Drift velocity in GaN semiconductors: Monte Carlo simulation and comparison with experimental measurements

AbstractMonte Carlo algorithms are developed to simulate the electron transport in semiconductors. In particular, the drift velocity in GaN semiconductors is calculated, and a comparison with experimental measurements is discussed. Explicit expressions for the scattering probabilities and distributions of the scattering angle of electrons on polar optical and intervalley phonons, and acoustic deformation potential as well are given. A good agreement of the simulation results and the experimental measurements reveals that the M-L valley is located at 0.7 eV higher than the Γ-valley. This value agrees with other experimental studies, while it is lower compared to ab initio calculations.

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A Monte-Carlo Simulation of the Behaviour of Electron Swarms in Hydrogen Using an Anisotropic Scattering Model

Australian Journal of Physics ◽

10.1071/ph780299 ◽

1978 ◽

Vol 31 (4) ◽

pp. 299 ◽

Cited By ~ 14

Author(s):

HA Blevin ◽

J Fletcher ◽

SR Hunter

Keyword(s):

Experimental Data ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

Electron Transport ◽

Anisotropic Scattering ◽

Isotropic Scattering ◽

Transport Parameters ◽

Simulation Code ◽

Scattering Model ◽

Good Agreement

Hunter (1977) found that a Monte-Carlo simulation of electron swarms in hydrogen, based on an isotropic scattering model, produced discrepancies between the predicted and measured electron transport parameters. The present paper shows that, with an anisotropic scattering model, good agreement is obtained between the predicted and experimental data. The simulation code is used here to calculate various parameters which are not directly measurable.

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MONTE CARLO SIMULATION OF STEADY-STATE TRANSPORT IN SUBMICROMETER InP AND GaAsn+–i(n)–n+ DIODE

Modern Physics Letters B ◽

10.1142/s0217984910022603 ◽

2010 ◽

Vol 24 (06) ◽

pp. 549-560 ◽

Cited By ~ 2

Author(s):

H. ARABSHAHI ◽

M. REZAEE ROKN-ABADI ◽

F. BADIEIAN BAGHSIAHI ◽

M. R. KHALVATI

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Steady State ◽

Electron Transport ◽

Anode Voltage ◽

Electronic States ◽

Electron Velocity ◽

Back Scattering ◽

Simulation Results ◽

Average Electron

Monte Carlo simulation of electron transport in an InP diode of n+–i(n)–n+ structure is compared with GaAs diode. The anode voltage ranges from 0.5 to 1.5 V. The distributions of electron energies and electron velocities and the profiles of the electron density, electric field and potential and average electron velocity are computed. Based on these data, the near ballistic nature of the electron transport in the 0.2 μm-long diode and the importance of the back-scattering of electrons from the anode n+-layer are discussed. In addition, the effects of the lattice temperature and doping on the length of the active layer are discussed. Electronic states within the conduction band valleys at the Γ, L, and X are represented by non-parabolic ellipsoidal valleys centered on important symmetry points of the Brillouin zone. Our simulation results have also shown that the electron velocity characteristics in InP diode are more sensitive to temperature than in other III–V semiconductors such as GaAs .

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Coping with uncertainties in integrated urban water management

Water Science & Technology ◽

10.2166/wst.1997.0677 ◽

1997 ◽

Vol 36 (8-9) ◽

pp. 265-269

Author(s):

Govert D. Geldof

Keyword(s):

Water Management ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

Interdisciplinary Approach ◽

Urban Water ◽

Urban Water Management ◽

Integrated Water Management ◽

Good Design ◽

Management Techniques ◽

Simulation Results

In the practice of integrated water management we meet complexity, subjectivity and uncertainties. Uncertainties come into play when new urban water management techniques are applied. The art of a good design is not to reduce uncertainties as much as possible, but to find the middle course between cowardice and recklessness. This golden mean represents bravery. An interdisciplinary approach is needed to reach consensus. Calculating uncertainties by using Monte Carlo simulation results may be helpful.

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Cheating at Craps

ACM SIGMETRICS Performance Evaluation Review ◽

10.1145/3466826.3466845 ◽

2021 ◽

Vol 48 (4) ◽

pp. 53-61

Author(s):

Andrea Marin ◽

Carey Williamson

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Modeling And Simulation ◽

Analytical Model ◽

Quantitative Evaluation ◽

Mathematical Analysis ◽

Simulation Modeling ◽

Analytical Modeling ◽

The World ◽

Simulation Results

Craps is a simple dice game that is popular in casinos around the world. While the rules for Craps, and its mathematical analysis, are reasonably straightforward, this paper instead focuses on the best ways to cheat at Craps, by using loaded (biased) dice. We use both analytical modeling and simulation modeling to study this intriguing dice game. Our modeling results show that biasing a die away from the value 1 or towards the value 5 lead to the best (and least detectable) cheating strategies, and that modest bias on two loaded dice can increase the winning probability above 50%. Our Monte Carlo simulation results provide validation for our analytical model, and also facilitate the quantitative evaluation of other scenarios, such as heterogeneous or correlated dice.

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A Comparison of Different Data-driven Procedures to Determine the Bunching Window

Public Finance Review ◽

10.1177/1091142121993055 ◽

2021 ◽

Vol 49 (2) ◽

pp. 262-293

Author(s):

Vincent Dekker ◽

Karsten Schweikert

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Income Distribution ◽

Prior Information ◽

Structural Breaks ◽

Data Driven ◽

Taxable Income ◽

Counterfactual Models ◽

Simulation Results ◽

Second Procedure

In this article, we compare three data-driven procedures to determine the bunching window in a Monte Carlo simulation of taxable income. Following the standard approach in the empirical bunching literature, we fit a flexible polynomial model to a simulated income distribution, excluding data in a range around a prespecified kink. First, we propose to implement methods for the estimation of structural breaks to determine a bunching regime around the kink. A second procedure is based on Cook’s distances aiming to identify outlier observations. Finally, we apply the iterative counterfactual procedure proposed by Bosch, Dekker, and Strohmaier which evaluates polynomial counterfactual models for all possible bunching windows. While our simulation results show that all three procedures are fairly accurate, the iterative counterfactual procedure is the preferred method to detect the bunching window when no prior information about the true size of the bunching window is available.

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The effect of social distancing on the reach of an epidemic in social networks

Journal of Economic Interaction and Coordination ◽

10.1007/s11403-021-00322-9 ◽

2021 ◽

Author(s):

Gregory Gutin ◽

Tomohiro Hirano ◽

Sung-Ha Hwang ◽

Philip R. Neary ◽

Alexis Akira Toda

Keyword(s):

Public Health ◽

Infectious Disease ◽

Social Networks ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

Disease Transmission ◽

Global Level ◽

Social Distancing ◽

The Public ◽

Simulation Results

AbstractHow does social distancing affect the reach of an epidemic in social networks? We present Monte Carlo simulation results of a susceptible–infected–removed with social distancing model. The key feature of the model is that individuals are limited in the number of acquaintances that they can interact with, thereby constraining disease transmission to an infectious subnetwork of the original social network. While increased social distancing typically reduces the spread of an infectious disease, the magnitude varies greatly depending on the topology of the network, indicating the need for policies that are network dependent. Our results also reveal the importance of coordinating policies at the ‘global’ level. In particular, the public health benefits from social distancing to a group (e.g. a country) may be completely undone if that group maintains connections with outside groups that are not following suit.

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Should a hotter paramagnet transform quicker to a ferromagnet? Monte Carlo simulation results for Ising model

Physical Chemistry Chemical Physics ◽

10.1039/d1cp00879j ◽

2021 ◽

Author(s):

Subir K Das ◽

Nalina Vadakkayil

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Ising Model ◽

Simulation Results ◽

Heating Up

For quicker formation of ice, before inserting inside a refrigerator, heating up of a body of water can be beneficial. We report first observation of a counterpart of this intriguing...

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Monte Carlo Modeling and Design of Photon Energy Attenuation Layers for >10× Quantum Yield Enhancement in Si-Based Hard X-ray Detectors

Instruments ◽

10.3390/instruments5020017 ◽

2021 ◽

Vol 5 (2) ◽

pp. 17

Author(s):

Eldred Lee ◽

Kaitlin M. Anagnost ◽

Zhehui Wang ◽

Michael R. James ◽

Eric R. Fossum ◽

...

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Quantum Yield ◽

Photon Energy ◽

High Efficiency ◽

High Energy ◽

Yield Enhancement ◽

X Ray ◽

Simulation Results ◽

Conversion Efficiencies

High-energy (>20 keV) X-ray photon detection at high quantum yield, high spatial resolution, and short response time has long been an important area of study in physics. Scintillation is a prevalent method but limited in various ways. Directly detecting high-energy X-ray photons has been a challenge to this day, mainly due to low photon-to-photoelectron conversion efficiencies. Commercially available state-of-the-art Si direct detection products such as the Si charge-coupled device (CCD) are inefficient for >10 keV photons. Here, we present Monte Carlo simulation results and analyses to introduce a highly effective yet simple high-energy X-ray detection concept with significantly enhanced photon-to-electron conversion efficiencies composed of two layers: a top high-Z photon energy attenuation layer (PAL) and a bottom Si detector. We use the principle of photon energy down conversion, where high-energy X-ray photon energies are attenuated down to ≤10 keV via inelastic scattering suitable for efficient photoelectric absorption by Si. Our Monte Carlo simulation results demonstrate that a 10–30× increase in quantum yield can be achieved using PbTe PAL on Si, potentially advancing high-resolution, high-efficiency X-ray detection using PAL-enhanced Si CMOS image sensors.

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