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

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rapid data acquisition and machine learning-assisted composition design of functionally graded alloys via wire arc additive manufacturing

Abstract The lack of high-quality datasets in materials science hinders artificial intelligence (AI)-driven alloy design. To address this challenge, wire arc additive manufacturing (WAAM) was employed to fabricate graded alloys, generating extensive data for machine learning (ML)-assisted property prediction. ML models were developed using high-throughput experiments, computational models, and genetic algorithm to optimize feature selection, successfully predicting hardness and porosity. The ML model demonstrated its efficacy by designing a gradient alloy with enhanced properties. However, scaling up revealed uncertainties in tensile property and porosity due to differences in size and thermal conditions between the designed alloy build and the gradient print used to construct the ML model. This underscores the need for uncertainty quantification and process optimization in WAAM-driven alloy design. Our work advances AI-integrated additive manufacturing, offering a rapid approach to exploring process–structure–property relationships and accelerating materials development.

Wang, Xin↗
DOE OSTI2024

Experimental testing of additively manufactured embedded fiber optic smart devices for clean energy applications

Abstract An additively manufactured prototype smart device was created to investigate in-flow temperature distributions using embedded high-definition fiber optic sensors within a component for clean energy systems. The devices were created using Ultrasonic Additive Manufacturing to create a unique embedded pathway within a flow conditioner for the high-definition fiber optic sensors to be placed within. The fibers used allowed for temperature measurements to be taken every 0.65 mm along the fiber. The high-resolution fibers were thermally calibrated enable the 2D reconstruction of the temperature profile in the flow path of the structure. This is due to the temperature-related strain response of the material and strain measurements of the fibers. Hot airflow testing of these devices showed the ability to identify localized temperature differences in the flow. The observed strain response within the smart device had higher strain concentrations in the thicker web regions than in the thinner web regions. These higher strain regions resulted in higher uncertainties for the temperature responses. Further calibration is needed to improve the accuracy of the smart devices, specifically within the inner web structures of a flow straightening component. Further investigations of the devices within flow showed the temperature sensing to be independent of the effects of flow velocity. The devices were able to distinguish temperature differences within single and two-phase flow and showed local sensitivity to the temperature changes with the identification of hot and cold spots. The presented results showed the viability of the smart device for obtaining detailed temperature distributions using common industrial components. Eventually, the goal for these smart devices will be to withstand higher temperature and pressure environments such as those experienced in nuclear, fusion, and concentrated solar energy systems.

Donlan, Connor F. (ORCID:0000000223317882)↗
DOE OSTI2024

Impacts of Superalloys on the Surface Quality of Additively Manufactured Channels

Abstract Gas turbines feature many components that require superalloys capable of handling extreme thermal environments. Increasing the selection of materials available for these components is important to their use in these extremely high-temperature environments. This study investigated two recently developed materials intended to be used for additive manufacturing (AM), with one superalloy based on cobalt and the other on nickel. Sets of four test coupons were built using the materials, in addition to the commonly used Inconel-718, on multiple laser powder bed fusion machines. Several build conditions were varied between coupon sets, including coupon orientation, contour settings, and upskin and downskin treatment. Each set of test coupons featured four unique cooling designs to explore how different cooling technologies would be impacted by the variations in build conditions. After being built, coupons were computed tomography (CT) scanned to determine accuracy to design intent and quantify the surface roughness. The CT scans indicated that horizontally built test coupons had a significantly higher deviation from design intent and higher surface roughness than those built vertically. Results also indicated that the cobalt-based alloy consistently had a smoother surface quality with lower surface roughness compared to the nickel-based alloy. After geometric characterization, the cooling performance of the test coupons was measured experimentally. Pressure losses were found to correlate with increases in surface roughness; however, in some cases, the convective heat transfer did not increase proportionally to the pressure loss as a result of surface features significantly blocking the flow without proportionally increasing convective heat transfer.

Engineering↗
DOE OSTI2025

Deep Learning Super-Resolution X-Ray Computed Tomography Algorithms for Additive Manufacturing

Industrial X-ray computed tomography (XCT) is a nondestructive method for inspection and characterization of additively manufactured (AM) materials and parts. In practice, the resolution of XCT can be limited by factors such as detector binning, restricted field of view for large-scale objects, system blur, motion during scanning, and acquisition settings. These limitations can reduce the detectability of critical flaws such as pores, cracks, and lack of fusion. Super-resolution (SR) techniques offer a promising solution for improving the effective resolution and image quality of XCT reconstructions without the need for expensive hardware upgrades or laborious, time-consuming scans. In particular, deep learning-based SR methods have garnered attention in recent years as powerful tools for reconstructing high-resolution volumes from low-resolution inputs. In this work, a novel deep learning-based SR method is proposed for XCT scans of AM parts, and compared against several existing state-of-the-art (SOTA) methods. The proposed method, Simurgh-SR, is built on the pre-existing Simurgh framework and consists of a 2.5D U-Net trained to map low-quality inputs containing noise and artifacts to high-quality reconstructions characterized by higher flaw contrast, better noise texture, and reduced artifacts. The experimental results demonstrate superior performance of Simurgh-SR in performing 4× SR on real industrial XCT scans of thick 316L components, enhancing the structural similarity score and peak signal-to-noise ratio (>7dB) compared to the LR counterpart while improving the F1-score for flaw detection by more than 2.3× when compared to alternative SOTA SR methods. This improvement enables more accurate and significantly faster characterization of metal AM components. Additionally, Simurgh-SR was trained for both 2X and 4X SR and performs effectively at both levels, enabling the use of a single model for various SR factors.

Rahman, Obaid [ORNL] (ORCID:0000000277810840)↗
DOE OSTI2026

Data for "Photoinduced Chemomimetic Biocatalysis for Enantioselective Intermolecular Radical Conjugate Addition"

Exploiting nature’s catalysts for non-natural transformations that are inaccessible to chemocatalysis is highly desirable but challenging. On the one hand, the widespread nicotinamide-dependent oxidoreductases have not been utilized for single-electron-transfer-induced bimolecular cross-couplings; on the other, the addition of catalytic asymmetric radical conjugate to terminal alkenes remains a challenge owing to strong racemic background reaction and unselective termination of prochiral radical species. Here we report a chemomimetic biocatalysitic approach for construction of alpha-carbonyl stereocentres via an unnatural intermolecular conjugate addition of N-(acyloxy)phthalimides-derived radicals with acceptor-substituted terminal alkenes, by combination of visible-light excitation and nicotinamide-dependent ketoreductases (KREDs). Based on protein crystal structure, we engineered KREDs via a semi-rational mutagenesis strategy to improve reaction outcomes with a small and high-quality variants library. Mechanistic investigations combining wet experiments, crystallographic studies and computational simulations demonstrate that the repurposed biocatalyst can suppress racemic background reaction and unselected side reactions, yielding enantioselectivity that is challenging to achieve by chemocatalysis.

Catalysis↗
DOE OSTI2026

Wire-arc Additive Manufacturing Benchmark

This is the dataset associated with the 2022 SRP Additive Manufacturing Prediction Challenge, originally hosted on Github at https://github.com/SRP-AM/SRP_AM_Prediction_Challenge. The benchmark was designed for validating prediction for the temperature history, residual stress, and distortion of an additively manufactured metal part with relatively simple geometry. A calibration problem with the same as-built geometry is provided with measured quantities of interest; including temperature histories at selective locations, post-build residual stress at selective locations, and overall distortion measurements. The challenge problem is presented with a different build sequence (i.e. thermal history). In this dataset, we include the actual recorded calibration and challenge measurements, as well as benchmark template files for testing predictions without incorporating the challenge data. Supplementary files around the materials and setup are available for transparency and reproducibility.

Bachus, Nicholas [UC Davis, Davis, CA]↗
DOE OSTI2025

AdditiveFOAM: A Continuum Multiphysics Code for Additive Manufacturing

AdditiveFOAM is a computational framework that simulates transport phenomena in Additive Manufacturing (AM) processes. It is built on OpenFOAM (Weller et al., 1998), the leading free, open-source software package for computational fluid dynamics (CFD). OpenFOAM offers an extensible platform for solving complex multiphysics problems using state-of-the-art finite volume methods. AdditiveFOAM leverages these capabilities to develop specialized tools aimed at addressing challenges in AM processing. Metal additive manufacturing, also known as metal 3D printing, is an advanced manufacturing technique that creates physical parts from a three-dimensional (3D) digital model by melting metal powder or wire feedstock. A significant area of research in metal AM focuses on process planning to mitigate anomalous features during printing that are deleterious to part performance (e.g., porosity and cracking), as well as controlling localized microstructure and material properties. Given the high costs and substantial time requirements associated with experimental methods for qualifying new materials and processes, there is a compelling incentive for researchers to utilize advanced computational simulations. In this context, AdditiveFOAM offers a simulation framework to better understand undesirable features in printing, thereby enhancing process planning and reducing the reliance on labor-intensive experimental campaigns.

Coleman, John [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2024

Integrated Turbine Component Cooling Designs Facilitated by Additive Manufacturing and Optimization

This research program involved the development of improved gas turbine cooling by optimizing the combined internal and film cooling configurations used for turbine blades and vanes. Improved cooling of turbine airfoils allows the gas turbines to be operated at higher temperatures which improves efficiency for gas turbine-based power generation. This also facilitates operation with hydrogen-based fuels which inherently generate higher operating temperatures. Designs of the new cooling configurations were based on the added geometric flexibility that is available when using metal additive manufacturing techniques. When making these designs, adjustments were made to account for imperfections occurring in the metal additive manufacturing process. New designs for film cooling holes were developed using computational adjoint gradient optimization techniques which generated a unique film cooling hole with 70% greater film cooling effectiveness compared to conventional shaped film cooling holes. A major factor in improving the film cooling effectiveness were small external protrusions on either side of the new hole which generated vortices that pushed coolant towards the surface and increased the lateral spreading of the coolant. Our studies also included optimization of film cooling holes that can be built with conventional manufacturing techniques and optimizing the internal coolant channels that supply coolant to the film cooling holes. Various internal coolant channel shapes were investigated and designs that maximized the cooling of the airfoil while minimizing pressure losses in the channel flows were identified. Testing and verification of the performance of the final configurations was done with a transonic wind tunnel facility which allowed testing at engine realistic high velocities. Final testing of the combined internal and film cooling configurations was done by incorporating the configurations in Penn State’s National Experimental Turbine (NExT) vane. These tests confirmed the enhanced overall cooling effectiveness provided by the new cooling configuration designs.

03 NATURAL GAS↗
DOE OSTI2024

Additive Manufacturing of Dissolvable Mandrels

ORNL collaborated with Mitsubishi Chemical America to investigate different grades of vinyl alcohol co-polymers as a potential feedstock material for large-scale material extrusion additive manufacturing (AM). Dissolvable polymers and can find potential applications in AM tooling for complex, hollow, and trapped composite structures without the need for specialized molds and tools. This CRADA Phase I work involved analysis of three different developmental grades of vinyl alcohol co-polymers for thermal and rheological properties, followed by print trials on the Big Area Additive Manufacturing (BAAM) system using these materials. Finally, printed part properties, including mechanical and thermal performance, as well as dissolvability were evaluated. The properties and performance evaluated in this phase of the project have provided guidelines to further develop these vinyl alcohol co-polymers to enable large-scale printing at high deposition rates and obtain parts that satisfy high temperature molds and dies requirements.

36 MATERIALS SCIENCE↗
DOE OSTI2024

In-Process Monitoring and Structural Health Monitoring of Large-Scale Additive Manufacturing Using Acoustic Emission Technique

ORNL collaborated with MISTRAS Group, Inc. to investigate acoustic emission (AE) as a structural health monitoring (SHM) method for large-scale additive manufacturing (AM). Large-scale AM is being adapted as method of producing large structures in a short lead time and cost-effective way. With the growing advancement in AM techniques and application, machine monitoring and part qualification is highly needed. There has been leading research focused on the manufacturing, feedstock material but minimum research on the SHM, defect detection, and nondestructive evaluation (NDE) for AM. Scanning large structure using conventional nondestructive testing (NDT) techniques, such as ultrasound or X-ray, and searching for potential defects can be very time consuming, challenging and cost prohibitive. AE is a passive technique that can be used to monitor and locate defect progression in large structure by distributing group of sensors around the part. This project utilized AE technique and system manufactured/designed by MISTRAS Group to monitor large-scale AM equipment (i.e. Big Area Additive Manufacturing (BAAM) system located at the Oak Ridge National Laboratory – Manufacturing Demonstration Facility (ORNL-MDF) and the printed parts it produces. The AE system provided valuable insight on defect development/progression during and post-printing process.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Compensating for Sintering Distortion in Additively Manufactured Shaped Charge Liners using Physics-Informed Machine Learning

Copper is a challenging material to process using laser-based additive manufacturing due to its high reflectivity and high thermal conductivity. Sintering-based processes can produce solid copper parts without the processing challenges and defects associated with laser melting; however, sintering can also cause distortion in copper parts, especially those with thin walls. In this study, we use physics-informed Gaussian process regression to predict and compensate for sintering distortion in thin-walled copper parts produced using a Markforged Metal X bound powder extrusion (BPE) additive manufacturing system. Through experimental characterization and computational simulation of copper’s viscoelastic sintering behavior, we can predict sintering deformation. We can then manufacture, simulate, and test parts with various compensation scaling factors to inform Gaussian process regression and predict a compensated as-printed (pre-sintered) part geometry that produces the desired final (post-sintered) part.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mechanical Performance of Additively Manufactured ODS 316L and 316H Stainless Steels

This work package within the Advanced Materials and Manufacturing Technologies (AMMT) program focused on the mechanical and microstructural characterization of oxide dispersion strengthened (ODS) stainless steels produced using advanced manufacturing techniques. The research aimed to identify an accelerated development path for ODS alloys by integrating additive manufacturing (AM) technologies with recent advancements in ODS materials and traditional manufacturing methods. For FY 24, the research specifically targeted exploring an accelerated development path for ODS alloys by combining AM technologies with these advancements. Novel AM and post-build processing routes were developed for ODS austenitic alloys, including Fe-Cr-Ni alloys such as 316L and 316H. Electron microscopy and mechanical characterizations were conducted to evaluate the impact of process variables on microstructure and properties, with the goal of optimizing these properties economically. Traditionally, producing ODS alloys involves multi-day, high-energy mechanical milling of alloy powder with yttria powder, followed by milled-powder consolidation through extrusion or other methods, and additional thermomechanical processing (TMP) for property control. To overcome the challenges associated with this complex and costly approach, we propose exploring alternative, cost-effective processing routes that emphasize AM and traditional TMP methods. The new processing routes for ODS alloys have achieved significantly higher strengths—several times greater than those of wrought stainless steels—while maintaining substantial ductility and fracture toughness. This report outlines the novel and economical AM-based processing routes for ODS austenitic alloys, combined with post-build TMPs, and discusses the mechanical and microstructural characteristics of the developed materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Preliminary Results on Process Modeling Tools for Determining Variability in Additively Manufactured Stainless Steel 316 Parts

The Advanced Materials and Manufacturing Technologies program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. However, the distinct characteristics of additive manufacturing (AM) materials, stemming from their unique processing history, microstructure, and properties, pose significant challenges for the qualification and certification of nuclear components. These challenges primarily arise from component-scale variations in microstructure and properties influenced by local process conditions and geometry, which affect thermal history, melt pool dynamics, and microstructure evolution. Computational modeling tools can play a crucial role in predicting and controlling this variability. This report presents preliminary results on process modeling tools designed to predict microstructure variability in additively manufactured stainless steel 316 parts. It details the software packages and physical modeling approaches employed to simulate an AM component within an automated process modeling workflow. Initial results are demonstrated through comparisons between predicted microstructures and experimental measurements across various representative processing conditions. The report concludes by discussing the challenges inherent in process modeling of AM components and outlines a plan for future development needs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High-Temperature Oxidation Behavior of Wrought and Additive Manufactured H282 in Direct-Fired Supercritical CO2 Power Cycle Environments

Materials selection is a key concern for corrosion resistance in high temperature and pressure direct-fired supercritical CO2 power cycles. The effect of elevated pressure on corrosion resistance can be critical, as impurities within the supercritical fluid such as H2O and O2 can result in additional corrosion behaviors. Utilizing additive manufacturing (AM) methods for construction of power cycle components requiring both compact and complex designs could be advantageous. AM H282 produced by laser powder bed fusion was exposed to direct-fired conditions (95CO2 – 4H2O – 1 O2) at 750 °C at both atmospheric pressure and supercritical conditions (20 MPa) for up to 4,000 hours. Oxidation behavior, sub-surface carbide formation, and chromia scale volatilization was dependent upon AM preparation techniques and surface modifications. These results are discussed in terms of the potential compatibility issues that may arise when using AM alloys in high temperature regions of direct-fired sCO2 power cycles, particularly for thin-walled components.

Carney, Casey↗
DOE OSTI2024

Additively Manufactured Carbon Fiber and Fused Deposition Modeling PLA Interlaminar Shear Testing Report

This test report summarizes the torsional test setup, procedure, and results for interlaminar shear (ILS) failure of additively manufactured carbon fiber (CFAM) material developed at LLNL. In addition, the report also includes testing of fused deposition modeled (FDM) polylactic acid (PLA), including ILS test standard D7078 and the same torsional test mentioned above. The test hopes to characterize ILS properties of CFAM, however substantial further testing and improvements still need to be done to induce a proper failure mode. This testing was performed by Sundi Win as part of her summer internship project in Kinetic Technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Binder jet additive manufacturing of silicon carbide solar reactor

Achieving high powder packing density is critical in binder jet additive manufacturing (BJAM), as it directly influences the final part density, mechanical properties, and sintering behavior. Multi-modal powder blends, which combine particles of different sizes, have been explored as a strategy to optimize packing efficiency and minimize defects. In this study, bimodal and trimodal powder blends were obtained by mixing silicon carbide powder in three different sizes. These results show that increased powder density is achievable with bimodal powder blends but is reduced in trimodal blends, and it was found that a 13% increase in the powder tap density was achieved using a bimodal blend of powder. The powder size distribution of the bimodal blend was measured at various stages during binder jet additive manufacturing and, no measurable powder separation occurred even after eight prints. Overall, this study shows limited advantage to trimodal powder blends but good promise for trimodal blends for increasing printed density while maintaining reusability in the binder jet process.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Using Additive Manufacturing to Repair Gas Turbine Hot Section Components

Ni-based superalloys are used in the hot sections of gas turbine engines due to their excellent high temperature performance. During service the material degrades due to exposure at high temperature and mechanical loads. Hence, utility provides often inspect, service, and repair components in gas turbine engines to ensure safe operation. A major challenge, however, is that the most heat-resistant alloys are generally considered ‘non-weldable’ rendering them difficult to repair via welding operations. In these cases components are often scrapped and then replaced by parts which must be re-manufactured. This burdens utilities with additional cost and supply chain issues can result in long term outages or reduced operating limits. In this work EPRI and ORNL investigated a proposed repair strategy for gas turbine hot section components. Hot section superalloy GTD-111 was selected as a candidate repair material system and AM material ABD-900 the repair material. Sandwich structures were fabricated via electron beam melting additive manufacturing (EBM-AM) producing tensile bars with gage sections consisting of dissimilar ABD-900 / GTD-111 / ABD-900 material. Metallography revealed that the interface exhibited no deleterious phases or processing defeats. Creep rupture experiments on heat treated material demonstrates that the emulated repair coupons exhibit creep resistance between GTD-111 and ABD-900. This study demonstrates that the proposed EBM-AM repair strategy presents a viable opportunity towards enabling AM repair of gas turbine engine components.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Design of Novel Hot Gas Component for Gas Turbine Engines Enabled by Materials and Additive Manufacturing Process Development

This CRADA project was the result of a project award under FOA-DOE-0001980. The overarching FOA project team consisted of researchers from Carpenter Technology Corporation (CTC), Solar Turbines Incorporated (Solar), Pennsylvania State University (PSU), University of California-Santa Barbara (UCSB), and Oak Ridge National Laboratory (ORNL). Evaluations were conducted on two high-γ’ superalloys that were designed by CTC and the UCSB. One alloy named GammaPrint-700 (GP-700) is a cobalt-base superalloy. The other alloy named GammaPrint-1100 (GP-1100) is a nickel-base (Ni-base) superalloy. PSU provided expertise and experimental testing of the thermal performance of AM micro-cooling architectures. ORNL provided expertise with the AM superalloy materials characterization and AM processing science. Solar provided turbine component design expertise. The focus of this CRADA report is to document the efforts between ORNL and CTC towards the development of superalloys designed for AM. The project goal was to use an AM processable high-temperature superalloy and design for Additive Manufacturing (DfAM) techniques to design an efficient turbine component (i.e. a turbine tip shoe) with enhanced cooling features that can only be fabricated through additive manufacturing (AM). The efficiencies of existing combined heat and power (CHP) engines are capped by both component design and materials limitations. However, AM of a tip shoe component from a γ’strengthened superalloy offers the design flexibility to increase the efficiency and power of an industrial gas turbine. This project brought about advancements in the DfAM tip shoe design space and in the area of high temperature superalloys processable through laser powder bed fusion (LPBF) AM. State of art computation design tools were utilized to optimize unique cooling features into a tip shoe component design. A two-prong materials development approach was taken to support development of the AM tip shoe geometry. The first approach centered on investigating the processability and the appropriate process science for the industry standard high-γ’ nickel-base (Ni-base) superalloy Mar-M247. This superalloy is typically cast and considered non-weldable by traditional welding standards. In the course of this work, the alloy was not deemed feasible for process scale-up due to significant cracking issues during printing. The second approach focused on the development and evaluation of a novel cobalt-base superalloy, GammaPrint™-700 (GP-700 and a Ni-base superalloy, GammaPrint™-1100 (GP-1100) designed to mitigate the significant AM processing issues with Mar-M247. The processability of these two alloys were investigated through electron beam melting (EBM) binder-jet AM (BJAM), and LPBF as a risk mitigation for manufacturability. To be considered a candidate material for down-selection to proceed to fullscale AM tip shoe engine testing trials, the high temperature creep rupture strength was required to achieve at a minimum, a Larsen Miller Parameter (LMP) increase of 10.9% over the baseline material LPBF AM Hastelloy X.

36 MATERIALS SCIENCE↗