Applications and Multifunctional Materials

We develop tailored, resource-efficient, and print-based solutions for functional applications. Our core expertise lies in applying functional materials to a wide range of substrates for printed electronics, sensors, heating and light-emitting layers, and energy storage devices. We combine classic printing techniques, such as screen printing and pad printing, with modern coating methods, such as blade coating, spraying, and dip coating.

Printed Electronics and Functional Layers

We use nanoscale materials, such as graphene, carbon nanotubes CNTs, silver nanowires, and conductive polymers, to design next-generation electronic components.
 

Typical Applications:

• Transparent, conductive electrodes
• Electrodes for energy storage
• Printed heating layers
• Electroactive polymers (EAPs)
• Printed ionic and dielectric actuators
• Printed systems with microencapsulation
• Light-emitting layers

Our sensor solutions detect temperature, humidity, and UV radiation. They are flexible and stretchable. Our team also focuses on applying capacitive sensors to both flat and uneven surfaces.

Highlights:

• Capacitive sensors on complex geometries
• Integration into wearables, smart textiles, and surfaces 

Digitalization and AI-supported Soft Sensor Technology

We link process data and simulations with AI models to optimize coating processes, enable real-time monitoring, and predict previously unmeasurable parameters.

For improvement and quality control, the process parameters and the characteristics of the manufactured coatings can be monitored with corresponding tight tolerances. To this end, existing data, e.g., from the machine control system and retrofitted sensors, are combined and used in simulations.

AI-driven models allow the creation of soft sensors for various unmeasured parameters.

Key Questions on AI in the Coating Process

What is a soft sensor – and what is it good for?
→ A soft sensor is a digital model that uses measurement and process data to calculate physical variables that are difficult or impossible to measure directly.

How does AI support quality control?
→ Data-driven predictions allow for target values to be precise in real time and with minimal testing effort.

Can soft sensors replace missing data?
→ Yes. They model values such as layer thickness or temperature profiles where physical sensors reach their limits.
 

Material Substitution and Sustainability

• We actively research the substitution of critical, health- or environmentally hazardous substances (e.g., PFAS) in pastes, inks, and processes, with a focus on bio-based alternatives.
   

Our approach

• Analysis and adjustment of formulations
• Process development for green alternatives
• Sustainable end products 
   

Layers and Electrode Characterization 

Electrode characterization is a key tool in our research. It provides in-depth insights into the performance and stability of materials and electrodes long before a product reaches market readiness. We conduct both mechanical and electrochemical testing to ensure optimal performance, stability, and service life.
 

Techniques and Methods

• Adhesion and weathering tests
• Layer thickness and resistance measurements
• Cyclic voltammetry (CV), chronopotentiometry (CP), electrochemical impedance measurement (EIS)
• Long-term tests under real conditions

Characterizing Batteries and Supercapacitors
 

Innovation through Interdisciplinary Research

Our work bridges materials science, digitalization, and future technologies. Using printing techniques, we design smart surfaces that are efficient, scalable, and application-oriented.