Segregation energies of oxygen vacancies and protons near three symmetric tilt grain boundaries (GBs) in BaZrO3 are determined using density functional theory. Two of the GBs have the $ \overline 1 ...$10 direction as tilt axis with a (111) or (112) plane as GB plane, while the third has the 001 direction as tilt axis and a (210) plane as GB plane. Both defects are found to segregate to all three GBs, with vacancy segregation energies of –0.5 and –1.5 eV and proton segregation energies of about –0.8 eV. The effects of the calculated segregation energies on defect concentrations and electrostatic potential in the GB region are investigated using a thermodynamic space charge model. An increased concentration of defects is seen in all GBs, giving electrostatic potential barriers around 0.6 V at 400–600 K. Protons are found to give important contributions to the space charge in all three GBs.
The cyclotron radiation emission spectroscopy (CRES) technique pioneered by Project 8 measures electromagnetic radiation from individual electrons gyrating in a background magnetic field to construct ...a highly precise energy spectrum for beta decay studies and other applications. The detector, magnetic trap geometry and electron dynamics give rise to a multitude of complex electron signal structures which carry information about distinguishing physical traits. With machine learning models, we develop a scheme based on these traits to analyze and classify CRES signals. Proper understanding and use of these traits will be instrumental to improve cyclotron frequency reconstruction and boost the potential of Project 8 to achieve world-leading sensitivity on the tritium endpoint measurement in the future.
In energy system models endogenous technological change can be introduced by implementing so-called technology learning rates specifying the quantitative relationship between the cumulative ...experience of a technology and its cost. The objectives of this paper are to: (a) provide a conceptual review of learning curve model specifications; and (b) conduct a meta-analysis of wind power learning rates. This permits an assessment of a number of important specification and data issues that influence these learning rates. The econometric analysis builds on 113 estimates of the learning-by-doing rate presented in 35 studies. The meta-analysis indicates that the choice of the geographical domain of learning, and thus the assumed presence of learning spillovers, is an important determinant of wind power learning rates. We also find that the use of extended learning curve concepts, e.g., integrating public R&D effects, appears to result in lower learning rates than those generated by so-called single-factor learning curve studies. Overall the empirical findings suggest that future studies should pay increased attention to the issue of learning and knowledge spillovers in the renewable energy field, as well as to the interaction between technology learning and R&D efforts.
► We review various learning curve approaches and conduct a meta-analysis of wind power learning rates. ► The choice of the geographical domain of learning greatly influences estimated learning rates. ► The single-factor learning curve generates higher learning rates than the extended model specifications.
Abstract
Segregation energies of oxygen vacancies and protons near three symmetric tilt grain boundaries (GBs) in BaZrO
3
are determined using density functional theory. Two of the GBs have the
$ ...\overline 1 $
10 direction as tilt axis with a (111) or (112) plane as GB plane, while the third has the 001 direction as tilt axis and a (210) plane as GB plane. Both defects are found to segregate to all three GBs, with vacancy segregation energies of –0.5 and –1.5 eV and proton segregation energies of about –0.8 eV. The effects of the calculated segregation energies on defect concentrations and electrostatic potential in the GB region are investigated using a thermodynamic space charge model. An increased concentration of defects is seen in all GBs, giving electrostatic potential barriers around 0.6 V at 400–600 K. Protons are found to give important contributions to the space charge in all three GBs.
Bayesian modeling techniques enable sensitivity analyses that incorporate detailed expectations regarding future experiments. A model-based approach also allows one to evaluate inferences and ...predicted outcomes, by calibrating (or measuring) the consequences incurred when certain results are reported. We present procedures for calibrating predictions of an experiment's sensitivity to both continuous and discrete parameters. Using these procedures and a new Bayesian model of the $\beta$-decay spectrum, we assess a high-precision $\beta$-decay experiment's sensitivity to the neutrino mass scale and ordering, for one assumed design scenario. We find that such an experiment could measure the electron-weighted neutrino mass within $\sim40\,$meV after 1 year (90$\%$ credibility). Neutrino masses $>500\,$meV could be measured within $\approx5\,$meV. Using only $\beta$-decay and external reactor neutrino data, we find that next-generation $\beta$-decay experiments could potentially constrain the mass ordering using a two-neutrino spectral model analysis. By calibrating mass ordering results, we identify reporting criteria that can be tuned to suppress false ordering claims. In some cases, a two-neutrino analysis can reveal that the mass ordering is inverted, an unobtainable result for the traditional one-neutrino analysis approach.
Project 8 has developed a novel technique, cyclotron radiation emission spectroscopy (CRES), for direct neutrino mass measurements. A CRES-based experiment on the beta spectrum of tritium has been ...carried out in a small-volume apparatus. Here, we provide a detailed account of the experiment, focusing on systematic effects and analysis techniques. In a Bayesian (frequentist) analysis, we measure the tritium endpoint as ${18}$ ${553}_{—19}^{+18}$ (${18}$ ${548}_{—19}^{+19}$) eV and set upper limits of 155 (152) eV (90% C.L.) on the neutrino mass. No background events are observed beyond the endpoint in 82 days of running. We also demonstrate an energy resolution of 1.66 ± 0.19 eV in a resolution-optimized magnetic trap configuration by measuring 83mKr 17.8-keV internal-conversion electrons. These measurements establish CRES as a low-background, high-resolution technique with the potential to advance neutrino mass sensitivity
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