<div class="csl-bib-body">
<div class="csl-entry">Herda, M., Jüngel, A., & Portisch, S. (2024). Analysis of a drift-diffusion model with Fermi–Dirac statistics for memristive devices. In <i>AMaSiS 2024: Applied Mathematics and Simulation for Semiconductor Devices</i> (pp. 28–28).</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/200864
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dc.description.abstract
Memristors can be seen as nonlinear resistors with memory. This makes them a promising device in neuromorphic computing, as they show a resistive switching behaviour, thus being ideal candidates to build artificial neurons or synapses. Perovskite solar cells have emerged as a groundbreaking technology, due to the perovskite materials’ outstanding optical and electronical properties. These perovskite materials exhibit a memristive behaviour, which naturally leads to their use in memristors. We analyze a drift-diffusion model for memristors including Fermi–Dirac statistics for the electrons and holes and Blakemore statistics for the oxygen vacancies, coupled to a Poisson equation for the electric potential. Using a-priori estimates obtained from the related free energy functional we prove the existence of weak solutions to the system. Additionally we show the uniform-in-time boundedness of solutions in three space dimensions.
en
dc.language.iso
en
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dc.subject
Drift-diffusion equations
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dc.subject
Fermi-Dirac statistics
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dc.subject
global existence
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dc.subject
bounded weak solutions
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dc.subject
memristors
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dc.subject
semiconductors
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dc.subject
neuromorphic computing
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dc.title
Analysis of a drift-diffusion model with Fermi–Dirac statistics for memristive devices
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dc.type
Inproceedings
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dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
Team Rapsodi - Inria Centre de recherche Lille Nord Europe (Villeneuve d'Ascq, FR)
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dc.description.startpage
28
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dc.description.endpage
28
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dc.type.category
Poster Contribution
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tuw.booktitle
AMaSiS 2024: Applied Mathematics and Simulation for Semiconductor Devices