Development of Metallic Magnetic Calorimeters and Paramagnetic Alloys of Ag and Er for Gamma-Ray Spectroscopy

A Metallic Magnetic Calorimeter (MMC) is a cryogenic calorimetric particle detector that employs a metallic paramagnetic alloy as the temperature sensor material. MMCs are used in many different applications, but this work will focus on their uses in high energy resolution gamma-ray spectroscopy. This technology is of great interest to the field of Nuclear Forensics and Nuclear Safeguards as a non-destructive assay for isotopic analysis of nuclear samples. The energy resolution of MMCs is an order of magnitude higher than the benchmark High Purity Germanium (HPGe) detectors that are currently used in the field and MMCs are also poised to outperform the current leading microcalorimeter, the Transition Edge Sensor (TES). This dissertation will cover the work in development of paramagnetic alloys of Ag and Er as the sensor material, and testing of two generations of devices. The heart of the MMC is the paramagnetic sensor material. The workhorse paramagnet for MMCs is currently an alloy of Au and Er. Although Au:Er is a high performing alloy, it starts to falter at the temperatures below 100 mK which are desirable to maximize the performance of the MMC. Au has a nuclear electric quadrupole moment, which at low temperatures, has its energy levels split by the radial electric fields created by the Er ions. This effect causes the specific heat of the alloy to increase as temperature is lowered, which diminishes device performance. A promising alternate paramagnet is an alloy of Ag and Er. Ag, with both naturally occuring isotopes having a nuclear spin of I=1/2, does not have a nuclear electric quadrupole moment. A technical challenge to working with Ag is that it has such a high affinity for oxygen that the usual method of creating Au:Er alloys may not be sufficient for Ag:Er. Much greater care has to be taken in removing oxygen from the alloy, as during creation the oxygen could adversely alter the Er dopant, thus degrading performance. To combat this, a vacuum induction furnace was developed to achieve the best possible control over synthesis process parameters. Description of the new furnace and test results from a successful synthesis of a Ag:Er alloy are discussed. The other half of the MMC is a high-performing Superconducting Quantum Interfence Device (SQUID) magnetometer. In previously reported devices, it was standard to have the sensing coil, magnetizing circuit, and paramagnet be on a separate chips from the SQUID magnetometer. The approach taken at UNM has been to integrate the SQUID magnetometer and paramagnetic sensor onto a single chip. Having an integrated device increases the performance of the MMC, at the cost of a more difficult fabrication process. Two exploratory wafers of magnetometers have been fabricated and tested for use as MMCs. The first wafer is a set of exploratory two-pixel devices, varying almost every aspect of the device to search for optimal device parameters. The second wafer consists of 14-pixel MMC arrays. A process of electroplating gold absorbers to the devices that now contain sensitive SQUIDs has been developed, using a two-mold system to define the legs and body of the absorbers. An initial Fe-55 spectrum from one of the new arrays is shown as a proof of concept measurement

InP and GaAs characterization with variable stoichiometry obtained by molecular spray

Both InP and GaAs surfaces were studied in parallel. A molecular spray technique was used to obtain two semiconductor surfaces with different superficial compositions. The structures of these surfaces were examined by electron diffraction. Electron energy loss was measured spectroscopically in order to determine surface electrical characteristics. The results are used to support conclusions relative to the role of surface composition in establishing a Schottky barrier effect in semiconductor devices

A weighted dual criterion for stochastic equivalent linearization method

A weighted dual mean square criterion for stochastic equivalent linearization method is considered in which the forward and backward replacements are weighted. The normalized weighting coefficient is suggested as a piecewise linear function of the squared correlation coefficient and is defined by the least square method based on the data of Lutes-Sarkani oscillator. The application to two typical nonlinear systems subjected to random excitation shows accurate approximations when the nonlinearity varies from the weak to strong levels

Comparing the Generating Strategies of Hydropower of Cascade Reservoirs to Mitigate the Shortage of Water Supply

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Oregon Coordinated Care Organizations: Impacts on Health and Health Care Utilization of Infants Enrolled in Medicaid

In August 2012, Oregon began enrolling Medicaid beneficiaries in coordinated care organizations (CCOs), a unique mandatory-enrollment accountable care organization (ACO) model with payment methods strongly tied to preventive care; care coordination; and integration of physical, mental and dental health care through patient-centered medical homes. This dissertation, consisting of two studies, examined the impact of the new delivery model on healthcare utilization and mortality among infants enrolled in Medicaid. Also, it investigated if the CCO model had heterogeneous impacts for preterm and full-term infants and if the effect of CCOs changed over the implementation timeline. Study 1 examined the extent to which CCOs had effects on healthcare utilization of infants during their two years of birth. Using Oregon birth certificates, Medicaid enrollment data, Medicaid claims, and hospital discharge data, a sample of 77,101 pre-CCO infants and 90,775 post-CCO infants was created whose healthcare utilization was followed for two years after birth. Service utilization outcomes included pediatric preventive care services, i.e., well-child visits and developmental screenings, emergency department (ED) visits, and hospital admissions. This study found that infants enrolled in CCOs received more preventive services compared to their pre-CCO counterparts. Impacts of CCOs on preventive care services also grew over the CCO implementation timeline. ED visits slightly increased and hospital admissions reduced after CCO implementation but not statistically significant. No statistically significant difference was found in the effects of CCOs on service utilization between preterm infants and full-term infants. Study 2 investigated the impact of CCO implementation on neonatal and infant mortality. The sample consisted of the pre-CCO birth cohort of 136,519 infants and the post-CCO birth cohort of 149,523 infants. Using difference-in-differences approach, the CCO model was found to be significantly associated with a reduction in both neonatal mortality (68% compared to the pre-CCO level) and infant mortality (37% compared to the pre-CCO level), and also with a greater reduction in infant mortality among preterm infants compared to full-term infants. The impact on infant mortality also grew in magnitude over the post implementation timeline. CCOs should continue their strategies to improve preventive care and health outcomes for infants. Given the plan to incorporate more specific policies to address children’s health in the next phase of CCO implementation in 2020-2024, future research should further investigate the effects of CCOs on utilization of ED and inpatient services and cost of care for children, as well as how CCOs would have an impact on different high-risk children populations