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:
- Thermal effects in semiconductor devices
- Noise in semiconductor devices (SDEs)
- Quantum Effects in semiconductor devices
- Electro-thermal coupling of optoelectronic semiconductor devices with electric circuits
- Efficient Co-Simulation of circuit/semiconductor problems (Dynamic Iteration schemes)
Former and ongoing projects
Cooperations
- Vittorio Romano, Università degli studi di Catania, Italy
- Giuseppe Ali, Universitá della Calabria, Italy
- Ansgar Jüngel, TU Vienna, Austria
- Pina Milisic, University of Zagreb, Croatia
Open subjects for theses
- Master Thesis: Two-dimensional thermal-electric simulation of semiconductor MOSFET-devices (M.Brunk)
Publications
- 2025
5435.
Kienitz, J; Moodliyar, L
Gaussian views explained
Wilmott, 2025 (135) :72–77
2025
Herausgeber: Wilmott Magazine5434.
Xu, Zhuo; Tucsnak, Marius
Global Exponential Stabilization for a Simplified Fluid-Particle Interaction System
Januar 20255433.
Bartel, Andreas; Schaller, Manuel
Goal-oriented time adaptivity for port-Hamiltonian systems
Journal of Computational and Applied Mathematics, 461 :116450
2025
ISSN: 0377-04275432.
Schäfers, Kevin; Finkenrath, Jacob; Günther, Michael; Knechtli, Francesco
Hessian-free force-gradient integrators
Computer Physics Communications, 309 :109478
2025
ISSN: 0010-46555431.
Schäfers, Kevin; Finkenrath, Jacob; Günther, Michael; Knechtli, Francesco
Hessian-free force-gradient integrators
Computer Physics Communications, 309 :109478
2025
ISSN: 0010-46555430.
Schäfers, Kevin; Finkenrath, Jacob; Günther, Michael; Knechtli, Francesco
Hessian-free force-gradient integrators and their application to lattice QCD simulations
PoS, LATTICE2024 :025
20255429.
Schäfers, Kevin; Finkenrath, Jacob; Günther, Michael; Knechtli, Francesco
Hessian-free force-gradient integrators and their application to lattice QCD simulations
PoS, LATTICE2024 :025
20255428.
Krhac, Kaja; Schuller, Frederic P.; Stramigioli, Stefano
Hybrid Schrödinger-Liouville and projective dynamics
20255427.
Shaju, K.; Laepple, T.; Hirsch, N.; Zaspel, P.
Ice borehole thermometry: Sensor placement using greedy optimal sampling
EGUsphere, 2025 :1—25
20255426.
Vinod, Vivin; Zaspel, Peter
Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
J. Chem. Theory Comput., 21 (6) :3077-3091
20255425.
Rajkovic, Michelle; Benter, Thorsten; Wissdorf, Walter
Investigation of Surface-Induced Dissociation Processes via Molecular Dynamics Simulations of Wall Collisions of Large Droplets Produced by Electrospray Ionization
Journal of the American Society for Mass Spectrometry, 36 (4) :760—770
April 2025
ISSN: 1044-0305, 1879-11235424.
Abel, Ulrich; Acu, Ana Maria; Heilmann, Margareta; Ra{ć{sa, Ioan
Kernels for composition of positive linear operators
20255423.
[german] Grandrath, Rebecca; Orhan, Nalan; Bohrmann-Linde, Claudia
Konzeption einer Projektwoche zu den Themen Food Waste und Food Loss für die gymnasiale Oberstufe
In Andreas Keil, Annika Hanau und Julian Dietze (Hg.): BNE in der Lehrkräftebildung. Erkenntnisse aus Forschung und Praxis., Editor
Seite 315-325
Herausgeber: Waxmann
Mai 2025
315-3255422.
[german] Cornelius, Soraya; Bohrmann-Linde, Claudia
Motivieren mit (Teil-)Aufgaben zur Erklärvideoproduktion im Chemieunterricht
In Johannes Huwer, Timm Wilke, Amitabh Banerji, Editor, Band Progress in Digitalisation in Chemistry Education 2024. Digitales Lehren und Lernen an Hochschule und Schule im Fach Chemie
Seite 37-42
Herausgeber: Waxmann-Verlag, Münster New York
2025
37-42ISBN: 978-3-8188-0042-0
5421.
Schweitzer, Marcel
Near instance optimality of the Lanczos method for Stieltjes and related matrix functions
SIAM J. Matrix Anal. Appl., 46 :1846-1865
20255420.
Bolten, Matthias; Doganay, Onur Tanil; Gottschalk, Hanno; Klamroth, Kathrin
Non-convex shape optimization by dissipative Hamiltonian flows
Engineering Optimization, 57 :384--403
20255419.
Beck, Christian; Jentzen, Arnulf; Kleinberg, Konrad; Kruse, Thomas
Nonlinear Monte Carlo Methods with Polynomial Runtime for Bellman Equations of Discrete Time High-Dimensional Stochastic Optimal Control Problems
Appl. Math. Optim., 91 (1) :26
20255418.
Figueira, José Rui; Klamroth, Kathrin; Stiglmayr, Michael; Sudhoff Santos, Julia
On the Computational Complexity of Multi-Objective Ordinal Unconstrained Combinatorial Optimization
Operations Research Letters :107302
20255417.
Löhken, Lara; Stiglmayr, Michael
On the multiobjective cable-trench problem
Journal of Combinatorial Optimization, 49 (55)
20255416.
Lorenz, Jan; Zwerschke, Tom; Günther, Michael; Schäfers, Kevin
Operator splitting for coupled linear port-Hamiltonian systems
Applied Mathematics Letters, 160 :109309
2025
Herausgeber: Elsevier5415.
Lorenz, Jan; Zwerschke, Tom; Günther, Michael; Schäfers, Kevin
Operator splitting for coupled linear port-Hamiltonian systems
Applied Mathematics Letters, 160 :109309
2025
Herausgeber: Elsevier5414.
Sinani, Mario; Wynn, Andrew; Palacios, Rafael
Physics-Informed Data-Driven Modelling of Nonlinear Aerodynamic Forces of the Pazy Wing
AIAA SciTech Forum, 6-10 January
01 20255413.
Vinod, Vivin; Lyu, Dongyu; Ruth, Marcel; R. Schreiner, Peter; Kleinekathöfer, Ulrich; Zaspel, Peter
Predicting Molecular Energies of Small Organic Molecules With Multi-Fidelity Methods
J. Comp. Chem., 46 (6) :e70056
20255412.
[german] Zeller, Diana; Bohrmann-Linde, Claudia; Mack, Nils; Schrader, Claudia
Produktion eigener VR-Lernsettings im Projekt FoPro-VR. Ein interdisziplinärer Lehransatz für die Lehramtsausbildung
In Mrohs, Lorenz; Franz, Julia; Herrmann, Dominik; Lindner, Konstantin; Staake, Thorsten, Editor, Digitales Lehren und Lernen an der Hochschule. Strategien - Bedingungen - Umsetzung
Seite 191-204
Herausgeber: transcript, Bielefeld
2025
191-204ISBN: 9783839471203
5411.
Vinod, Vivin; Zaspel, Peter
QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
Sci. Data, 12 (1) :202
2025
Herausgeber: Nature Publishing Group
ISSN: 2052-4463