Electron device simulation

The electronic devices simulate the different stages of the human olfactory system, resulting in volatile odor recognition, which can now be used to discriminate between different bacterial infections. (Turner Magan, 2004)... 

Given the substantial differences between the systems being simulated, the force-fields traditionally used by researchers in computational electronics and in chemistry are necessarily different. In particular, short-range coulombic interactions are either neglected in electron device simulations, or they are treated with a stochastic approach rather than deterministically. The same considerations apply for finite size effects. 

The nail penetration test is very important and is considered to simulate an internal short in a cell. No electronic device can protect against an internal short, so the cell... 

We have designed, manufactured and tested a prototype that may be applied in thermal control of electronic devices. It was fabricated from a silicon substrate and a Pyrex cover, serving as both an insulator and a window through which flow patterns and boiling phenomena could be observed. A number of parallel triangular micro-channels were etched in the substrate. The heat transferred from the device was simulated by different types of electrical heaters that provided uniform and non-uniform heat fluxes, defined here respectively as constant and non-constant values... 

The authors developed a multi-layered microreactor system with a methanol reforma- to supply hydrogen for a small proton exchange membrane fiiel cell (PEMFC) to be used as a power source for portable electronic devices [6]. The microreactor consists of four units (a methanol reformer with catalytic combustor, a carbon monoxide remover, and two vaporizers), and was designed using thermal simulations to establish the rppropriate temperature distribution for each reaction, as shown in Fig. 3. 

Klaessens [14-17] developed a laboratory simulator , written in SIMULA, which by a question-answering session assembles the simulation model. SIMULA [18] is a programming environment dedicated to the simulation of queuing systems. KEE [ 19] offers a graphics-driven discrete event simulator, in which the objects are represented by icons which can be connected into a logical network (e.g. a production line for the manufacturing of electronic devices). Although KEE has proven its potential in many areas, no examples are known of analytical laboratories simulated in KEE. 

M. Barbara, A. Bonfiglio, and L. Raffo, A charge-modulated FET for detection of biomolecular processes conception, modelling, and simulation. IEEE Trans. Electron Devices 53, 158-166 (2006). 

Like the performance of chemical reactors, in which the transport and reactions of chemical species govern the outcome, the performance of electronic devices is determined by the transport, generation, and recombination of carriers. The main difference is that electronic devices involve charged species and electric fields, which are present only in specialized chemical reactors such as plasma reactors and electrochemical systems. Furthermore, electronic devices involve only two species, electrons and holes, whereas 10-100 species are encountered commonly in chemical reactors. In the same manner that species continuity balances are used to predict the performance of chemical reactors, continuity balances for electrons and holes may be used to simulate electronic devices. The basic continuity equation for electrons has the form... 

R.A. Escobar, S.S. Ghai, M.S. Jhon, and C. Amon, Time-dependent simulations of subcontinuum heat generation effects in electronic devices using the lattice-Boltzmann method,... 

Bhaskara Reddy Penumalli, A Comprehensive Tvo-Dimensional VLSI Process Simulation Program, BICEPS, IEEE Tnns. Electron Devices, ED-30, No. 9, 986-992 (1983). 

Chlipala, J.D., Scarfome, L.M., and Lu, C.Y. (1989) Computer-Simulated Explosion of Poly-Silicide Links in Laser-Programmable Redundancy for VLSI Memory Repair, IEEE Trans, on Electron Devices, Vol. 36, pp. 2433-... 

As it is highly advantageous in terms of electronic device properties to restrict the chemistry to dopant and silicon molecules, the atomic species were kept unchanged, but the simulation model was used to change the bond structure at the silicon surface. It was shown that manipulating the structure of the silicon surface enables precise nanometer-scale control of the junction depth due to a... 

Gummel, H.K. (1964) A Self-consistent Iterative Scheme for One-dimensional Steady State Transistor Calculations. IEEE Trans. Electron Devices, ED-11, 455-465. Lee, C.M., Lomax, R.J. and Haddad, G.I. (1974) Semiconductor Device Simulation. IEEE Trans. Microw. Theory Techn., MTT-22, 160-177. 

Molecular Dynamics Simulations of a Molecular Electronics Device The NanoCell (.J. Seminario, P. Derosa, L. Cordova B. Bozard)... 

Based on the TD-HEDT, Chen et al. have proposed and developed a practical first-principles formalism for open electronic systems and implemented it to simulate transient currents through electronic devices [42, 60]. The resulting first-principles formalism for open system starts from a closed equation of motion (EOM) for the Kohn-Sham (KS) reduced single-electron density matrix (RSDM) of the entire system, and reduces to the following Liouville-von Neumann equation by projecting out the electronic degrees of freedom of the electrodes ... 

Eirst-principles simulation has been carried out to simulate the transient current through a series of molecular and nanoscopic electronic devices, based on the AWBL approximation for Qq, and EDA for exchange-correlation functional. Figure 2.1 depicts a carbon nanotube based electronic device. The device is a (5, 5)... 

The silicon photodiode output is analyzed using a device simulator intended for analyzing the semiconductor device electrical characteristics, with the added capability of analyzing the movement of electrons/holes when the silicon photodiode is exposed to light. Fig. 7.13.4, Fig. 7.13.5, and Fig. 7.13.6 show a photodiode analysis model, a mesh diagram, and an impurity density distribution map. 

Governing Equations. If the problem is to be solved rigorously, the BTE must be solved for electrons in each valley, optical phonons, and acoustic phonons. The distribution function of each of these depends on six variables—three space and three momentum (or energy). The solution to BTE for this complexity becomes very computer intensive, especially due to the fact that the timescales of electron-phonon and phonon-phonon interactions vary by two orders of magnitude. Monte Carlo simulations are sometimes used although this, too, is very time-consuming. Therefore, researchers have resorted mainly to hydrodynamic equations for modeling electron and phonon transport for practical device simulation. 

Foam was demonstrated to successfully humidify dry inlet air to 87% saturation at 60°C using a simulated power electronic device. 

M. Hack and M. Shur, Computer simulation of amorphous silicon based p-i-n solar cells, IEEE Electron Device Lett. EDL-4 (1983) 140-143. 

---