Journal articles: 'Monte-Charge'

1

Wang, Xidi, and George A. Baker. "Monte carlo calculations of the conformal charge." Journal of Statistical Physics 69, no. 5-6 (December 1992): 1069–95. http://dx.doi.org/10.1007/bf01058762.

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2

Yu, Unjong, Hoseung Jang, and Chi-Ok Hwang. "A diffusion Monte Carlo method for charge density on a conducting surface at non-constant potentials." Monte Carlo Methods and Applications 27, no. 4 (October 28, 2021): 315–24. http://dx.doi.org/10.1515/mcma-2021-2098.

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Abstract We develop a last-passage Monte Carlo algorithm on a conducting surface at non-constant potentials. In the previous researches, last-passage Monte Carlo algorithms on conducting surfaces with a constant potential have been developed for charge density at a specific point or on a finite region and a hybrid BIE-WOS algorithm for charge density on a conducting surface at non-constant potentials. In the hybrid BIE-WOS algorithm, they used a deterministic method for the contribution from the lower non-constant potential surface. In this paper, we modify the hybrid BIE-WOS algorithm to a last-passage Monte Carlo algorithm on a conducting surface at non-constant potentials, where we can avoid the singularities on the non-constant potential surface very naturally. We demonstrate the last-passage Monte Carlo algorithm for charge densities on a circular disk and the four rectangle plates with a simple voltage distribution, and update the corner singularities on the unit square plate and cube.

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3

Budrin, K. S., Yu D. Panov, A. S. Moskvin, and A. A. Chikov. "Unconventional phase separation in the model 2D spin-pseudospin system." EPJ Web of Conferences 185 (2018): 11006. http://dx.doi.org/10.1051/epjconf/201818511006.

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The competition of charge and spin orderings is a challenging problem for strongly correlated systems, in particular, for high-Tc cuprates. We addressed a simplified static 2D spin-pseudospin model which takes into account both conventional spin exchange coupling and the on-site and inter-site charge correlations. Classical Monte-Carlo calculations for large square lattices show that homogeneous ground state antiferromagnetic solutions found in a mean-field approximation are unstable with respect to phase separation into the charge and spin subsystems behaving like immiscible quantum liquids. In this case, with lowering of a temperature one can observe two sequential phase transitions: first, antiferromagnetic ordering in the spin subsystem diluted by randomly distributed charges, then, the charge condensation in the charge droplets. The inhomogeneous droplet phase reduces the energy of the system and changes the diagram of the ground states. On the other hand, the ground state energy of charge-ordered state in a mean-field approximation exactly matches the numerical Monte-Carlo calculations. The doped charges in this case are distributed randomly over a system in the whole temperature range. Various thermodynamic properties of the 2D spin-pseudospin system are studied by Monte-Carlo simulation.

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4

Kim, J. S., C. Liu, D. H. Edgell, and R. Pardo. "Monte Carlo beam capture and charge breeding simulation." Review of Scientific Instruments 77, no. 3 (March 2006): 03B106. http://dx.doi.org/10.1063/1.2170105.

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5

Akeyoshi, Tomoyuki, Koichi Maezawa, Masaaki Tomizawa, and Takashi Mizutani. "Monte Carlo Study of Charge Injection Transistors (CHINTs)." Japanese Journal of Applied Physics 32, Part 1, No. 1A (January 15, 1993): 26–30. http://dx.doi.org/10.1143/jjap.32.26.

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6

Ziaeian, Iman, and Károly Tőkési. "nl-Selective Classical Charge-Exchange Cross Sections in Be4+ and Ground State Hydrogen Atom Collisions." Atoms 10, no. 3 (September 9, 2022): 90. http://dx.doi.org/10.3390/atoms10030090.

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Charge-exchange cross sections in Be4+ + H(1s) collisions are calculated using the three-body classical trajectory Monte Carlo method (CTMC) and the quasi-classical trajectory Monte Carlo method of Kirschbaum and Wilets (QCTMC) for impact energies between 10 keV/amu and 300 keV/amu. We present charge-exchange cross sections in the projectile n = 2 and nl = 2s, 2p states. Our results are compared with the previous quantum-mechanical approaches. We found that the QCTMC model is a powerful classical model to describe the state-selective charge-exchange cross sections at lower impact energies and the QCTMC results are in good agreement with previous observations.

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7

Nicolis, Nikolaos George, and Athanasios Chatzikotelis. "Development of a simple algorithm for pre-fragment formation in proton-nucleus spallation reactions." HNPS Advances in Nuclear Physics 29 (May 5, 2023): 196–99. http://dx.doi.org/10.12681/hnpsanp.5084.

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A Monte-Carlo algorithm is developed and coded in FORTRAN to calculate the energy, mass and charge distribution of the pre-fragments produced in proton induced spallation. The algorithm is based on Glauber’s theory together with a reasonable assumption on the type of the promptly emitted nucleons. For the evaporation stage, correlated values of pre-fragment mass, charge and excitation energy were fed into a properly modified version of the code MCEF (Monte-Carlo Evaporation-Fission) written in Java. A good agreement is obtained with the experimental mass and charge distributions of residues observed in 56Fe+p spallation reactions at 300, 500 and 750 MeV/A

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8

Illescas, Clara, Luis Méndez, Santiago Bernedo, and Ismanuel Rabadán. "Charge Transfer and Electron Production in Proton Collisions with Uracil: A Classical and Semiclassical Study." International Journal of Molecular Sciences 24, no. 3 (January 21, 2023): 2172. http://dx.doi.org/10.3390/ijms24032172.

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Cross sections for charge transfer and ionization in proton–uracil collisions are studied, for collision energies 0.05<E<2500 keV, using two computational models. At low energies, below 20 keV, the charge transfer total cross section is calculated employing a semiclassical close-coupling expansion in terms of the electronic functions of the supermolecule (H-uracil)+. At energies above 20 keV, a classical-trajectory Monte Carlo method is employed. The cross sections for charge transfer at low energies have not been previously reported and have high values of the order of 40 Å2, and, at the highest energies of the present calculation, they show good agreement with the previous results. The classical-trajectory Monte Carlo calculation provides a charge transfer and electron production cross section in reasonable agreement with the available experiments. The individual molecular orbital contributions to the total electron production and charge transfer cross sections are analyzed in terms of their energies; this permits the extension of the results to other molecular targets, provided the values of the corresponding orbital energies are known.

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9

Buscemi, Fabrizio, Enrico Piccinini, Rossella Brunetti, Massimo Rudan, and Carlo Jacoboni. "Monte Carlo simulation of charge transport in amorphous chalcogenides." Journal of Applied Physics 106, no. 10 (November 15, 2009): 103706. http://dx.doi.org/10.1063/1.3259421.

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10

Jakobsson, Mattias, and Sven Stafström. "A Monte Carlo study of charge transfer in DNA." Journal of Chemical Physics 129, no. 12 (September 28, 2008): 125102. http://dx.doi.org/10.1063/1.2981803.

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11

Piccinini, E., F. Buscemi, M. Rudan, R. Brunetti, and C. Jacoboni. "Monte Carlo simulation of charge transport in amorphous chalcogenides." Journal of Physics: Conference Series 193 (November 1, 2009): 012022. http://dx.doi.org/10.1088/1742-6596/193/1/012022.

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12

Lugli, P. "Monte Carlo simulation of charge transport in semiconductor devices." Microelectronic Engineering 19, no. 1-4 (September 1992): 275–82. http://dx.doi.org/10.1016/0167-9317(92)90437-v.

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13

Lauwers, P. G., and G. Schütz. "Estimation of the central charge by Monte Carlo simulations." Physics Letters B 256, no. 3-4 (March 1991): 491–96. http://dx.doi.org/10.1016/0370-2693(91)91796-x.

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14

Kundrotas, Petras J., and Andrey Karshikoff. "Effects of charge–charge interactions on dimensions of unfolded proteins: A Monte Carlo study." Journal of Chemical Physics 119, no. 6 (August 8, 2003): 3574–81. http://dx.doi.org/10.1063/1.1588996.

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15

Kabbe, Gabriel, Christian Dreßler, and Daniel Sebastiani. "Proton mobility in aqueous systems: combining ab initio accuracy with millisecond timescales." Physical Chemistry Chemical Physics 19, no. 42 (2017): 28604–9. http://dx.doi.org/10.1039/c7cp05632j.

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16

Kaiser, Waldemar, Tim Albes, and Alessio Gagliardi. "Charge carrier mobility of disordered organic semiconductors with correlated energetic and spatial disorder." Physical Chemistry Chemical Physics 20, no. 13 (2018): 8897–908. http://dx.doi.org/10.1039/c8cp00544c.

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17

Fan, Jianzhong, Lili Lin, and Chuan-Kui Wang. "Molecular stacking effect on photoluminescence quantum yield and charge mobility of organic semiconductors." Physical Chemistry Chemical Physics 19, no. 44 (2017): 30147–56. http://dx.doi.org/10.1039/c7cp05451c.

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18

Maynard, G., C. Deutsch, P. Fromy, and K. Katsonis. "Atomic physics for inertial fusion using average correlated hydrogenic atom model." Laser and Particle Beams 13, no. 2 (June 1995): 271–79. http://dx.doi.org/10.1017/s0263034600009381.

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The influence of discrepancies between analytical expressions for charge changing cross section on the ionization state of swift heavy ions interacting with hot and dense plasmas is analyzed within the framework of our new average correlated hydrogenic atom model. Making use of our Classical Trajectory Monte-Carlo results, we show that the partial charge transfer cross section into the projectile atomic levels has the same importance as the total charge transfer cross section.

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19

Bridwell, LB, HJ Hay, LF Pender, CJ Sofield, and PB Treacy. "Excitation of Swift Heavy Ions in Foil Targets. IV. Preequilibrium Energy Losses and Mean Charge States." Australian Journal of Physics 41, no. 5 (1988): 681. http://dx.doi.org/10.1071/ph880681.

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Studies have been made of the approach to energy-loss and charge-state equilibrium of initially pure charge states of ions, transmitted through thin carbon targets. Ions of Li, F and C1 at 3 MeV per AMU were used. Detailed observations were made of outgoing energy losses and charge-state distributions, for outgoing charges equal to those ingoing. A Monte Carlo analysis is made of the charge changing processes, which allows calculation of energy losses due to projectile charge exchange. The residual electronic target-ionisation loss is analysed to predict in-target charge states of the projectile ions. Using these, a comparison is made between the in-target effective charge for target ionisation, and the averaged ionic charge which fits charge-exchange data.

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20

Patra, Chandra N. "Size and charge correlations in spherical electric double layers: a case study with fully asymmetric mixed electrolytes within the solvent primitive model." RSC Advances 10, no. 64 (2020): 39017–25. http://dx.doi.org/10.1039/d0ra06145j.

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21

Liu, F. H. "Article." Canadian Journal of Physics 76, no. 8 (August 1, 1998): 601–7. http://dx.doi.org/10.1139/p98-026.

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The conditional moments of the charge distributions of the projectile fragments in sulphur fragmentation at 200 GeV/N are obtained using the simple Monte Carlo partition method. Thus, the logarithmic correlations between the conditional moments can be observed. The distributions of conditional moments are investigated. The results of the nuclear diffractive excitation, electromagnetic dissociation, and Monte Carlo methods are compared.PACS Nos.: 25.70Np and 25.70-z

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22

Yan Yonghong, 闫永宏, 赵宗清 Zhao Zongqing, 吴玉迟 Wu Yuchi, 魏来 Wei Lai, 洪伟 Hong Wei, 谷渝秋 Gu Yuqiu, 曹磊峰 Cao Leifeng, and 姚泽恩 Yao Zeen. "Monte Carlo simulation on single photon counting charge coupled device." High Power Laser and Particle Beams 25, no. 1 (2013): 211–14. http://dx.doi.org/10.3788/hplpb20132501.0211.

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23

Bakhshandeh, Amin, Derek Frydel, and Yan Levin. "Reactive Monte Carlo simulations for charge regulation of colloidal particles." Journal of Chemical Physics 156, no. 1 (January 7, 2022): 014108. http://dx.doi.org/10.1063/5.0077956.

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24

Mandowski, A., and J. Swiatek. "Monte Carlo Simulation of Charge Carriers' Trapping in Polycrystalline Semiconductors." Solid State Phenomena 51-52 (May 1996): 367–72. http://dx.doi.org/10.4028/www.scientific.net/ssp.51-52.367.

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25

Gagorik, Adam G., Jacob W. Mohin, Tomasz Kowalewski, and Geoffrey R. Hutchison. "Monte Carlo Simulations of Charge Transport in 2D Organic Photovoltaics." Journal of Physical Chemistry Letters 4, no. 1 (December 13, 2012): 36–42. http://dx.doi.org/10.1021/jz3016292.

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26

Ortiz-Álvarez, H. H., C. M. Bedoya-Hincapié, and E. Restrepo-Parra. "Monte Carlo simulation of charge mediated magnetoelectricity in multiferroic bilayers." Physica B: Condensed Matter 454 (December 2014): 235–39. http://dx.doi.org/10.1016/j.physb.2014.08.002.

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27

Crow, G. C., and R. A. Abran. "Monte Carlo simulations of charge transport in high-speed lasers." IEEE Journal of Quantum Electronics 33, no. 7 (July 1997): 1190–96. http://dx.doi.org/10.1109/3.594883.

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28

Požela, Juras. "Monte Carlo simulation of charge-carrier behavior in electric fields." Computer Physics Communications 67, no. 1 (August 1991): 105–18. http://dx.doi.org/10.1016/0010-4655(91)90224-9.

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29

Patra, Chandra N. "Structure of fully asymmetric mixed electrolytes around a charged nanoparticle: a density functional and simulation investigation." RSC Advances 5, no. 32 (2015): 25006–13. http://dx.doi.org/10.1039/c5ra00643k.

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A systematic study on the structure of mixed electrolytes with arbitrary size and charge asymmetry around a charged nanoparticle is carried out using density functional theory and Monte Carlo simulation.

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30

Shukri, Seyfan Kelil, and Lemi Demeyu Deja. "Charge Carriers Density, Temperature, and Electric Field Dependence of the Charge Carrier Mobility in Disordered Organic Semiconductors in Low Density Region." Condensed Matter 6, no. 4 (November 3, 2021): 38. http://dx.doi.org/10.3390/condmat6040038.

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We investigate the transport properties of charge carriers in disordered organic semiconductors using a model that relates a mobility with charge carriers (not with small polarons) hopping by thermal activation. Considering Miller and Abrahams expression for a hopping rate of a charge carrier between localized states of a Gaussian distributed energies, we employ Monte Carlo simulation methods, and calculate the average mobility of finite charge carriers focusing on a lower density region where the mobility was shown experimentally to be independent of the density. There are Monte Carlo simulation results for density dependence of mobility reported for hopping on regularly spaced states neglecting the role of spatial disorder, which does not fully mimic the hopping of charge carriers on randomly distributed states in disordered system as shown in recent publications. In this work we include the spatial disorder and distinguish the effects of electric field and density which are not separable in the experiment, and investigate the influence of density and electric field on mobility at different temperatures comparing with experimental results and that found in the absence of the spatial disorder. Moreover, we analyze the role of density and localization length on temperature and electric field dependence of mobility. Our results also give additional insight regarding the value of localization length that has been widely used as 0.1b where b is a lattice sites spacing.

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31

Zhao, L., B. Cluggish, J. S. Kim, R. Pardo, and R. Vondrasek. "Simulation of charge breeding of rubidium using Monte Carlo charge breeding code and generalized ECRIS model." Review of Scientific Instruments 81, no. 2 (February 2010): 02A304. http://dx.doi.org/10.1063/1.3277192.

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32

KIM, SUNIL, JOONHYUN YEO, and CHAN IM. "TRANSIT TIME DISTRIBUTION AND MOBILITY IN MONTE CARLO SIMULATIONS OF THE GAUSSIAN DISORDER MODEL." International Journal of Modern Physics B 27, no. 05 (January 21, 2013): 1350010. http://dx.doi.org/10.1142/s0217979213500100.

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We study the distribution of transit times in Monte Carlo simulations of the Gaussian disorder model (GDM). The GDM is one of the most successful models to describe the charge transport in random organic materials. The transit time is the time it takes for a charge carrier to travel across a sample. We find that the distribution of transit times over many charge carriers and over different realizations of Gaussian energies shows a heavy tail in the long time limit at low temperatures. This heavy tail can be described by a power law with an exponent that depends on temperature. This sets a limitation on the calculation of mobility of charge carriers using an average transit time at low temperatures. We discuss the implication of these results on dispersive transport.

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33

Delhorme, Maxime, Bo Jönsson, and Christophe Labbez. "Gel, glass and nematic states of plate-like particle suspensions: charge anisotropy and size effects." RSC Adv. 4, no. 66 (2014): 34793–800. http://dx.doi.org/10.1039/c4ra05555a.

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The influence of the charge anisotropy and platelet size on the formation of gel and glass states and nematic phases in suspensions of plate-like particles is investigated using Monte Carlo simulations in the canonical ensemble.

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34

Borzdov V. M., Borzdov A. V., and Vasileuski Y. G. "Definition of electron polar scattering angle on ionized impurities for Monte Carlo simulation of charge carrier transport in semiconductors." Semiconductors 57, no. 1 (2023): 14. http://dx.doi.org/10.21883/sc.2023.01.55615.4425.

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Procedures of polar scattering angle simulation for electron scattering on ionized impurities are examined for Brooks--Herring, Conwell--Weisskopf and Ridley models as the most frequently used in Monte Carlo simulation of charge carrier transport in semiconductors. A more correct procedure for polar scattering angle simulation is proposed for Ridley model. Peculiarities of scattering angle distribution densities calculated in the framework of regarded models are analyzed taking silicon as an example. Comparison of electron mobility calculated by ensemble Monte Carlo method using considered models has been done for doped silicon at 300 K and for constant electric field strength F = 7· 104 V/m. Keywords: ionized impurity, electron scattering, Monte Carlo method.

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35

Fan, Jian-Xun, Li-Fei Ji, Ning-Xi Zhang, Pan-Pan Lin, Gui-Ya Qin, Shou-Feng Zhang, and Ai-Min Ren. "Theoretical study of synergetic effect between halogenation and pyrazine substitutions on transport properties of silylethynylated pentacene." New Journal of Chemistry 43, no. 8 (2019): 3583–600. http://dx.doi.org/10.1039/c8nj04714f.

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Combining quantum-tunneling-effect-enabled hopping theory with kinetic Monte Carlo simulation and dynamic disorder effects, the charge transport properties of a series of N-hetero 6,13-bis(triisopropylsilylethynyl)pentacene (TIPS-PEN) derivatives with halogen substitutions were studied.

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36

Ferdows, M., and M. Ota. "Density of CO2 Hydrate by Monte Carlo Simulation." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 220, no. 5 (May 1, 2006): 691–96. http://dx.doi.org/10.1243/09544062c13104.

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In order to perform the density of CO2 hydrate, Monte Carlo simulations have been carried out under constant temperature and pressure conditions. The physical property of density have been focused for the clathrate hydrate of CO2: CO2.5.75H2O; CO2.7.67H2O at temperatures ranging from 150 to 280 K and pressure up to 10 Mpa in the number of particles, temperature, and pressure (NPT) ensemble using simple point charge (SPC) intermolecular potential model of water. Comparisons between Monte Carlo-calculated result SPC and the result calculated by transferable intermolecular potential (TIP4P) model are also presented.

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37

Bastiaansen, Paul J. M., and Hubert J. F. Knops. "Monte Carlo method to calculate the central charge and critical exponents." Physical Review E 57, no. 4 (April 1, 1998): 3784–96. http://dx.doi.org/10.1103/physreve.57.3784.

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38

Bressanini, Dario, Massimo Mella, and Gabriele Morosi. "Stability of four-unit-charge systems: A quantum Monte Carlo study." Physical Review A 55, no. 1 (January 1, 1997): 200–205. http://dx.doi.org/10.1103/physreva.55.200.

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39

Zhou, J., Y. C. Zhou, X. D. Gao, C. Q. Wu, X. M. Ding, and X. Y. Hou. "Monte Carlo simulation of charge transport in electrically doped organic solids." Journal of Physics D: Applied Physics 42, no. 3 (December 18, 2008): 035103. http://dx.doi.org/10.1088/0022-3727/42/3/035103.

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40

Lee, Choongkeun, Mino Yang, Nam-Soo Lee, and Nakjoong Kim. "Monte Carlo simulation of trap effects on space-charge field formation." Chemical Physics Letters 418, no. 1-3 (January 2006): 54–58. http://dx.doi.org/10.1016/j.cplett.2005.09.135.

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41

Bratko, D., and V. Vlachy. "Monte Carlo studies of polyelectrolyte solutions. Effect of polyelectrolyte charge density." Chemical Physics Letters 115, no. 3 (April 1985): 294–98. http://dx.doi.org/10.1016/0009-2614(85)80031-2.

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42

Kerisit, Sebastien, and Kevin M. Rosso. "Kinetic Monte Carlo model of charge transport in hematite (α-Fe2O3)." Journal of Chemical Physics 127, no. 12 (September 28, 2007): 124706. http://dx.doi.org/10.1063/1.2768522.

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43

Yamamoto, O., T. Hara, I. Nakanishi, and M. Hayashi. "Monte Carlo simulation of surface charge on angled insulators in vacuum." IEEE Transactions on Electrical Insulation 28, no. 4 (1993): 706–12. http://dx.doi.org/10.1109/14.231554.

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44

Tata, B. V. R., and A. K. Arora. "The phase diagram of charge-polydisperse colloids: a Monte Carlo study." Journal of Physics: Condensed Matter 3, no. 40 (October 7, 1991): 7983–93. http://dx.doi.org/10.1088/0953-8984/3/40/019.

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45

Xie, Fengyu, Peichen Zhong, Luis Barroso-Luque, Bin Ouyang, and Gerbrand Ceder. "Semigrand-canonical Monte-Carlo simulation methods for charge-decorated cluster expansions." Computational Materials Science 218 (February 2023): 112000. http://dx.doi.org/10.1016/j.commatsci.2022.112000.

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46

Bässler, H. "Charge Transport in Disordered Organic Photoconductors a Monte Carlo Simulation Study." physica status solidi (b) 175, no. 1 (January 1, 1993): 15–56. http://dx.doi.org/10.1002/pssb.2221750102.

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47

González, T., I. Iñiguez-de-la-Torre, D. Pardo, J. Mateos, S. Bollaert, Y. Roelens, and A. Cappy. "Monte Carlo simulation of surface charge effects in T-branch nanojunctions." physica status solidi (c) 5, no. 1 (January 2008): 94–97. http://dx.doi.org/10.1002/pssc.200776512.

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48

Kaiser, Jan, Mike Castellano, David Gnandt, and Thorsten Koslowski. "Monte Carlo simulation and thermodynamic integration applied to protein charge transfer." Journal of Computational Chemistry 41, no. 11 (January 25, 2020): 1105–15. http://dx.doi.org/10.1002/jcc.26155.

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49

JIAXIN, DU, LI NA, and LIU LIANSHOU. "ON THE RELATION BETWEEN THE WIDTH OF CHARGE BALANCE FUNCTION AND HADRONIZATION TIME IN RELATIVISTIC HEAVY ION COLLISION." International Journal of Modern Physics E 16, no. 10 (November 2007): 3355–62. http://dx.doi.org/10.1142/s0218301307009336.

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A Monte Carlo study on the charge balance function in high energy hadron-hadron and relativistic heavy ion collisions are carried out using the Monte Carlo generators PYTHIA and AMPT, respectively. A strong dependence of the width of balance function on multiplicity is found in both cases. Using the mean parton-freeze-out time of a heavy-ion-collision event as the characteristic hadronization time for the event, it is found that for a fixed multiplicity interval the width of balance function is consistent with being independent of hadronization time.

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50

ALVAREZ-MUÑIZ, J., E. MARQUES, R. A. VAZQUEZ, and E. ZAS. "SIMULATIONS OF RADIO EMISSION FROM ELECTROMAGNETIC SHOWERS IN DENSE MEDIA." International Journal of Modern Physics A 21, supp01 (July 2006): 55–59. http://dx.doi.org/10.1142/s0217751x06033362.

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By means of GEANT4-based Monte Carlo simulations, we have studied the frequency and angular behavior of Cherenkov radio pulses originated by the excess charge in electromagnetic (EM) showers in different dense media. We have developed a simple model to relate the main characteristics of the electric field spectrum to the longitudinal and lateral development of the EM showers. Using this model the electric field spectrum is shown to have a scaling behavior with a number of medium parameters. We explore the validity of our model by comparing its predictions against full Monte Carlo simulations.

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Journal articles on the topic 'Monte-Charge'

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