Bright Field Imaging

With the TEM lamellae thinned to 50-100 nm in thickness, bright field imaging is quiet effective at creating sufficient contrast to differentiate a multitude of features within the microstructure. As a result, bright field imaging is the first technique used to achieve an overall sense of the microstructure and evaluate any potential changes due to

irradiation. For the as-received, proton- and neutron-irradiated specimens, the entire TEM lamellae is available for imaging of the microstructure. However, it is important to

recognize that only the first ~1 um depth of the Fe2+ irradiated lamellae are influenced by irradiation. Furthermore, within this depth, the target analysis region resides at a depth of only 400-600 nm, which provides a relatively narrow area of sample which has

experienced the target irradiation dose of each experiment and thus may be investigated. Image collection is conducted using Digital Micrograph software, while post-imaging analysis was conducted using ImageJ software.

The grain and lath structure of the alloys are typically imaged at a magnification of 5900x. Images are captured in succession while scanning across the analysis region of

the sample. Identification of grain and latch boundaries is accomplished through looking for continuously dark contrast lines, evidence of dislocation pile-up, and carbide phases, which typical reside on grain boundaries. For each grain that is identified, a measurement of its overall length (lgr) and width (wgr) is taken and the effective diameter (𝑑_𝑔𝑟𝑒𝑓𝑓) of each

grain is calculated as:

𝑑_𝑔𝑟𝑒𝑓𝑓 = √𝑙𝑔𝑟∙ 𝑤𝑔𝑟 (4.3)

An average effective diameter is also calculated for each specimen.

Carbide precipitates are typically imaged at a magnification of 12,000x and are identified primarily by their unique contrast with bright field imaging. Carbides typically display a darker, dislocation free contrast compared to the surrounding matrix, and are most often located on grain or lath boundaries. As with grains, the overall length (lp) and

width (wp) of each carbide is measured and the effective carbide diameter (𝑑_𝑝𝑒𝑓𝑓) is

calculated as:

𝑑_𝑝𝑒𝑓𝑓 = √𝑙𝑝∙ 𝑤𝑝 (4.4)

An average carbide effective diameter is also calculated. Within each image, the relative analysis area in which the carbides were identified is measured. It is important to ensure that the analysis area of one image does not overlap with that of an adjacent image. The number density of carbide precipitates (Np) is then calculated by:

𝑁𝑝 =

𝑛𝑝

𝐴𝑡𝑜𝑡∙𝑡𝑎𝑣 (4.5)

where np is the total number of carbides identified, Atot is the total image area analyzed,

and tav is the average measured thickness of the sample (see Section 4.4.3).

Dislocations are visible in bright field imaging as lines of dark contrast and are distributed throughout the microstructure. Depending on the orientation of each

individual grain, dislocations may be more or less visible, as typically Burgers vectors for the b.c.c. crystal structure are in the <111> family of directions [73]. In order to measure the dislocation density of an alloy, grains that exhibit the darkest contrast (and thus the highest density of dislocations) are selected for analysis. Within the selected grain, the areal density of dislocations is determined by measuring the linear density of dislocations for successively perpendicular measurements. A line of fixed length (l) is drawn within the grain and the number of intersecting dislocations across that line is counted (ndisl).

Areal density of dislocations (Ndisl) is then calculated for each line by:

𝑁_{𝑑𝑖𝑠𝑙} = (𝑛𝑑𝑖𝑠𝑙

𝑙 )

2

(4.6) Finally, an overall average areal density of dislocations is calculated for each specimen.

After irradiation, it is possible for voids to be present in the microstructure of ODS and F-M alloys. If present, these voids are typically imaged via the through-focus technique in bright field TEM. It is generally easier to image voids in grains that exhibit low dislocation contrast, particularly if the voids are small. However, larger voids (>15 nm) are generally quite easy to identify anywhere within the sample. The through focus technique is conducted by first focusing the TEM onto a grain with low dislocation contrast. Next, the image is alternately under-focused and over-focused, respectively, to observe any changes in Fresnel contrast within the image. Spherical voids will typical exhibit a dark perimeter with a "hollow" bright center in the under-focus image, but will switch to exhibiting a bright perimeter with a "solid" dark center in the over-focus image. Smaller voids also tend to be invisible in the in-focused image. It is important to

recognize that nanoscale phases (such as oxides) will also exhibit similar Fresnel contrast when imaged with the through-focus technique, although typically without a hollow

center in the over- or under-focused conditions. Larger oxides are also generally visible in the in-focused image. For each void identified, the diameter is measured, and an overall average diameter of voids (dv), along with the standard deviation, is calculated.

Similar to the carbides, a number density of voids (Nv) is determined as:

𝑁_𝑣 = 𝑛𝑣

𝐴𝑡𝑜𝑡∙𝑡𝑎𝑣 (4.7)

where nv is the total number of voids identified, Atot is the total image area analyzed, and

tav is the average measured thickness of the sample.

Upon irradiation, dislocation loops are a common side effect within the

microstructure. Archival literature studies have commonly used techniques within bright field TEM imaging to image dislocation loops. The most common method is imaging with multiple two-beam conditions. This method is accomplished by the following steps: 1) locating a grain oriented on a low index zone axis (relative to the electron beam) such as [001], [011], and [111], 2) tilting the sample to achieve a two-beam condition in which ideally only one direction of beams are illuminated in the diffraction pattern, 3) capturing images of dislocation loops that have burgers vectors which are visible as a result of the respective two-beam condition, and then 4) tilting to another two-beam condition on the same grain and capturing more images. Although this technique is proven and effective, some inherent challenges with ODS and F-M alloys make this technique cumbersome and somewhat unreliable: a) the small grain structure makes it very difficult to tilt the sample without the image moving away from the particular grain in question, b) the high dislocation density of grains tilted onto low index zone axes floods the image,

complicating the reliable distinguishing of loops from the rest of the dislocation forest. Due to these technical challenges in imaging dislocation loops, an alternate technique for

imaging dislocation loops via STEM was selected. The following section will outline the details of this relatively new method, which proved to be vastly more reliable.