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Institute of Solid State Physics
A bachelor project serves as an introduction to scientific research. During this project, 4 weeks are spent in a research laboratory (150 hours, 6 ECTS). At the conclusion of the research, a report about the results is written and a 20 minute public presentation is given. The time necessary to write the report and prepare the presentation are included in the 150 hours.
A true scientific publication must be original work; it should describe scientific results that have never been reported before. Ideally, a bachelor report should have the character of a scientific publication. A bachelor report is not intended to be a review of work done by others.
A scientific publication should begin with a short and clear description of what was done, why it was done, and what the main results are. It is not a novel where the reader should be kept in suspense until the last page. Tell the ending on the first page and then use the rest of the report to fill in the details.
After the initial statement of your own results, give the reader some background information. All scientific projects build on the work of others. You should make it clear what the state-of-the-art was at the start of your project. This section should be brief, no more than about 3 pages. Provide the reader with references to books or articles that describe your research topic in more detail.
The bulk of a bachelor report should contain a discussion of the scientific issue you attempted to resolve, the methodology you used, a presentation of the data, and a discussion of the results. The recommened length of the report is 15-25 pages.
The TU will scan all master and PhD theses electronically for plagiarism. While there is currently no plan to systematically scan the bachelor theses, everything in electronic form might be scanned at some time. It should be clear from the way the references are placed which ideas you claim as your own and which you have taken from others.
To protect the privacy of students, the university does not publish a list of student names or email addresses. However, when a bachelor student works in our institute, we typically list their names and email addresses on our institute website. This makes it easier for members of the institute to contact each other. If you do not want to be listed on the website, please inform the secretary when your project starts.
A list of possible bachelor projects is given below. There is a certain flexibility in defining bachelor projects. You may propose the topic of a bachelor project to a member of the scientific staff. If you have questions about bachelor projects at the Institute of Solid State Physics, please contact Peter Hadley.
Some bachelor reports that have been completed in our institute can be found here.
Richtlinien zur Erstellung einer Bachelorarbeit im Bachelorstudium Technische Physik
Classification of image features using a trainable detection algorithm
Microcomputed X ray tomography (μ-CT) holds the promise to determine the 3D microstructure of materials with micrometer resolution. To truly lift the potential of this imaging method, it is necessary to reliably distinguish and classify features in the 3D images (segmentation). Once classified, each feature of the microstructure can be analyzed in terms of composition, size distributions etc. Each imaged material poses unique challenges to classify its features. Trainable learning algorithms offer customized classifications that are tailored towards each material or even 3D image.
Here we are interested in an automated distinction of materials in images of paper using unsupervised segmentation learning schemes. These learning schemes are available via the widespread image analysis package ImageJ. The project will be dedicated to one of the two challenges related to the microstructure of paper:
(a) Towards automated detection: Incorporate existing classifications in training (prior knowledge) A major asset for any learning scheme is the ability to incorporate existing knowledge. Such a preliminary knowledge exists, as images of paper have been accurately classified using other approaches. However, as these other approaches require an extensive preprocessing of the images, it is highly desirable to pass the existing classification to the learning scheme. The aim of this project is to explore and implement a workflow to incorporate existing classifications into the training of the learning algorithm.
(b) Where is the water?
Contact: Karin Zojer (email@example.com; Tel.: 873-8974),
Developing tight-binding models for understanding charge transport in advanced materials
Organic semiconductors have attracted increasing attention over the past years because of numerous advantageous properties, including the tunability of electrical and optical properties, mechanical flexibility, and the possibility to build biocompatible electronics. For all these applications the charge transport is highly relevant. Key parameter in all commonly used transport models are inter-molecular transfer integrals, which are a measure for the electronic coupling between adjacent molecules. A strategy for obtaining these transfer integrals that we have intensively studied in the past months is the fitting of advanced tight-binding models (see lecture on Molecular and Solid State Physics) to the 3D band structures of a given material. The latter can be obtained, for example, via density-functional theory (DFT) based band-structure calculations. The purpose of this thesis is to expand our knowledge of the intricate details of this fitting procedure by studying deliberately designed 1D, 2D, and 3D model systems, which allow addressing the influence of dimensionality, complexity and symmetries. The gained knowledge can then be transferred from the model systems to highly relevant materials such as the already mentioned organic semiconductors and also to metal organic frameworks MOFs.
Bei Förster Resonanz Energie Transfer (FRET) interagieren zwei unterschiedlich fluoreszente Moleküle, ein Donor und ein Akzeptor, über Dipol Wechselwirkung und übertragen Energie. Kurz gesagt regt man den Donor an und misst ein Akzeptorsignal das nur von FRET stammen kann. Ohne zu tief in die Theorie zu gehen hängt FRET vom Überlapp der Fluoreszenzspektren der beiden Moleküle ab wie es in Abbildung 1 zu sehen ist. Durch die Wahl zweier verschiedener Moleküle wird erreicht, dass die Signale weiter voneinander getrennt werden und es so später, im angewendeten Algorithmus zur Auswertung, zu einer einfacheren Interpretation der Ergebnisse führt.
Bei dieser Arbeit geht es darum zu untersuchen ob sich die Qualität des Signals einer Messmethode durch die Anwendung von Korrekturfaktoren verbessern lässt. Das gemessene Signal kommt von Förster Resonanz Energie Transfer (FRET). Bei diesem Effekt können zwei unterschiedlich fluoreszente Moleküle, ein Donor und ein Akzeptor, über Dipol Wechselwirkung Energie übertragen. Das resultierende Signal wird nach der Messung mit einem Algorithmus (Matlab) getrennt um herauszurechnen wie viel des Signales tatsächlich von FRET kommt. In dieser Arbeit wird ein System untersucht wie es in Abbildung 1 zu sehen ist. Zwei Papierfasern werden mit verschiedenen Molekülen (Donor und Akzeptor) gefärbt und physikalisch gebunden. Anschließend wird das System über ein Mikroskop mit verschiedenen Filtersätzen untersucht und die resultierenden Bilder werden mit dem oben genannten Algorithmus bearbeitet und analysiert. Ziel der Arbeit ist es zu sehen ob der Algorithmus mit Korrekturfaktoren zu einer signifikanten Verbesserung des Signals führt gegenüber dem Algorithmus ohne Korrekturfaktoren.
Measurement of Nanoparticle transport through sack paper
In the course of this work a measurment system developed by Prof. Bergmann from the Institute of should be used to measure transport of different kinds of nanoparticles through sack paper samples.
Most semiconducting transistors contain regions that have been doped n-type and regions that have been doped p-type. In this project, capacitance-voltage measurements will be used to determine the doping concentrations od diodes, MOSFETs and JFETs. To quantify the measurement errors that are made, the frequency dependent noise behavior of the current preamp will be measured and a Fourier analysis of the noise will be performed. The instruments will be controlled with a Python script. Contact firstname.lastname@example.org