1000 resultados para Vapor baths.


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Thin (50-500 nm) films of TiO2 may be deposited on glass substrates by the atmospheric pressure chemical vapor deposition (APCVD) reaction of TiCl4 with ethyl acetate at 400600 C. The TiO2 films are exclusively in the form of anatase, as established by Raman microscopy and glancing angle X-ray diffraction. X-ray photoelectron spectroscopy gave a 1:2 Ti:O ratio with Ti 2P(3/2) at 458.6 eV and O 1s is at 530.6 eV. The water droplet contact angle drops from 60degrees to

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In this paper investigations of the voltage required to break down water vapor are reported for the region around the Paschen minimum and to the left of it. In spite of numerous applications of discharges in biomedicine, and recent studies of discharges in water and vapor bubbles and discharges with liquid water electrodes, studies of the basic parameters of breakdown are lacking. Paschen curves have been measured by recording voltages and currents in the low-current Townsend regime and extrapolating them to zero current. The minimum electrical breakdown voltage for water vapor was found to be 480 V at a pressure times electrode distance (pd) value of around 0.6 Torr cm (similar to 0.8 Pa m). The present measurements are also interpreted using (and add additional insight into) the developing understanding of relevant atomic and particularly surface processes associated with electrical breakdown.

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We have demonstrated a self-aligned process to fabricate organized iron nanowires on a planarized surface with wire dimensions down to 50 nm. Polishing was used to expose an alternating silicon silicon dioxide edge and a dual selective metal deposition process produced the nanowires. The initial selective deposition produced a tungsten layer on the exposed polysilicon regions. The discovery that selective chemical vapor deposition of iron from Fe(CO)(5) precursor on dielectric surfaces over tungsten surfaces is the key factor that enables the self-alignment of the iron nanowires. Dimensions of the wires are determined by the thickness of the thermal oxide. (c) 2007 The Electrochemical Society.

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The generalized Langevin equation (GLE) method, as developed previously [L. Stella et al., Phys. Rev. B 89, 134303 (2014)], is used to calculate the dissipative dynamics of systems described at the atomic level. The GLE scheme goes beyond the commonly used bilinear coupling between the central system and the bath, and permits us to have a realistic description of both the dissipative central system and its surrounding bath. We show how to obtain the vibrational properties of a realistic bath and how to convey such properties into an extended Langevin dynamics by the use of the mapping of the bath vibrational properties onto a set of auxiliary variables. Our calculations for a model of a Lennard-Jones solid show that our GLE scheme provides a stable dynamics, with the dissipative/relaxation processes properly described. The total kinetic energy of the central system always thermalizes toward the expected bath temperature, with appropriate fluctuation around the mean value. More importantly, we obtain a velocity distribution for the individual atoms in the central system which follows the expected canonical distribution at the corresponding temperature. This confirms that both our GLE scheme and our mapping procedure onto an extended Langevin dynamics provide the correct thermostat. We also examined the velocity autocorrelation functions and compare our results with more conventional Langevin dynamics.

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We investigate the transport of phonons between N harmonic oscillators in contact with independent thermal baths and coupled to a common oscillator, and derive an expression for the steady state heat flow between the oscillators in the weak coupling limit. We apply these results to an optomechanical array consisting of a pair of mechanical resonators coupled to a single quantized electromagnetic field mode by radiation pressure as well as to thermal baths with different temperatures. In the weak coupling limit this system is shown to be equivalent to two mutually-coupled harmonic oscillators in contact with an effective common thermal bath in addition to their independent baths. The steady state occupation numbers and heat flows are derived and discussed in various regimes of interest.

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We undertake a thorough analysis of the thermodynamics of the trajectories followed by a quantum harmonic oscillator coupled to $N$ dissipative baths by using a new approach to large-deviation theory inspired by phase-space quantum optics. As an illustrative example, we study the archetypal case of a harmonic oscillator coupled to two thermal baths, allowing for a comparison with the analogous classical result. In the low-temperature limit, we find a significant quantum suppression in the rate of work exchanged between the system and each bath. We further show how the presented method is capable of giving analytical results even for the case of a driven harmonic oscillator. Based on that result, we analyse the laser cooling of the motion of a trapped ion or optomechanical system, illustrating how the emission statistics can be controllably altered by the driving force.

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We extend the generalized Langevin equation (GLE) method [L. Stella, C. D. Lorenz, and L. Kantorovich, Phys. Rev. B 89, 134303 (2014)] to model a central classical region connected to two realistic thermal baths at two different temperatures. In such nonequilibrium conditions a heat flow is established, via the central system, in between the two baths. The GLE-2B (GLE two baths) scheme permits us to have a realistic description of both the dissipative central system and its surrounding baths. Following the original GLE approach, the extended Langevin dynamics scheme is modified to take into account two sets of auxiliary degrees of freedom corresponding to the mapping of the vibrational properties of each bath. These auxiliary variables are then used to solve the non-Markovian dissipative dynamics of the central region. The resulting algorithm is used to study a model of a short Al nanowire connected to two baths. The results of the simulations using the GLE-2B approach are compared to the results of other simulations that were carried out using standard thermostatting approaches (based on Markovian Langevin and Nosé-Hoover thermostats). We concentrate on the steady-state regime and study the establishment of a local temperature profile within the system. The conditions for obtaining a flat profile or a temperature gradient are examined in detail, in agreement with earlier studies. The results show that the GLE-2B approach is able to treat, within a single scheme, two widely different thermal transport regimes, i.e., ballistic systems, with no temperature gradient, and diffusive systems with a temperature gradient.

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Soil vapor extraction (SVE) is an efficient, well-known and widely applied soil remediation technology. However, under certain conditions it cannot achieve the defined cleanup goals, requiring further treatment, for example, through bioremediation (BR). The sequential application of these technologies is presented as a valid option but is not yet entirely studied. This work presents the study of the remediation of ethylbenzene (EB)-contaminated soils, with different soil water and natural organic matter (NOMC) contents, using sequential SVE and BR. The obtained results allow the conclusion that: (1) SVE was sufficient to reach the cleanup goals in 63% of the experiments (all the soils with NOMC below 4%), (2) higher NOMCs led to longer SVE remediation times, (3) BR showed to be a possible and cost-effective option when EB concentrations were lower than 335 mg kgsoil −1, and (4) concentrations of EB above 438 mg kgsoil −1 showed to be inhibitory for microbial activity.

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The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.