Renewable energies are the key to achieving a climate-neutral future in Germany, with photovoltaics playing a central role. However, the weather-dependent and thus fluctuating nature of solar power generation poses new challenges for the electricity grid. Accurate forecasts are essential to anticip...
We will build an end-to-end RFIC design flow (schematic → layout → EM → co-simulation) both with open-source tools and in commercial environments, and correlate the results.The work includes IC design (schematic, layout, verification) in Cadence/ADS and Ansys HFSS/CST, as well as with open-source tools (Qucs-S/Ngspice/Xyce, KLayout/gdsfactory, openEMS, scikit-rf).
We will build an end-to-end RFIC design flow (schematic → layout → EM → co-simulation) both with open-source tools and in commercial environments, and correlate the results.The work includes IC design (schematic, layout, verification) in Cadence/ADS and Ansys HFSS/CST, as well as with open-source tools (Qucs-S/Ngspice/Xyce, KLayout/gdsfactory, openEMS, scikit-rf).
We will build an end-to-end RFIC design flow (schematic → layout → EM → co-simulation) both with open-source tools and in commercial environments, and correlate the results.The work includes IC design (schematic, layout, verification) in Cadence/ADS and Ansys HFSS/CST, as well as with open-source tools (Qucs-S/Ngspice/Xyce, KLayout/gdsfactory, openEMS, scikit-rf).
Description
As part of a campus Joint Communication and Sensing (JCAS) system, machine learning methods for person detection and classification based on radar data are to be developed. Students will research and select suitable datasets (e.g., point clouds or range–Doppler data) and prepare them...
Description:
This thesis explores the application of artificial neural networks (ANNs) as surrogate models for simulating and designing high-Q piezoelectric acoustic wave resonators and filters. Traditional modeling techniques such as finite element methods or analytical approaches can be comput...
The high-frequency power amplifier (RF PA) plays a central role in every transmission and reception chain. Such amplifiers are not only used in classic applications such as mobile communications, aerospace and defence, but also in medical technology – especially in magnetic resonance imaging (MRI).
In MRI systems, a powerful RF pulse is emitted at the so-called Larmor frequency – i.e. the frequency at which the hydrogen nuclei (protons) precess in the static magnetic field. In a 3-Tesla MRI system, this frequency is approximately 128 MHz. The RF pulse excites the spins of the protons. When they return to their ground state, the protons emit energy in the form of RF signals, which are measured and used for image reconstruction.
The high-frequency power amplifier (RF PA) plays a central role in every transmission and reception chain. Such amplifiers are not only used in classic applications such as mobile communications, aerospace and defence, but also in medical technology – especially in magnetic resonance imaging (MRI).
In MRI systems, a powerful RF pulse is emitted at the so-called Larmor frequency – i.e. the frequency at which the hydrogen nuclei (protons) precess in the static magnetic field. In a 3-Tesla MRI system, this frequency is approximately 128 MHz. The RF pulse excites the spins of the protons. When they return to their ground state, the protons emit energy in the form of RF signals, which are measured and used for image reconstruction.
The high-frequency power amplifier (RF PA) plays a central role in every transmission and reception chain. Such amplifiers are not only used in classic applications such as mobile communications, aerospace and defence, but also in medical technology – especially in magnetic resonance imaging (MRI).
In MRI systems, a powerful RF pulse is emitted at the so-called Larmor frequency – i.e. the frequency at which the hydrogen nuclei (protons) precess in the static magnetic field. In a 3-Tesla MRI system, this frequency is approximately 128 MHz. The RF pulse excites the spins of the protons. When they return to their ground state, the protons emit energy in the form of RF signals, which are measured and used for image reconstruction.
Superparamagnetic iron-oxide nanoparticles (SPIONs), composed of a magnetic iron-oxide core and a tunable non-magnetic coating, exhibit rapid magnetic response along with exceptional stability and biocompatibility [1], [2]. These characteristics have fostered their applications in diverse medical fields including drug delivery [3], diagnostic imaging [4], and hyperthermia therapy [5].
The characteristics of nanoparticles are closely related to their structure. Their structure is well layered. Crystals, iron oxide nuclei, aggregates, clusters and agglomeration are gradually formed as the scale increases. The formation of these different hierarchical structures determines the macroscopic properties of the final nanoparticle.
