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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 OSTI2023

Aerosol Manufacturing Technology to Produce Low-Cobalt Li-ion Battery Cathodes

Although considerable progress has been made with battery materials over the last 10 years, the cathode remains a major performance-limiting material in Li-ion battery (LIB) technology. New materials and battery chemistries will overcome some of the remaining challenges, but cathode materials must also be manufactured at a lower cost and with a smaller environmental footprint using new processes that can also enable improved control over stoichiometry, morphology, and compositional homogeneity. Cabot, Argonne National Laboratory and SAFT research teams are combining their extensive expertise in particle synthesis, battery materials and cell design to develop a low-cost, flexible aerosol manufacturing technology for production of high-performance cathode active materials (CAM). This project will develop low-Co CAMs via Reactive Spray Technology (RST) and Flame Spray Pyrolysis (FSP) to reach performance targets of < 50 mg Cobalt/Wh.

25 ENERGY STORAGE↗
DOE OSTI2021

A Comparative Study of Direct and Indirect Additive Manufacturing Approaches for the Production of a Wind Energy Component

Additive manufacturing (AM) was developed in the 1980s to create three-dimensional prototypes through layer-wise approaches to fabrication. Since then, these approaches have seen improvements in both materials and processing technologies. To date, there are now 7 types of additive manufacturing processes and hundreds of materials, which can be directly printed – going directly from digital design to fabricated components. In this project, Oak Ridge National Laboratory (ORNL), Vestas Wind Systems, and The National Renewable Energy Laboratory (NREL) collaborated to evaluate the effectiveness of state-of-the-art large-scale AM processes in the production of a structural component for use in a wind turbine nacelle, through both direct and indirect manufacturing approaches. Here, experienced AM design engineers detail techniques for AM design, including topology optimization (TO), support minimization, reverse engineering, and techniques for mitigating poor interlaminar performance. Fabrication of the components is presented, including printing parameters and postprocessing, and followed with full-scale component testing by a 3rd party testing laboratory. To evaluate the potential of the developed approaches, a complete techno-economic analysis is provided which evaluates the cost of these techniques given current and near to long-term projections of AM system capabilities.

17 WIND ENERGY↗
DOE OSTI2023

Demonstration of Scaled-Production of Rare Earth Oxides and Critical Materials from U. S. Coal-Based Sources (Final Report)

The project objective was to demonstrate scaled production of high purity rare earth oxides (REO), nominally exceeding 90% grade, from coal refuse sources using innovative technologies that reduce cost and improve environmental outcomes relative to traditional rare earth processing technologies. The project utilized a critical material pilot plant constructed and tested as part of a previous U.S. Department of Energy project. Target performance criteria was a 50% reduction in production cost based on previous optimum values, 150% increase in recovery and greater than 2% concentrates of rare earth oxides, cobalt and manganese. Concentrate production goals were to produce a rare earth mix oxide product at a rate of 200 grams per day having a minimum purity of 50% as well as products of cobalt and manganese having a minimum purity of 2%. A previous pilot plant investigation identified acid cost as the major contributor to an operating cost that made the recovery of rare earth and other critical metals from bituminous coal sources economically challenging. As such, acid cost reduction was a major target using bio-oxidation reactors to produce sulfuric acid from naturally occurring coal pyrite. Based on laboratory data, a bio-oxidation circuit was designed for the pilot plant to produce 7.5 l/min of acid using two 11-m3 (3000 gallon) reactors equipped with 40 hp aerators for air dispersion. The pilot-scale tests revealed that acid concentration equivalent to as high as 1.0 M sulfuric acid could be continuously produced. However, the bio-acid contained exceptionally high iron concentrations, which complicated downstream processing of the pregnant leach solution (PLS). A TEA of the bio-oxidation circuit showed that production cost was approximately $0.13 per kg acid equivalent if produced using a four-day retention time in the reactors. This value represents a 48% reduction from that of purchased bulk sulfuric acid. Calcination (or roasting) studies were conducted on coarse refuse from West Kentucky No. 13 and Fire Clay coal seam sources. The test results revealed the potential to increase recovery by nearly 100% using temperatures between 500°C to 700°C with light REE recovery value being the most improved. Acid baking of the calcined products using sulfuric acid at 250°C increased heavy rare earth recovery from around 40% to 80% while decreasing the acid requirements by over 50%. The existing pilot plant was upgraded for the pilot scale demonstration of REE and CM recovery. The primary feedstocks were West Kentucky No.13 and heap leach pregnant leach solution (PLS) while a secondary feedstock was a lignite waste material from a construction sand operation. The pilot scale operation started with PLS generation through leaching followed by iron and aluminum removal, nominally at 3.3 and 4.5 pH, respectively. Leaching lixiviants used for the test were industrial grade sulfuric acid or bio-acid generated at the pilot scale facility. For most of the tests, the solid feed rate was 200 lb/hr whereas lixiviant was added at 2 gpm to provide an optimal residence time of 45 minutes. Following the contaminant removal step, several different process schematics were tested with the goal of maximizing REE recovery and purity. In the first test, direct processing of aluminum precipitation raffinate for REE recovery using oxalic acid at pH 1.5 was investigated. Overall REE recovery was approximately 45%. Unfortunately, elevated calcium content in the PLS significantly impacted the RE-Oxide product grade. Similarly, high calcium content decreased both the product purity and grades of CM products. As such, a new flowsheet was tested with the same initial process schematic but different precipitation stages for REEs and CMs at pH 6.0 and 9.0, respectively. It was noted that the overlapping precipitation behavior of Co, Ni and Zn with REEs limited the applicability of this process schematic. While this change increased the RE-Oxide grade from 36% in the first test to 87%, the loss of critical metals to the REE cake and bypass of the REEs to the CM cake significantly impacted the recovery of both REEs and CMs. Therefore, the modified process flowsheet combined oxalic acid precipitation stage raffinate and redissolved CM cake filtrate to maximize both the recovery and purity of the products. Consequently, a RE-Oxide product with 85% purity and CM cakes with over 19% Co, 38% Ni, 14% Zn and 9% Mn content were generated with significantly higher recoveries. While the modified process flowsheet improved recoveries and grades, elemental losses observed in separate precipitation and redissolution losses inspired the adaptation of a single precipitation stage at pH 9.0 for both REEs and CMs. This change was anticipated to maximize the REE recovery while minimizing the costs associated with separated redissolution and processing stages. As expected, REE recovery in this new circuit arrangement was over 56% with a product grade of over 87% RE-Oxide content. Similarly, Co, Ni, Mn, and Zn recoveries of 54%, 40%, 67%, and 66%, respectively, were achieved. Unfortunately, the elevated calcium content present in the solution due to its precipitation at pH 9.0 caused a decrease in the CM cake quality. Therefore, the final process flowsheet involved the addition of calcium oxalate precipitation following the oxalic acid precipitation stage, which effectively eliminated calcium contamination of the CM products. Finally, the pilot scale experiments conducted using bio-acid achieved comparable REE leaching recoveries to the conventional sulfuric acid leaching. Elevated iron concentration in the solution caused the co-precipitation of REEs with the iron and aluminum cake, resulting in the REE losses. Furthermore, elevated iron content bypassing the iron and aluminum precipitation stages contaminated the metal sulfide and manganese cake, respectively. A techno-economic analysis was performed based on a commercial facility capable of treating 500 tph of coal-based material. The production cost for West Kentucky No. 13 coarse refuse material ranged from approximately $500-$700/kg of total rare earth oxide whereas the lignite source had significantly lower production cost of $100-$300/kg. The significant difference in cost was due to the easier leaching characteristics of the lignite material and the higher feed concentrations. All process scenarios resulted in a negative net present value (NPV). For the lignite feedstock, laboratory REE leach recovery values were about 30% higher than the pilot plant data. Using the lab leach results, a positive net present value was achieved and the production cost decreased from $100-$300 $/kg to less than $150/kg of total REO.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Thermodynamics of Bimetallic Joints between Titanium and Tantalum Produced by Laser Powder Bed Fusion

Laser powder bed fusion (LBPF) is currently the most mature metal additive manufacturing (AM) technology. While it does not have the same flexibility as directed energy deposition techniques to produce compositional gradients, LPBF can still be used to generate bimetallic parts by depositing one metal on a build plate made of another. Here, in this study, we print combinations of Ti-6Al-4V with Ta and characterize defects that occur at the interface. We use thermodynamic modeling to explain the formation of keyhole porosity and solidification cracks when Ta is built on a Ti baseplate, and the lack of defects when the materials are reversed. By understanding the mechanisms that lead to defect formation, the methodology demonstrated here can be applied to other material systems to efficiently design bimetallic LPBF processes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Improving Elemental Mercury Recovery in DWPF by pH and Ionic Strength Studies Using Laboratory Scale Replica – 26141

In order to safely disposition nuclear material at large scales, the Savannah River Site (SRS) constructed the Salt Waste Processing Facility (SWPF) for the removal of actinides, the Saltstone facility for preparation of a low-level cementitious grout, and the Defense Waste Processing Facility (DWPF) for the vitrification of high-level waste (HLW). A few years after processing began, high concentrations of mercury were discovered in cementitious waste at the Saltstone facility which initiated a search for the source of mercury during processing at these SRS facilities. Mercury serves as a catalyst in the dissolution of spent nuclear fuel, aluminum-actinide alloys, for actinide recovery, but not enough is known about the behavior and properties of mercury within these process streams.

Pina, Jeanette [Savannah River National Laboratory↗
DOE OSTI2025

Incorporating corrosion design constraints in desalination process optimization: A case study in mechanical vapor compression

Corrosion is an expensive and complex challenge for desalination, yet current design approaches do not explicitly account for corrosion mechanisms in process modeling and technoeconomic analysis. Here, to address this gap, we present a workflow for incorporating corrosion design constraints directly into desalination process optimization models. We develop surrogate models for general and localized corrosion metrics as functions of temperature, pH, salinity, dissolved oxygen, and material using data from OLI Systems’ Corrosion Analyzer. We then integrate these surrogates as corrosion design constraints in a cost-optimization MVC model that minimizes the levelized cost of water (LCOW). For a case study of mechanical vapor compression (MVC) treating seawater across a range of recoveries, we find dissolved oxygen (DO) is the dominant driver of localized corrosion, and thus of cost-optimal material choice and operating conditions. Reducing the DO from 8 mg/L to 0.5 mg/L reduces the LCOW by 15-35%, informing the breakeven costs for implementing DO removal or selecting highly corrosion-resistant alloys. This framework is broadly applicable across corrosion types, materials, and components and enables desalination process design that minimizes capital costs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

X-ray tomography of damage dynamics in advanced materials using a laser wakefield accelerator

Additively manufactured (AM) metals offer the potential for customizable, cost-effective components, but qualification and certification are crucial. Key to this process is understanding pore dynamics under stress, typically analyzed using micro-computed tomography. This study introduces laboratory-scale “betatron” x-rays from laser wakefield acceleration as a high-throughput alternative for x-ray tomography of advanced materials, such as AM AlSi10Mg alloys. Coupled with 3D finite element modeling, this method provides detailed insights into stress-porosity interactions. The approach delivers high-resolution scans, revealing that pore shape and local triaxiality significantly influence fracture dynamics, supporting advanced material characterization. This work also demonstrates the potential and versatility of laser-betatron x-ray μCT for generating large datasets to accelerate our understanding of the stochastic, process-specific nature of pore formation in AM alloys.

Senthilkumaran, Vigneshvar↗
DOE OSTI2025

Hierarchical Gaussian process-based Bayesian optimization for materials discovery in high entropy alloy spaces

Bayesian optimization (BO) is a powerful and data-efficient method for iterative materials discovery and design, particularly valuable when prior knowledge is limited, underlying functional relationships are complex or unknown, and the cost of querying the materials space is significant. Traditional BO methodologies typically utilize conventional Gaussian Processes (cGPs) to model the relationships between material inputs and properties, as well as correlations within the input space. However, cGP-BO approaches often fall short in multi-objective optimization scenarios, where they are unable to fully exploit correlations between distinct material properties. Leveraging these correlations can significantly enhance the discovery process, as information about one property can inform and improve predictions about others. Here, this study addresses this limitation by employing advanced kernel structures to capture and model multi-dimensional property correlations through multi-task (MTGPs) or deep Gaussian Processes (DGPs), thus accelerating the discovery process. We demonstrate the effectiveness of MTGP-BO and DGP-BO in rapidly and robustly solving complex materials design challenges that occur within the context of complex multi-objective optimization over FCC FeCrNiCoCu high entropy alloy (HEA) spaces, where traditional cGP-BO approaches fail. Furthermore, we highlight how the differential costs associated with querying various material properties can be strategically leveraged to make the materials discovery process more cost-efficient.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Roll to Roll (R2R) Manufacturing of Electrolysis Electrodes for Low Cost Hydrogen Production: Cooperative Research and Development Final Report, CRADA Number CRD-18-00780

NREL, Argonne National Laboratory (ANL) and Oak Ridge National Laboratory (ORNL), which are also referred to collectively herein as the "Contractors" will perform electrode ink development and characterization, focusing on 1) inks with appropriate properties for R2R (gravure and slot-die) coating onto PFSA membrane and 2) catalysts suitable for electrolysis. Participant will develop acceptance criteria and characterization methods for direct coating on the membrane. The purpose of this project is to show feasibility for cost reduction of the electrode through increased throughput and improved material utilization. Successful completion of this project will result in more affordable hydrogen production via proton exchange membrane (PEM) electrolysis by substantially reducing the anode precious metal content and catalyst-coated membrane processing costs. Assists laboratory in achieving programmatic scope, adds new capability to the laboratory's core competencies. This project uses and enhances the laboratory's core competencies, and enhances U.S. competitiveness by utilizing DOE developed intellectual property and/or capabilities. This project will benefit the Fuel Cell subprogram within the EERE Fuel Cell Technologies Office (FCTO) by actively developing materials, formulations, components, and processes for PEM electrolyzer stacks for overcoming critical technical barriers to widespread hydrogen production for zero-emission transportation applications. Through this JWS, NREL, ANL and ORNL are assisting a key domestic industry partner, Proton Energy Systems, Inc., in the area of low-cost electrolyzer electrode formulation and coating technology. After completion of this project, NREL, ANL and ORNL will be able to verify whether the direct deposit coating processes investigated are suitable for producing CCMs for PEM electrolyzers, which is of great interest and benefit to the DOE EERE Fuel Cell Technologies Office (FCTO) and H2@Scale missions.

08 HYDROGEN↗
DOE OSTI2021

Jianlin Li: Accelerating battery manufacturing and recycling

With continued penetration of consumer electronics and electric vehicles into the evergrowing marketplace, there is a critical need for an efficient and sustainable battery supply chain. This includes the production of raw materials, the design, development, and processing of cell materials and systems, and end-of-life product recycling. The Oak Ridge National Laboratory (ORNL) has established a research program dedicated to addressing many aspects of these key challenges. Here, we asked Jianlin Li, a Senior R&D Staff and leader of the Energy Storage and Conversion Manufacturing Group, his opinion on the role of chemistry and materials science in mitigating the impacts of critical materials in battery supply chains.

25 ENERGY STORAGE↗
DOE OSTI2024

Release dynamics of nanodiamonds created by laser-driven shock-compression of polyethylene terephthalate

Laser-driven dynamic compression experiments of plastic materials have found surprisingly fast formation of nanodiamonds (ND) via X-ray probing. This mechanism is relevant for planetary models, but could also open efficient synthesis routes for tailored NDs. We investigate the release mechanics of compressed NDs by molecular dynamics simulation of the isotropic expansion of finite size diamond from different P-T states. Analysing the structural integrity along different release paths via molecular dynamic simulations, we found substantial disintegration rates upon shock release, increasing with the on-Hugnoiot shock temperature. We also find that recrystallization can occur after the expansion and hence during the release, depending on subsequent cooling mechanisms. Our study suggests higher ND recovery rates from off-Hugoniot states, e.g., via double-shocks, due to faster cooling. Laser-driven shock compression experiments of polyethylene terephthalate (PET) samples with in situ X-ray probing at the simulated conditions found diamond signal that persists up to 11 ns after breakout. In the diffraction pattern, we observed peak shifts, which we attribute to thermal expansion of the NDs and thus a total release of pressure, which indicates the stability of the released NDs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Coupled Hydrothermal Extraction and Ligand-Associated Swellable Glass Media Recovery of Rare Earth Elements from Coal Fly Ash (Final Report)

Wayne State University (WSU) researchers, in collaboration with the University of California-Los Angeles (UCLA) and Los Alamos National Laboratory (LANL), have successfully developed a new sorbent media used in a process that concentrated the rare earth content in a coal fly ash sample from southeast MI by >350×, resulting in >13 wt% REO powder. The project developed a new DTPA-associated media that was used to concentrate total REEs. This project demonstrated a coupled hydrothermal extraction and solid-liquid recovery process that produced REO powder from raw fly ash while nearly eliminating the use of organic solvents. The project successfully: 1) identified a commercially viable ash supply with >$2.5 M in REO value being deposited monthly, 2) hydrothermally extracted >77% of REEs in coal fly ash (20% more than acid alone), 3) developed a new sorbent media that was used to concentrate REEs, 4) and engineered a process that resulted in a >13 wt% REO powder. The media also demonstrates a selectivity for mid and heavy REEs over Ce and La and the potential for use in separating individual rare earth elements. An invention disclosure for the sorbent media has been filed with WSU and a patent application will be submitted in the near future. The project examined the potential to couple hydrothermal leaching of coal fly ash with the engineering of a custom ligand-associated media to provide an organic solvent-free method of extracting and recovering REEs. Fly ash feedstock was collected from Detroit area coal-fired power plants, characterized for REE content, and subjected to a bench-top batch hydrothermal leaching/dissolution process inside custom-build pressure reactors at Los Alamos National Laboratory (LANL). This process applied a dissolution technique previously developed to process spent nuclear fuel and other nuclear materials. The modified ash was acidified and the resulting leachate was enriched with REEs along with Ca, Al, and Si. Ligands known to be effective in lanthanide/actinide separation were evaluated based on a series of criteria such as selectivity and association to organosilica through hydrophobicity. Batch experiments were conducted to establish the best conditions (e.g., pH, eluent, etc.) and best ligand systems for the effective extraction of REEs from the alkaline feed solution obtained from the hydrothermal leaching process. Once the organosilica-ligand extraction media was developed for REE concentration, an acidic solution was used to back extract and concentrate the REEs into a heavily REE-laden strip solution. The REEs in the strip solution were precipitated with oxalate to produce rare earth oxides.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Advanced Interactive 3D Visualization Tool for Customizable Analyses of Tomography Datasets in Material Science

Current methods for visualizing and analyzing 3D tomography datasets in materials science often lack the interactivity and depth required for detailed structural insights. This limitation restricts a researchers' ability to accurately interpret complex data, which is critical for advancing material innovations and understanding structural properties. To address this issue, we have developed a novel, web-based interactive 3D visualization and analysis tool from the Trame framework that offers customizable features to enhance data interpretability. The tool allows users to adjust parameters such as visible range, slice planes, data rotation, and layering, providing a more detailed and dynamic view of complex structures. Its user-friendly web interface increases the accessibility and ease of use for both novice and experienced researchers, to visualize large volumetric datasets. The tool supports a diverse range of data formats, making it versatile for various research applications. Unique capabilities include real-time data manipulation, automated feature detection, context-sensitive feedback, and real-time volume calculations and distributions per sliced region or layer, alongside the ability to quickly generate high-quality screenshots and videos for presentations and reports. These advancements offer a comprehensive solution for enhanced 3D data exploration, significantly improving the analysis process and communication of results in materials science.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically associated with the dynamic behavior of the keyhole. So far, the accurate characterization and prediction of keyhole features, particularly keyhole depth, as a function of time, has been a challenging task. In situ characterization of keyhole dynamic behavior using the synchrotron X-ray technique is informative but complicated and expensive. Current simulations are generally hindered by their poor accuracy and generalization abilities in predicting keyhole depths due to the lack of accurate laser absorptance data. In this study, we develop a machine learning-aided simulation method that accurately predicts keyhole dynamics, especially in keyhole depth fluctuations, over a wide range of processing parameters. In two case studies involving titanium and aluminum alloys, we achieve keyhole depth prediction with a mean absolute percentage error of 10 %, surpassing those simulated using the ray-tracing method with an error margin of 30 %, while also reducing computational time. This exceptional fidelity and efficiency empower our model to serve as a cost-effective alternative to synchrotron experiments. Our machine learning-aided simulation method is affordable and readily deployable for a large variety of materials, opening new doors to eliminate or reduce defects for a wide range of laser materials processing techniques.

Computational fluid dynamics↗
DOE OSTI2025

ORNL Package Testing Program Overview

When transporting radioactive or hazardous materials, safety and security are top priorities. Packaging and transportation regulations require reliable evidence that containers have passed rigorous performance tests to ensure that the public and the environment are protected from the hazardous nature of the cargo. Because of its long history in energy and security research, Oak Ridge National Laboratory (ORNL) has needed to ship hazardous packages for the past 65 years. Since the 1940s, ORNL has made significant contributions to transportation regulations and has been at the forefront of regulatory testing development. Today, ORNL is a leader in standards development and testing of designs of radioactive material packages. ORNL plays a critical role in ensuring the safe transportation of radioactive materials across the United States by executing rigorous testing campaigns of packages that contain radioactive materials. Early testing activities focused on supporting the development of transportation regulations established by both the International Atomic Energy Agency (IAEA) and the United States. Currently, all package testing activities are performed under the Package Testing Program (PTP) at the Package Evaluation Facility (PEF) located at the National Transportation Research Center (NTRC), which is about 10 miles from the main ORNL campus. The PTP develops and evaluates testing solutions, ensuring that they are safe efficient, and in compliance with regulatory requirements. The vision for the PTP is to be a world-class leader in the evaluation and testing of radioactive and hazardous material packages. The key elements necessary to fulfill this mission are an experienced and professional staff; state-of-the-art facilities, equipment, and instrumentation; and completion of challenging programs and projects important to package transportation. Collaborations with other internal and external organizations play a significant role in building stronger teams and achieving this vision. By adhering to and advancing regulatory standards, ORNL’s PTP supports development of safe and compliant packaging, safeguarding the transportation process from potential risks associated with radioactive material logistics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Uncovering Uranium Isotopic Heterogeneity of Fuel Pellets from the Fifth Collaborative Materials Exercise of the Nuclear Forensics International Technical Working Group

In 2017, the Nuclear Forensics International Technical Working Group (ITWG) organized their fifth 37 Collaborative Materials Exercise (CMX-5). The exercise samples were two uranium dioxide fuel pellets 38 manufactured from the same starting materials by different processes to have similar bulk isotopic 39 composition, but different spatial uranium isotopic distributions. Sets of identical materials were sent to 40 all participating laboratories, who then utilized their existing nuclear forensic capabilities to 41 independently analyse fuel pellets and identify similarities and differences of the materials’ 42 characteristics. The analytical methods used to probe the fuel pellets included ex situ, such as sectioning 43 or breaking up the pellets and analyzing dissolved pieces using inductively coupled plasma mass 44 spectrometry (ICP-MS), analyzing particles collected from intact or fragmented pellets by secondary ion 45 mass spectrometry (SIMS), as well as in situ methods, such as laser ablation coupled with ICP-MS, 46 autoradiography and nanoSIMS. In this paper we present the results of these independent analyses and 47 compare the capabilities of those nuclear forensic analytical methods to uncover details of the isotopic 48 heterogeneity of uranium fuel pellets.

Nuclear Forensic Analysis of Uranium Fuel Pellets,↗
DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Shining Light on Halide Perovskites: Teaching Analytical Chemistry Using Flexible, Inquiry-Based Experiments

Two-dimensional (2D) metal halide perovskites are promising next generation semiconducting materials at the forefront of research in solar cells, LEDs, and other devices. Here, we report on an undergraduate intermediate analytical chemistry laboratory experience where students were taught fundamental chemistry concepts, including solubility, complexation, spectroscopy, and microscopy, through the introduction and study of 2D halide perovskite materials. Students explore multiple facets of perovskite synthesis, structure, and properties through a modular set of experiments that students used to form a holistic picture of this material. Importantly, this inquiry-based lab supports students through a guided research process, and students report high interest and learning gains from an end of the semester survey. We further discuss ways to adapt this lab to course, student, equipment, and budget needs. Overall, this laboratory experience teaches and applies the fundamental concepts and tools of analytical chemistry to the contemporary materials research field.

Analytical Chemistry↗