Browsing by Author "Li, Xuan"

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    Iron Nitride Based Magnetoresistance Devices For Spintronic Applications
    (2018-03) Li, Xuan
    The iron nitrides have been attracting a wide interest in spintronics researches due to their unique magnetic properties. In this thesis, I describe the experimental studies of the spintronic devices based on two important iron nitride materials, i.e. Fe16N2 and Fe4N. In the Fe16N2 based magnetoresistance device development, a heavy-metal free, low damping, and non-interface perpendicular current-perpendicular-to-plane (CPP) giant magnetoresistance (GMR) device with Fe16N2 magnetic layers has been demonstrated. The crystalline based perpendicular anisotropy of the Fe16N2 in the CPP GMR device is measured to be about 1.9 e7 erg/cm3, which is sufficient to maintain the thermal stability of the sub-10nm devices. The damping constant of the Fe16N2 thin film is determined to be 0.01 by a ferromagnetic resonance measurement, which is much lower than most existing materials with crystalline perpendicular magnetic anisotropy. The non-interface perpendicular anisotropy and low damping properties of make Fe16N2 a promising material for future spintronic applications. In the Fe4N material and device studies, both the (111) oriented and (001) oriented Fe4N thin films are prepared by optimizing the buffer layers, substrate temperatures and N:Fe composition. The most attractive properties of Fe4N in spintronics are the large spin asymmetric conductance and the negative spin polarization. The spin polarization of the (111) oriented Fe4N is investigated. The thickness dependence of the spin polarization of the (111) oriented Fe4N is also explored. Moreover, I have studied the Gilbert damping constant of the Fe4N (001) thin film by ferromagnetic resonance. The αFe4N is determined to be 0.021±0.02. Last but not least, the current-perpendicular-to-plane (CPP) giant magnetoresistance (GMR) device with Fe4N/Ag/Fe sandwich have also been fabricated and characterized. Giant inverse magnetoresistance is observed in the Fe4N based CPP GMR device, which confirms that the spin polarization of Fe4N and Fe4N/Ag interface is negative.
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    Regression Matters (2014-02-20)
    (2014) Li, Xuan
    Regression is a statistical approach to investigating the relationship between variables. Regression techniques have been widely used in almost every field. This talk will be given by STAT 5511 Regression Analysis students (2013 Fall semester ) based on their class projects: • Estimation of Risk Rates using Arbitrage Pricing Theory (Michal Hrabia) • Lake Superior - clear and cold, almost good enough to drink (Tim Cyr, Yvette Ibrahim, Dave Ongaro, Kelly Peterson, Andrea Samuelson, Miranda Steinmetz) • Effects of Minimum Wage on Inflation (Katherine Borchert, Shinjini Kar, Cole Mathson) • Cases of Infectious Diseases: Determinants of the Number of Deaths due to Tuberculosis across Nations (Matthew Arthur, Jasmine Helgeson, Xiao Li, Penghuan Ni, Kyle Vezina, Zichao Wang)
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    A study of a network-flow algorithm and a noncorrecting algorithm for test assembly
    (1996) Armstrong, R. D.; Jones, D. H.; Li, Xuan; Wu, Ing-Long
    The network-flow algorithm (NFA) of Armstrong, Jones, & Wu (1992) and the average growth approximation algorithm (AGAA) of Luecht & Hirsch (1992) were evaluated as methods for automated test assembly. The algorithms were used on ACT and ASVAB item banks, with and without error in the item parameters. Both algorithms matched a target test information function on the ACT item bank, both before and after error was introduced. The NFA matched the target on the ASVAB item bank; however, the AGAA did not, even without error in this item bank. The AGAA is a noncorrecting algorithm, and it made poor item selections early in the search process when using the ASVAB item bank. The NFA corrects for nonoptimal choices with a simplex search. The results indicate that reasonable error in item parameters is not harmful for test assembly using the NFA or AGAA on certain types of item banks. Index terms: algorithmic test construction, automated test assembly, greedy algorithm, heuristic algorithm, item response theory, marginal maximum likelihood, mathematical programming, simulation, test construction.