**3. Raman scattering monitoring oxidation corrosion of nuclear fuel claddings**

Acquiring and understanding the health condition of nuclear fuel cladding are vital for nuclear energy long‐term fuel storage systems. In this section, we present the use of Raman scattering technology to monitor oxidation corrosion on nuclear fuel cladding. Systematic Raman scans were performed to study the relationship between typical Raman spectra and various oxida‐ tion corrosion layer thicknesses. The thicknesses of the oxide layers were confirmed by cross‐ sectional scanning electron microscopy (SEM) examination. The results reveal that each oxide layer thickness can be directly related to the Raman scattering characteristic peaks and have proven that Raman scattering technology is an accurate, nondestructive, and sensitive method to monitor the oxidation corrosion of zirconium‐based cladding.

The tested Zr‐4 cladding samples were cut by saw from 1 mm thick Zr‐4 cladding into 1 cm × 1 cm specimens. The Zr‐4 samples were ground and polished to remove the native surface oxide layer and provide a smooth sample surface. The morphology of the oxide may be affected by the cold‐worked nature of the polished surface. The samples were loaded in a quartz tube with a 5 cm diameter and were oxidized in a Thermo Scientific F79335‐70 furnace chamber at 500 °C in flowing air. Samples were oxidized for 5, 10, 20, 50, and 100 h, respectively, to achieve different corrosion layer thicknesses. These oxidation times were chosen such that the thickness of the oxide layer can be clearly distinguished. After oxidation, the polished side of each oxidized sample was ready for f Raman scattering investigation.

The Raman scattering spectra of the oxidized samples were measured with a Thermal Scientific DXR micro‐Raman spectrometer. The excitation laser source is a DXR 532 nm green laser, and the output power was 10 mW. The spectra were acquired by a 50 μm aperture. The objective of the microscope was chosen as 10×, providing a laser beam spot size diameter of 2.1 μm. Raman spectra were collected from the entire 2.1 μm diameter spot. The scans implemented a 900 lines/mm grating to obtain full‐range spectra and find the interested spectrum range. For each sample, systematic scans for several spots randomly selected at different regions on the sample were carried out. Then, the representative spectra which appeared most frequently were chosen for further analysis.

From the full‐range scanned Raman spectra of bare Zr‐4 as well as samples oxidized for 5, 10, 20, 50, and 100 h, the characteristic Raman scattering peaks appear between wave number of 160 and 800 cm−1. **Figure 9** shows the selected representative Raman spectra in this wave number range. A baseline has been subtracted from each spectrum, which allowed all the spectra to be put at the same level to permit selection of the best peaks for measuring the oxide layer thickness. As the Raman spectra reveal, the characteristic Raman scattering peaks become more obvious as the sample's oxidation time increases. In the spectrum from the non‐oxidized sample, there is only one peak around 480 cm−1 with a very weak intensity. The spectrum from the 5 h sample exhibits the 480 cm−1 peak, which is similar to the bare sample. Meanwhile, two weak peaks around 180 and 630 cm−1 appear with a broad peak width. In the spectrum from the 10 h sample, the peaks at 180, 480, and 630 cm−1 become stronger and wider. In addition, two peaks at 340 and 380 cm−1 appear. The spectrum from the 20 h sample is similar to that of the 10 h sample, but the intensity of each peak increases slightly. The peaks at 180 and 630 cm −1 begin to split into two sub‐peaks at 175 and 187 cm−1 and 613 and 638 cm−1, respectively. In the spectrum from the 50 h sample, all these peaks still exist at the same positions but with much stronger intensities. New peaks at 220, 540, and 580 cm−1 also appear within this spectrum. The spectrum from the 100 h sample contains all the peaks in the 50 h sample's spectrum, but each of them displays an increase in intensity. Furthermore, there are two new peaks at 280 and 300 cm−1 with weak intensities.

**Figure 9.** The selected representative Raman spectra of the non‐oxidized, 5, 10, 20, 50, and 100 h oxidized Zr‐4 cladding samples. As the oxidation time increases, there are 12 characteristic peaks appearing in the spectra. From Ref. [58].

As the oxidation time increases, a thicker oxide layer is grown on top of Zr‐4, and in turn, the Raman spectrum of this sample can show stronger Raman scattering signals. Comparing all of these Raman spectra in detail, some characteristic peaks are helpful in identifying bare and oxidized samples. As discussed previously, there are 12 characteristic peaks appearing or enhanced in the spectra of the tested samples. In the spectra of the bare and 5 h samples, the differences are only observed for peaks at 180 and 630 cm−1, which do not exist in the bare sample spectrum. These two peaks exist in all the spectra of the oxidized samples (from 5 to 100 h), and their intensities increase consistently as the oxidation time increases, although there is splitting happening in these two peaks for samples exposed for longer times. These split peaks at 175, 187, 613, and 638 cm−1 correspond to the existence of the zirconium oxide tetragonal and monoclinic polymorphs in the oxide layer [44, 57]. When an oxide layer grows thicker, there will be more zirconium oxide in these polymorphs. Oxide layers grown in environments other than air will likely have a different morphology than those studied here. Future work is necessary to establish whether the approach used successfully in this study will apply to oxides grown under other conditions.

number range. A baseline has been subtracted from each spectrum, which allowed all the spectra to be put at the same level to permit selection of the best peaks for measuring the oxide layer thickness. As the Raman spectra reveal, the characteristic Raman scattering peaks become more obvious as the sample's oxidation time increases. In the spectrum from the non‐oxidized sample, there is only one peak around 480 cm−1 with a very weak intensity. The spectrum from the 5 h sample exhibits the 480 cm−1 peak, which is similar to the bare sample. Meanwhile, two weak peaks around 180 and 630 cm−1 appear with a broad peak width. In the spectrum from the 10 h sample, the peaks at 180, 480, and 630 cm−1 become stronger and wider. In addition, two peaks at 340 and 380 cm−1 appear. The spectrum from the 20 h sample is similar to that of the 10 h sample, but the intensity of each peak increases slightly. The peaks at 180 and 630 cm −1 begin to split into two sub‐peaks at 175 and 187 cm−1 and 613 and 638 cm−1, respectively. In the spectrum from the 50 h sample, all these peaks still exist at the same positions but with much stronger intensities. New peaks at 220, 540, and 580 cm−1 also appear within this spectrum. The spectrum from the 100 h sample contains all the peaks in the 50 h sample's spectrum, but each of them displays an increase in intensity. Furthermore, there are two new

**Figure 9.** The selected representative Raman spectra of the non‐oxidized, 5, 10, 20, 50, and 100 h oxidized Zr‐4 cladding samples. As the oxidation time increases, there are 12 characteristic peaks appearing in the spectra. From Ref. [58].

As the oxidation time increases, a thicker oxide layer is grown on top of Zr‐4, and in turn, the Raman spectrum of this sample can show stronger Raman scattering signals. Comparing all of these Raman spectra in detail, some characteristic peaks are helpful in identifying bare and oxidized samples. As discussed previously, there are 12 characteristic peaks appearing or enhanced in the spectra of the tested samples. In the spectra of the bare and 5 h samples, the differences are only observed for peaks at 180 and 630 cm−1, which do not exist in the bare sample spectrum. These two peaks exist in all the spectra of the oxidized samples (from 5 to 100 h), and their intensities increase consistently as the oxidation time increases, although there is splitting happening in these two peaks for samples exposed for longer times. These split

peaks at 280 and 300 cm−1 with weak intensities.

132 Raman Spectroscopy and Applications

After the Raman spectrum measurement, the oxidized Zr‐4 samples were prepared with phenolic mount for cross section measurement by SEM in order to examine the Raman results. Because of the different properties of phenolic, zirconium oxide, and Zr‐4, these three materials can be easily distinguished by the white‐black contrast. Zirconium oxide is a high dielectric constant material, so compared with Zr‐4, the zirconium oxide layer has a darker gray color in SEM images, and the boundary between the oxide layer and the Zr‐4 was obvious. Following this procedure, the zirconium oxide layer thickness can be measured accurately at different positions of cross section.

**Figure 10.** The cross‐sectional SEM images of Zircaloy‐4 samples oxidized at 500 °C in ambient air for (a) 5, (b) 10, (c) 20, (d) 50, and (e) 100 h. From Ref. [58].

The cross‐sectional SEM images of the samples are shown in **Figure 10(a)**–**(e)**. The SEM images were taken in more than 20 different regions over the whole cross section of each sample, so they can be representative of the sample oxide layer thickness. The statistical average thickness and standard deviation of the top oxide layer are shown in **Figure 11**. The thickness of the oxide layer increases roughly linearly with oxidation time. For the 5 h sample, there is a very thin uniform oxide layer on the Zr‐4. As the thickness increases, the top oxide layer becomes nonuniform, and the interface between zirconium oxide and Zr‐4 becomes rougher. The average thickness of the oxide layer for the 5 h sample is about 0.55 μm with a deviation of about 0.066 μm. But for the 100 h sample, the average thickness of the oxide layer is about 10.13 μm with a deviation of about 3.08 μm. This suggests that during oxidation, the growth rate of the oxide layer varies across the sample, and the oxide layer will have an uneven profile.

**Figure 11.** The calculated statistical average thickness and deviation of all oxidized samples as a function of oxidation time. From Ref. [58].

In order to analyze these two peaks quantitatively, the Gaussian-Lorentzian mode deconvolutions were carried out on two characteristic peaks around 180 and 630 cm−1, which are candidate signals for detecting the Zr-4 cladding oxide layer thickness. **Figure 12** shows the deconvolution processes of these two characteristic peaks from the selected representative spectra of the 10 and 100 h samples. After deconvolution, the two sub-peaks can be replaced by individual peaks at the 175 and 187 cm−1 and 613 and 638 cm−1 positions, respectively. The intensities of these four peaks from the representative Raman spectra of all oxidized samples are shown in **Figure 12** as a function of the average thickness of the oxide layer. The intensities of these four deconvoluted peaks increase consistently as the oxide layer becomes thicker. For the 10 h sample with average oxide layer thickness of 1.30 μm, the intensities of the deconvoluted peaks are 44.1, 26.6, 21.3, and 39.5. For the 100 h sample with average oxide layer thickness of 10.13 μm, the intensities have increased greatly to 645.5, 405.5, 264.9, and 356.5.

The difference in intensities of the peaks at 175, 187, 613, and 638 cm−1 is able to identify each sample with the corresponding oxide layer thickness with high resolution as shown in **Figure 13**. Taking the peak at 175 cm−1 as an example, the peak intensity increases from 0 for a bare sample to 3.5, 44.1, 63.2, 186.6, and 645.5 for 0.55, 1.30, 2.36, 5.27, and 10.13 μm oxide layer thicknesses. Because there is no peak at these positions for the bare sample, it is easy to distinguish it from the oxidized samples, even for the 5 h sample with a 0.55 μm thick oxide layer. Among the oxidized samples, the average thickness difference between 5 and 10 h samples is only about 0.75 μm, but the signal intensity of the 10 h sample is almost 10 times higher than that of the 5 h sample. Another three peaks show similar trends. This result reflects that during the oxidation process at 500 °C, as oxidation time increases, the components of the tetragonal and monoclinic polymorph zirconium oxide become more, and consequently, they show much stronger characteristic peaks in the Raman spectra [44].

Raman Spectroscopy for Monitoring Strain on Graphene and Oxidation Corrosion on Nuclear Claddings http://dx.doi.org/10.5772/65111 135

**Figure 11.** The calculated statistical average thickness and deviation of all oxidized samples as a function of oxidation

In order to analyze these two peaks quantitatively, the Gaussian-Lorentzian mode deconvolutions were carried out on two characteristic peaks around 180 and 630 cm−1, which are candidate signals for detecting the Zr-4 cladding oxide layer thickness. **Figure 12** shows the deconvolution processes of these two characteristic peaks from the selected representative spectra of the 10 and 100 h samples. After deconvolution, the two sub-peaks can be replaced by individual peaks at the 175 and 187 cm−1 and 613 and 638 cm−1 positions, respectively. The intensities of these four peaks from the representative Raman spectra of all oxidized samples are shown in **Figure 12** as a function of the average thickness of the oxide layer. The intensities of these four deconvoluted peaks increase consistently as the oxide layer becomes thicker. For the 10 h sample with average oxide layer thickness of 1.30 μm, the intensities of the deconvoluted peaks are 44.1, 26.6, 21.3, and 39.5. For the 100 h sample with average oxide layer thickness

of 10.13 μm, the intensities have increased greatly to 645.5, 405.5, 264.9, and 356.5.

show much stronger characteristic peaks in the Raman spectra [44].

The difference in intensities of the peaks at 175, 187, 613, and 638 cm−1 is able to identify each sample with the corresponding oxide layer thickness with high resolution as shown in **Figure 13**. Taking the peak at 175 cm−1 as an example, the peak intensity increases from 0 for a bare sample to 3.5, 44.1, 63.2, 186.6, and 645.5 for 0.55, 1.30, 2.36, 5.27, and 10.13 μm oxide layer thicknesses. Because there is no peak at these positions for the bare sample, it is easy to distinguish it from the oxidized samples, even for the 5 h sample with a 0.55 μm thick oxide layer. Among the oxidized samples, the average thickness difference between 5 and 10 h samples is only about 0.75 μm, but the signal intensity of the 10 h sample is almost 10 times higher than that of the 5 h sample. Another three peaks show similar trends. This result reflects that during the oxidation process at 500 °C, as oxidation time increases, the components of the tetragonal and monoclinic polymorph zirconium oxide become more, and consequently, they

time. From Ref. [58].

134 Raman Spectroscopy and Applications

**Figure 12.** The Gaussian-Lorentzian deconvolution processes of characteristic peaks around 180 and 630 cm−1 from the selected representative Raman spectra of the 10 (a) (b) and 100 h (c) (d) oxidized samples. From Ref. [58].

**Figure 13.** The intensities of the deconvoluted peaks at 175, 187, 613, and 638 cm−1 as a function of the average thickness of the oxide layer. From Ref. [58].

**Figure 14** shows the maximum intensity deviation percentages of each characteristic peak from different test positions for all oxidized samples as a function of the average thickness of the oxide layer. It is observed that the maximum intensity deviations for these characteristic peaks are in the range from about 5 % to a little lower than 25 %. This intensity variation comes from the difference in the thickness of the oxide layer. This result means that the uneven condition of the oxide layer thickness for the sample can be roughly reflected in intensity variation of the characteristic peaks. After analysis of these characteristic peaks, they can be confidently considered as sufficient scattering signals to detect the oxide layer thickness on Zr‐4 cladding and further employed to finish the task of converting the oxide layer thickness to detectable optical signals.

**Figure 14.** The maximum intensity deviation percentages of the characteristic peaks (deconvoluted) as a function of the average thickness of the oxide layer. From Ref. [58].

#### **4. Conclusion**

Raman spectroscopy has been demonstrated to successfully probe the tensile biaxial strain in monolayer graphene on the surface of SiO2 nanopillars patterned by a self‐assembled block copolymer. The characteristic Raman peaks of the G band and 2D band shifted due to the strain, and the Raman shifts accurately expressed the strain value distributed on graphene. The surface profile of the transferred graphene film on SiO2 nanopillars was carefully investigated by AFM, and the biaxial tensile strain generated in the graphene was extracted from the physical deformation. Then, finite element simulations were used to validate the measure‐ ments. Both the AFM experimental investigation and FEM theory modeling matched the strain results achieved from Raman spectroscopy study and proved the capability of Raman scattering to monitor the subtle mechanical property change of graphene.

Raman scattering technology was studied to monitor spent fuel cladding oxidation. The air‐ oxidized Zr‐4 cladding samples were systematically investigated by Raman spectroscopy. Straightforward Raman spectrum analysis reveals that there are characteristic peaks able to identify the bare and oxidized cladding samples and samples with different oxide layer thicknesses. SEM scans were carried out to visually examine oxide layer thicknesses on cladding. The comparison results confirmed this Raman scattering detection method displays high resolution in the determination of the oxidation corrosion degrees.

In summary, Raman scattering technology was proposed to monitor mechanical property of novel 2D carbon material and oxidation film thicknesses on nuclear fuel cladding Zircaloy. The positions and intensities of the characteristic peaks of the materials under test accurately and reliably revealed the changes in physical and chemical properties. The work reported in this chapter on observing materials with Raman spectroscopy extends the application of Raman scattering technology in monitoring new nanomaterial status and the health of nuclear storage systems in the research and engineering development.
