Blog | UES, Inc.

2024 Research Featuring Robo-Met Capabilities

Written by Sundar | Oct 1, 2024 6:18:47 PM

Every year our customers and teams find interesting applications to investigate. Learn more some of this year's new insights uncovered through Robo-Met.3D®'s automated serial sectioning here. Contact us to learn more about how you can use Robo-Met to get the material insights you need today.

 
Category: Structural Materials (Metals, Composites)

Characterization of direct ink writing carbon fiber composite structures with serial sectioning and DREAM.3D

Direct Ink Writing (DIW) combines the flexibility of 3D printing with increased material applications such as thermoset carbon fiber composites, ceramic composites, and metals. The usefulness of direct ink writing, like many additive manufacturing (AM) processes, remains limited for reasons ranging from quality control to lack of process parameter optimization. This study looks to introduce a methodology for characterizing direct ink written carbon fiber composites to facilitate exploration into the relationships between process parameters and material structure. The presented study utilized nine 3D specimens of direct ink writing carbon fiber composites printed with varying process parameters - speed differential, layer height, step-over distance, and nozzle diameter - as the data set. The data was collected with an automatic serial sectioning system, LEROY, from the Air Force Research Laboratory. The collected data was processed in DREAM.3D and analyzed with statistical comparisons of 2D orientation distributions of the fibers, 2D size distributions of the voids, and 2D shape distributions of the voids.

Citation: Clarke, K. M., Groeber, M., Wertz, J., Abbott, A., Haney, R., & Chapman, M. (2024). Characterization of direct ink writing carbon fiber composite structures with serial sectioning and DREAM. 3D. Composite Structures, 118730.

Comparative Study of High-Cycle Fatigue and Failure Mechanisms in Ultrahigh-Strength CrNiMoWMnV Low-Alloy Steels

This study provides a thorough analysis of the fatigue resistance of two low-alloy ultrahigh-strength steels (UHSSs): Steel A (fully martensitic) and Steel B (martensitic–bainitic). The investigation focused on the fatigue behaviour, damage mechanisms, and failure modes across different microstructures. Fatigue strength was determined through fully reversed tension–compression
stress-controlled fatigue tests. Microstructural evolution, fracture surface characteristics, and crack initiation mechanisms were investigated using laser scanning confocal microscopy and scanning
electron microscopy. Microindentation hardness (HIT) tests were conducted to examine the cyclic hardening and softening of the steels. The experimental results revealed that Steel A exhibited superior fatigue resistance compared to Steel B, with fatigue limits of 550 and 500 MPa, respectively.

Fracture surface analysis identified non-metallic inclusions (NMIs) comprising the complex MnOSiO2 as critical sites for crack initiation during cyclic loading in both steels. The HIT results after fatigue indicated significant cyclic softening for Steel A, with HIT values decreasing from 7.7 ± 0.36 to 5.66 ± 0.26 GPa. In contrast, Steel B exhibited slight cyclic hardening, with HIT values increasing from 5.24 ± 0.23 to 5.41 ± 0.31 GPa. Furthermore, the martensitic steel demonstrated superior yield and tensile strengths of 1145 and 1870 MPa, respectively. Analysis of the fatigue behaviour revealed the superior fatigue resistance of martensitic steel. The complex morphology and shape of the NMIs, examined using the 3D microstructure characterisation technique, demonstrated their role as stress concentrators, leading to localised plastic deformation and crack initiation.

Citation: Hamada, A., Ali, M., Ghosh, S., Jaskari, M., Allam, T., Schwaiger, R., ... & Mattar, T. (2024). Comparative Study of High-Cycle Fatigue and Failure Mechanisms in Ultrahigh-Strength CrNiMoWMnV Low-Alloy Steels. Metals, 14(11), 1238.

 

Category: Additive Manufacturing

NASA's Office Safety Mission Assurance Efforts to Improve Non-destructive Evaluation Methods for Additive Manufacturing and In-Space Inspection

The OSMA NDE Development Program is structured within NASA to
explore and apply advanced NDE tools across the agency. OSMA includes the  Mission Assurance Standards and Capabilities Division, 
Missions and Programs Assessment Division, Institutional 
Safety Management Division, and NASA Safety Center, as well 
as the Independent Verification and Validation Program. This presentation outlines OSMA's efforts in evaluating and integrating various NDE methods (ultrasound, CT, in situ monitoring), as well as efforts to validate these methods, including Robo-Met.

Citation: Burke, E., Juarez, P., Mavo, J., Subedi, R., Jones, J., & Bescup, J. (2024, October). NASA's Office Safety Mission Assurance Efforts to Improve Non-destructive Evaluation Methods for Additive Manufacturing and In-Space Inspection. In ASTM International Conference on Advanced Manufacturing.

Validation of x-Ray Computed Tomography Detection Limits for Stochastic Flaws in Additively Manufactured Ti-6Al-4 V

X-ray computed tomography (XCT) continues to be a primary means of defining flaw populations in fatigue-critical components fabricated by additive manufacturing (AM), and therefore, defining the detection capability of XCT is necessary. Stochastic flaw populations from four samples from a laser powder bed fusion (L-BPF) build of Ti-6Al-4V fatigue specimens were interrogated with XCT scans at various voxel sizes, followed by automated optical serial sectioning (AOSS) with a Robo-Met.3D system as a higher fidelity technique for comparison. Data sets were registered and processed with an automated defect recognition (ADR) algorithm. Comparison of the detected flaw populations showed a two to three orders of magnitude greater quantity in the AOSS data, with significant improvement in the XCT detection rate with refinement of voxel size. Although refined voxel size XCT scans revealed additional flaws, detection of 90% of the “ground truth” flaws present in the AOSS data was not achieved until flaws reached a size of 7-17 times the voxel size of the XCT scan. The need for additional study of targeted flaw sizes to validate and refine these predictions was identified.

Three-Dimensional Reconstruction of Defects and Structures in Additively Manufactured Parts with Automated Serial Sectioning

Metal additive manufacturing (AM) processes have been demonstrated to be effective at reducing costs and lead times associated with complex components for space flight applications. Laser powder bed fusion (L-PBF) is a commonly used AM technology due to the ability to produce complex parts with fine feature resolution in a wide variety of alloys and applications. L-PBF, like many other manufacturing processes, can produce minor flaws in parts when in nominal operation as well as process-escape defects when process abnormalities occur. The effects of the flaws and methods of detecting the flaws are a subject of interest to understand the difficulties in detecting these flaws with current technology and how much risk the flaws or defects pose to potential flight parts. Using a RoboMet.3D automated serial sectioning system, seeded defects as well as minor process flaws can be imaged and reconstructed in three dimensions to compare to non-destructive evaluation (NDE) techniques, such as x-ray computed tomography (CT), neutron CT, and in-situ monitoring. The RoboMet automates the metallography process by automatically grinding, polishing, and imaging samples in a single system and providing the control data for NDE comparisons to know the real size of defects built into coupons. These comparisons provide an understanding behind the technological limitations of the NDE techniques for different alloys. The same serial sectioning methods have also been utilized to characterize the surfaces of parts to reconstruct the surfaces and take measurements of internal features not easily examined with non-destructive methods. Using the RoboMet, fine lattice structures built with L-PBF have been characterized to determine the actual thicknesses of struts and density of the lattice structures. These structures have been used as finer build supports for the L-PBF process, designs for fine catalysts, and other design considerations for small components. The RoboMet data helps to inform the modeling and design efforts around these fine components.

Citation: Katsarelis, C., Medders, M., Tirado, F. R., Lanigan, E., Mavo, J., Duquette, D., & Caffrey, J. (2024, May). Three-Dimensional Reconstruction of Defects and Structures in Additively Manufactured Parts with Automated Serial Sectioning. In Marshall Jamboree & Poster Expo.

Melt pool width measurement in a multi-track, multi-layer laser powder bed fusion print using single-camera two-wavelength imaging pyrometry.

In laser powder bed fusion (LPBF) additive manufacturing, melt pool characterization is one of the potential approaches toward rapid process qualification and efficient non-destructive evaluation of printed parts. Especially melt pool width measurement is crucial for understanding the print process regimes, estimating the solidified melt pool depth, and identifying any process anomalies, among other attributes of interest. While existing works focus on monitoring melt pools of single scan tracks or single layer prints, melt pool characterization for a multi-track multi-layer (MTML) LPBF print has not been extensively studied. In this work, we employ our lab-designed coaxial single-camera two-wavelength imaging pyrometry (STWIP) system to monitor in-situ melt pool properties during a MTML LPBF process. The STWIP-measured melt pool widths are validated using a serial sectioning machine (Robo-Met, UES). The in-situ STWIP and ex-situ Robo-Met measurement data are in close agreement with each other, having a mean absolute error and root mean squared error of 9.83 μm and 16.53 μm, respectively. Furthermore, we demonstrate the successful mapping of melt pool location and melt pool size on the printed MTML part. In sum, this work demonstrates the capability and the applicability of STWIP for accurate large-scale melt pool monitoring during LPBF processing of practical parts, thereby facilitating the development of LPBF process models and control strategies.

Citation: Vallabh, C. K. P., Zhang, H., Anderson, D. S., To, A. C., & Zhao, X. (2024). Melt pool width measurement in a multi-track, multi-layer laser powder bed fusion print using single-camera two-wavelength imaging pyrometry. The International Journal of Advanced Manufacturing Technology, 132(5), 2575-2585.

In-Situ Infrared Camera Monitoring for Defect and Anomaly Detection in Laser Powder Bed Fusion: Calibration, Data Mapping, and Feature Extraction

Laser powder bed fusion (LPBF) process can incur defects due to melt pool instabilities, spattering, temperature increase, and powder spread anomalies. Identifying defects through in-situ monitoring typically requires collecting, storing, and analyzing large amounts of data generated. The first goal of this work is to propose a new approach to accurately map in-situ data to a three-dimensional (3D) geometry, aiming to reduce the amount of storage. The second goal of this work is to introduce several new IR features for defect detection or process model calibration, which include laser scan order, local preheat temperature, maximum pre-laser scanning temperature, and number of spatters generated locally and their landing locations. For completeness, processing of other common IR features, such as interpass temperature, heat intensity, cooling rates, and melt pool area, are also presented with the underlying algorithm and Python implementation. A number of different parts are printed, monitored, and characterized to provide evidence of process defects and anomalies that different IR features are capable of detecting.

Citation: Hinnebusch, S., Anderson, D., Bostan, B., & To, A. C. (2024). In-Situ Infrared Camera Monitoring for Defect and Anomaly Detection in Laser Powder Bed Fusion: Calibration, Data Mapping, and Feature Extraction. arXiv preprint arXiv:2407.12682.

Enhancing Image Processing in Single-camera Two-wavelength Imaging Pyrometry for Advanced In-situ Melt Pool Measurement in Laser Powder Bed Fusion

For in-situ measurement of the melt pool (MP) temperature profile in the laser powder bed fusion (LBPF) additive manufacturing (AM) process, a new technology is the single-camera two-wavelength imaging pyrometry (STWIP). Accurate temporally and spatially resolved MP temperature field measurement using this STWIP method requires a precise profiling of pixel-wise two-wavelength intensity ratio, which is highly dependent on optical alignment, and camera's spectral sensitivity, among other factors. Thus, it is essential to develop an accurate, robust, and fast transformation method for reliable and effective mapping of two-wavelength images acquired from the STWIP system. In this work we propose a Blob analysis-based MP guided Image Transformation (BMPIT) method as opposed to the typical feature detector descriptor-based image transformation approach like KAZE. The BMPIT's performance is assessed and compared with the KAZE in terms of efficiency, execution time, accuracy, and robustness. An experiment using a standard calibrated tungsten filament strip lamp is done to validate the effectiveness of BMPIT. Compared to the KAZE, the BMPIT successfully transformed 100% of the MP images with higher accuracy and faster speed. It is also shown that the BMPIT is a robust technique for image transformation, unaffected by the image size, MP position, and surrounding noise. Moreover, experimental ground truth data collected using Type C thermocouples implanted into an Inconel-718 build plate are used to further validate the LPBF MP temperature estimation accuracy of BMPIT-aided STWIP. Unlike KAZE, temperature estimated by BMPIT agrees well (error <5%) with both the lamp and thermocouple experiments. BMPIT is an appealing alternative for online measurement due to its reduced execution time, it takes only one fifth of the time that KAZE takes to transform two-wavelength images. In addition, the BMPIT can be used to calculate MP width, which is validated by comparing with ex-situ characterization. It enables a high level of agreement (with an error less than 1.89%) between MP images of two wavelengths. Overall, the BMPIT greatly improves STWIP image processing, allowing for measuring MP temperature and morphology more rapidly, accurately, and precisely. The developed BMPIT approach can be employed as part of a STWIP-feedback LPBF process control system to improve the quality of additively manufactured metal products.

Citation: Alam, M. J., Zhang, H., & Zhao, X. (2024). Enhancing Image Processing in Single-camera Two-wavelength Imaging Pyrometry for Advanced In-situ Melt Pool Measurement in Laser Powder Bed Fusion. Precision Engineering.

Comparative Analysis of Internal Porosity in AM Ti64 using X-ray Computed Tomography and Mechanical Polishing Serial Sectioning

X-ray computed tomography (XCT) is a widely adopted nondestructive technique for characterizing internal porosity in additive manufactured (AM) components. However, the accuracy and precision of porosity characterization using XCT can be affected by factors such as XCT system configuration and post-processing methodologies. This study investigates the influence of these variables on porosity characterization by comparing results obtained from four different XCT systems and two distinct analysis workflows applied to a single metallic AM sample. A benchmark is also established for the XCT performance by using a high-resolution reference dataset generated through mechanical polishing serial sectioning (MPSS). Porosity metrics, including volume fraction, pore count, size distribution, and equivalent spherical diameter (ESD), were computed for large pores (≥ 84 μm) within the XCT and MPSS datasets. By comparing these metrics across XCT systems and workflows, this research aims to demonstrate the variability introduced by different XCT configurations and analysis procedures, providing insights into the potential limitations and uncertainty considerations needed while carrying out XCT-based porosity characterization of AM components.

Citation: Jolley, B., Knott, C., Sparkman, D., & Uchic, M. (2024). Comparative Analysis of Internal Porosity in AM Ti64 using X-ray Computed Tomography and Mechanical Polishing Serial Sectioning. IEEE Open Journal of Instrumentation and Measurement.

3D Reconstruction of a High-Energy Diffraction Microscopy Sample Using Multi-modal Serial Sectioning with High-Precision EBSD and Surface Profilometry.

High-energy diffraction microscopy (HEDM) combined with in situ mechanical testing is a powerful nondestructive technique for tracking the evolving microstructure within polycrystalline materials during deformation. This technique relies on a sophisticated analysis of X-ray diffraction patterns to produce a three-dimensional reconstruction of grains and other microstructural features within the interrogated volume. However, it is known that HEDM can fail to identify certain microstructural features, particularly smaller grains or twinned regions. Characterization of the identical sample volume using high-resolution surface-specific techniques, particularly electron backscatter diffraction (EBSD), can not only provide additional microstructure information about the interrogated volume but also highlight opportunities for improvement of the HEDM reconstruction algorithms. In this study, a sample fabricated from undeformed “low solvus, high refractory” nickel-based superalloy was scanned using HEDM. The volume interrogated by HEDM was then carefully characterized using a combination of surface-specific techniques, including epi-illumination optical microscopy, zero-tilt secondary and backscattered electron imaging, scanning white light interferometry, and high-precision EBSD. Custom data fusion protocols were developed to integrate and align the microstructure maps captured by these surface-specific techniques and HEDM. The raw and processed data from HEDM and serial sectioning have been made available via the Materials Data Facility (MDF) at https://doi.org/10.18126/4y0p-v604 for further investigation.

Citation: Sparks, G., Mason, S. A., Chapman, M. G., Park, J. S., Sharma, H., Kenesei, P., ... & Obstalecki, M. (2024). 3D Reconstruction of a High-Energy Diffraction Microscopy Sample Using Multi-modal Serial Sectioning with High-Precision EBSD and Surface Profilometry. Integrating Materials and Manufacturing Innovation, 13(3), 773-803.

Comparison of Full-Field Crystal Plasticity Simulations to Synchrotron Experiments: Detailed Investigation of Mispredictions

Crystal plasticity-based digital twins are an alternative to expensive and time-consuming experiments for the investigation of micro-mechanical material behavior. However, before using simulations as an alternative for experiments, the capabilities and limitations of the modeling approach need to be known. This is best done by juxtaposing the predictions of digital twins against experimental data. The present work assesses the capabilities of full-field crystal plasticity simulations in an additively manufactured (AM) nickel-based superalloy that was characterized in situ by high-energy X-ray diffraction microscopy and electron backscatter diffraction as part of challenge 4 of air force research laboratory’s AM modeling challenge series. To ensure that the grains of interest are initialized with the measured eigenstrains, a novel scheme is proposed and its performance is evaluated. The overall agreement between simulation and experiment is assessed and compared to previous studies using the same dataset and aspects for which a systematic disagreement is seen are discussed.

Citation: Prabhu, N., & Diehl, M. (2024). Comparison of Full-Field Crystal Plasticity Simulations to Synchrotron Experiments: Detailed Investigation of Mispredictions. Integrating Materials and Manufacturing Innovation13(3), 804-826.

Category: Advanced Capabilities and Applications

Application of Polarized Light Microscopy for 3D Materials Science

For many polycrystalline materials, properties are directly influenced by the crystallographic orientation of the grains. Modern characterization techniques such as Electron backscatter diffraction (EBSD) can quantify crystallographic texture, though this approach is typically limited to sub-millimeter length scales and requires specialized equipment. Furthermore, extensions of two-dimensional crystallographic characterization techniques to the third dimension using destructive methods, e.g. 3D-EBSD, dramatically increases the effort required for data collection, especially for increasing sample dimensions [1, 2]. In some cases, the high resolution and fidelity of these methods directly competes with the benefits of faster collection time over larger sample dimensions. As such, there is currently a resurgence of interest in combining quantitative light microscopy techniques and computational methods to extract pertinent crystallographic information [3]. In this work, we pursue the application of polarized light microscopy (PLM) for 3D materials science to expand the portfolio of experimental methods for rapid determination of crystallographic orientation in centimeter-scale volumes.

Citation: Chao, P., Oakley, R. M., & Polonsky, A. T. (2024). Application of Polarized Light Microscopy for 3D Materials Science. Microscopy and Microanalysis, 30(Supplement_1).

Large-Scale 2D and 3D Orientation Datasets Obtained Using SRAS

The paper will introduce a new instrument for the destructive three-dimensional (3D) characterization of microstructures, including their crystallographic orientation. The system consists of a Robo-Met.3D serial sectioning and imaging system, but with a unique variant of an emerging characterization technique (spatially resolved acoustic spectroscopy, SRAS) that permits the mapping of grain orientation through the measurement of the velocities of surface acoustic waves, induced and measured at a sub-grain level. A distinguishing characteristic of SRAS is that it enables the collection of orientation microscopy datasets over very large areas (103-105 mm2) in a very short periods of time (102-105 sec). To enable 3D characterization, SRAS is configured to collect data in a manner geometrically analogous to an inverted microscope, permitting co-planar analysis and digital registration of datasets representing both stitched optical micrograph mosaics and a continuous (non-stitched) map representing the orientation of grains. This technique has been demonstrated and applied to a range of problems of relevance for titanium alloys, including both 2D and 3D problems. For the former, two exemplars will be presented, including (i) the orientation microscopy of large area electron beam additively manufactured Ti-6Al-4V and (ii) compositionally graded structures. For the latter, the 3D SRAS method has been applied to characterize beta titanium alloys as well as to characterize microtexture regions (MTRs).

Citation: Ales, T.K., Collins, P. C.  (2024). LARGE-SCALE 2D and 3D ORIENTATION DATASETS OBTAINED USING SPATIALLY RESOLVED ACOUSTIC SPECTROSCOPY. In Proceedings of the 15th World Conference on Titanium 2024.

Distributed strain sensing using Bi-metallic coated fiber optic sensors embedded in stainless steel

Silica fiber optic sensors are resistant to corrosive environments and high temperatures, making them attractive candidates for harsh conditions found in nuclear and aerospace industries. Moreover, fibers can be deployed remotely for continuous measuring of spatially distributed temperatures and strains. This study investigated embedding a Ni/Cu bi-metallic coated fiber in a stainless-steel 316 (SS316) matrix using laser powder bed fusion towards functionalizing metal components for site-specific health monitoring. The embedded fiber was continuously interrogated during controlled heating to 1000°C. The measured fiber strains were similar to the expected differential thermal strains between the fiber and the SS316 matrix, until divergent behavior was observed at temperatures >500°C. No debonding at the matrix–coating–fiber interfaces was observed during microscopy, but significant interactions between the coatings and matrix resulted in diffusion-driven chemistry variations and Kirkendall void formation. Applying the strain-lag theory revealed plastic behavior in the Ni coating at temperatures >500°C, limiting the strain transfer to the fiber at higher temperatures. It was estimated that the elastic modulus in the Ni coating had decreased from ∼200 GPa at room temperature to below 40 GPa, starting at 600°C. The low elastic modulus above 600°C is within the margin of what the tangent modulus would be in the case of bilinear isotropic hardening. Regardless of the divergent strain transfer at higher temperatures, the fiber was exposed to the equivalent of 1.9 % engineering strain at 1000°C, but measured only a 0.7 % engineering strain due to the poor strain transfer. Although compensating for the plastic behavior of Ni proved challenging, the bonding of a brittle silica fiber to a metal matrix surviving to 1000°C invites potential iterations on coating material for future application. For example, the embedded fiber is sufficient for acoustic energy transfer, realizing high temperature distributed acoustic sensing.

Citation: Hyer, H. C., & Petrie, C. M. (2024). Distributed strain sensing using Bi-metallic coated fiber optic sensors embedded in stainless steel. Additive Manufacturing91, 104355.

The Analytical Science Group at GRC

The Analytical Science Group is a comprehensive materials characterization solution.The ASG laboratories have advanced capabilities for characterizing the behavior, identifying the failure mechanisms, and assisting in the development of next-generation materials systems. The ASG staff has decades of experience dealing with the materials of interest to the hypersonics community (Ni-base superalloys, ceramic matrix composites, environmental and thermal barrier coatings, etc.)

Citation: Kulis, M. (2024, April). The Analytical Science Group at GRC. In AFRL-GRC Hi Temperature Materials and Structures TIM.

 

Robust Data-Driven Predictive Run-to-Run Control for Automated Serial Sectioning

This paper presents a one-step predictive run-to-run controller (R2R-MPC) for the automation of mechanical serial sectioning (MSS), a destructive material analysis process. To address the inherent uncertainty and disturbances in the MSS process, a robust closed-loop approach is presented. The robust R2R-MPC models the uncertainty of the MSS process using a linear differential inclusion. As an analytical model of the MSS process is unavailable, the differential inclusion is identified from historical data. The R2R-MPC is posed as an optimization problem that computes incremental changes to the control input which minimize the worst-case material removal errors. This optimization-based controller is combined with a run-to-run controller to provide integral action that rejects constant disturbances and tracks constant reference removal rates. To demonstrate the efficacy of our robust R2R-MPC, we present simulation results which compare the presented controller with a conventional non-robust R2R.3.

Citation: Oakley, R. M., Polonsky, A. T., Chao, P., & Danielson, C. (2024). Robust Data-Driven Predictive Run-to-Run Control for Automated Serial Sectioning. IEEE Control Systems Letters.

Category: Dissertations

In this work, in-situ alloying of a dispersion strengthened copper alloy made via laser powder bed fusion (LPBF) and the effect of hot isostatic pressing on the materials properties were examined. Dispersion strengthened copper alloys such as GRCop-42 that contain 7 vol% of Cr2Nb are used in high temperature applications such as rocket engines. This work examines the effects of HIP post processing on an in-situ alloyed dispersion strengthened Cu alloy. Elemental powders of Cu, Cr and Nb were mixed and used to print two different builds with different print settings that were characterized in the as-deposited and HIP conditions. Microstructure characterization included porosity measurements, metallography, EBSD, SEM, and EDS to examine the effectiveness of in-situ alloying to create Cr2Nb during AM as well as details of the dispersoids, grain morphology, and texture in the as-built and HIPed condition. Mechanical properties including tension, fatigue, and creep properties of the as-built and HIPed material were also determined. Uniaxial tension testing at 25˚ C, 400˚ C, and 600˚ C was conducted and Four-point bend fatigue at a load ratio, R = 0.1, was conducted on material to create S-N plots. Vacuum creep testing at 500˚ C, 650˚ C, and 800˚ C was also conducted on HIPed material, and all fracture surfaces were examined in the SEM. Results from characterization of the in-situ alloyed Cu alloy were compared to literature values for dispersion strengthened copper alloys. In summary, in-situ alloying of the dispersion strengthened copper alloy was demonstrated but improved printing parameters will be needed to produce fully dense materials with complete conversion of Cr2Nb. The effectiveness of HIP was dependent upon the degree of interconnected porosity in the as-deposited material.

Citation: Smith, J. L. (2024). Effects of Hot Isostatic Pressing on the Mechanical Properties of In-Situ Alloyed Dispersion Strengthened Copper Alloy Made Via Laser Powder Bed Fusion (Master's thesis, Case Western Reserve University).

Exploration and Modeling of In Situ Alloying via Additive Manufacturing for Dispersion Strengthened Copper Alloys X-Ray Computed Tomography and Mechanical Polish Serial Sectioning

In situ alloying is a technique in additive manufacturing that uses elemental powder blends to produce an alloy simultaneously while fabricating a desired geometry. This technique has the potential to benefit materials development by enabling rapid discovery of new alloys through a simplified method to blend new compositions, reduce the dependence of the growing additive manufacturing industry on pre-alloyed powder supply chains, and add compositional design freedom to additive manufacturing for seamless functionally gradient materials. Current research on in situ alloying via additive manufacturing has largely focused on eutectic alloys. Little research has been done on dispersion strengthened alloys, especially those where the alloying reaction is a small proportion of the overall composition. The present work explores the influence of energy in the additive manufacturing melt pool during in situ alloying of dispersion strengthened GRCop alloys (2:1 atomic ratio of Cr and Nb, balance Cu), where the dispersoid phase (Cr2Nb) is less than 7 wt% of the alloy. The energy in the melt pool was examined through differential scanning calorimetry experiments and modeled using melt pool dimension models. The models were validated with single track line scans varying the laser power from 60 W to 825 W and velocity from 100 mm/s to 1300 mm/s. Calibrated models produced isothermal maps that enabled discussion of the melt pool convection and cooling rate. A schematic of what occurs in an in-situ alloying melt pool from first heating to final solidification was constructed. The repeatability of in situ alloying was examined through the production of bulk material in the as-built condition. Density, chemistry, microstructure, and mechanical properties for the as-built material were examined and related to the modeled melt pool energy. Through this work, in situ alloying of dispersion strengthened copper alloys was demonstrated and patented. The largest copper alloy melt pool dimension database to date was constructed to support model validation. The validated melt pool dimension models can predict the experimentally measured melt pool dimensions with as little as 10% error. An increase in the melt pool width, increase in convection, and a decrease in cooling rate each improved the success of in situ alloying.

Citation: Scannapieco, D. S. (2024). Exploration and Modeling of In Situ Alloying via Additive Manufacturing for Dispersion Strengthened Copper Alloys (Doctoral dissertation, Case Western Reserve University).

Category: References Citing Robo-Met

  • Čermák, J., Ambrož, O., Jozefovič, P., & Mikmeková, Š. (2024). Enhancing precision and safety in metallographic sample preparation: Reduce the stochasticity and workload with robotization. Practical Metallography, 61(9-10), 589-613.
  • Fowler, J. E., Ruggles, T. J., Cillessen, D. E., Johnson, K. L., Jauregui, L. J., Craig, R. L., ... & Boyce, B. L. (2024). High-Throughput Microstructural Characterization and Process Correlation Using Automated Electron Backscatter Diffraction. Integrating Materials and Manufacturing Innovation13(3), 641-655.

  • Lemiasheuski, A., Kranzmann, A., & Pfennig, A. (2024). Challenges and possibilities of the manual metallographic serial sectioning process using the example of a quantitative microstructural analysis of graphite in cast iron. Practical Metallography61(9-10), 746-768.

  • Johnstone, B., Massey, C., Lewis, M., Huggins, W., Saleeby, K., & Saldaña, C. (2024, June). Quantifying Trapped Powder in Electron Beam Powder Bed Fusion. In International Manufacturing Science and Engineering Conference (Vol. 88100, p. V001T01A030). American Society of Mechanical Engineers.

  • Venkatesh, V., & Pilchak, A. (2024). A Summary of Ti-2023: The World Conference on Titanium. AM&P Technical Articles, 182(2), 20-23.
  • Miracle, D. B., and D. J. Thoma. "Autonomous research and development of structural materials–An introduction and vision." Current Opinion in Solid State and Materials Science 33 (2024): 101188.

Take a look at Robo-Met Publications from the following years:

 

 

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