MRAM commercialization potential evaluation Research Based on the Chinese Market

Regarding the Chinese data storage industries, there is an urgent need for a national strategy and new investments as there are new technologies emerging in the global markets. The storage technology commercialization activities are becoming a widespread concern for the Chinese government and their strategic enterprises. The promotion of storage technology commercialization has become a common goal for enterprise and national government strategies. How the potential for commercialization of a storage technology can be assessed, what evaluation index should be used, and what the factors affect the storage technology are the important issues that must be addressed

Magnetic materials : fundamental synthesis of two-dimensional magnets and applications to neuromorphic computing

Two dimensional magnetic materials hold the promise of helping to achieve beyond CMOS computing tasks. 2D magnetic materials can be used in fabricating magnetic tunnel junctions with higher tunnel magnetoresistance which can then be applied to making new neuromorphic computing architectures primarily geared towards artificial intelligence and machine learning applications. In this work I summarize my synthesis and investigation of the properties of Cr₂C which belongs to the group of 2D transition metal carbides or nitrides called MXenes. Cr₂C has been predicted to have intrinsic half metallic ferromagnetic behaviors. These magnetic behaviors can be tuned based on the level of functionalization of the surface of the material. I show different parameters such as etchant, reaction temperature, and molar concentration that I have tuned in order to optimally derive Cr₂C from its parent MAX phase Cr₂AlC by removing the Al layer with a fluoride salt and hydrochloric acid. I also show how magnetic tunnel junctions (MTJs), which are two ferromagnetic layers with a tunnel barrier in between, can be used to make a synapse which is a neuromorphic computing primitive. The synapse circuit that I have proposed displays spike timing dependent plasticity which is an integral component of learning and memory in the brain. I show how different delay conditions between the presynaptic signal and the postsynaptic signal lead to currents of different magnitudes flowing through the ferromagnetic layer of the magnetic tunnel junction synapse. I also show how these currents move the domain wall both in micromagnetic simulation and using a domain wall MTJ Spice model that has been developed. I went on to wire four of these synapses together to observe the temporal dynamics of the system. My results show that the lower the delay between the presynaptic pulse and the postsynaptic pulse, the higher the current through the MTJ synapse and hence the larger the domain wall displacement. These studies pave the way for empirical understanding of the Cr₂C MXene, including its potential magnetic properties, as well as doing online machine learning classification tasks with arrays of magnetic synapsesElectrical and Computer Engineerin