Auswahl der wissenschaftlichen Literatur zum Thema „Diffusion drift models“

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Zeitschriftenartikel zum Thema "Diffusion drift models"

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Glitzky, Annegret. „Analysis of spin-polarized drift-diffusion models“. PAMM 8, Nr. 1 (Dezember 2008): 10717–18. http://dx.doi.org/10.1002/pamm.200810717.

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Degond, Pierre, Florian M�hats und Christian Ringhofer. „Quantum Energy-Transport and Drift-Diffusion Models“. Journal of Statistical Physics 118, Nr. 3-4 (Februar 2005): 625–67. http://dx.doi.org/10.1007/s10955-004-8823-3.

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Hübner, Ronald, und Thomas Pelzer. „Improving parameter recovery for conflict drift-diffusion models“. Behavior Research Methods 52, Nr. 5 (10.02.2020): 1848–66. http://dx.doi.org/10.3758/s13428-020-01366-8.

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Abstract Several drift-diffusion models have been developed to account for the performance in conflict tasks. Although a common characteristic of these models is that the drift rate changes within a trial, their architecture is rather different. Comparative studies usually examine which model fits the data best. However, a good fit does not guarantee good parameter recovery, which is a necessary condition for a valid interpretation of any fit. A recent simulation study revealed that recovery performance varies largely between models and individual parameters. Moreover, recovery was generally not very impressive. Therefore, the aim of the present study was to introduce and test an improved fit procedure. It is based on a grid search for determining the initial parameter values and on a specific criterion for assessing the goodness of fit. Simulations show that not only the fit performance but also parameter recovery improved substantially by applying this procedure, compared to the standard one. The improvement was largest for the most complex model.
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Langner, M., J. Peinke, F. Flemisch, M. Baumann und D. Beckmann. „Drift and diffusion based models of driver behavior“. European Physical Journal B 76, Nr. 1 (04.06.2010): 99–107. http://dx.doi.org/10.1140/epjb/e2010-00148-8.

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Chalub, Fabio A. C. C., Peter A. Markowich, Beno�t Perthame und Christian Schmeiser. „Kinetic Models for Chemotaxis and their Drift-Diffusion Limits“. Monatshefte f�r Mathematik 142, Nr. 1-2 (01.06.2004): 123–41. http://dx.doi.org/10.1007/s00605-004-0234-7.

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Comte, Fabienne, und Valentine Genon-Catalot. „Drift estimation on non compact support for diffusion models“. Stochastic Processes and their Applications 134 (April 2021): 174–207. http://dx.doi.org/10.1016/j.spa.2021.01.001.

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Kordt, Pascal, Sven Stodtmann, Alexander Badinski, Mustapha Al Helwi, Christian Lennartz und Denis Andrienko. „Parameter-free continuous drift–diffusion models of amorphous organic semiconductors“. Physical Chemistry Chemical Physics 17, Nr. 35 (2015): 22778–83. http://dx.doi.org/10.1039/c5cp03605d.

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Stevens, A., K. Kang und H. J. Hwang. „Drift-diffusion limits of kinetic models for chemotaxis: A generalization“. Discrete and Continuous Dynamical Systems - Series B 5, Nr. 2 (Februar 2005): 319–34. http://dx.doi.org/10.3934/dcdsb.2005.5.319.

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Labiod, Samir, Saida Latreche, Mourad Bella und Christian Gontrand. „Combined Electromagnetic and Drift Diffusion Models for Microwave Semiconductor Device“. Journal of Electromagnetic Analysis and Applications 03, Nr. 10 (2011): 423–29. http://dx.doi.org/10.4236/jemaa.2011.310067.

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Brezzi, Franco, Luisa Donatella Marini und Paola Pietra. „Two-Dimensional Exponential Fitting and Applications to Drift-Diffusion Models“. SIAM Journal on Numerical Analysis 26, Nr. 6 (Dezember 1989): 1342–55. http://dx.doi.org/10.1137/0726078.

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Dissertationen zum Thema "Diffusion drift models"

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Fard, Pouyan R., Hame Park, Andrej Warkentin, Stefan J. Kiebel und Sebastian Bitzer. „A Bayesian Reformulation of the Extended Drift-Diffusion Model in Perceptual Decision Making“. Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-230313.

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Perceptual decision making can be described as a process of accumulating evidence to a bound which has been formalized within drift-diffusion models (DDMs). Recently, an equivalent Bayesian model has been proposed. In contrast to standard DDMs, this Bayesian model directly links information in the stimulus to the decision process. Here, we extend this Bayesian model further and allow inter-trial variability of two parameters following the extended version of the DDM. We derive parameter distributions for the Bayesian model and show that they lead to predictions that are qualitatively equivalent to those made by the extended drift-diffusion model (eDDM). Further, we demonstrate the usefulness of the extended Bayesian model (eBM) for the analysis of concrete behavioral data. Specifically, using Bayesian model selection, we find evidence that including additional inter-trial parameter variability provides for a better model, when the model is constrained by trial-wise stimulus features. This result is remarkable because it was derived using just 200 trials per condition, which is typically thought to be insufficient for identifying variability parameters in DDMs. In sum, we present a Bayesian analysis, which provides for a novel and promising analysis of perceptual decision making experiments.
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Lamboll, Robin Davies. „Two-dimensional modelling of novel back-contact solar cells“. Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/268518.

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This dissertation computationally and analytically investigates ways to model solar cells when the lateral motion of charge carriers and light are relevant. We focus on back-contact perovskite solar cells, and assessing the experimental technique of scanning photocurrent microscopy as a means to investigate them. Solar cells are three-dimensional objects frequently modelled as being one-dimensional. However, for more complex designs of solar cell or if the cell is only point-illuminated, one-dimensional modelling is insufficient. In the first study, some conditions for reducing the complexity of two-dimensional drift-diffusion simulations are investigated for a back-contact perovskite cell. Analytic expressions for the relationship in both the low extraction velocity and high extraction velocity regimes are demonstrated, and the conditions where these approximations break down are investigated. These findings are then applied a point-excited film with an extended electrode, a problem encountered during scanning photocurrent microscopy. We show the current recorded in this case should decay exponentially with the distance between excitation and electrode, with a decay constant that can be related to device parameters. The characteristic equilibration time for the system to reach this current is demonstrated to increase linearly with distance. Between this gradient and the exponent, information about the diffusion and recombination mechanics can be extracted from a variety of systems. Photon recycling is the process in whereby photogenerated carriers recombine to generate light that is absorbed again within the solar cell. In the second section, we apply the findings of the first section to show that experimental results published elsewhere are best explained by photon recycling in methylammonium lead iodide perovskite back-contact solar cells. However we do not have an established theoretical model for long-ranged lateral optical transport in these solar cells. Three models are developed: a bimolecular model for unscattered, coherent transport; a photon diffusion model for frequently scattered, noncoherent light; and a monomolecular, assisted-diffusion model. The modal nature of coherent optical transport is considered and modifications to previous one-dimensional theories are made. The nature of the photon diffusion model is discussed, as are theoretical shortcomings. All three models are then solved numerically and compared to experimental results. The low-scattering photon diffusion models correspond well to the experiment. The third investigation involves the performance of different architectures of back-contact perovskite cells. These cells potentially offer increased current due to less shadowing by front electrodes. We compare them to each other and to traditional vertical structures. It is found that, in terms of internal transport, the back-contact solar cells give less efficient performance than the vertical design. The best of the back-contact cells investigated is a flat interdigitated design. The increase in efficiency from optical factors would have to exceed 10% for the overall efficiency of back-contact cells to be higher than vertical devices. We also develop a model of photon recycling appropriate for short-ranged, bulk 2D transport and demonstrate that in perovskites, it produces little change in power conversion efficiency (and small changes in short-circuit voltage) when compared with the standard drift-diffusion equations with the second-order recombination constant is adjusted.
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Demir, Huseyin. „A Process-Based Model for Beach Profile Evolution“. Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19811.

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Beach profile models predict the changes in bathymetry along a line perpendicular to the shoreline. These models are used to forecast bathymetric changes in response to storms, sea level rise or human activities such as dredging and beach nourishment. Process-based models achieve this by simulating the physical processes that drive the sediment transport as opposed to behavior models which simulate observed profile changes without resolving the underlying processes. Some of these processes are wave shoaling and breaking, boundary layer streaming, and offshore-directed undertow currents. These hydrodynamic processes control the sediment processes such as sediment pick-up from the bottom, diffusion of the sediment across the water column and its advection with waves and currents. For this study, newly developed sediment transport and boundary layer models were coupled with existing models of wave transformation, nearshore circulation and bathymetry update, to predict beach profile changes. The models covered the region from the dry land to a depth of 6-8 meters, spanning up to 500 meters in the cross-shore direction. The modeling system was applied at storm time scales, extending from a couple of hours to several days. Two field experiments were conducted at Myrtle Beach, SC, involving the collection of wave, current and bathymetric data as a part of this study. The results were used to calibrate and test the numerical models along with data from various laboratory studies from the literature. The sediment transport model computes the variation of sediment concentrations over a wave period and over the water column, solving the advection-diffusion equation using the Crank-Nicholson finite-difference numerical scheme. Using a new approach, erosion depth thickness and sediment concentrations within the bed were also predicted. The model could predict sediment transport rates for a range of conditions, within a factor of two. It successfully computed the sediment concentration profile over the water column and within the bed and its variation throughout a wave period. Erosion depth and sheet flow layer thickness were also predicted reasonably well. Wave heights across the profile were predicted within ten percent when the empirical wave breaking parameter was tuned appropriately. Mean cross-shore velocities contain more uncertainty, even after tuning. The importance of capturing the location of the maximum, near-bottom, cross-shore velocity when predicting bar behavior was shown. Bar formation, erosion, accretion, onshore and offshore bar movement were all computed with the model successfully
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Bottemanne, Laure. „Influence de la motivation liée à autrui sur la décision : corrélats computationnels et magnétoencéphalographiques chez l’Homme“. Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1257/document.

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L’homme est un animal social. La majorité des décisions que nous prenons se font dans un contexte social et dépendent d’autrui, ce qui implique des calculs cérébraux complexes qui incluent tous les facteurs contextuels et environnementaux. La majorité des études ultérieures de la prise en compte d’autrui dans la décision ont utilisé des tâches de partage de récompenses entre soi et autrui. Les choix possibles amènent le décideur à considérer autrui, mais dans le but de gagner soi-même une récompense ; donc dans un contexte où les récompenses liées à soi et les récompenses liées à autrui sont confondues. Le travail présenté dans cette thèse avait pour but une meilleure compréhension des mécanismes cérébraux soutenant l’intégration d’autrui dans la prise de décision, sans que la récompense pour autrui n’interfère directement avec soi. Nous nous sommes appuyés sur le cadre théorique de la décision perceptuelle et des modèles de diffusion pour l'étude i) des modifications du processus décisionnel induites par une récompense monétaire allant à autrui et ii) de l’impact de l’effet d’audience (le fait de se sentir observé) sur la décision. Nos résultats computationnels montrent qu'une récompense pour autrui, par rapport à une récompense pour soi, et une audience, par rapport au secret, modifient le taux de dérive de la variable de décision. En magnétoencéphalographie, nos résultats indiquent que les décisions pour soi et pour autrui diffèrent pendant, mais aussi après, la prise de décision dans des zones cérébrales associées avec la transformation sensori-motrice, l'ajustement du compromis entre rapidité et justesse et avec la cognition sociale. Ainsi, le cortex temporal montre des différences de -1170 millisecondes (ms) à -1023 ms, de -993 ms à -915 ms et de -343 ms à -188 ms en amont de la réponse. Ce qui suppose une influence sur l’intégration des preuves sensorielles. Après la décision, les régions frontales ont également montré des différences entre soi et autrui, de 153 ms à 303 ms post-réponse, suggérant une différence entre soi et autrui dans l’ajustement du compris entre justesse et rapidité. Le bénéficiaire de la récompense associée à la décision modifie les paramètres décisionnels et les corrélats cérébraux de la décision perceptuelle, démontrant l’importance du contexte social dans l’implémentation de la prise de décision chez l’Homme. Ce travail appuie également l’utilité des modèles mathématiques tels que les modèles de diffusion dans la compréhension des processus décisionnels, même de ceux découlant de la cognition sociale
Humans are inherently social: most of human’s decisions are within a social context and depend on others. For more than a century, researchers explore aspects of social cognition. Aiming to understand human behavior in social contexts, neuro-economic researches showed that taking others into account involve complex brain computations that include all environmental and contextual factors. However, most of the work was made using money allocation tasks; mixing self-affecting and other-affecting rewards into the decision making process. The present work intended the understanding of the brain mechanisms underpinning the integration of others into the decision making process for decisions that include others and do not interfere with self-rewards.Taking advantage of mathematical models from the drift diffusion models framework, we conducted experiments investigating how others influence the mechanistic of perceptual decisions and their correlates in the human brain. We showed that taking rewards for others into account and being observed by others influence the drift rate of the decision variable. The drift rate is higher in audience than in secret and higher for self-rewards than for other-rewards. These results indicate that others are integrated into the accumulation process together with the evidence available for making a decision. At the brain level, we found difference between self and other decisions over the anterior temporal and centro-frontal cortices during decision making. This suggests that the beneficiary of a decision modifies sensory-motor transformation processes. In addition, self- and other-affecting difference showed difference over the medial frontal sensors after the decision making process, indicating a variation in the speed-accuracy tradeoff adjustment process
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Luzardo, A. „The Rescorla-Wagner Drift-Diffusion model“. Thesis, City, University of London, 2018. http://openaccess.city.ac.uk/19210/.

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Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this thesis we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 11 experimental phenomena and show that it can provide an adequate account for 9, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSCTD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used.
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Hemzalová, Zuzana. „Evoluční algoritmy pro ultrazvukovou perfúzní analýzu“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442504.

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This thesis deals with the principles of ultrasonic perfusion analysis and methods for determining perfusion parameters. It examines Evolutionary algorithms and their ability to optimize the approximation of dilution curves from ultrasond tissue scannig. It compares the optimization performance of three evolutionary algorithms. Continuous genetic algorithm GA, algorithm SOMA and PSO. Methods are evaluated on simulated and clinical data.
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Alles, Benjamin. „Coupled drift diffusion problems with implicit source functions and their applications“. Aachen Shaker, 2008. http://d-nb.info/989623653/04.

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Schmithüsen, Bernhard. „Grid adaptation for the stationary two-dimensional drift-diffusion model in semiconductor device simulation /“. Zürich : [s.n.], 2002. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=14449.

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Sonehag, Christian. „Modeling of Ion Injection in Oil-Pressboard Insulation Systems“. Thesis, Uppsala universitet, Fasta tillståndets elektronik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-177600.

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To make a High Voltage Direct Current (HVDC) transmission more energy efficient, the voltage of the system has to be increased. To allow for that the components of the system must be constructed to handle the increases AC and DC stresses that this leads to. One key component in such a transmission is the HVDC converter transformer. The insulation system of the transformer usually consists of oil and oil-impregnated pressboard. Modeling of the electric DC field in the insulation system is currently done with the ion drift diffusion model, which takes into account the transport and generation of charges in the oil and the pressboard. The model is however lacking a description of how charges are being injected from the electrodes and the oil-pressboard interfaces. The task of this thesis work was to develop and implement a model for this which improves the result of the ion drift diffusion model. A theoretical study of ion injection was first carried out and proceeding from this, a model for the ion injection was formulated. By using experimental data from 5 different test geometries, the injection model could be validated and appropriate parameter values of the model could be determined. By using COMSOL Multiphysics®, the ion drift diffusion model with the injection model could be simulated for the different test geometries. The ion injection gave a substantial improvement of the ion drift diffusion model. The positive injection from electrodes into oil was found to be in the range 0.3-0.6 while the negative injection was 0.3 lower. Determination of the parameters for the injection from oil-pressboard interfaces proved to be difficult, but setting the parameters in the range 0.01-1 allowed for a good agreement with the experimental data. Here, a fit could be obtained for multiple assumptions about the set of active injection parameters. Finally it is recommended that the investigation of the ion injection continues in order to further improve the model and more accurately determine the parameters of it. Suggestions on how this work could be carried out are given in the end.
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Sales, Michael F. „Context Dependent Numerosity Representations in Children“. The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1557146188226533.

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Bücher zum Thema "Diffusion drift models"

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Hänsch, W. The drift diffusion equation and its applications in MOSFET modeling. Wien: Springer-Verlag, 1991.

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Hänsch, W. The drift diffusion equation and its applications in MOSFET modeling. Wien: Springer-Verlag, 1991.

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Schmithüsen, Bernhard. Grid adaption for the stationary two-dimensional drift diffusion model in semiconductor device simulation. Konstanz: Hartung-Gorre, 2002.

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Ontario. Ministry of Environment and Energy. Draft guideline for preparing a source inventory and dispersion modeling report: Guide for demonstrating compliance with: Section 5 of Regulation 346, General -- Air Pollution R.R.O. 1990 made under the Environmental Protection Act. [Toronto]: Ontario Ministry of Environment and Energy, 1997.

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Branch, Ontario Ministry of Environment Approvals. Draft guideline for preparing a source inventory and dispersion modeling report: Guide for demonstrating compliance with: Section 5 of Regulation 346, General--Air Pollution R.R.O. 1990, made under the Environmental Protection Act. [Toronto]: Ministry of Environment, Approvals Branch, 1997.

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Figdor, Carrie. Cases. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198809524.003.0003.

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Chapter 3 introduces the use of mathematical models and modeling practices in contemporary biological and cognitive sciences. The familiar Lotka–Volterra model of predator–prey relations is used to explain these practices and show how they promote the extensions of predicates, including psychological predicates, into new and often unexpected domains. It presents two models of cognitive capacities that were developed to explain human behavioral data: Ratcliff’s drift-diffusion model of decision-making and Sutton and Barto’s temporal difference model of reinforcement learning. These are now used for fruit flies and neural populations. It also discusses contemporary and ongoing attempts to revise psychological concepts in response to empirical discovery.
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Berlin, Mark S. Criminalizing Atrocity. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198850441.001.0001.

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Why do countries adopt criminal legislation making it possible to prosecute government and military officials for human rights violations? Over the past thirty years, dozens of countries have prosecuted their own or other states’ officials for past atrocities. Criminalizing Atrocity tells the story of the global spread of national criminal laws against atrocity crimes—genocide, war crimes, and crimes against humanity—laws that have helped pave the way for this remarkable trend toward greater accountability. It traces the early-twentieth-century origins of national atrocity laws to a group of influential European criminal law scholars and explains the global patterns by which they have since spread. The book shows that understanding why countries criminalize atrocities requires understanding how they do so. In many cases, criminalization has not been the result of concerted government initiative, but of inconspicuous choices made by technocratic legal experts who have been delegated authority to draft large-scale reforms to countries’ criminal codes. Drawing on research in comparative law and norm diffusion, Criminalizing Atrocity explains how such reform projects prompt technocratic drafters to select legal ideas, like atrocity laws, that have been endorsed by their professional communities and deemed by drafters to be important features of a “modern” criminal code. To test this argument, Criminalizing Atrocity draws on a range of original quantitative and qualitative data, including in-depth case studies of Guatemala, Colombia, Poland, and the Maldvies, and a new, comprehensive dataset tracking the global spread of atrocity laws since Word War II. The book’s findings highlight the importance of professional communities in the modern renaissance of atrocity justice and the domestication of international legal norms.
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Buchteile zum Thema "Diffusion drift models"

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Farrell, Patricio, Nella Rotundo, Duy Hai Doan, Markus Kantner, Jürgen Fuhrmann und Thomas Koprucki. „Drift-Diffusion Models“. In Handbook of Optoelectronic Device Modeling and Simulation, 733–72. Boca Raton, FL : CRC Press, Taylor & Francis Group, [2017] |: CRC Press, 2017. http://dx.doi.org/10.4324/9781315152318-25.

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Jerome, Joseph W. „Development of Drift-Diffusion Models“. In Analysis of Charge Transport, 9–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-79987-7_2.

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Kubilius, Kęstutis, Yuliya Mishura und Kostiantyn Ralchenko. „Drift Parameter Estimation in Diffusion and Fractional Diffusion Models“. In Bocconi & Springer Series, 161–267. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71030-3_5.

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Kerkhoven, Thomas. „Drift-Diffusion Systems: Analysis of Discretized Models“. In Computational Electronics, 21–26. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4757-2124-9_3.

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Chalub, Fabio A. C. C., Peter A. Markowich, Benoît Perthame und Christian Schmeiser. „Kinetic Models for Chemotaxis and their Drift-Diffusion Limits“. In Nonlinear Differential Equation Models, 123–41. Vienna: Springer Vienna, 2004. http://dx.doi.org/10.1007/978-3-7091-0609-9_10.

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Jerome, Joseph W. „Algorithmic Aspects of the Hydrodynamic and Drift-Diffusion Device Models“. In Mathematical Modelling and Simulation of Electrical Circuits and Semiconductor Devices, 217–36. Basel: Birkhäuser Basel, 1990. http://dx.doi.org/10.1007/978-3-0348-5698-0_16.

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Mielke, Alexander, Dirk Peschka, Nella Rotundo und Marita Thomas. „On Some Extension of Energy-Drift-Diffusion Models: Gradient Structure for Optoelectronic Models of Semiconductors“. In Progress in Industrial Mathematics at ECMI 2016, 291–98. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63082-3_45.

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Jerome, Joseph W. „Drift-Diffusion Systems: Variational Principles and Fixed Point Maps for Steady State Semiconductor Models“. In Computational Electronics, 15–20. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4757-2124-9_2.

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Jüngel, Ansgar. „The Isentropic Drift-diffusion Model“. In Quasi-hydrodynamic Semiconductor Equations, 27–118. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8334-4_3.

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Lipperheide, Reinhard, und Uwe Wille. „Drift-Diffusion and Ballistic Transport“. In Springer Tracts in Modern Physics, 5–24. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05924-2_2.

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Konferenzberichte zum Thema "Diffusion drift models"

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Wang, Shu, und Ke Wang. „Quasi-neutral Limit of the Drift-Diffusion Models for Semiconductors with PN-Junctions“. In 2009 Fifth International Conference on Natural Computation. IEEE, 2009. http://dx.doi.org/10.1109/icnc.2009.361.

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Pisarenko, I. V., und E. A. Ryndin. „Development of drift-diffusion numerical models of high-speed on-chip photodetectors with heterojunctions“. In The International Conference on Micro- and Nano-Electronics 2016, herausgegeben von Vladimir F. Lukichev und Konstantin V. Rudenko. SPIE, 2016. http://dx.doi.org/10.1117/12.2266628.

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3

Richardson, Giles, Nicola Courtier, Laurence Bennett, Juan Anta und Antonio Exposito. „Using Drift-Diffusion Models as a Tool to Probe the Physics of Perovskite Solar Cells“. In 2nd nanoGe International Conference on Perovskite Thin Film Photovoltaics and Perovskite Photonics and Optoelectronics. València: Fundació Scito, 2019. http://dx.doi.org/10.29363/nanoge.nipho.2020.032.

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4

Salem, Ali F., Arlynn W. Smith und Kevin F. Brennan. „Comparison of hydrodynamic and drift diffusion models as applied to interdigitated metal-semiconductor-metal photodetectors“. In SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, herausgegeben von Kathleen Muray und Kenneth J. Kaufmann. SPIE, 1995. http://dx.doi.org/10.1117/12.221405.

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5

Wedel, G., T. Nardmanrr und M. Schroter. „On the use of Drift-Diffusion and Hydrodynamic Transport Models for Simulating the Negative Differential Mobility Effect“. In 2018 IEEE BiCMOS and Compound Semiconductor Integrated Circuits and Technology Symposium (BCICTS). IEEE, 2018. http://dx.doi.org/10.1109/bcicts.2018.8550970.

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Koganemaru, Masaaki, Naohiro Tada, Toru Ikeda und Noriyuki Miyazaki. „Device Simulation for Effects of Mechanical Stress on Electrical Performances of nMOSFETs: The Impacts of Stress-Induced Change of Intrinsic Carrier Density“. In ASME 2013 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/ipack2013-73248.

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This paper discusses a numerical model for analysing the effects of mechanical stress on semiconductor devices. In other words, drift-diffusion device simulation is conducted using a physical model incorporating the effects of mechanical stress. Then, each impact of the stress-induced physical phenomena is analysed. In our previous study, three physical phenomena that were attributed to mechanical stress have been modeled in our electron mobility model, i.e., the changes in relative population, the momentum relaxation time and the effective mass of electrons in conduction-band valleys. In addition, in this study, the stress-induced change of intrinsic carrier density is modeled. Stress-induce variations of drain current characteristics on n-type Metal Oxide Semiconductor Field Effect Transistors (nMOSFETs) are evaluated using a drift-diffusion device simulator including above mentioned physical models. It is demonstrated that the impact of stress-induced change of intrinsic carrier density is small for our evaluated nMOSFETs.
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7

Mesbah, S., K. Bendib-Kalache, A. Bendib, El-Hachemi Amara, Saïd Boudjemai und Djamila Doumaz. „Generalized Drift-Diffusion Model In Semiconductors“. In LASER AND PLASMA APPLICATIONS IN MATERIALS SCIENCE: First International Conference on Laser Plasma Applications in Materials Science—LAPAMS’08. AIP, 2008. http://dx.doi.org/10.1063/1.2999949.

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Abouchabaka, J., R. Aboulaich, A. Nachaoui und A. Souissi. „The study of a drift-diffusion model“. In ICM'2001 Proceedings. 13th International Conference on Microelectronics. IEEE, 2001. http://dx.doi.org/10.1109/icm.2001.997485.

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Aniel-Buchheit, Sylvie, und Michael Z. Podowski. „On the Modeling of Local Neutronically-Coupled Flow-Induced Oscillations in Advanced Boiling Water Reactors“. In 14th International Conference on Nuclear Engineering. ASMEDC, 2006. http://dx.doi.org/10.1115/icone14-89867.

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The purpose of this paper is to discuss the development in progress of a complete space- and time-dependent model of the coupled neutron kinetic and reactor thermal-hydraulics. The neutron kinetics model is based on two-group diffusion equations with Doppler and void reactivity feedback effects. This model is coupled with the model of two-phase flow and heat transfer in parallel coolant channels. The modeling concepts considered for this purpose include one-dimensional drift flux and two-fluid models, as well a CFD model implemented in the NPHASE advanced computational multiphase fluid dynamics (CMFD) computer code. Two methods of solution for the overall model are proposed. One is based on direct numerical integration of the spatially-discretized governing equations. The other approach is based on a quasi-analytical modal approach to the neutronics model, in which a complete set of eigenvectors is found for step-wise temporal changes of the cross-sections of core materials (fuel and coolant/moderator). The issues investigated in the paper include details of model formulation, as well as the results of calculations for neutronically-coupled density-wave oscillations.
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Erlebach, A., K. H. Lee und F. M. Bufler. „Empirical ballistic mobility model for drift-diffusion simulation“. In ESSDERC 2016 - 46th European Solid-State Device Research Conference. IEEE, 2016. http://dx.doi.org/10.1109/essderc.2016.7599675.

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Berichte der Organisationen zum Thema "Diffusion drift models"

1

Tan, Cheng-Yan. A simple drift-diffusion model for calculating the neutralization time of H- in xe gas for choppers placed in the LEBT. Office of Scientific and Technical Information (OSTI), März 2010. http://dx.doi.org/10.2172/974354.

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