First Principles Study of Surface States and Tetragonal Distortion in Half Metals

Magnetic materials have been an increasingly popular area of research over the past decade. Half-metallic materials, in particular, are of specific interest due to their high degree of spin-polarization. One application of these materials that is of interest is spintronics. Electronics utilize the electric charge of electrons, while spintronics utilizes the spin of these electrons instead. Half-metals are very promising for this application, as they generally hold their magnetic properties up to high temperatures, and are relatively cheap compared to other metals. The following research has two goals for two different half metals. Firstly, identify the so called ‘surface properties’ of Ti2MnAl0.5Sn0.5,. Second, determine the crystal structure of Mn2PtSn

Atomic disorder induced modification of magnetization in MnCrVAl

We have investigated the physical mechanism behind magnetization reduction in a potential spingapless semiconducting compound MnCrVAl by analyzing various atomic disorder schemes. In particular, we show that depending on the degree of disorder, exchanging atomic positions between Mn/Cr and V/Al leads to reduced total magnetization due to either spin flip, or vanishing spin magnetic moments. The latter is attributed to the itinerant character of magnetism in Cr-, Mn-, and V-containing Heusler alloys, and to the frustration of antiferromagnetic exchange interactions, and is accompanied by a tetragonal distortion, but such distortion alone (i.e., in a fully ordered crystal, with no atomic disorder) is not sufficient for a transition to zero magnetization. Besides, we demonstrate that in certain disordered structures the spin polarization of MnCrVAl significantly increases, reaching the half-metallic state. Our calculations indicate that exchange of atomic positions of Mn with Cr, and V with Al has no significant effect on electronic and magnetic properties of MnCrVAl. We also show that antisite disorder does not result in significant reduction of magnetization. At the same time, some types of antisite disorder result in essentially 100% spin-polarized structures. These findings may contribute to understanding the role of atomic disorder on magnetic properties of materials with potential applications in spin-based electronics

Effect of Structural Disorder on Magnetic Properties of MnCrVAl

Operation of virtually any modern electronic device relies on magnetic materials. In particular, these materials are the cornerstone of data storage and processing in computer hardware elements, such as hard drives and random access memories. Here, we theoretically study an interplay between structural and magnetic properties of MnCrVAl, a material which recently attracted significant attention due to its rather exotic electronic structure. In particular, this material behaves either as an insulator or as a metal, depending on which “spin” (an intrinsic property of any fundamental particle) of the electron is considered. Using advanced computer simulation techniques (density functional calculations on a supercomputer), we show that structural disorder (i.e. displacement of atoms from their regular positions) in this material has a decisive impact on its magnetic properties. Our theoretical findings are in excellent agreement with recently published experimental results, and may open new avenues in an emerging field of spin-based electronics

System for beating CAPTCHA using artificial intelligence

A CAPTCHA (completely automated public Turing test to tell computers and humans apart) is a type of challenge-response test used in websites to determine whether the user is a human or not. CAPTCHAs were invented to prevent computer bots from spamming websites. With the advent of online businesses, CAPTCHAs became more and more important and are now employed by almost all websites. For example, Paypal uses CAPTCHA before any money transfer to make sure that the user owns the profile, Facebook limits the creation of fraudulent profiles which are used to cheat people, and Reddit prevents bots from flooding the webpage with directed messages. Although CAPTCHAs play a crucial role in the web, as computer hardware and artificial intelligence techniques evolved, artificial intelligence gained the ability to beat CAPTCHAs. If we know what kind of algorithms can beat it, only then can we prepare next-generation CAPTCHAs that are more resilient. This project focuses on devising and implementing various artificial intelligence, image processing and procedural programming techniques to create a system that solves CAPTCHAs with significant accuracy. It tackles the most widely used CAPTCHA 1 scheme which uses a combination of distorted characters that humans can recognize but that may be difficult for automated scripts