Applied and Computational Mathematics (ACM)

Semiconductor

Semiconductor devices are solid state bodies, whose electrical conductivity strongly depends on the temperature and other internal properties like the so-called doping. Depending on the temperature or other internal settigns, they can be regarded as insulator or conductor. (Physically speaken: Semiconductor materials have a band gap between.. and .. electron Volt)
This property makes them extremely useful in electronics, since this property can be easily employed to use them as switches. On nowadays computerchips and prozessors, millions of semiconductor devices (especially transistors) are included in an electronic circuit. In order to use common circuit simulation tools to simualte circuits containing those devices, semiconductor devices are often reflected by compact models - subcircuits of basic elements like resistors, capacitors, inductors and current/voltage sources. Those compact models shoul rebuild the input/output behaviour of the semiconductor device.

Ongoing miniaturization and the step from miro- to nanotechnology, however, leads to more powerful prozessors and chips, since higher packing density can be achieved. On the other hand, this higher packing density and miniaturization of the devices makes parasitic effects like heating predominant. Incorporation of those effects into compact models results in large compact models to describe a single semiconductor device. This makes it desireable to include more exact distributed device models - device models based on partial differential equations - into circuit simulation.

Moreover, smaller devices are driven by smaller signals, what makes them more energy efficient. On the other hand this results in a larger noise/signal ratio, what makes inclusion of non-deterministic effects into device models interesting. All in all, this leads to the following recent question in semiconductor/circuit modelling and simulation:

Former and ongoing projects

Cooperations

Open subjects for theses

  • Master Thesis: Two-dimensional thermal-electric simulation of semiconductor MOSFET-devices (M.Brunk)

Publications



2020

4364.

Crouse, Jeff; Haack, Alexander; Benter, Thorsten; Hopkins, W. Scott
Understanding Nontraditional Differential Mobility Behavior: A Case Study of the Tricarbastannatrane Cation, N(CH \(_{2}\) CH \(_{2}\) CH \(_{2}\) ) \(_{3}\) Sn \(^{+}\)
Journal of the American Society for Mass Spectrometry, 31 (4) :796-802
April 2020

4363.

Crouse, Jeff; Haack, Alexander; Benter, Thorsten; Hopkins, W. Scott
Understanding Nontraditional Differential Mobility Behavior: A Case Study of the Tricarbastannatrane Cation, N(CH \(_{2}\) CH \(_{2}\) CH \(_{2}\) ) \(_{3}\) Sn \(^{+}\)
Journal of the American Society for Mass Spectrometry, 31 (4) :796-802
April 2020

4362.

Crouse, Jeff; Haack, Alexander; Benter, Thorsten; Hopkins, W. Scott
Understanding Nontraditional Differential Mobility Behavior: A Case Study of the Tricarbastannatrane Cation, N(CH 2 CH 2 CH 2 ) 3 Sn +
Journal of the American Society for Mass Spectrometry, 31 (4) :796-802
April 2020

4361.

Izak-Nau, Emilia; Campagna, Davide; Baumann, Christoph; Göstl, Robert
Polymer mechanochemistry-enabled pericyclic reactions
Polymer Chemistry, 11 (13) :2274--2299
März 2020
ISSN: 1759-9962

4360.

Haack, Alexander; Benter, Thorsten; Kersten, Hendrik
Computational analysis of the proton bound acetonitrile dimer, (ACN) \(_{2}\) H \(^{+}\)
Rapid Communications in Mass Spectrometry
März 2020

4359.

Haack, Alexander; Benter, Thorsten; Kersten, Hendrik
Computational analysis of the proton bound acetonitrile dimer, (ACN) \(_{2}\) H \(^{+}\)
Rapid Communications in Mass Spectrometry
März 2020

4358.

Haack, Alexander; Benter, Thorsten; Kersten, Hendrik
Computational analysis of the proton bound acetonitrile dimer, (ACN) 2 H +
Rapid Communications in Mass Spectrometry
März 2020

4357.

Sun, Jing; Su, Juanjuan; Ma, Chao; Göstl, Robert; Herrmann, Andreas; Liu, Kai; Zhang, Hongjie
Fabrication and Mechanical Properties of Engineered Protein-Based Adhesives and Fibers
Advanced Materials, 32 (6) :1906360
Februar 2020
ISSN: 1521-4095

4356.

[english] Meuter, Nico; Spinnen, Sebastian; Tausch, Michael W.
Two Versatile Experiments for Teaching Photochemistry: Photon Upconversion by TTA and All Optical INHIBIT Logical Gate
EPA (European Photochemistry Association) Newsletter (97) :9-15
Februar 2020

4355.

Stratigaki, Maria; Baumann, Christoph; Breemen, Lambert C. A. van; Heuts, Johan P. A.; Sijbesma, Rint P.; Göstl, Robert
Fractography of poly(N-isopropylacrylamide) hydrogel networks crosslinked with mechanofluorophores using confocal laser scanning microscopy
Polymer Chemistry, 11 (2) :358--366
Januar 2020
ISSN: 1759-9962

4354.


1-Nitrogen-Functionalized 2-Haloalkenes (Update 2020)
Science of Synthesis, Knowledge Updates (2) :235–275
2020

4353.

Budde, Christian; Farkas, B{\'a}lint
A {D}esch-{S}chappacher perturbation theorem for bi-continuous semigroups
Math. Nachr., 293 (6) :1053-1073
2020

4352.

Budde, Christian; Farkas, Bálint
A Desch-Schappacher perturbation theorem for bi-continuous semigroups
Math. Nachr., 293 (6) :1053-1073
2020

4351.

Ankirchner, Stefan; Kruse, Thomas; Urusov, Mikhail; others
A functional limit theorem for coin tossing Markov chains
, Annales de l'Institut Henri Poincaré, Probabilités et StatistiquesBand56, Seite 2996--3019
Institut Henri Poincaré
2020

4350.

Ankirchner, Stefan; Kruse, Thomas; Urusov, Mikhail; others
A functional limit theorem for coin tossing Markov chains
Annales de l'Institut Henri Poincaré, Probabilités et Statistiques, 56 (4) :2996–3019
2020
Herausgeber: Institute of Mathematical Statistics

4349.

Teng, Long; Lapitckii, Aleksandr; Günther, Michael
A multi-step scheme based on cubic spline for solving backward stochastic differential equations
Applied Numerical Mathematics, 150 :117–138
2020
Herausgeber: Elsevier

4348.

Teng, Long; Lapitckii, Aleksandr; Günther, Michael
A multi-step scheme based on cubic spline for solving backward stochastic differential equations
Applied Numerical Mathematics, 150 :117--138
April 2020
Herausgeber: North-Holland

4347.

Teng, Long; Lapitckii, Aleksandr; Günther, Michael
A multi-step scheme based on cubic spline for solving backward stochastic differential equations
Applied Numerical Mathematics, 150 :117–138
2020
Herausgeber: Elsevier

4346.

Teng, Long; Wu, Xueran; Günther, Michael; Ehrhardt, Matthias
A new methodology to create valid time-dependent correlation matrices via isospectral flows
ESAIM: Mathematical Modelling and Numerical Analysis, 54 (2) :361–371
2020
Herausgeber: EDP Sciences

4345.

Teng, Long; Wu, Xueran; Günther, Michael; Ehrhardt, Matthias
A new methodology to create valid time-dependent correlation matrices via isospectral flows
ESAIM: Mathematical Modelling and Numerical Analysis, 54 (2) :361–371
2020
Herausgeber: EDP Sciences

4344.

Teng, Long; Wu, Xueran; Günther, Michael; Ehrhardt, Matthias
A new methodology to create valid time-dependent correlation matrices via isospectral flows
ESAIM: Mathematical Modelling and Numerical Analysis, 54 (2) :361--371
Februar 2020
Herausgeber: EDP Sciences

4343.

Teng, Long; Wu, Xueran; Günther, Michael; Ehrhardt, Matthias
A new methodology to create valid time-dependent correlation matrices via isospectral flows
ESAIM: Mathematical Modelling and Numerical Analysis, 54 (2) :361–371
2020
Herausgeber: EDP Sciences

4342.

Hutzenthaler, Martin; Jentzen, Arnulf; Kruse, Thomas; Nguyen, Tuan Anh
A proof that rectified deep neural networks overcome the curse of dimensionality in the numerical approximation of semilinear heat equations
SN Partial Differential Equations and Applications, 1 (2) :1--34
2020
Herausgeber: Springer International Publishing

4341.

Hutzenthaler, Martin; Jentzen, Arnulf; Kruse, Thomas; Nguyen, Tuan Anh
A proof that rectified deep neural networks overcome the curse of dimensionality in the numerical approximation of semilinear heat equations
SN Partial Differential Equations and Applications, 1 (2) :1–34
2020
Herausgeber: Springer International Publishing

4340.

Aab, Alexander; others
A Search for Ultra-high-energy Neutrinos from TXS 0506+056 Using the Pierre Auger Observatory
Astrophys. J., 902 (2) :105
2020