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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Discovery and Synthesis of a Family of Boride Altermagnets

Borides are a rich material family. To push the boundaries of borides’ properties and applications into broader fields, we have conducted systematic theoretical and experimental searches for synthesizable phases in ternary borides TM 2 B 2 (T = 3d, M = 4d/5d transition metals). We find that TM 2 B 2 in the FeMo 2 B 2 -type and CoW 2 B 2 -type structures form a large family of stable/metastable materials of 120 members. Among them, we identify 40 materials with stable magnetic solutions. Further, we discover 11 altermagnets in the FeMo 2 B 2 -type structure. So far, boride altermagnets are rare. In these altermagnets, T = Fe or Mn atoms are arranged in parallel T-chains with strong ferromagnetic intrachain couplings and antiferromagnetic interchain couplings. They simultaneously exhibit electronic band spin splitting, typical of ferromagnetism, and zero net magnetization, typical of antiferromagnetism. They also exhibit magnonic band chiral splitting. Both effects originate from the unique altermagnetic symmetries crucially constrained by the nonmagnetic atoms in the structure. Transport properties of relevance to spintronic applications, including the strain-induced spin-splitter effect and anomalous Hall effect, are predicted. An iodine-assisted synthesis method for TM 2 B 2 is developed, using which 7 of the predicted low-energy phases are experimentally synthesized and characterized, including 4 altermagnets. This work expands the realm of borides by offering new opportunities for studying altermagnetism and altermagnons in borides. It also provides valuable insights into the discovery and design of altermagnets. Here, by demonstrating that altermagnets can exist as families sharing a common motif, this work paves a feasible route for discovering altermagnets by elemental substitutions and high-throughput computations.

Chemical structure↗
DOE OSTI2026

Applied genomics for industrially relevant microalgal strain development & optimization: characterizing genotype-phenotype relationships towards scalable environment-enhancing energy systems

Multiple planetary boundaries considered a safe operating space for humanity have been exceeded in recent years, with twice as many boundaries transgressed in 2023 as in 2009. Bioenergy systems are unique in that they can interact with and improve many of the transgressed boundaries directly, including multiple geochemical cycles, water and land use, and climate change. Among bioenergy systems, microalgae-based environment enhancing energy (E 2 -energy) are promising bioenergy systems for drop-in biofuels, valuable materials, chemicals and therapeutics, while making deep emission cuts and remediating wastewater, all without competing for agricultural resources.

09 BIOMASS FUELS↗
DOE OSTI2025

Combined Creep and Fatigue Modeling

Simultaneous consideration of creep and fatigue is of paramount importance to accurately predict component life in many industrial applications. For example, growing penetration of renewable energy onto the grid is forcing many power plants to transition from base-load power generation to more complex operation modes, characterized by a combination of base-load generation and frequent start-up and shut-down cycles. The frequent start-stop of power plants is causing a significant toll in the component life due to fatigue. As such, creep alone is not adequate anymore to predict the component life. Most existing life prediction models consider creep or fatigue independently while neglect their interactions. In this presentation, we talk about some recent efforts at NETL to develop a unified modeling framework where both creep and fatigue can be considered. The creep-fatigue interaction mechanism is studied. High-throughput simulations are performed under various hold stress and hold time, and analytical expressions are fitted for the crack growth rates under creep and/or fatigue conditions demonstrating some applications of this newly developed modeling capability.

advanced alloy development↗
DOE OSTI2025

Orthorhombic Structures as Inorganic Halide Perovskite Models for High-Throughput DFT Investigations

Although high-symmetry Pm-3m space group cubic models are computationally efficient for high-throughput density functional theory (DFT) calculations of inorganic ternary (ABX 3 ) halide perovskites (HPs), they frequently predict band gaps (E g ) that disagree with experiment. Conversely, while low-symmetry cubic polymorphous networks (PN) comprised of 160 to 320 atoms incur significantly greater computational cost, they predict E g ’s that are more closely aligned with experiment. Here, in this study, we compare the DFT total energies and E g ’s predicted by four high-symmetry structure models (Pnma orthorhombic, R3m trigonal, P4/mbm tetragonal, and Pm-3m cubic) to cubic PNs for 5 experimentally characterized ternary HPs and find that the orthorhombic model computes Eg’s with the smallest MAD of 0.23 eV relative to the PNs. Pair distribution functions and DFT-computed total energies show that octahedral tilting, which is present in the 20-atom orthorhombic and 160-atom cubic PN models but not in the 5-atom cubic models, stabilizes all 5 compositions in our benchmarking set. We also find that imposing PN constraints when generating and optimizing these orthorhombic structures by fixing the unit cell lattice vectors and displacing the atoms prior to ionic relaxation with DFT, which we call the orthorhombic surrogate model (OSM), lowers the MAD of E g predictions to 0.09 eV. Our OSM predicts the PN band gaps of an additional 95 theoretical inorganic ternary HPs with MAD of 0.08 eV, supporting its usage in high-throughput DFT investigations to closely estimate PN band gaps with much less computational expense.

14 SOLAR ENERGY↗
DOE OSTI2025

High-throughput multimodal exploration of a nanocrystalline Cu-Ag library

Sputter-deposited, nanocrystalline Cu-Ag thin films produced across a broad compositional and deposition-parameter space were evaluated to unravel the process-structure-property relationships important for creating hard, conductive electrical contacts and coatings. Combinatorial deposition involving pulsed direct current magnetron sputtering of elemental targets enabled swift examination of nearly the full range of alloy compositions and a relevant portion of deposition atomistics. Several high-throughput characterization modalities were employed to evaluate the chemistry, structure, and properties of the films. The resultant hardness, modulus, film density, crystal texture, and resistivity were analyzed in terms of key deposition characteristics (incident atom kinetic energy and incidence angle) predicted by binary-collision, kinematic Monte Carlo simulations. The study revealed improved hardness, parabolic resistivity dependence on composition, and compositional and process dependencies of film tarnishing. The results are discussed in the context of variations in microstructure and film density. Transmission electron microscopy and X-ray diffraction demonstrate several forms of compositional variation including solute segregation to grain boundaries as well as periodic, intragranular compositional modulations. Annealing of a Cu-rich alloy film exhibiting grain boundary segregation showed that this as-deposited, compositional variation is not stable above 100 °C. Finally, the Cu-Ag system is shown to have potential for hard, conductive, tarnish-resistant and room temperature-stable nanocrystalline thin films across the composition space.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Automated Gold Nanorod Spectral Morphology Analysis Pipeline

The development of a colloidal synthesis procedure to produce nanomaterials with high shape and size purity is often a time-consuming, iterative process. This is often due to quantitative uncertainties in the required reaction conditions and the time, resources, and expertise intensive characterization methods required for quantitative determination of nanomaterial size and shape. Absorption spectroscopy is often the easiest method for colloidal nanomaterial characterization. However, due to the lack of a reliable method to extract nanoparticle shapes from absorption spectroscopy, it is generally treated as a more qualitative measure for metal nanoparticles. This work demonstrates a gold nanorod (AuNR) spectral morphology analysis tool, called AuNR-SMA, which is a fast and accurate method to extract quantitative structural information from colloidal AuNR absorption spectra. To demonstrate the practical utility of this model, we apply it to three distinct applications. First, we demonstrate this model's utility as an automated analysis tool in a high-throughput AuNR synthesis procedure by generating quantitative size information from optical spectra. Second, we use the predictions generated by this model to train a machine learning model to predict the resulting AuNR size distributions under specified reaction conditions. Third, we apply this model to spectra extracted from the literature where no size distributions are reported and impute unreported quantitative information on AuNR synthesis. This approach can potentially be extended to any other nanocrystal system where absorption spectra are size dependent, and accurate numerical simulation of absorption spectra is possible. In addition, this pipeline could be integrated into automated synthesis apparatuses to provide interpretable data from simple measurements, help explore the synthesis science of nanoparticles in a rational manner, or facilitate closed-loop workflows.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Supported-Single Nickel Atom Catalysts for the Methanation of Carbon Dioxide

Synthesis of twenty-seven bimetallic catalysts consisting of nickel and one of nine different dopants (B, Co, Cu, Fe, Mg, Mn, Sn, V, and Zn) supported on three different metal oxides (Al 2 O 3 , CeO 2 , and SiO 2 ) is carried out via organometallic grafting. The catalysts are evaluated for their activity and selectivity for the CO 2 methanation reaction at a feed ratio of H 2 /CO 2 of 4 at 300 °C in a high-throughput flow reactor system. After in situ pre-activation (500 °C in H 2 ), Ni/Co/CeO 2 exhibited high conversion (84.3%) and selectivity for methane (99.6%). Ni/Co/CeO 2 was characterized by high-resolution transmission electron microscopy (HRTEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction, H 2 -temperature-programmed reduction (H 2 -TPR), and CO 2 -temperature-programmed desorption (CO 2 -TPD). HRTEM showed the presence of single Ni and Co atoms on ceria after pre-reduction at 500 °C and after the methanation reaction at 300 °C for 15 h. XPS determined that the strong interaction between Ni, Co, and ceria increased after the reduction, leading to a charge transfer between Ni and Ce that created oxygen vacancies in ceria. Nickel was found to be Ni 2+ in the as-prepared material and was partially reduced in the presence of cobalt and after the activation in H 2 at 500 °C. The DFT results show that both nickel and cerium exhibit lower Bader charges in the Ni/Co/CeO 2 system, confirming that the presence of cobalt enhances the reduction of both Ni and Ce through electronic interactions. This indicates that single cationic Ni atoms are highly effective for the methanation reaction. In conclusion, the organometallic grafting technique is found to be efficient for synthesizing catalysts with highly homogeneous dispersed species at low metal loadings (0.16 wt % Ni–0.15 wt % Co), which leads to high turnover frequency (up to 248.7 h –1 ) and durability for methanation.

CO2 conversion↗
DOE OSTI2025

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

In materials science, plant biology, agriculture, and environmental research, the automated analysis of high-magnification, complex microscopy images, such as those generated by freeze-fracture electron microscopy (FF-TEM), remains a critical challenge that limits the scalability of data interpretation. We present a deep learning computer vision pipeline for high-throughput detection and morphological characterization analysis of cellulose synthase complexes (CSCs, or rosettes) in FF-TEM images. The pipeline integrates preprocessing, detection, human-in-the-loop verification, and semantic segmentation to quantify features such as rosette diameter and inter-lobe spacing. The approach was trained and tested on a curated dataset of high-resolution FF-TEM micrographs of Physcomitrium patens, expanded via strategic tiling and augmentation to over 650 images. We compare YOLOv8 and YOLOv9 architectures and demonstrate that YOLOv9 achieves superior performance in both localization accuracy (mAP50-95 = 0.854) and inference speed. The resulting distributions revealed biological variability consistent with prior manual studies, validating the approach for high-throughput applications. Our results show that the pipeline achieves human-expert level accuracy while dramatically reducing analysis time, enabling scalable, reproducible structural characterization of intramembrane protein complexes. The pipeline is broadly applicable to other domains requiring precise interpretation of complex microscopy data and establishes a foundation for future artificial intelligence (AI)-assisted workflows in biological imaging.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Design, Processing, and Properties of WTaCrV-Hf Multi-principal Element Alloys

Refractory multi-principal element alloys are candidates for high-temperature structural components due, in part, to their high strength and high melting points. Single-phase materials are initially preferred for isotropic material properties as a function of time and temperature in service conditions. This work outlines a computational rank-ordering and experimental validation methodology for single-phase body-centered-cubic phase stability in WTaCrV-Hf alloys using order–disorder transition temperature. Eight compositions were fabricated by arc-melting and heat-treated at 1400 °C for 24 hrs. X-ray diffraction, energy-dispersive x-ray spectroscopy, and Vickers hardness testing showed alloys with order–disorder transition temperatures below 600 °C formed a single-phase body-centered-cubic structure during solidification and remained single-phase after heat-treatment. The sample possessing the lowest order–disorder transition temperature exhibited slip traces suggestive of room-temperature plastic deformation under Vickers indentation, with both heat-treated single-phase samples exhibiting hardnesses over 800 HV with little cracking compared to tungsten. These results establish order–disorder transition temperature as a viable predictive parameter for multi-principal element alloy phase stability. The methodology outlined in this work provides a framework for future design, fabrication, and characterization of high-temperature structural multi-principal element alloys.

CALPHAD↗
DOE OSTI2026

A Six-Membered Concerted Mechanism for CO 2 Capture by Amines Studied under Charged Microdroplet Reaction Conditions

Carbon dioxide (CO 2 ) capture and storage represents an important technological challenge. A mechanistic understanding of interactions involved in the capture process is necessary not only for technological development but also for efficient conversion of captured CO 2 into value-added materials. Herein, we present a novel contained secondary electrospray ionization platform for studying the interactions of gaseous amines and CO 2 gas under microdroplet reaction conditions, which enables mass spectrometry (MS) characterization of CO 2 capture products and intermediates in real time. We detected [2 M + CO 2 + H] + species, which corresponds to a six-membered intermediate. DFT calculations confirmed the high stability of the protonated six-membered ring intermediate. This finding provides a plausible concerted mechanism in the microdroplet environment that excludes the involvement of thermodynamically disfavored ionic species. The carbamic acid counterpart of the final product/salt was readily characterized by tandem MS. The carbamic acid/amine salt was also isolated and characterized by Fourier transform infrared spectroscopy. By virtue of the fact that headspace vapors of amines are sampled, we were able to establish a high-throughput platform that enabled the CO 2 capture capacity of five different amines to be studied in under 2 min. The same device also enabled the absolute quantification of capture capacity.

Amines↗
DOE OSTI2025

Synthetic Accessibility and Sodium Ion Conductivity of the Na8–x A x P2O9 (NAP) High-Temperature Sodium Superionic Conductor Framework

Advancement of solid-state electrolytes (SSEs) for all solid-state batteries typically focuses on modification of a known structural framework to improve conductivity, e.g., cation substitution for an immobile ion or varying the concentration of the mobile ions. Novel frameworks can be disruptive by enabling fast ion conduction aided by different structure and diffusion mechanisms, thereby unlocking optimal conductors with different properties. Herein, we perform a high-throughput survey of a structural framework for sodium ion conduction, Na8–x A x P2O9 (NAP), to understand the family’s thermodynamic stability, synthesizability, and ionic conduction. We show that the parent phase Na4TiP2O9 (NTP) undergoes a structural distortion (with accompanying conductivity transition) due to unstable phonons arising from pseudo-Jahn–Teller mode in the 1D titanium chains. Screening compounds in which Ti is substituted by other metals computationally reveal a number of candidates that are predicted to be low in formation energy and have high predicted ionic conductivities. High-throughput experimental and subsequent methodology optimization trials deliver one new compound, Na4SnP2O9 (NSP). X-ray diffraction (XRD), microscopy, and spectroscopy characterization indicate that the room-temperature structure of NSP is similar to the high-temperature, orthorhombic NTP phase but with some small unresolved structural differences. These uncharacterized structural details are speculated to limit the ion conductivity. Temperature-dependent XRD and electrochemical impedance spectroscopy indicate multiple coupled conductivity–structure transitions at a high temperature. We demonstrate the challenges with synthesis development and a priori identification of promising SSE phases as a major bottleneck in new (energy) materials development.

Chemical reactions↗
DOE OSTI2025

Demonstration of active neutron interrogation of special nuclear materials using a high-intensity short-pulse-laser-driven neutron source

Detecting shielded special nuclear material, such as nuclear explosives, is a difficult challenge pursued by non-proliferation, anti-terrorism, and nuclear security programs worldwide. Interrogation with intense fast-neutron pulses is a promising method to characterize concealed nuclear material rapidly but is limited by suitable source availability and proven instrumentation. In this study we have pioneered a demonstration of such an interrogation method using a high-intensity, short-pulse, laser-driven neutron source that offers potential benefits compared to conventional neutron sources. The measurement results reported here represent the first experimental demonstration of this interrogation approach on enriched uranium items and demonstrate the feasibility of a precise measurement using realistic nuclear materials, representative of field scenarios, even with just a single laser-driven neutron pulse. Bright pulsed sources can overcome the nuisance background of items with strong internal neutron sources, improving analytical power, while single-shot assay is attractive in high-throughput situations where time is at a premium. The science and technology of this type of neutron production is developing rapidly, and we anticipate that practical mobile interrogation systems will become available based on the detection concepts demonstrated here to meet the growing measurement needs.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
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

High-throughput synthesis of high-entropy alloys via parallelized electric field assisted sintering

Materials discovery and design is an expensive and time-consuming process, though necessary to advance many engineering fields. In this work, a novel tooling design is utilized in conjunction with electric field assisted sintering (EFAS) to effectively create a new high-throughput synthesis technique: parallelized EFAS. Through this technique, a wide range of material compositions and geometries can be synthesized in parallel as isolated samples or as part of contiguous arrays. Multiple tooling designs are explored to examine both the flexibility and limitations of the technique. A series of increasing complex alloys is produced simultaneously using in situ alloying, beginning with pure Ni and adding equimolar constituents up to the septenary high-entropy alloy AlCoCrCuFeMnNi. Microstructural characterization reveals each sample is effectively fully dense and chemically homogenous while exhibiting phases in agreement with CALPHAD predictions. Scalability of parallelized EFAS is then experimentally demonstrated and the implications for materials discovery and automation are discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Solar Spectrum Conversion for an Algae Bioreactor (CRADA Final Report)

This project focused on developing advanced optical coatings to improve solar energy utilization. The research aimed to create lanthanide-doped upconversion nanoparticles (UCNPs) capable of capturing unused near-infrared (NIR) light from the sun and converting it into visible light (blue and red photons) that can be used for photosynthesis. The primary goal was to identify, synthesize, and integrate highly efficient UCNPs into a transparent thin-film device. Through a comprehensive workflow involving computer simulations, high-throughput robotic synthesis, and detailed optical characterization, the project successfully developed a high-performance material. The key technical achievement was the creation of a core-shell UCNP (NaYF₄:20%Yb³⁺, 2%Er³⁺ coated with a 10 nm NaYF₄ shell) that demonstrated a quantum yield of 3.2% for converting 980 nm NIR light into visible light. Transparent thin films fabricated from these nanoparticles showed excellent optical properties, confirming their potential for practical applications. This research adds to the scientific understanding of energy transfer in lanthanide materials and demonstrates a technically effective method for creating efficient light-converting coatings. The primary benefit to the public lies in the potential for these coatings to enhance the efficiency of solar-driven processes, such as boosting the growth of algae in photobioreactors for biofuel production.

14 SOLAR ENERGY↗
DOE OSTI2025

Process-Microstructure-Property Relationships in Low Heat Input Wire-Arc Additive Manufacturing (WAAM) of Ni-Based Superalloy Haynes 282

Conference presentation on WAAM process optimization on Ni-based superalloy Haynes® 282®. This alloy is targeted for advanced power generation systems for its superior high temperature mechanical properties. Wire-arc additive manufacturing (WAAM) offers attractive cost and materials savings with high deposition rates. Based on initial build process optimization, WAAM blocks were made, and screened for defects using high-throughput CT scanning. The microstructural evolution in arc energy range of 250-700 J/mm was characterized in the as-built and aged conditions, using electron microscopy. Results showed self-consistent microstructure across conditions, with grain size dependence on arc energy, MC and M6C carbides in as-built, and blocky grain boundary M23C6 in as-heat-treated condition. Further reductions in as-built porosity were explored through 20+ combinations of H2 and CO2 additions to shielding gas. Initial results show improved wetting behavior, and bead overlap with up to 1% H2 and up to 0.25% CO2. Combination of experimentally determined datasets provided comprehensive understanding of process-structure-property relationships in WAAM Haynes 282.

Haynes 282↗
DOE OSTI2025

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗