3 resultados para density function theory

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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This thesis focuses on studying molecular structure and internal dynamics by using pulsed jet Fourier transform microwave (PJ-FTMW) spectroscopy combined with theoretical calculations. Several kinds of interesting chemical problems are investigated by analyzing the MW spectra of the corresponding molecular systems. First, the general aspects of rotational spectroscopy are summarized, and then the basic theory on molecular rotation and experimental method are described briefly. ab initio and density function theory (DFT) calculations that used in this thesis to assist the assignment of rotational spectrum are also included. From chapter 3 to chapter 8, several molecular systems concerning different kind of general chemical problems are presented. In chapter 3, the conformation and internal motions of dimethyl sulfate are reported. The internal rotations of the two methyl groups split each rotational transition into several components line, allowing for the determination of accurate values of the V3 barrier height to internal rotation and of the orientation of the methyl groups with respect to the principal axis system. In chapter 4 and 5, the results concerning two kinds of carboxylic acid bi-molecules, formed via two strong hydrogen bonds, are presented. This kind of adduct is interesting also because a double proton transfer can easily take place, connecting either two equivalent or two non-equivalent molecular conformations. Chapter 6 concerns a medium strong hydrogen bonded molecular complex of alcohol with ether. The dimer of ethanol-dimethylether was chosen as the model system for this purpose. Chapter 7 focuses on weak halogen…H hydrogen bond interaction. The nature of O-H…F and C-H…Cl interaction has been discussed through analyzing the rotational spectra of CH3CHClF/H2O. In chapter 8, two molecular complexes concerning the halogen bond interaction are presented.

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This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

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Chalcogenides are chemical compounds with at least one of the following three chemical elements: Sulfur (S), Selenium (Sn), and Tellurium (Te). As opposed to other materials, chalcogenide atomic arrangement can quickly and reversibly inter-change between crystalline, amorphous and liquid phases. Therefore they are also called phase change materials. As a results, chalcogenide thermal, optical, structural, electronic, electrical properties change pronouncedly and significantly with the phase they are in, leading to a host of different applications in different areas. The noticeable optical reflectivity difference between crystalline and amorphous phases has allowed optical storage devices to be made. Their very high thermal conductivity and heat fusion provided remarkable benefits in the frame of thermal energy storage for heating and cooling in residential and commercial buildings. The outstanding resistivity difference between crystalline and amorphous phases led to a significant improvement of solid state storage devices from the power consumption to the re-writability to say nothing of the shrinkability. This work focuses on a better understanding from a simulative stand point of the electronic, vibrational and optical properties for the crystalline phases (hexagonal and faced-centered cubic). The electronic properties are calculated implementing the density functional theory combined with pseudo-potentials, plane waves and the local density approximation. The phonon properties are computed using the density functional perturbation theory. The phonon dispersion and spectrum are calculated using the density functional perturbation theory. As it relates to the optical constants, the real part dielectric function is calculated through the Drude-Lorentz expression. The imaginary part results from the real part through the Kramers-Kronig transformation. The refractive index, the extinctive and absorption coefficients are analytically calculated from the dielectric function. The transmission and reflection coefficients are calculated using the Fresnel equations. All calculated optical constants compare well the experimental ones.