Research Center for Sensor Materials and Sensor Systems “MatBeyoNDT“

Over two thirds of all technical innovations are directly or indirectly attributable to new materials. Materials science therefore plays a key role in meeting the increasing demands and functions of commercially available products in industry due to the ever-increasing requirements for the materials to be used.

In many industrial sectors and in the production of consumer goods, there is an increasing move away from non-specific applications towards individual solutions adapted to specific applications. This development has a direct impact on the type and complexity of materials and, accordingly, on the material development process. In addition to the standard material properties, many other options are already available at laboratory level to influence material behavior. As the complexity of materials increases, so do the requirements for characterization methods to describe them and enable their industrial use.


Fraunhofer IZFP Research Center “MatBeyoNDT“

At Fraunhofer IZFP, the known non-destructive testing methods are being prepared for the changes in the industrial process environment. On the one hand, this is done by taking a holistic view of the life cycle of a product and the role that non-destructive methods play in it. All data, processes and conditions relating to the product under consideration are understood and used as information carriers. Furthermore, this approach places completely new demands on data processing and on understanding the interaction mechanisms of non-destructive testing methods with the product and its environment.

In order to be able to map the complexity of material innovations, the methods for their characterization must also be further developed. In order to understand the materials, not just a single test method can be used, but a combination of several, which, together with advanced computer-based methods for data processing, provide information about complex materials or lead to the development of new sensor materials.

MatBeyoNDT accompanies the development of future material innovations from initial laboratory tests to large-scale industrial quality assurance. In this way, the requirements for testing methods are determined and further developed so that they can be marketed as industrially suitable testing systems. This helps to ensure that more complex materials such as programmable materials can be increasingly used in industry.

While the MatBeyoNDT group is very broadly positioned and aims to develop a variety of interesting projects in the field of materials with 3D architecture, two global topics will particularly shape the group in the coming years: Additive manufacturing processes will dominate the way 3D-structured materials are produced and digitalization in materials science will determine how data describing materials and processes are handled in the future.


Fraunhofer research grant “Attract“ - From the idea to innovation

The MatBeyoNDT research group is funded by the Fraunhofer-Gesellschaft as part of the Fraunhofer research grant “Attract“. It offers outstanding external scientists the opportunity to advance their ideas towards application within an optimally equipped Fraunhofer Institute close to the market. The scientist has a maximum budget of 2.5 million euros over 5 years to set up and lead a group. The aim is to consolidate the respective research topic on the basis of personal expertise beyond the funding period and thus contribute to the future strategy of the respective institute.


Coded ultrasound methods and applications

Optimization of existing NDT processes in terms of speed, interference immunity and accuracy using coded ultrasound


Characterization under multimodal stress

Development of non-destructive in-situ characterization methods to predict the state of damage


Data methods for new sensor systems

Creating added value in conventional sensor technology by means of intelligent data processing


Powder characterization for AM components

To improve the quality and reduce the post-treatment of additively manufactured components and to increase the cost-effectiveness of the manufacturing process


Programmable materials and metamaterials


Dr.-Ing. Sarah Fischer

Head of research center “MatBeyoNDT“


Michael Becker

Chief engineer

Michael Ganster

Research associate


Simon Herter

Doctoral candidate

Bashar Ibrahim

Project engineer

Lea Sophie Kollmannsperger

Doctoral candidate

Rebecca Kose

Doctoral candidate

Marius Schäfer

Doctoral candidate

Katharina Bollmann

Student assistant

Alina Ehre

Student assistant

Kshema George

Student assistant

Chinmay Joshi

Student assistant

Rachita Prasad

Student assistant

Monseej Purkayastha

Student assistant

Katrin Pusse

Student assistant

Aparnaa Santosh Bindu

Student assistant

Coming soon!

Here you will find publications of the "MatBeyoNDT" group dating back to 2020.

Publication Type
2023 Influence of the Dross Formation of the Laser-Cut Edge on the Fatigue Strength of AISI 304
Bach, Julia; Zeuner, André; Wanski, Thomas; Fischer, Sarah; Herwig, Patrick; Zimmermann, Martina
Journal Article
2023 Soft Tactile Coil-Based Sensor for Misalignment Detection of Adhesive Fibrillary Gripping Systems
Herter, Simon; Stopp, Philipp; Fischer, Sarah
Journal Article
2023 Characterization of Filigree Additively Manufactured NiTi Structures Using Micro Tomography and Micromechanical Testing for Metamaterial Material Models
Straub, Thomas; Fell, Jonas; Zabler, Simon; Gustmann, Tobias; Korn, Hannes; Fischer, Sarah
Journal Article
2023 Design framework for programmable mechanical metamaterial with unconventional damping properties under dynamic loading conditions
Kaal, William; Becker, Michael; Specht, Marius; Fischer, Sarah
Journal Article
2023 Ultraschallbasierte in situ Vorspannkraftermittlung an Schrauben ohne Referenzmessung im nicht verspannten Zustand durch Kombination von Longitudinal- und Transversalwellen
Niwinski, Thomas Jerzy; Kraemer, Frank; Klein, Marcus; Oechsner, Matthias; Herter, Simon; Becker, Michael
Journal Article
2023 Evaluation of the bi Wave Method for Ultrasound Preload Determination in the Field with Machine Learning
Herter, Simon; Becker, Michael; Fischer, Sarah
Conference Paper
2023 Influence of a Pronounced Pre-Deformation on the Attachment of Melt Droplets and the Fatigue Behavior of Laser-Cut AISI 304
Zeuner, André; Wanski, Thoma; Schettler, Sebastian; Fell, Jonas; Wetzig, Andreas; Kühne, Robert; Fischer, Sarah; Zimmermann, Martina
Journal Article
2022 Design and Manufacturing of a Metal-Based Mechanical Metamaterial with Tunable Damping Properties
Kappe, Konstantin; Wahl, Jan P.; Gutmann, Florian; Boyadzhieva, Silviya; Hoschke, Klaus; Fischer, Sarah
Journal Article
2022 Vorspannkraft-Monitoring mittels Ultraschallmethoden ohne Referenzmessung
Herter, Simon; Niwinski, Thomas; Klein, Marcus; Oechsner, Matthias; Becker, Michael
Journal Article
2022 Optimization of Eddy Current Sensor for Proximity and Deformation Detection
Ibrahim, Bashar
Master Thesis
2021 Machine Learning Based Preprocessing to Ensure Validity of Cross-Correlated Ultrasound Signals for Time-of-Flight Measurements
Herter, Simon; Youssef, Sargon; Becker, Michael M.; Fischer, Sarah C.L.
Journal Article
2021 Optimization of the Unambiguity of Cross-Correlated Ultrasonic Signals through Coded Excitation Sequences for Robust Time-of-Flight Measurements
Schäfer, Marius; Theado, Hendrik; Becker, Michael M.; Fischer, Sarah C.L.
Journal Article
2020 Nondestructive Characterization of Residual Stresses Using Micromagnetic and Ultrasonic Techniques
Rabung, Madalina; Amiri, Meisam; Becker, Michael M.; Kopp, Melanie; Tschuncky, Ralf; Veile, Ines; Weber, Fabian; Weikert-Müller, Miriam; Szielasko, Klaus
Aufsatz in Buch
Book Article
2020 Mechanical metamaterials on the way from laboratory scale to industrial applications: Challenges for characterization and scalability
Fischer, Sarah C.L.; Hillen, Leonie; Eberl, Chris
Journal Article
2020 Steigerung der Zuverlässigkeit der Laufzeitmessung mittels Machine Learning Algorithmen zur ultraschallbasierten Vorspannkraftbestimmung
Herter, Simon
Master Thesis
2020 Rückführbare Überprüfung von Ultraschall-Eigenspannungsprüfsystemen für klotzgebremste Eisenbahnräder am Beispiel des neuen UER-mobil Prüfsystems
Becker, Michael; Schuchhardt, Jörg
Conference Paper
Diese Liste ist ein Auszug aus der Publikationsplattform Fraunhofer-Publica

This list has been generated from the publication platform Fraunhofer-Publica

Current research projects



AI-based object recognition and adaptive control for intelligent, bio-inspired robotic gripping systems for embedding in Industry 4.0 environments



Reliability of non-destructive test methods for determining the longitudinal rail tension in the track under changing seasons and variable test environments



Development of an interactive sensor system for recording animal activity for intelligent, group-specific optimization of the barn environment in pig fattening

Fraunhofer Cluster of Excellence Programmable Materials CPM

Materials or material composites whose structure is designed in such a way that their properties can be specifically controlled and reversibly changed.

Expired research projects



Increasing the economic efficiency of aquaculture systems using machine learning


Silviya Boyadzhieva

Cedric Mathieu