Jean-Charles Stinville

Transmission scanning electron microscopy: Defect observations and image simulations

The new capabilities of a FEG scanning electron microscope (SEM) equipped with a scanning transmission electron microscopy (STEM) detector for defect characterization have been studied in parallel with transmission electron microscopy (TEM) imaging. Stacking faults and dislocations have been characterized in strontium titanate, a polycrystalline nickel-base superalloy and a single crystal cobalt-base material. Imaging modes that are similar to conventional TEM (CTEM) bright field (BF) and dark field (DF) and STEM are explored, and some of the differences due to the different accelerating voltages highlighted. Defect images have been simulated for the transmission scanning electron microscopy (TSEM) configuration using a scattering matrix formulation, and diffraction contrast in the SEM is discussed in comparison to TEM. Interference effects associated with conventional TEM, such as thickness fringes and bending contours are significantly reduced in TSEM by using a convergent probe, similar to a STEM imaging modality, enabling individual defects to be imaged clearly even in high dislocation density regions. Beyond this, TSEM provides significant advantages for high throughput and dynamic in-situ characterization.

Microstructural statistics for fatigue crack initiation in polycrystalline nickel-base superalloys

In advanced engineering alloys where inclusions and pores are minimized during processing, the initiation of cracks due to cyclic loading shifts to intrinsic microstructural features. Criteria for the identification of crack initiation sites, defined using elastic-plastic loading parameters and twin boundary length, have been developed and applied to experimental datasets following cyclic loading. The criteria successfully quantify the incidence of experimentally observed cracks. Statistical microstructural volume elements are defined using a convergence approach for two nickel-base superalloys, IN100 and René 88DT. The material element that captures the fatigue crack-initiating features in René 88DT is smaller than IN100 due to a combination of smaller grain size and higher twin density.

Prediction of Fatigue-Initiating Twin Boundaries in Polycrystalline Nickel Superalloys Informed by TriBeam Tomography

Fatigue is the life limiting property of polycrystalline nickel-base superalloys used for turbine disks. Alloys processed through advanced powder metallurgical routes have minimal concentrations of pores, inclusions, or other extrinsic defects that commonly serve as crack initiation sites. Instead, fatigue cracks initiate at intrinsic defects resulting in microstructurally sensitive and difficult to predict fatigue response [1]. Crack formation and short crack growth accounts for 80% of lifetime in the high cycle fatigue regime resulting in highly variable lifetimes spanning up to three orders of magnitude [1, 2]. Identifying and characterizing regions amenable to initiation and initial propagation of cracks is crucial for improving fatigue life predictions.

Microstructure and Property-Based Statistically Equivalent Representative Volume Elements for Polycrystalline Ni-Based Superalloys Containing Annealing Twins

This paper has three major objectives related to the development of computational micromechanics models of Ni-based superalloys, containing a large number of annealing twins. The first is the development of a robust methodology for generating 3D statistically equivalent virtual polycrystalline microstructures (3D-SEVPM) of Ni-based superalloys. Starting from electron backscattered diffraction (EBSD) images of sections, the method develops distributions and correlation functions of various morphological and crystallographic parameters. To incorporate twins in the parent grain microstructure, the joint probability of the number of twins and parent grain size, and the conditional probability distributions of twin thickness and twin distance are determined. Subsequently, a method is devised for inserting twins following the distribution functions. The overall methodology is validated by successfully comparing various statistics of the virtual microstructures with 3D EBSD data. The second objective is to establish the microstructure-based statistically equivalent representative volume element or M-SERVE that corresponds to the minimum SERVE size at which the statistics of any morphological or crystallographic feature converge to that of the experimental data. The Kolmogorov–Smirnov (KS) test is conducted to assess the convergence of the M-SERVE size. The final objective is to estimate the property-based statistically equivalent RVE or P-SERVE, defined as the smallest SERVE, which should be analyzed to predict effective material properties. The crystal plasticity finite-element model is used to simulate SERVEs, from which the overall material response is computed. Convergence plots of material properties including the yield strength and hardening rate are used to assess the P-SERVE. A smaller P-SERVE compared to the M-SERVE indicates that the characteristic features of twins implemented in determining the M-SERVE are more stringent than those for determining material properties.