Petru Andrei

Some Possible Approaches for Improving the Energy Density of Li-Air Batteries

A physics-based model is proposed for the simulation of Li-air batteries. The model is carefully calibrated against published data and is used to simulate standard Li-air batteries with nonaqueous (organic) electrolyte. It is shown that the specific capacity is mainly limited by the oxygen diffusion length which is a function of the oxygen diffusivity in the electrolyte and the discharge current density. Various approaches to increase the specific capacity of the cathode electrode and the energy density of Li-air batteries are discussed. It is shown that, in order to increase the specific capacity and energy density, it is more efficient to use a nonuniform catalyst that enhances the reaction rate only at the separator-cathode interface than a catalyst uniformly distributed. Using uniformly distributed catalysts will enhance the current and power density of the cell but will not increase significantly the specific capacity and energy density. It is also shown that the specific capacity and energy density can be increased by suppressing the reaction rate at the oxygen-entrance interface in order to delay the pinch-off of the conduction channel in this region. Other possibilities to enhance the energy density such as using solvents with high oxygen solubility and diffusivity, and partly wetted electrodes are discussed.

Statistical analysis of semiconductor devices

A technique for the analysis of random dopant-induced effects in semiconductor devices is presented. It is based on the “small signal analysis” (perturbation) technique. It is computationally much more efficient than the existing purely “statistical” techniques, and it yields the information that can be directly used for the design of dopant fluctuation-resistant structures of semiconductor devices. This technique requires only the knowledge of variances of fluctuating doping concentrations and in this sense, it is a “second-moment characterization” technique. This technique can be naturally extended to take into account random fluctuations of oxide thickness and oxide charges in metal–oxide–semiconductor filed-effect transistor. The numerical implementation of this technique is discussed and numerous computational results are presented and compared with those previously published in the literature.

The Theoretical Energy Densities of Dual-Electrolytes Rechargeable Li-Air and Li-Air Flow Batteries

The theoretical energy densities of dual-electrolytes rechargeable Li-air batteries using a nonaqueous electrolyte in the anode andan aqueous electrolyte in the cathode are estimated based on the electrochemical reaction mechanisms and the solubility of thedischarge product. It is assumed that there is no solid deposition in a cathode during discharge. A number of basic and acidicelectrolytes with high solubility of the discharge product are proposed. The theoretical energy densities of these rechargeable Li-airbatteries vary from 140 to over 1100 Wh/kg depending on the type of the electrolytes in a cathode.Afew structures of Li-air flowbattery systems for possible large scale applications are also proposed.© 2010 The Electrochemical Society. DOI: 10.1149/1.3515330 All rights reserved.Manuscript submitted August 3, 2010; revised manuscript received September 19, 2010. Published November 23, 2010.

Quantum mechanical effects on random oxide thickness and random doping induced fluctuations in ultrasmall semiconductor devices

Quantum mechanical effects on fluctuations in ultrasmall semiconductor devices are studied. Quantum mechanical effects are included in the analysis by using the density gradient model, for which the main parameters (effective masses) are identified through the two-dimensional Schrodinger equation. A very fast technique for the computation of threshold voltage fluctuations induced by random oxide thickness and doping variations is proposed. This technique is based on linearization of the transport equations with respect to the fluctuating quantities. This technique is computationally very efficient because it avoids numerous simulations for various doping and oxide realizations (as in the case of Monte Carlo techniques). At the same time, it provides information about the sensitivity of threshold voltage to the fluctuations of oxide thicknesses and doping at different locations. Sample simulation results are reported and compared with those previously published and good agreement is observed.

Analysis of fluctuations in semiconductor devices through self-consistent Poisson-Schrödinger computations

The effects of random doping and random oxide thickness fluctuations in metal-oxide-semiconductor field-effect transistors are analyzed by using self-consistent Poisson-Schrodinger computations. The Poisson and Schrodinger equations are solved by using the Newton iteration technique in which the Jacobian matrix is computed through first-order perturbation theory in quantum mechanics. A very fast technique based on linearization of the transport equations is presented for the computation of threshold voltage fluctuations. This technique is computationally much more efficient than the traditional Monte Carlo approach and it yields information on the sensitivity of threshold voltage fluctuations to the locations of doping and oxide thickness fluctuations. Hence, it can be used in the design of fluctuation resistant structures of semiconductor devices. Sample simulation results obtained by using this linearization technique are reported and compared with those obtained by using the Monte Carlo technique.

Random doping-induced fluctuations of subthreshold characteristics in MOSFET devices

Abstract The random doping-induced fluctuations of subthreshold characteristics in MOSFET devices are analyzed. A technique for the computations of sensitivity coefficients and variances of subthreshold parameters is presented and applied to the computation of fluctuations of subthreshold current and gate-voltage swing. This technique is based on the linearization of transport equations with respect to the fluctuating quantities. It is computationally much more efficient than purely “statistical” methods (Monte-Carlo methods) that are based on the simulations of a large number of devices with different doping realizations. The numerical implementation of this technique is discussed and numerous computational results are presented.

Analysis of random-dopant induced fluctuations of frequency characteristics of semiconductor devices

A technique for the analysis of fluctuations of frequency characteristics of semiconductor devices induced by random-doping fluctuations is presented. This technique completely avoids computations for numerous doping realizations and, therefore, it is computationally much more efficient than purely “statistical” methods. This technique yields information on the sensitivity of variances of frequency characteristics to different locations of doping fluctuations. This information can be directly used for the design of dopant fluctuation-resistant structures of semiconductor devices. The numerical implementation of this technique is discussed and numerous computational results are presented and compared with those obtained by using purely statistical techniques.

Noise-Driven Phenomena in Hysteretic Systems

Description based on online resource; title from PDF title page (ebrary, viewed December 9, 2013).

Magnetic characterization of samples using first- and second-order reversal curve diagrams

The paper deals with the problem of magnetic characterization of samples with the first-order reversal curve (FORC) diagrams. Second-order reversal curves (SORCs) are introduced in a similar manner as in the generalized deltaM experimental procedure. SORC diagrams are calculated and compared with the well-known FORC diagrams. The difference between the FORC and SORC diagrams is explained. This difference represents an estimation of the errors made when the FORC distribution is considered as the distribution of coercive and interaction fields. Both Preisach and micromagnetic simulations of the FORC/SORC diagrams are presented and discussed.

Differential phenomenological models for the magnetization processes in soft MnZn ferrites

Jiles-Atherton, Hodgdon, and Preisach models have been used to simulate the magnetization processes measured for soft MnZn ferrite cores. Magnetization curves that were not used in the identification are calculated. The differences between the results of the simulations and the experimental data are discussed.