Student Jobs, Thesis

Am Zentrum für Mikro- und Nanotechnologien ist im Rahmen eines Forschungsprojekts zur supraleitenden Mikroelektronik eine studentische Arbeit (Projekt-, Bachelor- oder Masterarbeit) zu vergeben. Der Fokus liegt auf der Prozessentwicklung und Charakterisierung von Niob-Schichten (Nb).

Projektinhalt und Aufgabenstellung

Niob (Nb) ist ein zentrales Material für supraleitende Strukturen. Ziel der Arbeit ist die Optimierung der Abscheidungsprozesse für mikroelektronische Anwendungen. Der Student/die Studentin wird aktiv in den Prozess eingebunden – beginnend mit dem Einbau eines neuen Nb-Targets bis hin zur eigenständigen Prozessführung.

Der Umfang der Arbeit wird je nach Modulvorgabe definiert:

• Prozessierung: Durchführung von PVD-Beschichtungen (Magnetron-Sputtern).

• Analytik: Systematische Untersuchung der Schichteigenschaften mittels Profilometrie (Dicke), Schichtspannungsmessung, Vier-Punkt-Methode (elektrische Charakterisierung) und AFM (Rauigkeitsmessung).

• Optionale Erweiterung: Strukturierung der Schichten durch Trockenätzverfahren oder Lift-Off-Prozesse.

Anforderungsprofil

• Studienrichtung: Studium der Physik, Biomedizinischen Technik, Mikrosystemtechnik, Materialwissenschaften oder einer vergleichbaren Fachrichtung.

• Arbeitsweise: Nach einer umfassenden Einarbeitung wird eine eigenständige und verantwortungsbewusste Arbeitsweise im Labor- bzw. Reinraumumfeld erwartet.

• Methodische Kompetenz: Ausgeprägtes analytisches Denken sowie die Fähigkeit, Messergebnisse kritisch zu hinterfragen und eigenständig Hypothesen zur Validierung der Resultate zu entwickeln.

• Interesse: Motivation zur experimentellen Forschung an der Schnittstelle von Materialwissenschaft und Mikroelektronik.

Rahmenbedingungen

• Zeitraum: 01. April bis 30. Oktober 2026.

• Angebot: Wir bieten eine fundierte Ausbildung an den Anlagen sowie die Möglichkeit zur eigenständigen wissenschaftlichen Arbeit in einem modernen Forschungsumfeld.

Contact: Apply for this job by email

Possible as: Student research project, Bachelor-Thesis, Master-Thesis

Addressed topics: MEMS, Micro- and Nanoelectronics, Others, Measurement / analytics, Processes / technology

Sensors play a pivotal role in modern
analytical sciences, particularly in the development of high-performance
platforms for detecting biological and chemical analytes. Applications span healthcare,
environmental monitoring, breath diagnostics (breathomics), and industrial
safety. Whether detecting biomarkers in body fluids or volatile organic
compounds (VOCs) in exhaled breath, target molecules are typically found at
trace concentrations, often in complex sample matrices. This necessitates the
design of sensing systems that are highly sensitive, selective, and robust
under diverse operating conditions. Nanomaterial-based sensor platforms, such
as carbon nanotube (CNT)-based field-effect transistors (FETs), emerged as
promising candidates, enabling the development of compact, label-free, and
real-time sensors suitable for point-of-care diagnostics and opening doors for
wearable health technologies.

This project work or master's thesis
focuses on the analytical and structural characterization of such
nanoengineered sensors tailored for biological sensing or gas detection
applications. The work includes the selective functionalization of sensor surfaces,
optimization of sensor interface chemistry, and evaluation of device
performance in liquid or gaseous environments. The device functionalization and
structural modifications are studied via microscopy analysis, Raman
spectroscopy, atomic force microscopy, and the sensor response is monitored via
electrical measurements. The goal is to correlate surface structure and
composition with sensing behavior, contributing to a multimodal understanding
of sensor performance.

What will you do:

·        
Conduct
a literature review on sensor technologies, nanomaterials, and surface
functionalization

·        
Prepare
and handle solutions or gas mixtures for sensor testing

·        
Execute
fabrication processes, optimize parameters, and carry out experimental analysis

·        
Present
your results regularly in scientific meetings and seminars

What you bring along:

·        
You
are studying physics, chemistry, materials science, biosciences, or a related
discipline

·        
Interest
in micro- and nanotechnology, surface analysis, and analytical characterization
methods

·        
An
organized, data-driven, and proactive working style

·        
Strong
English reading and comprehension skills

What you can expect:

·        
Work
with advanced nanomaterial-based sensing platforms for biological and chemical
applications

·        
Gain
hands-on experience with surface characterization techniques (Raman, AFM,
microscopy) and electrical measurements

·        
Collaborate
in an interdisciplinary research team with opportunities to contribute your own
ideas

·        
Professional
supervision and a varied range of tasks

·        
Flexible
working hours that support the compatibility of studies and practice

Contact: Apply for this job by email

Possible as: Student Assistance, Bachelor-Thesis, Master-Thesis, Diploma Thesis

Addressed topics: Electronics, Micro- and Nanoelectronics, Nano technology, Measurement / analytics, Processes / technology, Review of Literature

The growing importance of the
artificial intelligence in almost all areas of life necessitates the
development of new hardware concepts that are more closely based on the
function of the biological brain. The science, which researches the replication
of biological components, synapses and neurons with nanotechnological
functional elements, is called as “Neuromorphic computing”. Artificial synapses
are typically designed in the form of so-called crossbar arrays, Figure 1,
which contain nanoionic memory cells in the individual nodes.

These memory cells are known as “memristors”, which are resistors that change in a time-dependent and non-volatile manner depending on the voltage applied. In this way, synaptic weights can be stored. In order to be able to train the network architectures created in this way, “on-chip training”, it is necessary to describe the single memory cells individually, which presupposes that all surrounding cells are inactive. Here, so-called nanoswitches, also known as “atomic switches”1,2, are used, which can be switched on and off with targeted voltage pulses. This allows the cells to be activated and deactivated individually and the memristors to be programmed in this way. Figure 2 shows a diagram of the structures to be set up and how they are controlled.

The subject of the announced master's thesis is the development of a nanoionic atomic layer switch and its implementation in memristive memory cells in order to be able to activate and deactivate them in a targeted manner. Such a switch consists of an inert and a soluble electrode, between which a very thin metal-oxide electrolyte is located. When a voltage pulse is applied, the material of the soluble electrode dissolves in the electrolyte and a conductive filament is formed. When this reaches the inert counter electrode, the cell becomes resistive and the switch is activated. When a negative voltage pulse is applied, the switch can be opened again. The aim of the work is the construction of such an atomic layer switch, the optimization of the layer system and the electrical characterization. The focus is on the relationship between the deposition conditions of the individual layers and the electrical behavior of the switch.

The Atomic Layer Deposition (ALD) is an important method for the formation of thin metallic, (semi)metal oxide or nitride layers from a precursor molecule under use of a second reactant. The reaction takes place thermally induced or enhanced by plasma. The growth rate is dependent on several parameters, like temperature and dosing time. The self-limiting character of the surface reaction is a special attribute of this method. The layer formation occurs during two separated process steps from a precursor and a second reactant. Due to the self-limiting character the deposited layers are typically highly conformal, homogeneous, without defects, and with a thickness of a few nanometers.

One suitable material for atomic switches is hafnium oxide which is deposited by ALD with an oxygen source as second reactant as exemplarily shown with water in Figure 3.

Also titania is mentioned as suitable material for memristive elements.4 Additionally, doping of the pristine oxides is described to purposeful enhance the layer properties.5 The material of memristive layers is as much relevant as the electrode materials and deposition methods.
Tasks:

• Literature review
• Fabrication of reference system of HfO2 and TiO2 (ALD) layers
• Variation of layer thicknesses under perpetuation of the materials
• Use of thermal and plasma-enhanced processes
• Variation of the ALD-deposition conditions and post-treatments
• Al-doping of hafnia and titania layers
• Deposition of top electrode layers, comparison of deposition method-dependent properties
• Implementation in switchable memristive memory cells
• Characterization: spectroscopic ellipsometry, electrical characterization, SEM (e.g., cross sectional analysis), memristive properties
• Electrical characterization of the finished switching elements

References

(1) Aono, M.; Hasegawa, T. The Atomic Switch. Proc. IEEE 2010, 98 (12), 2228–2236. https://doi.org/10.1109/JPROC.2010.2061830.

(2) Hino, T.; Hasegawa, T.; Terabe, K.; Tsuruoka, T.; Nayak, A.; Ohno, T.; Aono, M. Atomic Switches: Atomic-Movement-Controlled Nanodevices for New Types of Computing. Science and Technology of Advanced Materials 2011, 12 (1), 013003. https://doi.org/10.1088/1468-6996/12/1/013003.

(3) Li, J.; Guo, J.; Zhou, Z.; Xu, R.; Xu, L.; Ding, Y.; Xiao, H.; Li, X.; Li, A.; Fang, G. Atomic Layer Deposition Mechanism of Hafnium Dioxide Using Hafnium Precursor with Amino Ligands and Water. Surfaces and Interfaces 2024, 44, 103766. https://doi.org/10.1016/j.surfin.2023.103766.

(4) Ullah, F.; Tarkhan, M.; Fredj, Z.; Su, Y.; Wang, T.; Sawan, M. A Stable Undoped Low-Voltage Memristor Cell Based on Titania (TiOx). Nano Ex. 2024, 5 (1), 015003. https://doi.org/10.1088/2632-959X/ad1413.

(5) Park, W.; Park, Y.; Kim, S. Ferroelectric Properties of HfAlOx-Based Ferroelectric Memristor Devices for Neuromorphic Applications: Influence of Top Electrode Deposition Method. The Journal of Chemical Physics 2024, 161 (23), 234706. https://doi.org/10.1063/5.0239966.

The given references are just examples. The comprehensive literature is the base for this topic.

The topic is suitable for masters’ theses.
Estimated start of work: June 2025

We look for students with a solid background in technical understanding, physics, electrical engineering, thin film deposition methods or related fields. 

If you are an interested and engaged student than apply with a short note of motivation and your CV. Describe your skills and give an overview of your recent marks. 

Please contact us for more details.

Advisors

Falk Schaller
Fraunhofer Institute for Electronic Nano Systems ENAS
E-Mail: falk.schaller@enas.fraunhofer.de
Phone: +49 (0) 371 531 39048/ +49 371 45001 460

Shan Song
Fraunhofer Institute for Electronic Nano Systems ENAS
E-Mail: shan.song@enas-extern.fraunhofer.de
Phone: +49 (0) 371 531 33224/ +49 371 45001 461

And 

Mathias Franz
Fraunhofer Institute for Electronic Nano Systems ENAS
E-Mail: mathias.franz@enas.fraunhofer.de
Phone: +49 (0) 371 531 33639 / +49 371 45001 612

Contact: Apply for this job by email

Possible as: Master-Thesis, Diploma Thesis

Addressed topics: Micro- and Nanoelectronics, Nano technology, Measurement / analytics, Processes / technology, Review of Literature

We offer a couple of open student positions in the field of  modeling and simulation of semiconductor processes and materials. In our team we cover simulation of semi processes and materials from the atom to the wafer. We use methods from theoretical and computational physics for applications in semiconductor engineering. Our high performance computing systems are ready to be used for your innovative simulation projects.

We look for students with a solid background in physics, mathematics, electrical engineering or related fields. You should be familiar with Python and have a strong interest to work with computers and software.

Please contact us for details and for arrangement of individual student projects. Please provide a short note of motivation, describe your skills and give an overview of your recent marks.

Contact: Apply for this job by email

Possible as: Student Assistance, Bachelor-Thesis, Master-Thesis, Diploma Thesis

Addressed topics: Electronics, Fluidics, Micro- and Nanoelectronics, Nano technology, Others, Programming, Simulation

Are you passionate about exploring
new frontiers in ultrasonic technology? We’re looking for talented students to
join our team and work on exciting projects that leverage Capacitive
Micromachined Ultrasonic Transducers (CMUTs) in innovative acoustic
communication setups. As part of our team, you'll contribute to refining the use case of acoustic communication using state-of-the-art CMUT
technology.

Key Responsibilities:

• Acoustic characterization of CMUTs


• Explore innovative use cases for CMUT-based
  communication


• Explore different modulation schemes


• Utilize CMUTs to create and optimize acoustic
  communication systems.


• Analyze acoustic data to extract valuable insights


• Develop a fully functional demo setup for acoustic
  communication using CMUT technology

Qualifications:

• Bachelor’s degree in Electrical/ Electronics/ Physics,
  Microsystems or a comparable field


• Excellent problem-solving abilities with a focus on
  real-world applications of acoustic communication.


• A deep interest in interdisciplinary work combining
  acoustics, electronics, and communication systems.


• Basic knowledge of programming (MATLAB, Python, or C++)
  for signal processing and system development is a bonus

We are currently offering
opportunities for Master's theses, research project, and student assistant
positions.

Apply Now!

Send your application to Dr. Nooshin
Saeidi and join the SP Integration Technologies team at Fraunhofer ENAS.

Apply today and help us unlock the
potential of CMUTs in acoustic communication!

Contact: Apply for this job by email

Possible as: Student research project, Master-Thesis, Diploma Thesis

Addressed topics: Electronics, MEMS, Micro- and Nanoelectronics, Packaging, Design, Measurement / analytics, Programming, Review of Literature, Simulation

Der technologische Fortschritt im Bereich der Halbleiterindustrie beruht im Wesentlichen auf der fortgesetzten Miniaturisierung von integrierten Schaltungen und Mikro-Elektro-Mechanischen-Systemen (MEMS). Eine der Schlüsseltechnologien, um diese Skalierung zu erreichen ist die lithographische Strukturierung von Substraten. Gängige kritische Dimensionen dieser Strukturen liegen heutzutage im Bereich zwischen 20-100nm. Um diese Höchstauflösung zu ermöglichen, sind besondere Anforderungen an das Lithographietool und den zu verwendenden Lack zu stellen.
Am Fraunhofer Institut ENAS steht mit dem Vistec SB254 ein hochmoderner Elektronenstrahlbelichter (Formstrahler) der neuesten Generation zur Verfügung, der SEMI-Standard Si Substrate der Größen 4“,6“ und 8“ belichten kann. Im Rahmen dieser studentischen Arbeit soll die wechselseitige Abhängigkeit zwischen Elektronenstrahlparametern und Lack Prozessparametern untersucht werden.

Im Besonderen sollen die erzielten Lackprofile & Lackstrukturen im Rasterelektronenmikroskop (JEOL JSM7800 F) charakterisiert werden und für die nachfolgende Prozesstechnologie optimiert werden. Dabei soll ein neuartiges Lacksystem als Alternative zum HSQ-Lack, welches in Kooperation mit dem Lackhersteller Allresist GmbH entwickelt wird, untersucht werden:

Insbesondere der Negativlack weist chemische Eigenschaften auf, der ihn gleichermaßen sensitiv für die Belichtung im optischen Spektrum und mit Elektronen macht. In einem ersten Schritt werden die Homogenität und die Schichtdicke der Lacke über den Wafer statistisch erfasst. Anschließend werden Teststrukturen in den Lack belichtet und mit dem REM charakterisiert. Basierend auf diesen Ausgangswerten werden die Belichtungsparameter und Prozessparamter variiert.

Die Aufgaben im Einzelnen:

• Erstellung einer Untersuchungsserie (Variation der Lackdicke
• Spin-Kurven) auf 6“-Si Substraten mit dem zuvor genannten Lack (Oberflächenprofilometrie)
• Erstellung einer Testbelichtung mit Variation der Belichtungs- und Prozessparameter (Kontrastkurven)
• Auswertung einer Belichtungsserie (Variation der Elektronendosis/ Prozessparameter) belackter Wafer mit einem Testdesign und Bewertung der Lackprofile/Strukturen

Art der Arbeit: Bachelorarbeit, Projektarbeit, Masterarbeit

Contact: Apply for this job by email

Possible as: Student research project, Bachelor-Thesis, Master-Thesis

Addressed topics: MEMS, Micro- and Nanoelectronics, Nano technology, Measurement / analytics, Processes / technology

Are you passionate about cutting-edge research at the intersection of healthcare, technology, and data science? Join us as a student in the exciting field of multi-energy X-ray imaging for more accurate diagnoses, improved treatment planning, and enhanced image quality across various applications in healthcare and beyond. This internship offers a unique opportunity to work on an innovative project that combines artificial intelligence (AI) with advanced medical imaging techniques.

Qualifications:

• Candidates with a strong understanding and practical experience with AI and Machine Learning algorithms are preferred.
• Excellent programming skills (preferably with Python) are required.
• A strong interest in interdisciplinary work at the intersection of medical engineering, physics, mathematics, and data science is essential.

We are currently seeking candidates for Master's theses, internships, and student assistant positions.

Interested candidates should send their applications to Dr. Jan Langer.

Don't miss this opportunity to contribute to cutting-edge research in health care and technology! Apply now and be part of the Data-Based Methods team at Fraunhofer ENAS.

Contact: Apply for this job by email

Possible as: Student Assistance, Master-Thesis

Addressed topics: Artificial Intelligence, Others

Are you passionate about cutting-edge research at the intersection of hardware design and software programming? Join us as a student and help program heterogeneous compute platforms of the future, that incorporate FPGAs, GPUs and AI acceleration engines in the same device. These advanced platforms need new programming paradigms, software tools and languages to be utilized efficiently. In our group we strive to accelerate applications from medical engineering, machine learning and image processing on heterogeneous platforms.

Qualifications:

• Candidates with a strong understanding and practical experience in the principles of hardware design and/or GPU programming are preferred.
• Excellent programming skills are required.
• A strong interest in interdisciplinary work at the intersection of hardware design, mathematical methods and software development is essential.

We are currently seeking candidates for Master's theses, internships, and student assistant positions.

Interested candidates should send their applications to Dr. Jan Langer.

Don't miss this opportunity to contribute to cutting-edge research in the programmability of heterogeneous compute platforms! Apply now and be part of the Data-Based Methods team at Fraunhofer ENAS.

Contact: Apply for this job by email

Possible as: Student Assistance, Master-Thesis

Addressed topics: Artificial Intelligence, Others

Are you passionate about developing application-driven computer vision pipelines for semiconductor metrology? Join our team as a student and contribute to the development of computer vision models for analyzing measurements of metrology devices. Our mission is to enhance the efficiency of semiconductor manufacturing by automating image analysis, utilizing web-based user interfaces and simplifying report generation.

Key Responsibilities:

• Develop computer vision models for analyzing metrology measurements.
• Extract meaningful information from metrological data.
• Deploy your pipeline in web-based user interfaces.

Qualifications:

• Strong understanding and practical experience in image processing methods or computer vision models.
• Excellent programming skills (preferably with Python) are required.
• Strong abstract and mathematical thinking skills.
• A strong interest in interdisciplinary work at the intersection of software development, data science, and semiconductor metrology is essential.

We are currently seeking candidates for Master's theses, internships, and student assistant positions.

Please send your application to Dr. Jan Langer.

Don't miss this opportunity to contribute to cutting-edge research in the programmability of heterogeneous compute platforms! Apply now and be part of the Data-Based Methods team at Fraunhofer ENAS.

Contact: Apply for this job by email

Possible as: Student Assistance, Master-Thesis

Addressed topics: Artificial Intelligence, Others

Are you passionate about cutting-edge research at the intersection of semiconductor technology and artificial intelligence?
Join us as a student in our team for artificial intelligence and data based methods at the Fraunhofer Institute of Electronic Nanosystems (ENAS).

We're on a mission to create digital twins for highly complex semiconductor manufacturing processes - enabling process optimization and model-based control. As the industry moves towards more individualized processes and products, a significant challenge is to enable accurate predictions with limited reference data. We, therefore, employ a broad range of artificial intelligence algorithms that enrich process data with sophisticated domain knowledge, as well as semi-supervised approaches to incorporate unlabeled data.

Qualifications:

• A strong understanding as well as practical experience with AI and Machine Learning algorithms.
• Excellent programming skills (preferably with Python).
• A strong interest in interdisciplinary work at the intersection of semiconductor technology, data science and artificial intelligence.

We are currently seeking candidates for Master's theses, internships, and student assistant positions.

Please send your application to Dr. Jan Langer.

Don't miss this opportunity to contribute to cutting-edge research in the programmability of heterogeneous compute platforms! Apply now and be part of the Data-Based Methods team at Fraunhofer ENAS.

Contact: Apply for this job by email

Possible as: Student Assistance, Master-Thesis

Addressed topics: Artificial Intelligence, Others

The particular strength of the Fraunhofer Institute for Electronic Nano Systems ENAS lies in the development of smart systems - so-called intelligent systems for various applications. The systems combine electronic components, micro and nano sensors and actuators with interfaces for communication. Fraunhofer ENAS develops individual components, the technologies for their production as well as system concepts and system integration technologies and transfers them into practical use. Fraunhofer ENAS accompanies customer projects from the idea to thedesign, technology development or implementation using existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is on semiconductor manufacturing and medical technology.

Are you passionate about cutting-edge research at the intersection of healthcare, technology and data science?

Join our team in the Horizon Europe project "NOVO: Next Generation Imaging for Real-Time Dose Verification Enabling Adaptive Proton Therapy". Work in an international team of experts from different disciplines such as proton therapy, computer science, applied mathematics, detector physics and medical physics.

We are currently looking for students for Master's theses, internships and student assistants.

We can discuss our ideas together to find theright job for you.

What you bring to the table?

• You already have some practical experience with AI and machine learning algorithms? Then you've come to the right place.
• Excellent programming skills (preferably in Python) are required.
• A strong interest in interdisciplinary work at the intersection of medical engineering, physics, mathematics and data science is essential.

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnicand social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equalsuitability.

Interested? Apply online now. We look forward to getting to know you!

Dr. Jan Langer will be happy to answer any questions you may have about the position.

Contact: Apply for this job by email

Possible as: Student Assistance, Master-Thesis

Addressed topics: Artificial Intelligence, Others

Ziel der Arbeit ist, mit Plasmaätzverfahren Gruben mit vertikalen Wänden in einkristallinem Silizium zu ätzen. Im Sinne einer Verbesserung des Umwelt- und Klimaschutzes dürfen hierfür keine fluorkohlenstoffhaltigen Prozeßgase zum Einsatz kommen.
Eine Möglichkeit der Umsetzung dieser Aufgabe wurde von Nguyen u. a. gezeigt [1–4].

Aufgabenstellung

1. Literaturrecherche zum Thema
2. Vermessung bzw. Charakterisierung vor und nach den Ätzversuchen
3. Übertragung eines in der Literatur beschriebenen und geeigneten Ätzprozesses auf die Gegebenheiten am ZfM
4. Versuchsplan aufstellen
5. Durchführung der Ätzversuche
6. Untersuchung der Ätztiefen und -profile mit unterschiedlichen Meßmethoden z.B. Oberflächenprofilometrie, Fokusdifferenzmethode am Lichtmikroskop
7. Auswertung der Ergebnisse

[1] V. T. H. Nguyen et al. , “The CORE Sequence: A Nanoscale Fluorocarbon-Free Silicon Plasma Etch Process Based on SF6/O2 Cycles with Excellent 3D Profile Control at Room Temperature”, ECS Journal of Solid State Science and Technology , Bd. 9, H. 2, Art. 24002, Jan. 2020.

[2] V. T. H. Nguyen, E. Shkondin, F. Jensen, J. Hübner, P. Leussink, and H. Jansen, “Ultrahigh aspect ratio etching of silicon in SF6-O2 plasma: The clear-oxidize-remove-etch (CORE) sequence and chromium mask”, Journal of Vacuum Science & Technology A , Bd. 38, H. 5, Art. 53002, Sep. 2020.

[3] V. T. H. Nguyen, F. Jensen, J. Hübner, P. Leussink, and H. Jansen, “On the formation of black silicon in SF6-O2 plasma: The clear, oxidize, remove, and etch (CORE) sequence and black silicon on demand”, Journal of Vacuum Science & Technology A , Bd. 38, H. 4, Art. 43004, Jul. 2020.

[4] V. T. H. Nguyen, “Directional Nanoscale Silicon Etching using SF6 and O2 Plasma,” Diss., Dänemarks Technische Universität, 2020.

Art der Arbeit: Projektarbeit

Contact: Apply for this job by email

Possible as: Student research project

Addressed topics: MEMS, Micro- and Nanoelectronics, Nano technology, Measurement / analytics, Processes / technology

Im Rahmen dieser Arbeit sollen Trockenätzversuche an SiO2 und Si3N4 auf Waferlevel durchgeführt, Versuchsparameter hinsichtlich Selektivität variiert und die Ergebnisse ausgewertet werden.
Konkret soll eine Selektivität von mindestens 1:30 zwischen SiO2 und Si3N4 erreicht werden, indem das F/C-Verhältnis eingestellt wird. Praktisch wird dieses Verhältnis über den Gasfluss der Prozessgase (CHF3, CF4) bestimmt. Die Experimente werden an SiO2 und Si3N4 Schichten sowie SiO2/Si3N4 Stapeln auf Si-Wafern durchgeführt.

Zu den Aufgaben zählen:

• Literaturrecherche (Trockenätzen/RIE, F/C-Verhältnis, SiO2/SiN Ätzmechanismen, …)
• Versuchsplanung
• Versuchsdurchführung an der Ätzanlage
• Charakterisierung an Messgeräten (Mikroskop, Profilometer, REM, …)
  
• Auswertung und Präsentation der Ergebnisse
  Die praktischen Versuche werden im Reinraum durchgeführt.

Literatur:

[1] Journal of Vacuum Science & Technology A 17, 26 (1999); https://doi.org/10.1116/1.582108

[2] J. Vac. Sci. Technol. A 38, 050803 (2020); https://doi.org/10.1116/6.0000395

Contact: Apply for this job by email

Possible as: Student research project

Addressed topics: MEMS, Nano technology, Measurement / analytics, Processes / technology, Review of Literature

In den vergangenen Jahren ist unsere Elektronik Landschaft stark von Trends wie dem Internet der Dinge oder der Industrie 4.0 geprägt wurden. Inzwischen geht der Trend zu multifunktionalen Endgeräten, die neben Rechen- und Kommunikationsaufgaben auch sensorische Aufgaben zum Zwecke der Zustandsüberwachung übernehmen. Perspektivische Anwendungen zielen auf Point-of-Care-Diagnostik, Luft- und Lebensmittelüberwachung, oder der Analyse von krankheitsspezifischen Biomarkern in der ausgeatmeten Luft ab.

Niedrigdimensionale Nanomaterialien bieten aufgrund Ihres hohen Oberflächen-zu-Volumenverhältnisses die ideale Materialbasis für hoch-sensitive Gassensoren mit geringem Energieverbrauch, welche in diesem Kontext benötigt werden.
Das Ziel dieser Forschungsarbeit, besteht in der systematischen elektrischen Charakterisierung von Nanomaterialbasierten Gassensoren in Feldeffekttransistor-Konfiguration unter verschiedenen Gasen. Es sind methodische Entwicklungen, wie Skript-basierter Auswerteverfahren zur Extraktion der Sensitivität bei verschiedenen Prüfgaskonzentrationen zu tätigen und statistisch zu bewerten. Im Weiteren sind die Querempfindlichkeiten auf verschiedene Gase zu analysieren. Die Arbeit kann je nach Fortschritt auf die Implementierung von speziellen Funktionalisierungen erweitert werden. Die Untersuchungen werden dabei durch analytische Methoden wie etwa Rasterkraft-Mikroskopie, Raman-Spektroskopie, und elektrischer Feldeffekttransistor-Messungen unterstützt.

Hauptaufgaben:

1. Literaturrecherche
2. Methodische Entwicklungen am Gassensorteststand oder zur skriptbasierten Evaluation
3. Aufnahme und Evaluierung von systematischen Versuchsreihen zur Sensitivität der Sensoren
4. Regelmäßige wissenschaftliche Präsentationen des Projektfortschritts in Rahmen des Arbeitsgruppenseminars
   

Anforderungen:

1. Studium der Physik, Ingenieurwissenschaften (Mikro/Nanotechnologie), Chemie oder äquivalenter Studiengänge
2. Grundkenntnisse zu analytischen Charakterisierungsmethoden
3. Selbstständiger und unabhängiger Arbeitsstil
4. Sprachen: Deutsch, Englisch

Contact: Apply for this job by email

Possible as: Student research project, Bachelor-Thesis, Master-Thesis

Addressed topics: Micro- and Nanoelectronics, Nano technology, Measurement / analytics, Processes / technology

Die CarbonNanodevice Gruppe am ZfM/ Fraunhofer ENAS erforscht und entwickelt Kohlenstoff-basierende nano-elektronische Bauelemente für Elektronik und Sensoranwendungen. Es konnte bereits gezeigt werden, dass mit einer noch nicht optimierten Kohlenstoffnanoröhren-Technologie die Performance von State-of-the-art Silizium Hochfrequenz-Transistoren erreicht werden kann. Hierfür wird hochspezielles und einzigartiges Equipment verwendet, welches auf die Integration und Vermessung von Nanomaterialien in Bauelementen und Systemen ausgelegten ist. Im Rahmen einer Studentenarbeit soll die Leistungsfähigkeit solcher HF Transistoren weiter verbessert werden.

Aufgaben:

Durchführung und Untersuchung von verschiedenen nass- und trochenchemischen Reinigungsprozeduren von Kohlenstoffnanoröhren in Feldeffekttransistoren. Die Verschiedenen Reinigungverfahren werden hinsichtlich ihrer Effektivität durch XPS-Spektroskopie, Rasterkraftmikroskopie, Raman-Spektroskopie sowie durch elektrische Messungen der Transistoren charakterisiert. Speziell soll das Verfahren/ die Prozedur ermittelt werden, welche den Kontaktwiederstand zwischen Kohlenstoffnanoröhre und Metallelektrode minimiert.

Voraussetzung:

• Studium in den Fachrichtungen: Physik, Elektrotechnik und Informationstechnik, Mikrosysteme und Mikroelektronik, o.Ä.
• Laborerfahrung
• Erfahrung beim Datenauswerten
• Selbstständige und zuverlässige Arbeitsweise
• englische und deutsche Sprachkenntnisse
  

Contact: Apply for this job by email

Possible as: Student research project, Bachelor-Thesis, Master-Thesis

Addressed topics: Micro- and Nanoelectronics, Nano technology, Measurement / analytics, Processes / technology, Review of Literature

Ähnlich wie der Mensch reagiert das Vieh (Rinder) mit auffälligen Augenbewegungen, wenn es sich gestresst fühlt.
Es ist wünschenswert, dass ein Tierarzt während der Behandlung, z.B. bei der Klauenpflege durch automatische Beobachtung dieser Augenbewegung mittels Videotechnik unterstützt wird. Durch geeignete Klassifizierung des Videostreams, evtl. auch eines solchen im infraroten Bereich, soll der Stresslevel bestimmt werden.

Similar to humans, livestock (cattle) react with eye movements when they feel stressed.
It is desirable that a veterinarian is supported during the treatment, e.g. during hoof care, by automatically observing this eye movement using video technology. The stress level should be determined by suitable classification of the video stream, possibly also one in the infrared range.

https://www.uq.edu.au/news/article/2016/07/eyes-have-it-revealing-secrets-of-cow-emotions

Aufgabenstellung

1. Literaturrecherche zum Thema
2. Analyse vorhandener Software und vorhandener Vorarbeiten
3. Bewertung geeigneter Methoden
4. Implementierung

Voraussetzungen:

• Selbstständige, zielorientierte Arbeitsweise
• Spaß am Programmieren
• Kenntnisse in Python (Jupyter Notebook)
• Grundlagen KI-Methoden

task

1. Literature research on the topic
2. Analysis of existing software and existing preliminary work
3. Evaluation of suitable methods
4. Implementation

Requirements:

• Independent, goal-oriented way of working
• Enjoy programming
• Knowledge of Python (Jupyter Notebook)
• Basics of AI methods

Bitte senden sie Ihre Unterlagen mit aktuellem Notenspiegel an die untenstehenden Kontaktdaten.

Start der Arbeit: ab sofort

Art der Arbeit: Masterarbeit

Arbeitsgebiet: Computer Vision

Addressed topics: computer vision, Artificial Intelligence, Image Processing, Bild/Videoanalyse

Contact: Apply for this job by email

Possible as: Master-Thesis

Addressed topics: Others, Programming, Simulation

Ziel der Arbeit ist, aluminiumbasierte Schichten zur Verwendung während des reaktiven Ionenätzens zu untersuchen. Wegen ihres geringeren Abtrags im Vergleich zu üblicherweise als Maskierung eingesetzten Stoffen wie Fotolack oder Siliziumdioxid werden längere und damit tiefere Ätzungen ermöglicht. Zum Einsatz können z. B. Schichten aus Aluminium, Aluminiumoxid, Aluminiumnitrid oder anderen Aluminiumverbindungen kommen. Die Untersuchungen sollen am Beispiel des tiefen Siliziumätzens (DRIE) erfolgen. Besonderes Augenmerk soll auf die Qualität des Ätzgrunds gerichtet werden. Zum Einstieg in die einschlägige Literatur kann [1-] herangezogen werden.

Aufgabenstellung

1. Literaturrecherche zum Thema
2. Vermessung bzw. Charakterisierung der Maskenschichten vor und nach den Ätzversuchen
3. Durchführung der Messungen am Ellipsometer und Profilometer
4. Untersuchung der Ätztiefen und -profile mit unterschiedlichen Meßmethoden z.B. Oberflächenprofilometrie,
   Fokusdifferenzmethode am Lichtmikroskop
5. Auswertung der Ergebnisse, Vergleich der Maskenmaterialien

[1] A. Bagolini, P. Scauso, S. Sanguinetti, and P. Bellutti, “Silicon Deep Reactive Ion Etching with aluminum hard mask”, Materials Research Express, Bd. 6, H. 8, Art. 085913, Mai 2019.

[2] M.Drost, S. Marschmeyer, M. Fraschke, O. Fursenko, F. Bärwolf, I. Costina, M. K. Mahadevaiah, M. Lisker, “Etch mechanism of an Al2O3 hard mask in the Bosch process”, Micro and Nano Engineering, Bd. 14, Art. 100102, April 2022

[3] M. D. Henry, T. R. Young, and B. Griffin, “ScAlN etch mask for highly selective silicon etching” , Journal of Vacuum Science & Technology B, Bd. 35, H. 5, Art. 052001, Sep. 2017.

Art der Arbeit: Projektarbeit

Contact: Apply for this job by email

Possible as: Student research project

Addressed topics: MEMS, Micro- and Nanoelectronics, Nano technology, Processes / technology