Uzhhorod National University

About: Uzhhorod National University is a education organization based out in Uzhhorod, Ukraine. It is known for research contribution in the topics: Raman spectroscopy & Laser. The organization has 1089 authors who have published 1056 publications receiving 5187 citations. The organization is also known as: State Higher Education Establishment "Uzhhorod National University" & Uzhhorod State University.

Electron-Impact Excitation of Uracil Luminescence on a Ceramic Surface

Abstract: Photoelectron spectroscopy was applied to pyrimidine nitrogenous bases, an important class of six-membered heterocyclic compounds incorporated into nucleic acids. The emission spectrum of uracil adsorbed on a ceramic surface that was obtained by bombardment with 600-eV electrons in a high vacuum was analyzed. Broad bands with maxima at 335, 435, and 495 nm were observed in the UV and visible regions. The strongest band (λ = 335 nm) was attributed to fluorescence and corresponded to a singlet–singlet transition from the first excited electronic state into the molecular ground state. Electronic transitions from a triplet T1 into the ground state formed a weaker phosphorescence band (λ = 435 nm). The nature of the band maximum at 495 nm is discussed. The obtained luminescence spectrum was compared with photoluminescence spectra in various phases.

Raman scattering in chalcogenide‐based ferroelectrics: from bulk to nanoscale

Abstract: Evolution of Raman spectra of Sn2P2S6 and SbSI ferroelectrics is traced with the size reduction from bulk to nanometric crystals by milling. The role of confinement-related selection rules relaxation and surface phonon modes in the observed Ranam line broadening and asymmetry is discussed. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

Low-pressure ultraviolet emitter utilizing chlorine and krypton chloride molecules

Abstract: Results are given of an investigation of the electrical and optical characteristics of the plasma of a longitudinal high-frequency discharge in a krypton/chlorine mixture (P ≤ 1000 Pa). The high-frequency discharge is ignited in a cylindrical quartz tube with an inside diameter of 14 mm and a distance between the anode and cathode of 30 mm. The dynamics of current and radiation of the high-frequency discharge utilizing krypton/chlorine mixtures of different compositions and pressures are investigated. It is found that a longitudinal high-frequency in a krypton/chlorine mixture is a broadband excimer-halogen emitter in the 200–260 nm spectral range. The ultraviolet spectrum of the lamp is formed as a result of overlapping of broadened radiation bands of chlorine and krypton chloride molecules (200 nm , 222 nm KrCl 2 ** , and 257 nm Cl 2 * ). The optimal composition of a Kr/Cl2 mixture is determined, which is necessary to obtain the maximal power of ultraviolet radiation.

Production of excimer molecules and the excitation of nitrogen in a steady-state low-pressure electric discharge

Abstract: Conditions for the simultaneous production of argon and xenon chlorides and excited nitrogen molecules in a longitudinal dc glow discharge in Ar/Cl2/air, Xe/Cl2/air, and Ar/Xe/Cl2/air mixtures are studied. The electrical parameters of the plasma and its optical characteristics in the 130-to 350-nm wavelength range are investigated. It is shown that a small admixture of air added to argon or xenon leads to the production of excited nitrogen molecules, whose decay is accompanied by the molecular band emission in the range Δλ=176–271 nm. The conditions for simultaneous emission of the ArCl(B-X), XeCl(B-X), and nitrogen molecular bands are determined.

Project financing risk assessment technology

Abstract: The paper presents the technology of obtaining a quantitative assessment of the risk of financing projects at the stage of business expansion. The technology on the one hand uses quantitative assessments of the project on different indicators and on the basis of different models, and on the other hand uses the experience, knowledge, and competencies of experts in the subject area. The model uses a neuro-phase network of deep learning, increases the accuracy and objectivity of assessment.