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The purpose of this paper is to establish a systemic yoyo model‐based explanation for the internal structure of atoms, which is totally different of the conventional ones.

The spin fields of systemic yoyos are used to explain the interactions between electric and magnetic fields and between elementary particles.

The concepts of potential pits (traps) and ramparts for electrons and those of nuclear, atomic, and molecular bonds are introduced. These concepts are employed successfully to describe the topological structure of atoms.

Other than providing a brand new model for the internal structure of atoms, this paper establishes a deeper understanding of the general systemic yoyo mode.

We compare two approaches of incorporating the long‐range Coulomb electron‐electron interaction into Monte Carlo simulations of bulk, degenerate GaAs, i.e., the semi‐classical approach of solving the Poisson equation self‐consistently, and the first order quantum mechanical treatment in which the electron‐plasmon interaction is included as an additional scattering mechanism. The critical issues involved in the semi‐classical, direct approach are the mesh size, charge assignment to the mesh nodes, and interpolation of the field at the particle location. All of these factors determine the stability of the system, the accuracy and computational time required in the calculation. The steady‐state electron drift velocity in bulk GaAs calculated using the direct, semi‐classical approach for the electron‐plasmon interaction is significantly less than the corresponding bulk drift velocity in the absence of the electron‐plasmon interaction. The alternative approach of treating the electron‐plasmon interaction as a scattering mechanism is attractive since it is computationally easier to include and is, at least to first order, quantum mechanically based. It is found that the calculated steady‐state electron drift velocity in bulk GaAs based on this model is affected in the opposite way, i.e., the velocity is greater than in the absence of the electron‐plasmon interaction. The cause of the discrepancy in the calculated results of the two approaches is not too surprising since they attack the problem from very different directions. Neither model can at present be considered complete. Further detailed investigations are required to achieve a better model for the electron‐plasmon interaction.

This paper aims to present a new physically inspired meta-heuristic algorithm, which is called Plasma Generation Optimization (PGO). To evaluate the performance and capability of the proposed method in comparison to other optimization methods, two sets of test problems consisting of 13 constrained benchmark functions and 6 benchmark trusses are investigated numerically. The results indicate that the performance of the proposed method is competitive with other considered state-of-the-art optimization methods.

In this paper, a new physically-based metaheuristic algorithm called plasma generation optimization (PGO) algorithm is developed for solving constrained optimization problems. PGO is a population-based optimizer inspired by the process of plasma generation. In the proposed algorithm, each agent is considered as an electron. Movement of electrons and changing their energy levels are based on simulating excitation, de-excitation and ionization processes occurring through the plasma generation. In the proposed PGO, the global optimum is obtained when plasma is generated with the highest degree of ionization.

A new physically-based metaheuristic algorithm called the PGO algorithm is developed that is inspired from the process of plasma generation.

The results indicate that the performance of the proposed method is competitive with other state-of-the-art methods.

The purpose of this paper is to reach two goals: one is to generalize the well‐studied theories of electricity and magnetism to the enrichment of deepened understanding of the general systemic yoyo model, and the other is to employ the established yoyo model to provide more refined explanations for some of the known experimental observations in physics.

The general structure and the field characteristics of the general systemic yoyo model are employed as the basis of our exploration in this paper. Then, methods of quantitative analysis are introduced to address some of the problems encountered.

Among several new results, many important concepts, such as ring‐shaped electric fields, cylinders of equal potential intensities, yoyo resistances, yoyo capacitors, etc. are introduced and studied in some detail. Several important Laws in electromagnetic theory, such as Ohm's law, Kirchhoff's laws, etc. are generalized to the case of the general systemic yoyo model. The refined theory is applied to provide theoretical explanations for some laboratory‐observed phenomena that cannot be well illustrated by either Faraday's theory of electromagnetic induction or Lenz's law.

Phenomena related to electricity and magnetism are explained the first time in history by using a unified model: the systemic yoyo model. At the same time, some well established Laws in physics are generalized to scenarios of this general mode with the hope that these new Laws can be applied equally well to natural and social sciences in the coming years.

This study seeks to explain how a cybernetic system, the human brain, creates the cognitive models that are applied by physics to explain particular phenomena of the physical world, namely, the electrostatic force and the annihilation of matter and antimatter.

This study applies findings in cognitive psychology of vision, neuropsychology of the hemispheric mechanisms and quantum mechanics in order to explain how the electrostatic force operates at distance between two charged particles.

In addition to the quantum fields theory, which explains the electrostatic force by photons that carry this force between charged particles (and is related to the left‐hemispheric cognitive mechanism) a dual theory is suggested that explains this force by interchanging of features between particles (and is related to the right‐hemispheric cognitive mechanism).

Like Fidelman's previous studies, this too demonstrates that cybernetic considerations which use cognitive psychological, neuropsychological and physical‐knowledge can obtain testable and applicable physical theories.

A new quantum effect device which is capable of highly coherent electron emission is theoretically proposed and analysed. The new device works by using the potential induced accumulation layer at a heterointerface to produce dimensionally reduced electrons. These electrons tunnel through a heterobarrier ensuring that their energy is quantised in the direction of propagation. To avoid the problem of unquantised three dimensional electrons dominating the current the two dimensional electrons that tunnel through the barrier are replenished by electrons from two side contacts. A self‐consistent model is used to analyse the performance of the device and it is found that the new device performs very well, producing electrons with a very narrow energy spread in the direction of propagation. The current density/coherency combination is easily controlled by the applied bias and the device also offers the potential for ultra fast switching through the transition between coherent and incoherent states.

With the advent of sophisticated growth techniques such as Molecular Beam Epitaxy and Metal Organic Chemical Vapor Deposition, the calculation of the energy boundstates and electron wave‐functions of the one‐electron Schrödinger equation has received a lot of attention over the last decade. With the more recent fabrication of quantum wires and dots, it seems now imperative to extend the boundstates calculation to systems containing only a few electrons. Hereafter, we investigate the effect of electron exchange and Coulomb interactions on the boundstates of a two‐electron system in a square quantum well. The technique is based on a general Alternating Direction Implicit algorithm ( T. Singh and M. Cahay, SPIE Vol. 1675, Quantum Wells and Superlattice Physics IV (1992), p.11) combined with a Fourier spectrum analysis of the two‐particle wavefunction correlation , <ψ(χ1,χ2;0)/ψ(χ1,χ2;τ)> , where χ1, χ2 are the coordinates of the two electrons. The precise location of the energy eigenvalues requires the appropriate use of window functions before calculating the Fourier transform of the correlation function. We also compare our results for the boundstate energies with those obtained using a first order time‐independent perturbation theory.

The purpose of this work is to study the capability of heuristic algorithms like genetic algorithm to estimate the electron transport parameters of the Gallium Arsenide (GaAs). Also, the paper provides a simple but complete electron mobility model for the GaAs based on the genetic algorithm that can be suitable for use in simulation, optimization and design of GaAs‐based electronic and optoelectronic devices.

The genetic algorithm as a powerful heuristic optimization technique is used to approximate the electron transport parameters during the model development.

The capability of the model to approximate the electron transport properties of Gallium Arsenide is tested using experimental and Monte Carlo data. Results show that the genetic algorithm based model can provide a reliable estimate of the electron mobility in Gallium Arsenide for a wide range of temperatures, concentrations and electric fields. Based on the obtained results, this paper shows that the genetic algorithm can be a useful tool for the estimation of the transport parameters of semiconductors.

For the first time, the genetic algorithm is used to calculate the electron transport parameters in Gallium Arsenide. A complete electron mobility model for a wide range of temperatures, doping concentrations, compensation ratios and electric fields is developed.

An energy‐momentum transport model for sub‐micron silicon devices is modified to include new sets of simple interband scattering models representing impact ionization, auger recombination, trapping and photo generation. These have been developed using a simplified physical modelling approach. A discretization scheme suitable for application to an irregular spatial grid is presented. The resulting model is suitable for the study of small geometry effects in silicon devices.

The basis of most semi‐conductor devices is the p‐n junction. Here p‐type material is brought into contact with n‐type material by a suitable process so that between the two types of material we have a zone of transition — the depletion layer. This layer spans the region where purely p‐type properties change to purely n‐type. On one side of the layer there are many holes in the valence band and on the other there are many electrons in the conduction band. How we present this state of affairs to the student may be open to question, but, as electrons are the particles which move, it is considered better to represent the conduction electrons as possessing higher energy, i.e. to let electron energy be considered to be positive upward in any model or diagram produced to explain the p‐n junction and its rectifying properties.