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Sample records for giaever ivar

  1. Ivar Giaever, Tunneling, and Superconductors

    Office of Scientific and Technical Information (OSTI)

    Ivar Giaever, Tunneling, and Superconductors Resources with Additional Information * Patents Ivar Giaever Courtesy of Rensselaer Polytechnic Institute 'Dr. Giaever received his engineering degree at the Norwegian Institute of Technology. After college, he emigrated to Canada, where he worked as a mechanical engineer with General Electric, and later transferred to GE's Development Center in Schenectady, N.Y. There, he shifted his interest to physics, and did graduate work at Rensselaer, receiving

  2. Patents -- Ivar Giaever (1977-1979)

    Office of Scientific and Technical Information (OSTI)

    ... US 4,163,983 SOLID STATE NEURON -- Giaever, Ivar; Cline, Harvey E.; Anthony, Thomas R.; August 7, 1979 A semiconductor neuron comprises a tunnel diode having a region of recrystallized ...

  3. Patents -- Ivar Giaever (1980-2008)

    Office of Scientific and Technical Information (OSTI)

    US 4,514,500 CELL GROWTH ON LIQUID-LIQUID INTERFACES -- Giaever, Ivar; Keese, Richard C.; April 30, 1985 Droplets having an electrical charge on the surface thereof are prepared ...

  4. Patents -- Ivar Giaever (1976)

    Office of Scientific and Technical Information (OSTI)

    ... used to provide large and widely-distributed surface area for sorting out and separating select viruses, bacteria and other cells from multi-cell, bacteria or virus populations. ...

  5. Patents -- Ivar Giaever (1976)

    Office of Scientific and Technical Information (OSTI)

    and separating select viruses, bacteria and other cells from multi-cell, bacteria or virus populations. US 3,975,238 METHOD AND APPARATUS FOR DETECTING MOLECULES IN SOLUTIONS --...

  6. Jian-Xin Zhu Los Alamos National Laboratory

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    electronic structure and inhomogeneity in heavy fermion systems Jian-Xin Zhu Los Alamos National Laboratory QDM 2015, Santa Fe, Mar. 9, 2015 Collaborators: Jean-Pierre Julien (UJF) Joseph Wang (LANL) Ivar Martin (ANL) Alan R. Bishop (LANL) Yoni Dubi (Ben Gurion) Sasha Balatsky (LANL) Supported by DOE BES Program LANL-LDRD * Emergent phenomena and electronic inhomogeneity in correlated electron systems * Staggered Kondo Phase * Local electronic structure in Kondo hole * Local electronic structure

  7. A Physically Based Correlation of Irradiation-Induced Transition Temperature Shifts for RPV Steels

    SciTech Connect (OSTI)

    Eason, Ernest D.; Odette, George Robert; Nanstad, Randy K; Yamamoto, Takuya


    The reactor pressure vessels (RPVs) of commercial nuclear power plants are subject to embrittlement due to exposure to high-energy neutrons from the core, which causes changes in material toughness properties that increase with radiation exposure and are affected by many variables. Irradiation embrittlement of RPV beltline materials is currently evaluated using Regulatory Guide 1.99 Revision 2 (RG1.99/2), which presents methods for estimating the shift in Charpy transition temperature at 30 ft-lb (TTS) and the drop in Charpy upper shelf energy (?USE). The purpose of the work reported here is to improve on the TTS correlation model in RG1.99/2 using the broader database now available and current understanding of embrittlement mechanisms. The USE database and models have not been updated since the publication of NUREG/CR-6551 and, therefore, are not discussed in this report. The revised embrittlement shift model is calibrated and validated on a substantially larger, better-balanced database compared to prior models, including over five times the amount of data used to develop RG1.99/2. It also contains about 27% more data than the most recent update to the surveillance shift database, in 2000. The key areas expanded in the current database relative to the database available in 2000 are low-flux, low-copper, and long-time, high-fluence exposures, all areas that were previously relatively sparse. All old and new surveillance data were reviewed for completeness, duplicates, and discrepancies in cooperation with the American Society for Testing and Materials (ASTM) Subcommittee E10.02 on Radiation Effects in Structural Materials. In the present modeling effort, a 10% random sample of data was reserved from the fitting process, and most aspects of the model were validated with that sample as well as other data not used in calibration. The model is a hybrid, incorporating both physically motivated features and empirical calibration to the U.S. power reactor surveillance data. It contains two terms, corresponding to the best-understood radiation damage features, matrix damage and copper-rich precipitates, although the empirical calibration will ensure that all other damage processes that are occurring are also reflected in those terms. Effects of material chemical composition, product form, and radiation exposure are incorporated, such that all effects are supported by findings of statistical significance, physical understanding, or comparison with independent data from controlled experiments, such as the Irradiation Variable (IVAR) Program. In most variable effects, the model is supported by two or three of these different forms of evidence. The key variable trends, such as the neutron fluence dependence and copper-nickel dependence in the new TTS model, are much improved over RG1.99/2 and are well supported by independent data and the current understanding of embrittlement mechanisms. The new model includes the variables copper, nickel, and fluence that are in RG1.99/2, but also includes effects of irradiation temperature, neutron flux, phosphorus, and manganese. The calibrated model is a good fit, with no significant residual error trends in any of the variables used in the model or several additional variables and variable interactions that were investigated. The report includes a chapter summarizing the current understanding of embrittlement mechanisms and one comparing the IVAR database with the TTS model predictions. Generally good agreement is found in that quantitative comparison, providing independent confirmation of the predictive capability of the TTS model. The key new insight in the TTS modeling effort, that flux effects are evident in both low (or no) copper and higher copper materials, is supported by the IVAR data. The slightly simplified version of the TTS model presented in Section 7.3 of this report is recommended for applications.