Question
Asked 9th Oct, 2022

# How to use XRD to test the residual stress of Graphene-copper composites?

What is the residual stress of such large composite materials prepared by CVD growing graphene on copper?

## All Answers (1)

22nd Dec, 2022
Suganth Velumani
Anna University, Chennai
Residual stress in graphene-copper composites can be studied using X-ray diffraction (XRD) techniques. There are several methods that can be used to measure residual stress using XRD, including the sin2ψ method and the modified sin2ψ method.
The sin2ψ method involves measuring the XRD peaks for the graphene and copper phases separately, and then calculating the residual stress based on the peak positions and the known lattice parameters of the phases. This method is based on the fact that the peak positions of the diffraction patterns are affected by the residual stress in the material, and the shift in peak position can be used to calculate the residual stress.
The modified sin2ψ method is similar to the sin2ψ method, but it involves measuring the peak positions of the diffraction patterns for both the graphene and copper phases simultaneously. This method is more accurate than the sin2ψ method, but it requires more detailed analysis and may be more time-consuming.
To use XRD to measure the residual stress in graphene-copper composites, you will need to follow these general steps:
1. Prepare the samples: Cut the composite samples into small, thin pieces that are suitable for XRD analysis.
2. Measure the XRD patterns: Use an X-ray diffractometer to measure the XRD patterns of the samples at different diffraction angles.
3. Calculate the residual stress: Use the sin2ψ method or the modified sin2ψ method to calculate the residual stress based on the peak positions and known lattice parameters of the graphene and copper phases.
It is important to carefully follow the specific procedures and techniques for measuring residual stress using XRD, as the accuracy and reliability of the results will depend on the quality of the measurements and the correctness of the analysis. It may also be helpful to consult with experts or review the relevant literature to ensure that you are using the appropriate method and techniques for your specific materials and application.

## Similar questions and discussions

How to iterate through multiple subjects in a text file using python?
Question
5 answers
• Milad Najafzadeh
For my projects I need to iterate over a text file containing some subjects and change the directory to access some files using continiuos loop in python .
The text file (test.txt) has some subjects listed line by line:
sub-3101
sub-3166
sub-3168
and each of them has its own directory for exmaple:
path = '/mnt/wwn-0x5000039a52203bb1-part1/run/backup_PD_swedd/PD_total/derivatives/nipype-1.8.0/sub-3101/ses-1/diffusion_pipeline/connectome_stage/compute_matrice'
Here is my code:
import os
import networkx as nx
from scipy.io import savemat
import numpy as np
import scipy.io
with open('test.txt') as f:
for line in f:
path = '/mnt/wwn-0x5000039a52203bb1-part1/run/backup_PD_swedd/PD_total/derivatives/nipype-1.8.0/line/ses-1/diffusion_pipeline/connectome_stage/compute_matrice'
os.chdir(path)
conn_mats = {}
connectivity_weights = ['FA_mean', 'ADC_mean', 'number_of_fibers', "fiber_density", "fiber_proportion","fiber_length"]
G = nx.read_gpickle('connectome_scale1.gpickle')
for weight in connectivity_weights:
conn_mats[weight] = nx.to_numpy_array(G, weight=weight)
fiber_length_mean = nx.to_numpy_array(G, weight='fiber_length_mean')
fiber_length_mean_mat = {'fiber_length_mean':fiber_length_mean}
savemat("fiber_length_mean_sub_3102.mat", fiber_length_mean_mat)
As you can see, this code must read the subjects from text file , change the directory, read the file named "connectome_scale1.gpickle" and finally create a mat file.
But when I run it, There is an error as below:
FileNotFoundError: [Errno 2] No such file or directory: '/mnt/wwn-0x5000039a52203bb1-part1/run/backup_PD_swedd/PD_total/derivatives/nipype-1.8.0/line/ses-1/diffusion_pipeline/connectome_stage/compute_matrice'
What is wrong with my approach? How to run the code for all subjects?
Any help would be much appreciated.

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