Tag Archives: magnetism

Tr-AMR angle

Obtaining magnetization orientation from magneto resistance

Obtaining magnetization orientation from magneto-resistance

Magnetism is a fascinating subject, not in terms of the science and understanding of it, but in terms of the application it has unfolded in the recent years. With the discovery of the Giant Magnetoresistance effect, which led to the birth of spintronics, technology around us has changed drastically and rapidly.  Data storage has transformed from bulky HDD s to more recent MRAMS, and DRAMS.

Spintronics which means the field of study on spin dependent magnetism phenomena, has done great  invaluable impacts not only to the storage industry but to the communication industry as well.  I will try to post more articles about the history of spintronics and their practical implications in another post .

As such, it can be realized that it is very much necessary to understand the process of the magnetization change in order to have any product designed out of it. One such tool to probe the magnetic property of a material is by performing a magneto resistance measurement of the material.

However the measured magneto-resistance is obtained  in units of resistance (ohms) and therefore it becomes necessary to extract the magnetization angles from the resistance to understand a quantitative magnetization switching process.   In this post, I have included a code, which converts the measured transverse anisotropic magneto resistance into magnetization angle with respect to the [010] crystal axes.

It is quite useful to have the AMR in terms of magnetization angle, because we can then explain the path of the reversal process, and design materials to alter or control the magnetization.

Find the code here:

GitHub link.  for the code.

 

 

Image processing of multiple images simultaneously

Image processing of multiple images simultaneously

Image processing is one of the very important aspect of every branch of science. Scientists and students (including PhD’s), collect so much data, be that in ASCII format, or sometimes images. The information sometimes is buried deep down in the cornered pixels of an image. To decipher that, they need some tool to dig out this data from the buried levels of noise and blur. processor

One such tool is the image processing toolbox in Matlab. The toolbox has many attributes and functionalities which can be used straightforward to do the basic operations like contrast, brightness, colour etc.

From the science point of view, we people may need to find the mean, median, or may be the threshold of any given gray scale image.  In this post, I have attached a Matlab code which loads multiple 32 bit gray scale images stored in the same folder. The program then finds the median of each image in a given region of interest (ROI) and plots them for different image images.

The code is quite useful when you have  multiple images and you need to load them all together and do the operation. To mention here is that the image stored must have the same path, but file names in ascending (or descending) order .

Find the Matlab code here.