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DOE OSTI2024

Dissolution zone model of the oxide structure in additively manufactured dispersion-strengthened alloys

The structural evolution of oxides in dispersion-strengthened superalloys during laser-powder bed fusion is considered in detail. Alloy chemistry and process parameter effects on oxide structure are assessed through a parameter study on the model alloy Ni-20Cr, doped with varying concentrations of Y 2 O 3 and Al. Small angle neutron scattering measurements of the dispersoid size distribution show the dispersoid size increases with higher laser power, slower scan speed, and increasing Y 2 O 3 and Al content. Complementary electron microscopy measurements reveal reactions between Y 2 O 3 and Al, even in nanoscale dispersoids, and the presence of micron-scale oxide slag inclusions in select specimens. A scaling analysis of mass and momentum transport within the melt pool, presented here, establishes that diffusional structural evolution mechanisms dominate for nanoscale dispersoids, while fluid forces and advection become significant for larger slag inclusions. These findings are developed into a theory of dispersoid structural evolution, integrating quantitative models of diffusional processes – dispersoid dissolution, nucleation, growth, coarsening – with a reduced order model of time-temperature trajectories of fluid parcels within the melt pool. Calculations of the dispersoid size in single-pass melting reveal a zone in the center of the melt track in which the oxide feedstock fully dissolves. Within this zone the final Y 2 O 3 size is independent of feedstock size and determined by nucleation and growth kinetics. If the dissolution zones of adjacent melt tracks overlap sufficiently with each other to dissolve large oxides, formed during printing or present in the powder feedstock, then the dispersoid structure throughout the build volume is homogeneous and matches that from a single pass within the dissolution zone. Gaps between adjacent dissolution zones result in oxide accumulation into larger slag inclusions. Predictions of final dispersoid size and slag formation using this dissolution zone model match the present experimental data and explain process-structure linkages speculated in the open literature.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Laser pulse shaping for additive manufacturing

The present disclosure relates to an apparatus for additively manufacturing a product in a layer-by-layer sequence, wherein the product is formed using powder particles deposited on an interface layer of a substrate. A laser generates first and second beam components. The second beam component has a higher power level and a shorter duration than the first beam component. A mask creates a 2D optical pattern in which only select portions of the second beam components can irradiate the powder particles. The first beam component heats the powder particles close to a melting point, where the particles experience surface tension forces relative to the interface layer. While the particles are heated, the second beam component further heats the particles and also melts the interface layer before the surface tension forces can act on and distort the particles, enabling the particles and the interface layer are able to bond together.

DeMuth, James A.↗

DOE OSTI2023

Laser pulse shaping for additive manufacturing

DeMuth, James A.↗

DOE OSTI2020

Binderjet Additive Manufacturing for Complex Heat Exchanger Geometries

Concentrated Solar Power (CSP) systems play a role in the worlds development of renewable energy. Mirrors are used to concentrate sunlight that is converted into electricity or other forms of useful energy. CSP impact depends significantly on its overall economics. The U.S. Department of Energy’s (DOE’s) Solar Energy Technology Office (SETO) cost goals for 2030include $0.05/kWh levelized cost of electricity (LCOE) for a baseload plant [1]. The power cycle cost goal is $900/kWe [1]. The envisioned recompression supercritical carbondioxide (sCO2) power cycle includes four heat exchangers, which together are at least ¾ of the total power cycle cost. Meeting the cost target requires reducing the heat exchanger cost. The 260 bar and 588 °C heat exchanger requirements are challenging. Shell and tube heat exchangers can meet the requirements, but the size and cost are prohibitive. State-of-the-art diffusion bonded printed circuit heat exchanger designs are 3 m3 or larger and expensive to manufacture. Additive manufacturing enables novel heat exchanger geometries that can reduce heat exchanger size and mass [2]. Binderjet technology is an additive manufacturing modality. It selectively deposits binder material onto the powder bed to form a solid part one layer at a time. Once applied, the binder is cured, the remaining powder removed, and the part heat treated in steps to remove the binder, sinter the metal powder, and densify the part. The Binderjet printing process is more than 10x faster than the best-known metal additive modality, direct metal laser melting (DMLM), thus enabling 10x the part through-put rate [3]. The high throughput rate results in a low-cost manufacturing process capable of creating complex heat exchanger geometries. This paper introduces a complex heat exchanger geometry and methods of Binderjet processing to fabricate the geometry.

Barua, Ananda↗

DOE OSTI2024

Evaluation of DED and LPBF Fe-based Alloys Process Application Envelopes based on Performance, Process Economics, Supply Chain Risks, and Reactor-specific Targeted Components

The U.S. Department of Energy (DOE), Office of Nuclear Energy (NE), Advanced Materials and Manufacturing Technologies (AMMT) program aims to develop extreme-environment materials solutions for use in the deployment of advanced nuclear reactors and the sustainment of the current fleet. To achieve this objective, a combination of experiment, a computational tool, and machine learning (ML) for the design of materials is adopted for the maturation of materials for nuclear technology. Through advanced manufacturing techniques such as laser powder bed fusion (LPBF) and laser powder direct energy deposition (LP-DED), components with complex geometries can be fabricated with reduced time and effort. Such advanced manufacturing methods can also provide the opportunity to improve materials performance through optimized microstructures and mechanical properties. However, existing engineering alloys are not always well suited for fabrication with additive manufacturing (AM), as their compositions have been tuned to optimize fabrication via conventional methods. Thus, similar alloys with modified compositions that are better suited for AM can be studied for improved performance. Over the past three years, the AMMT teams from Argonne National Laboratory (ANL) and Pacific Northwest National Laboratory (PNNL) studied various known Fe-based alloys by evaluating their initial printability using LPBF, and an AMMT-developed down-selection and decision matrix reduced the number of alloys to be studied from six to three in fiscal year (FY) 2024. Additionally, in FY 2024, for parallel evaluation, these three alloys were studied using LPDED. While LPBF is better for small- to medium-sized components with high detail and internal features, LP-DED combines a material feed system to place the powder onto the exact spot where the laser will melt the material. This AM method can be easily scaled to extremely large components and provides high build rate speeds compared to those of conventional LPBF systems. Additionally, DED is a better choice for complex geometries and compositional gradients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Development of Mischmetal–Fe–Co–B Permanent Magnet Alloys via High-Throughput Methods

Additive manufacturing synthesis using laser engineered net shaping (LENS) is utilized in this work to rapidly print libraries of mischmetal (MM = La, Ce, Nd, and Pr) containing R 2 TM 14 B alloys (R = MM + separated Nd and TM = Fe and Co) enabling robust evaluation of physical properties over a wide composition range. High-throughput characterization of the magnetic and thermal properties are used to identify compositions for potential high-temperature, high-performance permanent magnets with reduced critical rare-earth elements. Improved Curie temperature ( T c ~ 450 °C) is obtained with substitution of Fe by Co in pseudoternary R 2 TM 14 B alloys. Furthermore, a 4-fold decrease in the Nd content can be achieved through substitution with less critical Ce- and La-rich MM, while retaining high T c . Guided by the properties of the LENS printed samples, selected compositions with and without TiC additions are synthesized via melt-spinning techniques to produce nanostructured ribbons. The maximum room temperature coercivity ( H c ) and energy product ((BH) max ) without TiC are found to be 5.8 kOe, 8.5 MGOe, respectively, while TiC additions as a grain refiner gave H c and (BH) max of 4.9 kOe, 9.8 MGOe, respectively. Structural characterization of the melt-spun ribbons shows homogeneous grain refinement with TiC additions, which leads to an increase in the energy product.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Tracking of Marangoni driven motion during laser powder bed fusion

Laser Powder Bed Fusion (LPBF) can be used to create Functionally Graded Materials (FGMs) by selectively distributing property augmenting particles throughout the build matrix. With this method parts can be created with nonhomogeneous properties tuned to spatially varied, pre-determined design constraints. To unlock this capability, the fluid motion that occurs in the molten liquid phase must be thoroughly understood. More importantly, the actual tracking of motion during the LPBF process is needed. Further, a numerical model of heat transfer and fluid flow in LPBF process was created. Using results from the model the motion of particles starting at many different locations was tracked. The average change in position for these particles based on starting location was calculated. The effects of non-dimensional parameters on melt pool size were examined. These results were validated experimentally and compared to what is available in the literature.

42 ENGINEERING↗

DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Low-temperature selective laser sintering 3D printing of PEEK-Nylon blends: Impact of thermal post-processing on mechanical properties and thermal stability

Herein, a high-performance polymer (HPP) (polyether ether ketone, PEEK) blended with a commercial low-temperature polymer (polyamide 12, PA-12) was fabricated using a low-temperature selective laser sintering (SLS) 3D printer. Different post-processing heat treatments were implemented after fabrication to tune the thermal and mechanical properties of printed blends. The specific mechanical modulus of the blend was increased up to 79% in comparison to printed PA-12 samples with heat treatment. Additionally, the thermal resistance of the treated blends greatly exceeded the properties observed using PA-12 alone. This research proposes a methodology to fabricate and engineer HPP using desktop SLS printers through a secondary lower melting temperature material and heat treatments.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Additive Manufacturing of Cryogenic Austenitic Steel JK2LB via Wire-Fed Directed Energy Deposition (DED) for Fusion Energy Applications

This study explores the feasibility of fabricating cryogenic austenitic steel JK2LB via both laser-based directed energy deposition (laser-DED) and arc-based directed energy deposition (arc-DED) additive manufacturing processes for potential application in fusion reactors. JK2LB, a low-nickel, high-manganese stainless steel developed for ITER, offers excellent cryogenic toughness, radiation resistance, and decay-to-clearance characteristics. Although JK2LB was originally designed to endure cyclic stresses at cryogenic temperatures in tokamaks, its low-temperature mechanical integrity and radiation tolerance also make it a promising candidate for structural components, such as the coil case/support structure in nonplanar high-temperature superconducting magnet assemblies in stellarators. Directed energy deposition (DED) additive manufacturing was selected for this study due to its capability to fabricate large structures with complex geometries. Here, to address the long lead time and high cost associated with acquiring conventional JK2LB solid wire, JK2LB powder-cored wire was developed as the feedstock material. Testing blocks were then fabricated using both wire-fed laser-DED and arc-DED processes. Microstructural and compositional analyses revealed that both DED approaches yield fully austenitic phase and columnar grain structures. Mechanical testing at room temperature revealed that both DED routes achieved yield strength and elongation comparable to those of conventionally processed JK2LB via vacuum melting, electroslag remelting, extrusion, and drawing, though ultimate tensile strength was reduced due to Mn loss and large columnar grains. As a study mainly focusing on the additive manufacturing process, this work demonstrates the potential of additive manufacturing for fusion energy applications and provides a basis for optimization and future cryogenic mechanical evaluation.

Cryogenic steel↗

DOE OSTI2020

Wire-Based Additive Manufacturing of Stainless Steel Components

In this work three different wire-fed additive manufacturing (AM) processes were employed to evaluate differences between laser, arc, and electron beam heat sources used for high-deposition-rate AM on the order of 1 kg/h. Optimum weld and build parameters were developed independently to match the characteristics of each heat source using 308L stainless steel welding wire as the feedstock. Laser-wire AM was made with the lowest energy per unit length of weld and had the best control of the melt pool and surface finish. Wire arc-based AM had an intermediate energy per unit length of weld of approximately 5× that of the laser process, while electron beam wire AM had the highest energy per unit length of weld at approximately 10× that of the laser process. Analysis of the parts that were built included evaluation of mechanical properties and microstructures, and these properties are discussed with respect to the difference in input energy and cooling rates. Results show that all three processes build parts with properties that exceed those of annealed 304L wrought stainless steel. However, significant differences exist between the processes, and the results presented here can be used to help select the best wire-fed process for a given high-deposition-rate application.

36 MATERIALS SCIENCE↗

DOE OSTI2023

On the melt pool dynamic of voxel-controlled metal matrix composites via hybrid additive manufacturing: Laser powder bed fusion and ink-jetting

In this study, the effect of the addition of reinforcement nanoparticles to the 316L matrix by adopting ex-situ and in-situ method (drop on demand jetting) to produce 316L/Al 2 O 3 nanocomposite was investigated. In the ex-situ method, the Al 2 O 3 nanoparticles (NPs) were lightly mixed with 316L powder and processed by laser powder bed fusion. In the in-situ method, an ethanol-based ink containing Al 13 nanoclusters (NCs) was added to 316L powder and then processed by laser. Both ex-situ and in-situ method produced nanocomposites with Al-Si-Mn-O-enriched precipitations within the 316L matrix. The addition of NPs/NCs to the 316L matrix, altered the geometrical characteristic of the single-track melt pools. At the same laser power, with increasing the amount of Al 2 O 3 NPs and Al 13 NCs the melt pool deepened due to reduced thermal conductivity and prolonged liquid presence. Further, as a result, 316L/1 wt% Al 13 NCs deposited single track showed larger grains in comparison to 316L single track. At a high laser power of 150W, the Marangoni flow and the buoyancy force caused the nanoparticles to agglomerate and float to the top surface of tracks; therefore, the wt% fraction of precipitation was drastically reduced due to the loss of Al. The 316L/Al 2 O 3 NPs and 316L/Al 13 NCs exhibited the microhardness of 285 ± 13 HV and 293 ± 7 HV, respectively, higher than the deposited 316L single track, 265 ± 15 HV. Lastly, a hybrid LPBF+ink-jet printer was adopted to selectively change the composition of different zones by adding Al 13 NCs ink to 316L and producing a voxel-controlled metal matrix composite.

316L↗

DOE OSTI2025

Microstructural evolution and phase stability in Nb-containing interstitial Fe-Mn-Co-Cr-C high-entropy alloys: An in-situ synchrotron X-ray diffraction study during laser melting

The influence of Nb on phase stability and microstructural evolution in an interstitial Fe-Mn-Co-Cr-C high-entropy alloy was investigated using in-situ synchrotron X-ray diffraction (SXRD) during laser melting. Scheil-Gulliver simulations predict the formation of σ and γ-f.c.c. phases in all three alloys, along with NbC in Nb-containing compositions. SXRD confirmed the presence of most predicted phases, but the σ phase was absent. Nb promotes crystallite refinement and increases dislocation density, though excessive additions reduce refinement efficiency due to solubility limits and secondary phase formation. Furthermore, Nb addition also enhances ε-h.c.p. phase formation by reducing stacking fault energy through NbC-induced carbon depletion. Analysis of intensity peak evolution reveals that Nb alters preferred grain orientations, reducing {111} γ intensity while enhancing {220} γ , leading to a more isotropic grain distribution. Overall, Nb plays a key role in phase selection, microstructure refinement, and preferred orientation evolution, allowing the tailored microstructure of high-entropy alloys via rapid solidification.

Interstitial high entropy alloys↗

DOE OSTI2026

In-situ sensor monitoring of multi-class gas porosity formation in laser powder bed fusion using convolutional neural network

In-situ monitoring of defect formation remains a significant challenge in the laser powder bed fusion (LPBF) process. Recent advances have enabled real-time defect detection with machine learning and in-situ sensing technologies; however, most studies focus on binary classification of keyhole pores, limiting nuanced multi-class pore differentiation and formation mechanisms. This work introduces a multi-class pore detection framework (no pore, small pores < 15 µm, and large pores > 15 µm) by leveraging photodiode sensor data alongside high-fidelity synchrotron X-ray imaging. The 15 µm threshold is selected to distinguish between two fundamentally different defect mechanisms, following the physical size-mechanism boundary established by prior high-resolution synchrotron X-ray characterization of Al6061 LPBF. Distinguishing these classes is critical because large keyhole pores are structurally detrimental, whereas small gas pores are often benign, requiring different process control strategies. Thermal emission monitoring data collected simultaneously with high-speed X-ray imaging at the Stanford Synchrotron Radiation Lightsource (SSRL), are correlated with subsurface melt pool dynamics to establish ground truth. Continuous Wavelet Transform (CWT) with optimized parameters converts the photodiode time-series signals into time–frequency images, facilitating feature extraction. Convolutional Neural Networks (CNN) are then applied for real-time multi-class pore classification in an average inference time of 1 ms per signal window. It achieves 79% accuracy and an Area Under the Receiver Operating Characteristic curve (AUC ROC) score of 0.89 with five-fold cross-validation. The results demonstrate that coupling CWT-based feature engineering with CNN architecture enables reliable multi-class pore detection in Al6061 builds using affordable in-situ sensors. This approach advances scalable and affordable quality assurance in additive manufacturing by moving beyond binary defect detection toward more nuanced classification of porosity mechanisms with in-situ sensors and machine learning.

Laser powder bed fusion, Multi-class pores, In-sit↗

DOE OSTI2022

Optimization of stochastic feature properties in laser powder bed fusion

Process parameter selection in laser powder bed fusion (LPBF) controls the as-printed dimensional tolerances, pore formation, surface quality and microstructure of printed metallic structures. Measuring the stochastic mechanical performance for a wide range of process parameters is cumbersome both in time and cost. As such, in this study, we overcome these hurdles by using high-throughput tensile (HTT) testing of over 250 dogbone samples to examine process-driven performance of strut-like small features, ~1 mm 2 in austenitic stainless steel (316 L). The output mechanical properties, porosity, surface roughness and dimensional accuracy were mapped across the printable range of laser powers and scan speeds using a continuous wave laser LPBF machine. Tradeoffs between ductility and strength are shown across the process space and their implications are discussed. While volumetric energy density deposited onto a substrate to create a melt-pool can be a useful metric for determining bulk properties, it was not found to directly correlate with output small feature performance.

316 L stainless steel↗

DOE OSTI2021

Hybrid of multi‐dimensional fillers for thermally enhanced polyamide 12 composites fabricated by selective laser sintering

Abstract Selective laser sintering (SLS) is an additive manufacturing technology that can provide a novel strategy to manufacture complex polymer‐based composites with tailored properties. In this study, polyamide 12 (PA12) composite powders based on Al 2 O 3 , boron nitride (BN), and carbon nanotubes (CNTs) were prepared via a two‐step mixing approach. Morphology characterization techniques indicated that the fillers were uniformly dispersed in the PA12 matrix as expected. Under the optimum 3D‐printing parameters, the fabrication of SLS parts with high filler loading could be obtained. With 40 wt% Al 2 O 3 , 8 wt% BN, and 2 wt% CNT hybrid fillers, the thermal conductivity of PA12 composites could reach 1.09 W/mK. It could be attributed to the synergistic effect of multi‐dimensional fillers to form dense and continuous thermal conduction paths. The factors influencing the performance of PA12 composites such as melting and crystallization behaviors, dielectric properties, and mechanical properties were also discussed. The results show that these composites have favorable dielectric and mechanical properties. Overall, the PA12 composites fabricated by SLS technology in this study exhibit excellent thermal management ability.

Yuan, Yue↗

DOE OSTI2021

Melt Pool and Heat Treatment Optimization for the Fabrication of High-Strength and High-Toughness Additively Manufactured 4340 Steel

Additively manufactured (AM) components offer superior design flexibility compared to their conventionally manufactured counterparts, and optimizing processing parameters is key to achieving high-quality depositions with desirable and predictable mechanical properties. This study was focused on 4340 steel fabricated using laser powder bed fusion (LPBF), and 42 laser power and scan speed combinations have been systematically investigated to determine an optimized melt pool geometry that would ensure fully-dense parts. The AM material was compared with a wrought 4340 equivalent and studied in two customized heat treated conditions, optimized for strength and toughness, respectively. The microstructures of the as-fabricated and heat treated AM and wrought materials were characterized to assess differences introduced by the layer-by-layer fabrication process and subsequent heat treatment. Tensile properties of both materials were also evaluated and demonstrate that the AM materials offer equal or superior properties compared to the wrought equivalents. Differences in fracture surface morphologies indicate the distinct failure mechanisms associated with the materials’ characteristic microstructures, and the role of inclusions in the failures was studied to elucidate these differences. Complementary to the experimental investigations, the dataset was leveraged to make recommendations for future design of experiments to optimize AM build parameters in other material systems. A statistical Monte Carlo analysis was used to predict the interpolation error produced using reduced datasets and to enable informed processing parameters selection. These findings are discussed to make recommendations for the use of AM materials for high-integrity structural applications.

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 full-scale 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.

99 GENERAL AND MISCELLANEOUS↗