8 research outputs found
Magnetische Kernresonanzuntersuchungen an einkristallinem TiO2 (Rutil)
SIGLEAvailable from the library of Dortmund Univ. (DE) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman
Design and operation of a variable high-temperature oxygen partial-pressure probe device for solid-state NMR
Localized Proton NMR spectroscopy in the striatum of patients with idiopathic Parkinson's disease: a multicenter pilot study
Microstructural Analysis of Peripheral Lung Tissue through CPMG Inter-Echo Time R2 Dispersion
Science with e-ASTROGAM A space mission for MeV-GeV gamma-ray astrophysics
e-ASTROGAM ('enhanced ASTROGAM') is a breakthrough Observatory space mission, with a detector composed by a Silicon tracker, a calorimeter, and an anticoincidence system, dedicated to the study of the non-thermal Universe in the photon energy range from 0.3 MeV to 3 GeV - the lower energy limit can be pushed to energies as low as 150 keV for the tracker, and to 30 keV for calorimetric detection. The mission is based on an advanced space-proven detector technology, with unprecedented sensitivity, angular and energy resolution, combined with polarimetric capability. Thanks to its performance in the MeV-GeV domain, substantially improving its predecessors, e-ASTROGAM will open a new window on the non-thermal Universe, making pioneering observations of the most powerful Galactic and extragalactic sources, elucidating the nature of their relativistic outflows and their effects on the surroundings. With a line sensitivity in the MeV energy range one to two orders of magnitude better than previous generation instruments, e-ASTROGAM will determine the origin of key isotopes fundamental for the understanding of supernova explosion and the chemical evolution of our Galaxy. The mission will provide unique data of significant interest to a broad astronomical community, complementary to powerful observatories such as LIGO-Virgo-GEO600-KAGRA, SKA, ALMA, E-ELT, TMT, LSST, JWST, Athena, CTA, IceCube, KM3NeT, and LISA. (C) 2018 Elsevier B.V. All rights reserved