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[[File:GPU-Accelerated Nanoelectronic Device Simulations.jpg|thumb]]
 
 
==Short Description==
 
==Short Description==
Driven by Moore's scaling law, the size of the transistors, the active components of integrated circuits, has been drastically reduced to reach the nanometer scale nowadays. To accelerate the innovation of a new transistor technology, it is advantageous in terms of cost and efficiency to first simulate their characteristics rather than directly fabricate and measure them. However, to accurately predict their performance, nanoelectronic devices such as the nanowire transistor depicted here must be simulated at the quantum mechanical level by solving the Schrödinger equation with open boundary conditions and an atomistic resolution, which induces a heavy computational burden. In effect, the resulting problem takes the form of several thousands sparse linear systems of equations, each of them being solved in parallel to minimize the computation time and allow for large device structures. A parallel sparse linear solver has been developed for that purpose that works with CPUs only. The goal of this project is to port this solver to GPUs using the CUDA language from NVIDIA and to boost nanodevice simulations. The new solver should be heterogeneous (MPI+CUDA) and general enough so that one single system of equations can be solved on several CPUs and GPUs.  
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he goal of this project is to determine the relevant Redox processes taking place at metal/oxide interfaces and derive the parameters describing them. For this purpose, the electronic structure of exemplary systems represinting the different  reaction  stages  (e.g. metallic  atom  in  bulk  metal, metal  ion  at  the metal/oxide  interface, metal  ion dissolved in the oxide) will be calculated. These simulations will be conducted on our in-house HPC clusters using density functional theory (DFT). From the obtained data sets, the student will derive the essential parameters by using post-processing and analysis scripts. If time allows (Master’s thesis), the developed work flow will be applied to a large number of different metal/oxide pairs so that their applicability in CBRAM applications can be validated.
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==The Big Picture ==
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Conductive bridging RAM (CBRAM)is an emerging (non-)volatile memory storage technolgy. Its operation principle relies on the repeatable formationand disruption of a metallic filament bridging an oxide layer sandwiched between two electrodes. The electrochemical properties ofthe metal/oxide interface play a crucial roleby determining the rates of the Redox reactions.The latter strongly influences the growth,dissolutionand stabilityof the filament.The Nano-TCAD group has developed an electrochemical model in COMSOL to simulate ON/OFF switching in CBRAM. So far, the model still depends on a number of free input parameters, among them critical onessuch as the Redox parameters of the involved chemical species. Therefore, we aim at replacingthese by values derived from DFT. Eventually, this refined model should not only help us to understand and confirm results obtained from experimental measurements, but could also be used to predict the behaviour of new, not-yet-fabricated devices.  
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===Status: Available ===
 
===Status: Available ===
 
: Looking for 1 Master student
 
: Looking for 1 Master student
: Contact: [[:User:Mluisier | Mathieu Luisier]]
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: Interested candidates please contact: [mailto:aejan@iis.ee.ethz.ch Jan Aeschlimann]
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===Prerequisites===
 
===Prerequisites===
: Experience with CUDA or any other GPU language requested
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We are looking for a candidate with a general interest in electrochemistry and molecular modelling techniques(no former experience required). Basic knowledge in MATLAB and/or Python is advantageous.
: Knowledge about MPI and sparse linear solvers recommended
 
 
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===Status: Completed ===
 
===Status: Completed ===
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: Supervision: [[:User:Mluisier | Mathieu Luisier]]
 
: Supervision: [[:User:Mluisier | Mathieu Luisier]]
 
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===Character===
 
===Character===
: 30% Theory
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: Theory (30%), model development (40-60%), simulation & analysis (10-30%)
: 70% Implementation
 
  
 
===Professor===
 
===Professor===
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[[#top|↑ top]]
 
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==Detailed Task Description==
 
==Detailed Task Description==
  
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* '''[[Final Report]]'''
 
* '''[[Final Report]]'''
 
* '''[[Final Presentation]]'''
 
* '''[[Final Presentation]]'''
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==Results==  
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==Results==
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==Links==  
 
==Links==  
  
[[#top|↑ top]]
 
 
[[Category:Nano-TCAD]]
 
[[Category:Nano-TCAD]]
 
[[Category:Available]]
 
[[Category:Available]]
[[Category:Semester Thesis]]
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[[Category:Master Thesis]]
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[[Category:Hot]]
  
 
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Latest revision as of 16:12, 16 September 2021

Short Description

he goal of this project is to determine the relevant Redox processes taking place at metal/oxide interfaces and derive the parameters describing them. For this purpose, the electronic structure of exemplary systems represinting the different reaction stages (e.g. metallic atom in bulk metal, metal ion at the metal/oxide interface, metal ion dissolved in the oxide) will be calculated. These simulations will be conducted on our in-house HPC clusters using density functional theory (DFT). From the obtained data sets, the student will derive the essential parameters by using post-processing and analysis scripts. If time allows (Master’s thesis), the developed work flow will be applied to a large number of different metal/oxide pairs so that their applicability in CBRAM applications can be validated.

The Big Picture

Conductive bridging RAM (CBRAM)is an emerging (non-)volatile memory storage technolgy. Its operation principle relies on the repeatable formationand disruption of a metallic filament bridging an oxide layer sandwiched between two electrodes. The electrochemical properties ofthe metal/oxide interface play a crucial roleby determining the rates of the Redox reactions.The latter strongly influences the growth,dissolutionand stabilityof the filament.The Nano-TCAD group has developed an electrochemical model in COMSOL to simulate ON/OFF switching in CBRAM. So far, the model still depends on a number of free input parameters, among them critical onessuch as the Redox parameters of the involved chemical species. Therefore, we aim at replacingthese by values derived from DFT. Eventually, this refined model should not only help us to understand and confirm results obtained from experimental measurements, but could also be used to predict the behaviour of new, not-yet-fabricated devices.

Status: Available

Looking for 1 Master student
Interested candidates please contact: Jan Aeschlimann

Prerequisites

We are looking for a candidate with a general interest in electrochemistry and molecular modelling techniques(no former experience required). Basic knowledge in MATLAB and/or Python is advantageous.

Character

Theory (30%), model development (40-60%), simulation & analysis (10-30%)

Professor

Mathieu Luisier

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