Process Models

Sandia National Laboratories continued evaluation of the total system performance assessment (TSPA) for License Application (LA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. The FY21 task included continued operation of the cluster; maintenance of the TSPA-LA models (with GoldSim 9.60.300); continued assessment of the status of the Infiltration Model; (a process model that feeds the TSP -LA) and preliminary assessments of the Unsaturated Zone Flow Model and the Saturated Zone Flow and Transport Model Abstraction (process models that feed the TSPA-LA). The 2014 cluster and supporting software systems are currently fully operational to support TSPA-LA type analyses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Optimization of screw design for continuous wet granulation: A case study of metoprolol succinate ER tablets

This study aimed at understanding the effect of screw design on the critical characteristics of granules and tablets of an extended-release (ER) formulation for twin screw granulation process. The screw design parameters assessed included number of kneading elements (KEs) per kneading zone, distance separating kneading zones, staggering angle (SA) of kneading elements and number of sizing elements (SEs). These input variables were varied using a design of experiment (DoE) approach to manufacture granules. Particle size distribution (PSD), flow and bulk properties of the granules, breaking strength and dissolution of tablets manufactured using these granules were characterized. The results of least square fitting showed that KEs, SA, and SEs of the screws significantly (p -values < 0.05) affected the PSD, cohesion, compressibility (CPS), conditioned bulk density (CBD) and permeability of the granules. The KEs and SEs significantly (p -value < 0.05) affected the dissolution, which was attributed to their effects on CPS and CBD of the granules. The distance between kneading zones had no significant effect on granules and tablet characteristics. Finally, these results may be used to further study the interaction of the identified critical screw design parameters with other processing parameters for continuous manufacturing of this ER matrix-based tablet formulation.

60 APPLIED LIFE SCIENCES↗

Circular Reprocessing of Thermoset Polyurethane Foams

Thermoset polyurethane (PU) foams are widely used in industrial applications, but they cannot be recycled by conventional melt reprocessing because of their cross-linked structures. The introduction of carbamate exchange catalysts converts thermoset PU into covalent adaptable networks (CANs), which are amenable to reprocessing at elevated temperatures. However, this approach has produced solid PU films, which have fewer uses and lower commercial demand. In this work, simultaneous reprocessing and refoaming of thermoset PU foams is demonstrated by leveraging the melt-processability of PU CANs and allowing cell growth by gas generation in a twin-screw extruder. The optimal operating temperature of the refoaming process is determined through chemical, thermal, and structural analysis of PU foam extrudates. The foam-to-foam extrusion process produces controllable, continuous, and uniform foam structures, as characterized by cell diameter and cell number density. Low-density PU foams are obtained through a process simulating injection molding. The compression properties of reprocessed PU foam are compared with as-synthesized PU foam to demonstrate efficacy of the refoaming processes. These results demonstrate that PU foams can be prepared through recycling while maintaining microstructural and chemical integrity. In the future, this strategy may be applied to thermoset PU foams of various chemical compositions and shows promise for scalability.

36 MATERIALS SCIENCE↗

Quantum advantage for differential equation analysis

Quantum algorithms for differential equation solving, data processing, and machine learning potentially offer an exponential speedup over all known classical algorithms. However, there also exist obstacles to obtaining this potential speedup in useful problem instances. The essential obstacle for quantum differential equation solving is that outputting useful information may require difficult postprocessing, and the essential obstacle for quantum data processing and machine learning is that inputting the data is a difficult task just by itself. In this study, we demonstrate that, when combined, these difficulties solve one another. We show how the output of quantum differential equation solving can serve as the input for quantum data processing and machine learning, allowing dynamical analysis in terms of principal components, power spectra, and wavelet decompositions. To illustrate this, we consider continuous-time Markov processes on epidemiological and social networks. These quantum algorithms provide an exponential advantage over existing classical Monte Carlo methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Variational Optical Phase Learning on a Continuous-Variable Quantum Compiler

Quantum process learning is a fundamental primitive that draws inspiration from machine learning with the goal of better studying the dynamics of quantum systems. One approach to quantum process learning is quantum compilation, whereby an analog quantum operation is digitized by compiling it into a series of basic gates. While there has been significant focus on quantum compiling for discrete-variable systems, the continuous-variable (CV) framework has received comparatively less attention. We present an experimental implementation of a CV quantum compiler that uses two-mode squeezed light to learn a Gaussian unitary operation. We demonstrate the compiler by learning a parameterized linear phase unitary through the use of target and control phase unitaries to demonstrate a factor of 5.4 increase in the precision of the phase estimation and a 3.6-fold acceleration in the time-to-solution metric when leveraging quantum resources. We further show how our approach can be extended to higher-dimensional compilation tasks. Our results are enabled by the tunable control of our cost landscape via variable squeezing, thus providing a critical framework to simultaneously increase precision and reduce time-to-solution.

97 MATHEMATICS AND COMPUTING↗

Characteristics of oxide-dispersion strengthened alloys produced by high-temperature severe deformation

This study is to explore an economically attractive and technically feasible processing method for oxide-nanoparticle strengthened alloys for fusion reactor application. Despite many scientific merits of the advanced oxide-dispersion strengthened (ODS) alloys, such as the nanostructured ferritic alloy (NFA) 14YWT, the only viable production path for a high-quality NFA is the high-power mechanical alloying process. This process is often a multi-day high-speed ball milling of alloy powder with a small quantity of yttria (Y 2 O 3 ) powder, followed by the milled-powder consolidation using extrusion or other methods and additional thermomechanical processing (TMP) for property control. This complex production path, including the low-temperature mechanical alloying in particular, has limited technical advancement toward the cost-effective and scale-up production of ODS alloy components. To overcome such a practical limitation, we proposed to explore alternative low-cost processing routes using traditional thermomechanical processing (TMP) method only. Further, a series of continuous TMP cycles, which were designed to impose high-temperature severe plastic deformation (HT-SPD) conditions to the consolidated powder mixtures, were applied to achieve the effective distribution of oxide particles in nanograin structure and thus desirable mechanical properties. Since the reduced-activation ferritic-martensitic (RAFM) alloy powders (Fe-10Cr and Fe-14Cr alloys with various Y contents) are available in our inventory, we focused to utilize the new solid-state synthesis approach for controlling oxide (oxygen source) dissolution and nanoscale clustering in nanograin structure in those alloys. A combination of powder consolidation at 900 °C and continuous thermomechanical activation at 600 °C yielded two essential ODS alloy microstructure contents–nanograin structure and nanoparticle distribution–and thus demonstrated a good combination of strength and ductility.

36 MATERIALS SCIENCE↗

Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization

Herein this article presents a new type of hybrid model for Bayesian optimization (BO) adept at managing mixed variables, encompassing both quantitative (continuous and integer) and qualitative (categorical) types. Our proposed new hybrid models (named hybridM) merge the Monte Carlo Tree Search structure (MCTS) for categorical variables with Gaussian Processes (GP) for continuous ones. hybridM leverages the upper confidence bound tree search (UCTS) for MCTS strategy, showcasing the tree architecture’s integration into Bayesian optimization. Our innovations, including dynamic online kernel selection in the surrogate modeling phase and a unique UCTS search strategy, position our hybrid models as an advancement in mixed-variable surrogate models. Numerical experiments underscore the superiority of hybrid models, highlighting their potential in Bayesian optimization.

97 MATHEMATICS AND COMPUTING↗

Enhanced, continuous, liquid-liquid extraction and in-situ separation of volatile fatty acids from fermentation broth

In 2018 alone, the US landfilled 35.3 million tons of food waste, about 24% of the total landfilled mass. In addition to the negative impacts landfills have demonstrated on the environment and human health, some states have begun to outlaw or dissuade the disposal of food waste and sewage sludge into landfills altogether. An urgent need has thus been created for the development of digestion processes like anaerobic digestion (AD) and arrested methanogenesis (AM) to convert food waste into valuable chemical products. Unfortunately, the buildup of volatile fatty acids (VFAs) during these processes eventually halts the reaction, and energy efficient methodologies for VFA removal are critical for the operation of fermenters. Additionally, VFAs themselves can serve as valuable chemical precursors, and recently AD processes have been modified to increase VFA production during fermentation. However, even with significant research over the past three decades, the separation of VFAs from the fermenter broth has remained expensive. Moreover, the separation of these VFAs from the fermenter broth may cost up to 50% of the entire process budget, hindering the widespread commercial adoption of AD and AM. Here we present a novel liquid-liquid extraction process termed CLEANS (Continuous Liquid-liquid Extraction And iN-situ Separation) as a highly efficient method for continuously separating VFAs from a real fermentation broth solely under gravity. Our optimized process (using an aqueous broth feed pH of 2.5, tri-noctylamine as an extractant, and a 10:1 ratio of aqueous broth to organic extractant), achieved a VFA distribution constant K D = 44.5 ± 7.9, a single-pass recovery = 81.3 ± 2.5%, and an extraction factor = 8.1 ± 0.3. These KD values are over an order of magnitude higher than what has been previously reported for comparable processes. A high aqueous-to-organic flowrate ratio, enabled for the first time by CLEANS, was found to be particularly crucial for achieving optimal extraction. Our separation process demonstrates excellent reproducibility and potential for scalability. The economic and environmental implications of this work are briefly discussed.

42 ENGINEERING↗

Analysis and Recommendation of Tritium Gas Continuous Air Monitor Alarm Setpoints for the RPL Stack Exhaust

The Radiochemical Processing Laboratory (RPL) tritium continuous air monitor (CAM) is used for near real-time detection of tritium gas (i.e., elemental tritium [HT] and tritiated water vapor [HTO]) in the stack exhaust. The CAM interfaces with software developed by the Pacific Northwest National Laboratory (PNNL)—called the “PNNL OS3700 Tritium Monitoring Software”—that provides near real-time estimates of tritium gas air concentrations and integrated daily activities that are calculated from measured CAM counts. The OS3700 software implements alarm setpoints to alert the facility of larger tritium gas releases that if allowed to persist, could begin to challenge permitted emission and established dose constraints. This report performs a detailed review of historical and current tritium alarm setpoints used at RPL, including discussion of the technical basis used in their development, analysis of alarm frequencies using measured historical data, and performs a detailed dose assessment using more realistic release scenarios and meteorology. Based on the results, the tritium air concentration and integrated daily tritium activity alarm setpoints will remain 2.0 × 10 -5 µCi/ml and 25 Ci/day, respectively. These setpoints achieve the right operational balance in identifying larger releases from planned tritium work at RPL, without being overly conservative so as to cause nuisance alarming. Furthermore, implied doses associated with these setpoints are well below defined and regulatory limits.

325RPL↗

Gradient process parameter optimization in additive friction stir deposition of aluminum alloys

As one of the most novel additive manufacturing methods, currently selection and optimization of processing parameters in additive friction stir deposition (AFSD) have mainly relied on experiments and subsequent characterization of microstructural and mechanical properties. Such approaches are both time- and resource-consuming. Therefore, an ultrasound elastography enhanced gradient process parameter optimization method was applied in the present work to obtain a window of optimized processing parameters for AFSD processing of aluminum alloy by varying both rotational and linear deposition speeds. Further, the quality of AFSD processed layer was investigated for physical nature of surface, dynamic elastic modulus, and microstructural aspects in cross-sections of the deposited layer. The efficiency in exploring process parameters was significantly enhanced by implementing a high-throughput screening experimental design based on application of gradient process parameters and continuous ultrasound elastographs. In addition, the applied ultrasonic elastography technique assisted in evaluating the homogeneity in microstructure and mechanical properties of AFSD sample over the entire gradients of the process parameters. The techniques adopted in current work can be further extended to identify suitable parameters for AFSD fabrication of components with desired mechanical properties such as hardness, fatigue, etc.

36 MATERIALS SCIENCE↗

Continuous multimodal technologies in industrial microbiology: potential for achieving high process performance and agility

The field of industrial microbiology has great potential to tackle the most pressing challenges facing society, but today, this entails much more than classical fermentation technology followed by product upgrading. Methods are needed to confer unit-operation-level functionality and whole-system-level robustness, as well as flexibility. As examples of this concept, we focus here on methodologies often deployed at industrial scale as discrete processes—such as biological, chemical, and electrochemical unit operations—that are also capable of substantial complementarity when combined sequentially and operated continuously. A key and relatively new type of conversion step is made possible by catalyst immobilization methods at both the enzymatic and cellular level. Cases drawn from electro-fermentation for acetoin production and syngas-mediated microbial electrosynthesis of ethanol exemplify the synergy of combined operational approaches. Because modular processes can be treated as a series of reactor elements, considerable flexibility is possible. As discussed, however, not all processes are amenable to this intensification.

09 BIOMASS FUELS↗

A simultaneous depolymerization and hydrodeoxygenation process to produce lignin-based jet fuel in continuous flow reactor

Economical production of lignin-based jet fuel (LJF) can improve the sustainability of sustainable aviation fuels (SAFs) as well as can reduce the overall greenhouse gas emissions. However, the challenge lies in converting technical lignin polymer from biorefinery directly to jet fuel in a continuous operation. In this work, we demonstrate a simultaneous depolymerization and hydrodeoxygenation (SDHDO) process to produce lignin-based jet fuel from the alkali corn stover lignin (ACSL) using engineered Ru-HY-60-MI catalyst in a continuous flow reactor at first time. The maximum carbon yield of LJF of 17.9wt% was obtained, and it comprised of 60.2wt% monocycloalkanes, and 21.6wt% polycycloalkanes. Catalyst characterization of Ru-HY-60-MI suggested there was no significant change in HY zeolite structure and its crystallinity after catalyst engineering. Catalyst characterizations performed post the SDHDO experiments indicate presence of carbon and K content in the catalyst. K content presence in the spent catalyst was due to K + ion was exchanged between lignin solution and HY-60 while carbon presence validated the SDHDO chemistry on the catalyst surface. Tier a fuel property testing indicates that LJF production using SDHDO chemistry can offer SAF with high compatibility, good sealing properties, low emissions, and high energy density for aircraft.

09 BIOMASS FUELS↗

Reinforcement learning for real-time process control in high-temperature superconductor manufacturing

With high efficiency and low energy loss, high-temperature superconductors (HTS) have demonstrated their profound applications in various fields, such as medical imaging, transportation, accelerators, microwave devices, and power systems. The high-field applications of HTS tapes have raised the demand for producing cost-effective tapes with long lengths in superconductor manufacturing. However, achieving the uniform and enhanced performance of a long HTS tape is challenging due to the unstable growth conditions in the manufacturing process. Although it is confirmed that the process parameters during the advanced metal organic chemical vapor deposition (A-MOCVD) process influence the uniformity of the produced HTS tapes, the high-dimensional process parameter signals and their complicated interactions make it difficult to develop an effective control policy. In this paper, we propose a local measure for the uniformity of HTS tapes to provide instant feedback for our control policy. Then, we model the manufacturing of HTS tapes as a Markov decision process (MDP) with continuous state and action spaces to assess the instant reward in real time in our feedback control model. As our MDP involves continuous and high-dimensional state and action spaces, a neural fitted Q-iteration (NFQ) algorithm is adopted to solve the MDP with artificial neural network (ANN) function approximation. The collinearity of process parameters can restrict our capability of adjusting the process parameters, which is addressed by the principal component analysis (PCA) in our method. The control policy adjusts the PCA of process parameters using the NFQ algorithm. In conclusion, based on our case studies on real A-MOCVD dataset, the obtained control policy increases the average uniformity of tapes by 5.6% and performs especially well on sample HTS tapes with a low uniformity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Development of a Technical, Economic, and Risk Assessment Tool for the Evaluation of Work Reduction Opportunities

Efficient and cost-effective operation of a nuclear power plant (NPP) is essential to ensuring long-term economical and safe operation. Multiple cost saving opportunities exist, referred to here as work reduction opportunities (WRO). These WROs reduce plant operating costs by employing various cost-effective strategies (e.g., implementation of modern technologies). Identifying and objectively screening WROs is an essential task to help reduce overall costs. However, there is no comprehensive framework for assessing WROs in the nuclear industry and evaluating their impact on plant operations. This report presents a novel framework for systematically evaluating WROs from a technical, economic, and risk perspective. As NPPs continue to add new technology and implement modernization strategies into their current processes, potential WROs are commonly identified. Although most WROs have the potential to reduce costs, not all opportunities will result in significant cost savings due to unforeseen risks, large implementation costs, or benefits that fall short of expectations. Examples of this can be the result of a technology that is not fully developed, uncertainty in the amount of cost reduction, or difficulties introducing a new process into an organization. These uncertainties can manifest several ways and can result in a WRO with limited cost savings or even a loss of investment. The framework developed emphasizes the importance of effectively screening the WROs from a holistic perspective to objectively identify inefficiencies and ensure a positive impact to the organization. This report presents the Technical, Economic, and Risk Assessment (TERA) as a key methodology for the screening and evaluation of potential WROs. The TERA framework begins with a screening phase where the process is examined through a hybrid combination of Lean Six Sigma and Integrated Operations for Nuclear (ION) guiding principles. This framework examines the current processes using the Lean Six Sigma SIPOC (Suppliers, Inputs, Process, Outputs, Consumers) methodology but retains the ION key elements of People, Technology, Process, and Governance as important factors to the nuclear decision-making process. By combining the principles of Lean Six Sigma and ION, the developed screening process is specific to the nuclear industry in that it systematically evaluates WROs in order to implement new technology that is comprehensively evaluated. The TERA begins by mapping current processes as they relate to WROs and examining the inefficiencies. Furthermore, the created process map can be used to identify and evaluate potential solutions. Using key performance indicators (KPIs), the TERA evaluates each area—technology, economics, and risk—for uncertainties and to perform cost-benefit analysis. The results of the TERA are important KPIs that allow for an evaluation of different processes and technology implementations. This assessment enables decision-makers to compare various WROs based on metrics and then make informed decisions for which opportunity to implement first. This research includes not only the creation of the TERA framework, but also the evaluation of its performance. A case study for screening potential WROs at Southern Nuclear Company is presented that utilizes the TERA methodology. Through the use of TERA, various WROs were screened, and the solutions evaluated for cost-benefit expectations. The report concludes by summarizing the overall effort and implications for utility modernization. The performance of the screening and TERA are discussed as well as the impact on the nuclear industry. The TERA process enables utilities to evaluate and inform investment decisions for WROs and mitigate any potential risks. Through this research, we provide utilities with a valuable framework to optimize operations, reduce costs, and drive continuous process improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Report on use of Inoculants in Missile Application Alloys

This report documents the status of current inoculant research relevant to missile application alloys and MTCR control language. The information is intended to provide data on current inoculants for us determining the current state of development and identifying potential research directions. Although there has been significant scientific research into the development and synthesis of inoculants, their current availability is limited is traditional powder inoculants employed during casting processes. However, research continues the development of complex oxides, ribbon materials, high entropy alloys, and other inoculant product forms, including the use of inoculants in the melt pools produced during additive manufacturing. Research to date has focused primarily on aluminum and steel alloys with emphasis on refining grain structures and evolving equiaxed morphologies while increasing strength and castability. The primary inoculants in steel and cast irons include TiN, SiC, FeSi75, and Ce which have increased strength properties. Chief inoculants for Al alloys often include TiC, SiC, Al3Sc(x) and TiB2 to aid in precipitation and refinement. Ti and Ni alloys have fewer research activities involving inoculants, although TiN, TiB, ZrN and LaB6 (for Ti alloys) and WC, Co3FeNb2, and CrFeNb (for Ni alloys) have been used. Sic, Al2O3, Mg and Ti are key inoculants for Mg alloys. Multiple cast alloys from each of the material classes demonstrated increased strength and performance properties using inoculants, with several approaching requirements applicable to missile service environments. The continued evolution of advanced manufacturing capabilities is making it easier to produce high temperature near net shape structural materials using inoculant powders. These shapes may include the geometric shapes addressed within the MTCR (tubes and limited wall thicknesses). The use of inoculants may enable further development of high temperature alloys into near net shapes traditionally produced via casting processes due to limited ductility. This may decrease material and manufacturing costs. In addition, inoculation provides controlled kinetics and achievable chemical segregation that enables potential for far-from equilibrium thermodynamic microstructures and chemistries that could provide new metastable alloy states and subsequent properties to address co-design engineering constraints, including needs for increased strength and ductility. It is recommended that specific material combinations within these alloy classes be carefully watched as the materials evolve, with controls aimed at those having material properties above current MTCR levels. This specifically includes the use of refractory inoculants in alloys, and the application of inoculants in high strength and high temperature alloys via additive manufacturing processes, with care to link capabilities to product forms similar to the current requirements on tube geometries and material feed stocks. The continued development of nanoparticle inoculants will increase strength and ductility of high strength castings and additive manufactured metallic components. For example, adding inoculants into the casting of maraging steels and other precipitation strengthened alloys may drastically elevate mechanical properties above the control limit of current regulations.

36 MATERIALS SCIENCE↗