71,407 research outputs found
Superconductivity in the A15 Structure
The cubic A15 structure metals, with over 60 distinct member compounds, held
the crown of highest Tc superconductor starting in 1954 with the discovery of
Tc=18 K in Nb3Sn. Tc increased over the next 20 years until the discovery in
1973 of Tc = 22.3 K (optimized to approximately 23 K a year later) in sputtered
films of Nb3Ge. Attempts were made to produce - via explosive compression -
higher (theorized to be 31-35 K) transition temperatures in not stable at
ambient conditions A15 Nb3Si. However, the effort to continue the march to
higher Tc values in A15 Nb3Si only resulted in a defect-suppressed Tc of 19 K
by 1981. Focus in superconductivity research partially shifted with the advent
of heavy Fermion superconductors (CeCu2Si2, UBe13, and UPt3 discovered in 1979,
1983 and 1984 respectively) and further shifted away from A15 superconductors
with the discovery of the perovskite structure cuprate superconductors in 1986
with Tc=35 K. However, the A15 superconductors, and specifically doped Nb3Sn,
are still the material of choice today for most applications where high
critical currents (e. g. magnets with dc persistent fields up to 21 T) are
required. Thus, this article discusses superconductivity, and the important
physical properties and theories for the understanding thereof, in the A15
superconductors which held the record Tc for the longest time (32 years) of any
known class of superconductor since the discovery of Tc=4.2 K in Hg in 1911.
The discovery in 2008 of Tc=38 K at 7 kbar in A15 Cs3C60 (properly a member of
the fullerene superconductor class), which is an insulator at 1 atm pressure
and otherwise also atypical of the A15 class of superconductors, will be
briefly discussed.Comment: contribution to the special issue on Superconductivity and Its
Applications in Physica C, Volume 51
Amplifier enhances ring-down spectroscopy
In recent years, investigators have adapted the principles of ringdown spectroscopy (see sidebar, facing page) to fiber optic configurations by placing high reflectors on each end of a fiber and observing the ringdown time of an injected pulse. But a major drawback is the difficulty of creating a low-loss, high-Q resonator in an optical fiber
Hamiltonian theory of nonlinear waves in planetary rings
The derivation of a Hamiltonian field theory for nonlinear density waves in Saturn's rings is discussed. Starting with a Hamiltonian for a discrete system of gravitating streamlines, an averaged Hamiltonian is obtained by successive applications of Lie transforms. The transformation may be carried out to any desired order in q, where q is the nonlinearity parameter defined in the work of Shu, et al (1985) and Borderies et al (1985). Subsequent application of the Wentzel-Kramer-Brillouin Method approximation yields an asymptotic field Hamiltonian. Both the nonlinear dispersion relation and the wave action transport equation are easily derived from the corresponding Lagrangian by the standard variational principle
Multistage multiple-reentry turbine Patent
Multistage multiple reentry axial flow reaction turbine with reverse flow reentry ductin
A selective control information detection scheme for OFDM receivers
In wireless communications, both control information and payload (user-data) are concurrently transmitted and required to be successfully recovered. This paper focuses on block-level detection, which is applicable for detecting transmitted control information, particularly when this information is selected or chosen from a finite set of information that are known at both transmitting and receiving devices. Using an orthogonal frequency division multiplexing architecture, this paper investigates and evaluates the performance of a time-domain decision criterion in comparison with a form of Maximum Likelihood (ML) estimation method. Unlike the ML method, the proposed time-domain detection technique requires no channel estimation as it uses the correlation (in the time-domain) that exists between the received and the transmitted selective information as a means of detection. In comparison with the ML method, results show that the proposed method offers improved detection performance, particularly when the control information consists of at least 16. However, the implementation of the proposed method requires a slightly increased number of mathematical computations
Saccharomyces cerevisiae in the production of fermented beverages
Alcoholic beverages are produced following the fermentation of sugars by yeasts, mainly (but not exclusively) strains of the species, Saccharomyces cerevisiae. The sugary starting materials may emanate from cereal starches (which require enzymatic pre‐hydrolysis) in the case of beers and whiskies, sucrose‐rich plants (molasses or sugar juice from sugarcane) in the case of rums, or from fruits (which do not require pre‐hydrolysis) in the case of wines and brandies. In the presence of sugars, together with other essential nutrients such as amino acids, minerals and vitamins, S. cerevisiae will conduct fermentative metabolism to ethanol and carbon dioxide (as the primary fermentation metabolites) as the cells strive to make energy and regenerate the coenzyme NAD+ under anaerobic conditions. Yeasts will also produce numerous secondary metabolites which act as important beverage flavour congeners, including higher alcohols, esters, carbonyls and sulphur compounds. These are very important in dictating the final flavour and aroma characteristics of beverages such as beer and wine, but also in distilled beverages such as whisky, rum and brandy. Therefore, yeasts are of vital importance in providing the alcohol content and the sensory profiles of beverages. This Introductory Chapter reviews, in general, the growth, physiology and metabolism of S. cerevisiae in alcoholic beverage fermentations
Electrocardiogram-based feature extraction for machine learning classification of obstructive sleep apnea
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