2022 Research Using Robo-Met's Materials Analysis

September 05, 2022

Robo-Met Product Icon Every year our customers 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.


Read also Robo-Met Publications in the following years:


 Category: Composite Materials Applications

Numerical and experimental study of hot-pressing technique for resin-based friction composites

A fully coupled thermomechanical computational framework based on the Hot Optimal Transportation Meshfree (HOTM) method is presented to derive the process-microstructure-properties correlation for resin-based friction composites manufactured by hot pressing technique. The raw material is considered as reinforcing fibers and strengthening particles explicitly embedded in a continuum porous media. The manufacturing process is modeled as the raw material experiencing extremely large compression under applied pressure and temperature boundary conditions to predict the formation and evolution of the composite’s microstructure.To investigate the various phases including porosity and fiber content (and orientation), sections of the samples are examined using the RoboMet.3D®system (UES inc, OH, USA). Each sample was sliced into 146 slices used for 3D rendering.
 
A chemo-thermo-mechanical constitutive model is proposed to describe the dynamic response of the matrix material involving large inelastic deformation, resin melting and polymerization. The microstructure of the final product produced by hot pressing processes is predicted by solving the deformation, temperature and curing degree of the raw material using the HOTM method. The computational framework is validated by comparing the calculated fiber orientation distribution in the friction materials to experimental measurements under various processing conditions. The sensitivity of composite’s mechanical properties on the fiber orientation is further studied by the proposed numerical method and experiments.
 
Citation: Wang, H., Li, X., Phipps, M., & Li, B. (2022). Numerical and experimental study of hot-pressing technique for resin-based friction composites. Composites Part A: Applied Science and Manufacturing, 153, 106737. 

Effects of debulking on the fiber microstructure and void distribution in carbon fiber reinforced plastics

cfiber

Carbon Fiber Reinforced Plastics (CFRPs) are widely used due to their high stiffness to weight ratios. A common process manufacturers use to increase the strength to weight ratio is debulking. Debulking is the process of compacting a dry fibrous reinforcement prior to resin infusion. This process is meant to decrease the average inter-fiber distance, effectively increasing the fiber volume fraction of the sample. While this process is widely understood macroscopically its effects on fibrous microstructures have not yet been well characterized. The aim of this work is to compare the microstructures of three CFRP laminates, varying only the debulking step in the manufacturing process. High resolution serial sections of all three laminates were taken for analysis. Using these scans, the fiber positions were reconstructed. Statistical descriptors such as local fiber and void volume fractions, fiber orientation, and void distribution and morphology were then generated for each sample. Fiber clusters present within the material were identified and analyzed for each level of debulking applied. Using these descriptors, the effects of debulking on the morphology and organization of the composite microstructure was evaluated.
 
Citation: Schey, M., Beke, T., Owens, K., George, A., Pineda, E., & Stapleton, S. (2022). EFFECTS OF DEBULKING ON THE FIBER MICROSTRUCTURE AND VOID DISTRIBUTION IN CARBON FIBER REINFORCED PLASTICS. Composites Part A: Applied Science and Manufacturing, 107364.
 

Category: Structural Metals

A Study on the Interrelationship between the Microstructural Features and the Elevated Temperature Strength of Multicomponent Al-Si-Cu-Ni Casting Alloys

The elevated temperature strength of multicomponent Al-Si alloys is greatly affected by the volume fraction and the interconnectivity of hard phases formed upon solidification. In the present investigation, such influences were examined for two Al-Si-Cu-Ni alloys with different total volume fractions of hard phases. To control the microstructural features related to the size of the phase, the specimens were prepared with and without ultrasonic melt treatment (UST) at different cooling rates. The microstructures of the alloys were composed of primary Si, eutectic Si, (Al,Si)3(Zr,Ni,Fe), Al9FeNi and Al3(Cu,Ni)2 phases. The microstructural features, such as the size and aspect ratio of each phase, changed with UST and cooling rate, and accordingly, the elevated temperature strength at 350 oC was changed. The alloy with a high volume fraction of about 30 vol.% exhibited increased elevated temperature strength at 350 oC when ultrasonic melt treated, and the alloy having a volume fraction as low as about 18 vol.% exhibited the opposite results. Considering the microstructural features of the multi-component Al-Si alloy, a hexagonal shear-lag model was suggested, based on the well-known shearlag model proposed by Nardone and Prewo (Scr. Metall. 20;1986:43-48). Using the 2-D microstructural factors such as the size, aspect ratio of the phase and secondary dendrite arm spacing, the elevated temperature strength was calculated and compared with the measured value. Based on the hexagonal shear-lag model, the influence of microstructural factors on the elevated temperature strength was discussed for multi-component Al-Si-Cu-Ni alloys.
 
 
Citation: Jo, M. S., Cho, Y. H., Lee, J. M., Kim, S. B., Kim, S. H., & Jang, J. I. (2022). A Study on the Interrelationship between the Microstructural Features and the Elevated Temperature Strength of Multicomponent Al-Si-Cu-Ni Casting Alloys. Korean Journal of Metals and Materials, 60(7), 489-501.
 

Unveiling the influence of dendrite characteristics on the slip/twinning activity and the strain hardening capacity of Mg-Sn-Li-Zn cast alloys

This work explores the correlation between the characteristics of the cast structure (dendrite growth pattern, dendrite morphology and macro-texture) and strain hardening capacity during high temperature deformation of Mg-5Sn-0.3Li-0 and 3Zn multi-component alloys. The three dimensional (3D) morphology of the dendrite structure demonstrates the transition of the growth directions from<113>,<110> and <112> to< 113> and <110> due to the addition of Zn. The simultaneous effects of growing tendency and the decrement of dendrite coarsening rate at the solidification interval lead to dendrite morphology transition from the globular-like to the hyper-branch structure. This morphology transition results in the variation of the solidification macro-texture, which has effectively influenced the dominant deformation mechanisms (slip/twin activity). The higher activity of the slip systems increases the tendency of the dendrite arms for bending along the deformation direction and fragmentation. Apart from this, the dendrite holding hyper-branch structure with an average thickness below 20 µm are more favorable for fragmentation. The dendrite fragmentation leads to considerable softening fractions, and as an effective strain compensation mechanism increases the workability of dendritic structure.
 
Citation: Jalali, M. S., Zarei-Hanzaki, A., Mosayebi, M., Abedi, H. R., Malekan, M., Kahnooji, M., ... & Kim, S. H. (2022). Unveiling the influence of dendrite characteristics on the slip/twinning activity and the strain hardening capacity of Mg-Sn-Li-Zn cast alloys. Journal of Magnesium and Alloys.
 

Effect of Ultrasonic Melt Treatment on Solidification Microstructure of Al–5Ti–1B Alloy Containing Numerous Inoculant Particles

The effect of ultrasonic melt treatment (UST) on the solidification microstructure of an Al–5Ti–1B alloy containing high-volume fractions of Al3Ti and TiB2 particles is investigated for various UST times with different melt holding times. The as-cast Al–5Ti–1B alloy is composed of TiB2 and polygonal Al3Ti particles (present prior to UST), plate-like Al3Ti particles, and Al grains (formed during UST and/or solidification). The UST causes a size reduction and homogeneous distribution of the TiB2-agglomerated region containing many submicron-sized TiB2 particles pushed to the grain boundaries. The UST slightly decreases the size and improves the distribution of polygonal Al3Ti particles enriched in the TiB2-agglomerated region. Unlike the TiB2 and polygonal Al3Ti particles, which exhibit a minor refining effect, the plate-like Al3Ti particles show a significant refinement with UST application. The UST has a significant effect on the size distribution of Al grains by inducing the formation of medium-sized grains at the expense of small and large grains; however, it only has a slight effect on grain refinement. The degree of microstructure modification increases with increasing UST time but decreases with melt holding time after UST. The mechanisms for the refinement and dispersion of the TiB2 and Al3Ti particles and Al grains are discussed considering fragmentation, nucleation, and growth behaviors induced by the UST and subsequent solidification.
 
 
Citation: Kim, S. B., Jung, J. G., Cho, Y. H., Kim, S. H., Euh, K., & Lee, J. M. (2022). Effect of Ultrasonic Melt Treatment on Solidification Microstructure of Al–5Ti–1B Alloy Containing Numerous Inoculant Particles. Metals and Materials International28(7), 1549-1560.

Category: Autonomous Experimentation

 
 
A Framework for Closed-Loop Optimization of an Automated Mechanical Serial-Sectioning System via Run-to-Run Control as Applied to a Robo-Met.3D

Optimization of automated data collection is gaining increased interest for the purposes of enabling closed-loop self-correcting systems that inherently maximize operational efficiencies and reduce waste. Many data collection systems have several variables which influence data accuracy or consistency and which can require frequent user interaction to be monitored and maintained. Operating upon a Robo-Met.3D automated mechanical serial-sectioning system, a run-to-run control algorithm has been developed to accelerate data collection and reduce data inconsistency. Using historical data amassed over a decade of experiments, a linear regression model of the deterministic system dynamics is created and used to employ a run-to-run control algorithm that optimizes selected system inputs to reduce operator intervention and increase efficacy while reducing variance of system output.

Citation: Gallegos-Patterson, D., Ortiz, K., Danielson, C., Madison, J. D., & Polonsky, A. T. (2022). A Framework for Closed-Loop Optimization of an Automated Mechanical Serial-Sectioning System via Run-to-Run Control as Applied to a Robo-Met. 3D. JOM, 74(8), 2930-2940.

Improving Autonomous Data Collection by Run-to-Run Control Algorithm as Applied to a Robo-Met Mechanical Serial-Sectioning System

This presentation describes Sandia's Robo-Met systems (v2 and v3) and the implementation of autonomous data collection customizations in these systems.

sandiarobomets

Citation: Gallegos-Patterson, D., Polonsky, A., Madison, J., & Danielson, C. (2022). Improving Autonomous Data Collection By Run-to-Run Control Algorithm as Applied to a RoboMet Mechanical Serial-Sectioning System (No. SAND2022-2525C). Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

Conducting Materials Research During and After a Global Pandemic

The Covid-19 pandemic presented challenges that were non-existent just a few years prior: -Restricted lab access-Travel restrictions-Supply chain issues-Delayed milestones However, this was also a period where new advanced solutions could help improve materials research moving forward: Automation, Remote Working, Advanced modeling techniques, and Faster collaboration with Video conferences. When the challenges from Covid-19 subside these new solutions/techniques are poised to help advance materials science beyond where it was before the pandemic.


GlennRoboMet

Citation: Smith, T. M., & Bonacuse, P. (2022, February). Conducting Materials Research During and After a Global Pandmic. In TMS 2022 150th Annual Meeting & Exhibition. 

Run-to-Run Control via Constrained Optimization of a Mechanical Serial-Sectioning System

This thesis develops a methodology for run-to-run (R2R) control of a mechanical serial sectioning (MSS) system for microstructural investigations. MSS is a destructive material characterization process which repeatedly removes a thin layer of material and images the exposed surface. The images are then used to gain insight into the internal structure and arrangement of a material and are often used to generate a 3-dimensional(3D) reconstruction of the sample. Currently, an experienced human operator selects the parameters for MSS to achieve the desired per slice removal rate. The proposed R2R control methodology automates this process while improving the precision and repeatability of material removal.The proposed methodology does this by solving an optimization problem designed to minimize the variance of the material removal subject to achieving the expected target removal rate.This optimization problem was embedded in an R2R framework to provide iterative feedback for disturbance rejection and convergence to the target removal amount. Since an analytic model of the MSS system is unavailable, a data-driven approach to synthesize our R2R controller from historical data was used.

Citation: Gallegos-Patterson, Damian L. "Run-to-Run Control via Constrained Optimization of a Mechanical Serial-Sectioning System." (2022), MS Thesis, UNM.

Category: Additive Manufacturing

Refractory Alloy Additive Manufacture Build Optimization (RAAMBO)

Refractory metals and alloys are used for service in extreme high temperature environments. Nondestructive techniques can have individual strengths and limitations based on the high atomic numbers and high radiopacity of refractory metals. NASA Marshall used layer-wise imaging using Robo-Met to provide Control data.

NasaMarshallRoboMet

Citation: Mireles, O. (2022, June). Refractory Alloy Additive Manufacture Build Optimization (RAAMBO). In TechConnect World Innovation Conference and Expo.

Characterization of Additively Manufactured Circular Disks Using Traditional Computed Tomography Volume Segmentation and Machine Learning Algorithms

Additively manufactured (AM) components contain discontinuities, indications and defects that can change the component’s mechanical performance during high energy impact events. X-ray computed tomography (XCT) reconstructions of AM metastable titanium disks (Ti-5Al-5V-5Mo-3Cr or Ti-5553) were generated on an industrial micro-focus system. Each sample was scanned before and after high velocity impact testing. The porosity resulting from the direct metal laser sintering (DMLS) powder bed fusion machine was detected and characterized. The samples were placed in a gas gun configuration to induce a high-rate tensile load (shock test). The post-test results on the recovered disks contained incipient spall cavities. These features were identified by standard volume segmentation techniques. This inspection data is also evaluated with machine learning (ML) algorithms. A comparison between ML segmentation of the pores/cavities to standard commercial segmentation algorithms will be presented. Improvements using ML were specifically seen in the identification of pores and spall planes in regions of low x-ray attenuation (brightness and contrast). Common XCT artifacts, which include beam hardening and systematic noise, were overcome by the applied ML methods. Porosity and spall plane regions identified by the machine learning analysis were then compared to serial sectioning and scanning electron microscope (SEM) data to judge the precision and accuracy of the machine learning technique. Results show that the CT reconstructed porosity aligned well with the serial sectioned and SEM data. The only discrepancies were in the small pores near the detectability limit and other metrics dependent on the XCT reconstruction resolution.

Citation: Moore, D. G. (2022). Characterization of Additively Manufactured Circular Disks Using Traditional Computed Tomography Volume Segmentation and Machine Learning Algorithms.

Understanding Phase and Interfacial Effects of Spall Fracture in Additively Manufactured Ti-5Al-5V-5Mo-3Cr

Additive manufactured Ti-5Al-5V-5Mo-3Cr (Ti-5553) is being considered as an AM repair material for engineering applications because of its superior strength properties compared to other titanium alloys. Here, we describe the failure mechanisms observed through computed tomography, electron backscatter diffraction (EBSD), and scanning electron microscopy (SEM) of spall damage as a result of tensile failure in as-built and annealed Ti-5553. We also investigate the phase stability in native powder, as-built and annealed Ti-5553 through diamond anvil cell (DAC) and ramp compression experiments. We then explore the effect of tensile loading on a sample containing an interface between a Ti-6Al-V4 (Ti-64) baseplate and additively manufactured Ti-5553 layer. Post-mortem materials characterization showed spallation occurred in regions of initial porosity and the interface provides a nucleation site for spall damage below the spall strength of Ti-5553. Preliminary peridynamics modeling of the dynamic experiments is described. Finally, we discuss further development of Stochastic Parallel PARticle Kinteic Simulator (SPPARKS) Monte Carlo (MC) capabilities to include the integration of alpha-phase and microstructural simulations for this multiphase titanium alloy.

sandiaspallcav

Citation: Branch, B., Ruggles, T., Miers, J. C., Massey, C., Moore, D., Brown, N., ... & Specht, P. (2022). Understanding Phase and Interfacial Effects of Spall Fracture in Additively Manufactured Ti-5Al-5V-5Mo-3Cr (No. SAND2022-14061). Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

Crystallographic Variability in Additive Manufacturing

3dstructure fonda

The crystallographic textures produced during additive manufacturing can be understood, predicted, and manipulated by varying the grain nucleation and growth processes.  The resultant textures are primarily dictated by the melt pool geometry, which defines the local thermal gradient and thus the preferred crystal growth directions, as well as the scan strategy, which controls the propagation of grain orientations into subsequent layers. This texture can be diluted through heterogeneous nucleation of new grain orientations, which can occur through a variety of mechanisms. This ability to control the texture during additive manufacturing can enable the location-specific control of properties as a function of position in the build.

Citation: Fonda, R. W., & Rowenhorst, D. J. (2022, July). Crystallographic Variability in Additive Manufacturing. In IOP Conference Series: Materials Science and Engineering (Vol. 1249, No. 1, p. 012007). IOP Publishing.

Assessing flaw detection capability of laser powder bed fusion in situ monitoring

 

Monitoring systems developed for laser powder bed fusion (LPBF) metal additive manufacturing (AM) can be useful in qualifying parts. Aerospace applications often require nondestructive evaluation (NDE) as part of a damage tolerance approach. However, AM poses a challenge for NDE due to the typical part size and complexity. In situ monitoring can potentially take advantage of the layer-wise manufacturing process to inspect the part as it is built. This requires correlating indications in the monitoring data with the formation of flaws in the finished part. To develop this correlation, LPBF samples were made with seeded voids. Destructive serial sectioning metallography was used to provide ground truth flaw characterization. The resolution capability of in situ monitoring was compared to the typical NDE method, computed tomography (CT). In situ monitoring was able to detect the presence of voids that were below the detection limit of CT but observable using serial sectioning metallography.

Citation: Lanigan, E. (2022). Assessing flaw detection capability of laser powder bed fusion in situ monitoring, Theses, 390, https://louis.uah.edu/uah-theses/390.

Category: Articles Mentioning Robo-Met.3D

  • Boyce, B. L. (2022, July). Microstructural Black Swans. In IOP Conference Series: Materials Science and Engineering (Vol. 1249, No. 1, p. 012004). IOP Publishing.
  • Bukkapatnam, S. T. (2023). Autonomous Materials Discovery and Manufacturing (AMDM): A review and perspectivesIISE Transactions55(1), 75-93.Bukkapatnam, S. T. (2022).
  • Polonsky, A. T., & Callahan, P. G. (2022). Applications of Autonomous Data Collection and Active Learning. JOM, 74(8), 2895-2896.
  • Mehra, A., Howes, B., Manzuk, R., Spatzier, A., Samuels, B. M., & Maloof, A. C. (2022). A Novel Technique for Producing Three-Dimensional Data Using Serial Sectioning and Semi-Automatic Image Classification. Microscopy and Microanalysis, 1-16.
  • Sous, F., Herrig, T., Bergs, T., Karges, F., Feiling, N., & Zeis, M. (2022). Electrochemical Defect Analysis of Additive Manufactured Components. Journal of Engineering for Gas Turbines and Power144(1).
  • Gomes, D. S. Aplicação e validação de um código computacional para reconstrução 3D utilizando imagens oriundas do seccionamento em série.
  • Liu, W. (2022). Microstructure modeling guided design of high-strength steels (Doctoral dissertation, university library).

 


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