CHARACTERIZATION OF RADIATION DAMAGE TO A NOVEL PHOTONIC CRYSTAL SENSOR

New methods of nuclear fuel and cladding characterization must be developed and implemented to enhance the safety and reliability of nuclear power plants. One class of such advanced methods is aimed at the characterization of fuel performance by performing minimally intrusive in-core, real time measurements on nuclear fuel on the nanometer scale. Nuclear power plants depend on instrumentation and control systems for monitoring, control and protection. Traditionally, methods for fuel characterization under irradiation are performed using a “cook and look” method. These methods are very expensive and labor-intensive since they require removal, inspection and return of irradiated samples for each measurement. Such fuel cladding inspection methods investigate oxide layer thickness, wear, dimensional changes, ovality, nuclear fuel growth and nuclear fuel defect identification. These methods are also not suitable for all commercial nuclear power applications as they are not always available to the operator when needed. Additionally, such techniques often provide limited data and may exacerbate the phenomena being investigated. This thesis investigates a novel, nanostructured sensor based on a photonic crystal design that is implemented in a nuclear reactor environment. The aim of this work is to produce an in-situ radiation-tolerant sensor capable of measuring the deformation of a nuclear material during nuclear reactor operations. The sensor was fabricated on the surface of nuclear reactor materials (specifically, steel and zirconium based alloys). Charged-particle and mixed-field irradiations were both performed on a newly-developed “pelletron” beamline at Idaho State University's Research and Innovation in Science and Engineering (RISE) complex and at the University of Maryland's 250 kW Training Reactor (MUTR). The sensors were irradiated to 6 different fluences (ranging from 1 to 100 dpa), followed by intensive characterization using focused ion beam (FIB), transmission electron microscopy (TEM) and scanning electron microscopy (SEM) to investigate the physical deformation and microstructural changes between different fluence levels, to provide high-resolution information regarding the material performance. Computer modeling (SRIM/TRIM) was employed to simulate damage to the sensor as well as to provide significant information concerning the penetration depth of the ions into the material.

Predictors of feelings of depression among Asian American college students

The purpose of this study is to explore the relationship between various collegiate experiences including substance use, religiosity, campus climate, academic life, social life, self-concept, satisfaction with college, and perceived feelings of depression among Asian American college students compared to other racial groups. Employing Astin’s (1993) I-E-O model, the study utilized the 2008 Cooperative Institutional Research Program (CIRP) the Freshman Survey (TFS) and the follow up College Senior Survey (CSS) in 2012 with the final sample of 10,710 students including 951 Asian American students. Descriptive analysis, cross-tabulations, blocked hierarchical multiple regression analysis, the equality of the unstandardized beta coefficients from the regression analyses, and a one-way ANOVA were conducted for the data analysis. Asian American students who are female, from low SES backgrounds, academically less achieved, frequent substance users, less religiously involved, and less satisfied with overall college experiences showed higher levels of feeling depressed. For the rate of feeling depressed across racial groups, Asian American college students showed the highest rate of feeling depressed while White students reported the lowest rate of feeling depressed. For Asian American college students, feeling depressed in high school, hours spent per week on studying and homework, and self-confidence in intellectual ability were the most significant predictors of feelings of depression while drinking beer, drinking liquor, spirituality, failing to complete homework on time, hours spent per week on socializing, self rated self-confidence in social ability, and satisfaction with overall college experiences were significant predictors of feelings of depression. Asian American college students spent the longest hours on studying and homework, reported the highest GPA, but showed the lowest self-confidence on intellectual ability. For all four racial groups, feeling depressed in high school and self-confidence in intellectual ability were significant predictors of feelings of depression in common. Implications for practice and directions for future research emphasize the need for better understanding the unique cultural background and impact of academic life associated with feelings of depression among Asian American college students and developing customized psycho-educational and outreach programs to meet unique needs for psychological well-being for each racial group on campus.