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Bachelor Projects

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 deep learning 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. Deep 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 a deep learning segmentation schemes developed for soft materials (as implemented in Dragonfly). The project will be dedicated to one of the two challenges related to the microstructure of paper:

(a) Classify a phase contrast image with deep learning Microcomputed X ray tomography (μ-CT) exploits different aspects of the interaction between Xrays and matter. In this topic, deep learning shall be utilized to segment a scanned image that relies on phase contrast.

(b) Where is the water?
The μ-CT images reveal how water is incorporated into the fiber network of paper. A deep learning method using pseudo 3D training images has been shown to segment the image into the consituents the paper sample reasonably well. This project aims at quantification of the prediction quality of the convolutional network and extract the speed of water intrusion from a time-dependent series of 3D images.

This project can be carried out remotely if COVID-19 regulations prevent presence at the university

Contact: Karin Zojer (karin.zojer@tugraz.at; Tel.: 873-8974),
Eduardo Machado Charry (machadocharry@tugraz.at; Tel.: 873-8465)

Relaunch of the software STEREOPOLE



The suggested project will be a series of individual Bachelor projects with the goal to develop a state of the art version of the software STEREOPOLE. The software was developed in the year 2004 by the Master student Ingo Salzmann, and became a frequently used tool in X-ray diffraction science. The software is used to visualize X-ray diffraction pole figures and compare them with stereographic projections. The software will be completely new written using state of the art possibilities in terms of programming language, visualization and simulation.

additional information: http://scripts.iucr.org/cgi-bin/paper?S002188980402165X


Model air flow through a pore cluster in the microstructure of paper

Describing the flow of air through the actual microstructure of paper using the Navier Stokes equation is an elaborate task even if established software such as COMSOL is used. A decisive and challenging step is to cast the pore space (3D voxel volume information) into a surface mesh enclosing the pore space. This project will establish the workflow for a complete air flow simulation in COMSOL on an excerpt of the microstructure containing a cluster of pores.

This project can be carried out remotely if COVID-19 regulations prevent presence at the university

Contact: Karin Zojer (karin.zojer@tugraz.at; Tel.: 873-8974),
Eduardo Machado Charry (machadocharry@tugraz.at; Tel.: 873-8465)

Extract pore networks from measured microstructures of paper

The 3D microstructure of paper recorded at micrometer resolution reveals the pore space available for transport in paper. Storing the full information of this pore space is very expensive. With this project we intend to learn how to dramatically reduce the information required to characterize the pore space. Using a selected toolset of mathematical transformations available in the software Dragon fly, the pore space is cast into a pore network presentation.

This project can be carried out remotely if COVID-19 regulations prevent presence at the university

Contact: Karin Zojer (karin.zojer@tugraz.at; Tel.: 873-8974),
Eduardo Machado Charry (machadocharry@tugraz.at; Tel.: 873-8465)

Intrusion of mercury into paper: A pore network perspective

Pore networks are a representation of complex pore spaces that honor the pore sizes, connections and separations between them. In terms of modelling transport, pore networks offer an illustrative and feasible way to trace transport of a gas or liquid through an extended network. This project aims at establishing a pore network model for describing the intrusion of mercury into paper sheets using the OpenPNM package. Such simulation yield valuable insights into details of the intrusion process and help to interpret mercury porosimetry experiments with paper.


This project can be carried out remotely if COVID-19 regulations prevent presence at the university


Contact: Karin Zojer (karin.zojer@tugraz.at; Tel.: 873-8974),
Eduardo Machado Charry (machadocharry@tugraz.at; Tel.: 873-8465)

Simulation von Phononenbandstrukturen organischer Halbleiter

Ein weiterer interessanter Themenkomplex wären Phononenbandstrukturen organischer Halbleiter, die (im Kontext von Wärmeleitung und elastischen Materialeigenschaften) aktuell im wissenschaftlichen Fokus unseres Teams liegen. Bei der Beschreibung der für viele Materialeigenschaften ganz besonders wichtigen niederenergetischen Phononen spielt eine akkurate Modellierung der van der Waals Wechselwirkung zwischen benachbarten Molekülen eine zentrale Rolle. Diese ist nämlich im Rahmen der typischerweise verwendeten Dichtefunktionaltheorie nicht adäquat beschrieben, weshalb in den letzten Jahren diverse Korrekturmethoden zur Überwindung dieses Problems entwickelt wurden. Hier haben wir schon einige Tests durchgeführt (und veröffentlicht), wobei im Rahmen der Bachelorarbeit geplant wäre, diese Tests noch zu erweitern. Dies würde eine wichtige Grundlage zu einem im nächsten Februar startenden Forschungsprojekt zur Simulation von Wärmetransportprozessen in organischen Halbleitern darstellen.

Diese Arbeiten lassen sich in der aktuellen Covid-19 Situation auch remote durchführen, da es zu den Codes zur quantenmechanischen Simulation der Bandtsrukturen gute Tutorials gibt.

Egbert.Zojer@tugraz.at

Anwendung des Tight Binding Modells zur Beschreibung der Bandstruktur organischer Halbleiter

In einigen Bacherlorarbeiten in den vergangenen Semestern haben sich die Studierenden damit beschäftigt, inwieweit das Tight Binding Modell dazu geeignet ist, organische Halbleitermaterialien auch quantitativ zu beschreiben und inwieweit es möglich ist, aus diesen Modellen direkte Rückschlüsse auf die elektronischen Kopplungen zwischen benachbarten Molekülen zu ziehen. In dem Zusammenhang wurden bisher speziell designte Modellsysteme mit dem Ziel untersucht, festzustellen, unter welchen Umständen es bei so einer Beschreibung fundamentale mathematisch/numerische Probleme gibt, wobei wir aktuell an der Zusammenstellung einer Veröffentlichung zu diesen Daten arbeiten. Der nächste Schritt wäre, die bisher erzielten Erkenntnisse auf konkrete Beispiele von organischen Halbleitern anzuwenden.

Diese Arbeit lässt sich in der aktuellen Covid-19 Situation auch remote durchführen, da es zu den Codes zur quantenmechanischen Simulation der elektronischen Bandtsrukturen gute Tutorials gibt. Außerdem hat Christian Winkler schon im ersten Lockdown ein Tutorial zu den Tight Binding Fits zusammengestellt.

Egbert.Zojer@tugraz.at

Structure Prediction      >> more >>

Our experimental colleagues are currently working on a new molecule-substrate combination which forms interesting structures. Since we have now a graphical user interface to facilitate the usage of our code, performing a structure prediction SAMPLE is now easily possible for a real-world system. With support from the group you will predict the energetically most favorable structures yourself and investigate how they compare to experimental observations.

Transfer Learning       >> more >>

Very often, projects entail the investigation of several similar systems, e.g. the same molecule on Cu, Ag, and Au, or molecules with similar shape and interaction. Presently, our approach requires to apply machine learning for each system from scratch. However, clearly, there is something that can be learned from one system that can be transferred to the next. The aim of this topic is to combine physical insight with the description of the structures within our machine learning model, in order to transfer knowledge between different systems.

Hessian Learning and Geometry Optimization      >> more >>

One of the key factors determining the efficiency of geometry optimization at the quantum-mechanical level is the initial guess of the Hesse matrix, i.e. the second derivative of energy with respect to atomic displacements. Most contemporary geometry optimization algorithms are designed with molecules or solid crystals in mind but yield poor results for interfaces. The task of the present topic is to use machine-learning approaches to create an improved Hesse-Matrix guess for specific polymorphs based on pre-calculated Hesse-Matrices of other structures.

Structure Classification (Phase or Defect?)      >> more >>

Interface unit cells often contain several molecules. Just from looking at the geometries, it is often hard to tell whether a given structure is just a defect of a certain thermodynamic phase (i.e., a misaligned molecule, a vacancy, etc.), or whether it is a new phase altogether. The target of this thesis is to test different parameters (e.g. bond-order ordering parameters) and to write a machine-learning based clustering algorithm to classify the different structures obtained by SAMPLE. This will allow us not only to predict the prevalence of defects in structures, but also whether a given phase transformation is a first-order or second order transition.

Automated comparison of theory and experiment (LEED simulation)      >> more >>

Because theory allows creating a multitude of different structures, finding the one that corresponds to the one measured in experiment is often non-trivial. The situation is complicated by the fact that often different choices for unit cells exist, whose equivalence is not necessarily obvious. To solve this conundrum, we need to simulate observables directly related to the atomic structure, such as the diffraction pattern, and compare the results to experimentally obtained result. The aim of this thesis is to write a tool that simulates the theoretical spectrum and analyses the similarity to the experiment.

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.
Having such tight-binding models in hand one can then investigate electronic band structures in more detail – for example identifying super-exchange type effects, or calculating the full effective mass tensor at specific k-points.

We are looking for: Highly motivated students with an interest in solid state physics and computational material science. Basic programming skills are required (Matlab, Python).


Contact: Egbert Zojer (egbert.zojer@tugraz.at; Tel.: 873-8475),
Christian Winkler (christian.winkler@student.tugraz.at)

Performancevergleich zweier Moleküle bei der Messung eines FRET Signals      >> more >>

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.
In dieser Arbeit wird ein System untersucht wie es in Abbildung 2 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 einem bestehenden Algorithmus bearbeitet und analysiert.
Ziel der Arbeit ist es zu sehen ob durch die geschickte Wahl zweier Moleküle eine einfachere Interpretation der Ergebnisse möglich gemacht werden kann.

Untersuchung der Verbesserung eines Signales durch die Anwendung von Korrekturfaktoren      >> more >>

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.

Contact: Robert Schennach

 

 


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