Research Projects

Development of an Innovative CFRP Casing for Reusable Rocket Engines

BMWE ZIM (2025–2027)

Driven by the commercialization of space travel and operations (also known as New Space) and the associated need for more efficient and cost-effective reusable launch vehicles and rocket engines, the RKT-E project aims to meet these requirements through material-specific and process-technology developments. To this end, the RKT-E project aims to develop an innovative CFRP structural shell for a reusable rocket engine. In addition to the associated weight reduction and the optimization of the layup to meet application-specific requirements, the project places particular emphasis on predictive modeling of the properties and the proof-ofconcept regarding the manufacturability of the structure and the associated requirements in an innovative, production-ready winding process. A health monitoring concept is intended to provide support as early as the development phase and offers in-depth insights into the failure criteria and mechanisms of the complex fiber-reinforced composite structure, serving as the basis for a later in-line monitoring system during operation.

EcoPreg – Prepreg System for Sustainable and Circular Fiber-Reinforced Composites in Lightweight Construction

Lightweight construction is a major driver of innovation in many high-tech industries and is considered a key technology not only in Germany. Its application is based on the principle: less material = less weight = fewer emissions, thereby ensuring resource and energy efficiency. Fiber-reinforced plastics, in particular, offer great potential for lightweight construction due to their properties, which can be specifically tailored. Biocomposites are composite materials in which at least one of the components (fiber, matrix) is bio-based or biodegradable. Natural fibers can be compared to glass fibers in terms of their specific properties and are distinguished by their favorable material-energy balance.

EcoPreg aims to establish the infrastructure for the research and development of sustainable and recyclable prepregs. Competitive materials require cost-effective production, reproducible quality, ease of handling, and consistent processability. This is precisely where EcoPreg comes in. As part of the project, a highly flexible research facility is being planned and implemented in collaboration with industry partners to preimpregnate dry fiber semi-finished products with a thermosetting or thermoplastic polymer matrix. This prepreg facility is intended to develop novel fiber-reinforced composites for sustainable and recyclable lightweight construction and to stabilize and increase the efficiency of the manufacturing process.

Collaborative Project: Digitalization for Efficient Process Selection and Design of Hybrid Structures Based on Experimental and Synthetic Data (HybridDigital) – Subproject: Microstructural and Mechanical Characterization of Metal-CFRP Hybrids

Hybrid materials, also known as multimaterial combinations, are increasingly being used today in mechanical engineering, aerospace, and the automotive sector. The material combinations are just as diverse as the joining techniques. In addition to adhesive bonding, mechanical joining is also widely used. The properties of hybrid materials depend heavily on the joining technique and process parameters. Currently, there is no systematic documentation of these properties. The development of new hybrid structures is largely driven by “trial and error.” HybridDigital makes a significant contribution to the digitized and sustainable establishment of hybrid structures for lightweight construction. With the help of a digital twin for hybrids, it will be possible in the future to develop resource-optimized and robust hybrid structures based on customized joining connections.

The research project focuses on the identification, systematization, structuring, modeling, and ultimately formal-language description of process-dependent parameters. Data collection is based on the characterization and description of hybrid structures at the experimental and numerical levels for a selected multimaterial combination (steel-carbon fiber-reinforced plastic composite, or steel-CFRP for short). The necessary knowledge is gathered through systematic specimen fabrication and comparative characterization of behavior under load for two joining techniques (adhesive bonding and bolting), supplemented by acoustic emission analyses. This allows damage in the material to be detected at the micro level and correlated with the failure behavior of the hybrid at the macro level.

This enables the properties of the hybrid materials to be linked to the process parameters and the properties of the respective input materials. The aim is to facilitate both the selection of the appropriate joining technique and the design of the joint, as well as the automated evaluation of failure and damage patterns.

Numerical modeling of the variation in material properties due to material fluctuations and systematic machine errors offers further added value. This allows for better prediction of property variations—and thus failure behavior—which can then be appropriately accounted for in component design. By adjusting safety factors, material usage and component weight can be reduced, thereby making a direct contribution to the conservation of resources and the environment.

The work on the HSAA can be summarized as follows:

Conducting and documenting the surface pretreatment of metallic joining partners
Experimental characterization of quasi-static and cyclic material properties while varying the preparation parameters
Characterization of interfacial phenomena
Processing and provision of data for numerical modeling and ontology creation

Holistic circular engineering for sustainable plastic products

Post-consumer recycled materials (PCR) typically consist of complex multi-plastic composites, such as multilayer films, which are used in large quantities for functional packaging. The volume of waste is growing steadily. Today, due to the lack of viable material recycling options, the majority of heterophasic post-consumer waste is incinerated, emitting CO2 into the environment!

This project demonstrates that, with a holistic engineering approach, material recycling of heterophasic PCR to produce usable, technical products is sustainably feasible. The proposed solution requires interdisciplinary collaboration among various experts in plastics technology and takes into account not only material and processing aspects, recycling-friendly product development, and process simulation, but also the machinery and process engineering requirements for the practical processing of PCR.

The industrial partners in the planned consortium cover all the necessary areas of expertise required to jointly address the outstanding environmental issues. The digital development of demonstrators and their subsequent manufacturing require a holistic plastics engineering approach. The proof of concept for the demonstrators demonstrates the effectiveness of “circular engineering” as a prerequisite for returning PCR to the material cycle and for the manufacture of durable—and thus sustainable—products. The results make it possible to derive new development guidelines for the use of PCR in products and to integrate these into existing product development processes.

Developments in the material recycling of heterophasic PCR will make a significant contribution to the “Green Deal,” as they conserve resources, reduce CO2 emissions, and contribute to material recycling and thus to the implementation of a consistent circular economy.

Sustainable Biocomposites for Lightweight Construction

BioLeit is pursuing the development of new biocomposites for lightweight construction

Whether in safety helmets, brake pads, or as load-bearing structural components in mechanical engineering—thermosets are found in many important components. These plastics, which can no longer be deformed once cured, are characterized by their high strength and stiffness, even at elevated temperatures. When combined with glass, aramid, or carbon fibers, they can be further optimized for lightweight construction applications.

Thermosets used today are still predominantly petroleum-based. This research project focuses on the development of so-called biocomposites for lightweight construction. What makes them unique: From today’s perspective, a material is considered a biocomposite if even just one of its components is bio-based. BioLeit, on the other hand, aims to develop a 100-percent biogenic composite material. This involves the use of bio-based thermosets, with natural fibers serving as the reinforcing material.

The CZS Research Start grant provides the newly appointed professor with the necessary freedom to pursue initial research activities in the field of biocomposites. In doing so, she is working to establish a research group focused on sustainable lightweight construction at Aalen University of Applied Sciences to advance her vision of innovative materials as part of a circular economy.

Development of a method for realistic and cost-effective calculation and design of damping elements for vibration decoupling

The design of damping elements, such as rubber-metal buffers, for vibration isolation is currently based primarily on designers’ many years of experience. A more time- and thus cost-efficient method is design using the finite element method (FEM). However, this requires material data for creating the material model.

The goal of the project is therefore to provide temperature- and frequency-dependent material properties of the rubber component so that the material model used has the highest possible descriptive accuracy.

To this end, a testing methodology and an evaluation strategy are being developed to determine the temperature- and frequency-dependent stiffness and damping properties of technical elastomers for the relevant deformation range. In addition, the material properties will be appropriately implemented in commercial FEM programs, and the calculation results will be evaluated based on real component tests.

Project Leader
Prof. Dr. Iman Taha, Chair of Sustainable Materials in Plastics Engineering

Project Partners
Prof. Dr. Achim Frick, Institute of Polymer Science and Processing (iPSP)

AI-Supported, Viscosity-Adapted Injection Molding Process Optimization to Promote the Circular Economy of Plastics

In the injection molding of so-called post-consumer recycled materials (PCR), significantly greater batch-to-batch variations occur compared to virgin material of the same type, particularly with regard to the polymer’s viscosity (flow resistance), which is critical for processing. The reasons for this include undefined polymer aging states resulting from cascading use, the limited sorting depth of current sorting facilities, and seasonal and local variations in the waste streams from which these polymers are produced. This can lead to process instabilities as early as the regranulation stage and, consequently, during the subsequent injection molding process to produce the molded part. Due to this issue, the widespread use of PCR has so far been limited for many injection-molded products.

The goal of the project is therefore to analyze the effect of the viscosity properties characteristic of PCR on the resulting process parameters (temporal progression of mold cavity pressure) and to use these correlations, summarized in a training dataset, for an AI model. The datasets are generated through the combined use of process simulations and real-world mold internal pressure sensors. The model should then be able to determine the viscosity of the processed PCR with sufficient accuracy based on the identification of existing process parameters. If a change in process parameters occurs as a result of a viscosity fluctuation, the model should propose a quantitative adjustment to relevant machine settings in order to maintain identical process parameters—and thus enable series-production-ready processing of PCR—despite the changed viscosity. Finally, the AI model can be used as the basis for developing an adaptive control system for machine settings to compensate for viscosity fluctuations while maintaining process stability.

Plastic packaging is indispensable for the protection and transport of food and consumer goods. However, recycling it often faces limitations. Multilayer packaging and labels made of different materials, in particular, complicate sorting and recycling. Intelligent, data-driven solutions are needed to make recycling processes more efficient and precise.

The KI-Sort project is developing artificial intelligence (AI)-based methods for the precise identification and sorting of complex plastic waste. By combining image data (RGB) with spectral information from near-infrared and mid-infrared spectroscopy (NIR/MIR), the project aims to reliably detect even multilayer packaging with different label materials.

The goal is to unambiguously identify the primary plastic despite overlapping layers, thereby significantly improving material recovery. This will increase recycling rates and drive important progress toward a resource-efficient, circular plastics economy.

Plastics such as polyethylene terephthalate (PET) have become an integral part of our daily lives—especially in the packaging sector, where they combine shelf life, safety, and resource efficiency. Nevertheless, the production of packaging has so far been based predominantly on fossil raw materials, as recycled material often varies in quality and is difficult to process.

The MobiDig research project aims to make the plastics industry more sustainable through the targeted use of digitalization and data networking. Using PET as an example, the entire life cycle of food packaging—from production through use and recycling to reuse—is examined and digitally mapped. Aalen University of Applied Sciences is responsible for the comprehensive characterization of PET and the correlation of process parameters and material properties across multiple life cycles. The data obtained is incorporated into a semantic data model (ontology), which forms the basis for optimized, AI-supported processing and sorting. The goal is a digital product passport that transparently consolidates material properties, process data, and the carbon footprint. Through this holistic approach, MobiDig makes an important contribution to the digitization of materials research and to the establishment of a circular plastics economy in Germany.

Carl Zeiss Foundation (CZS) Center for Circular Economy and Resource Efficiency through Additive Manufacturing Technologies

The CZS Center KRAFt brings together the expertise of Aalen University of Applied Sciences, Trier University of Applied Sciences at the Birkenfeld Environmental Campus, and the Karlsruhe Institute of Technology in the field of additive manufacturing of plastics and metals within a research consortium. The Universities of Applied Sciences are supported in this effort by 24 industry partners, who contribute technical solutions, equipment, or material supplies to address the respective research questions.

The Institute for Sustainable Polymers and Composites (iSPC) at the CZS Center focuses on the circular economy and resource efficiency in the additive manufacturing of plastics. In this context, the iSPC addresses research questions related to the processing of secondary raw materials of known or unknown origin and the identification of qualification criteria used to define the printability of such secondary raw materials. In addition, the iSPC plays a leading role in advancing the additive manufacturing of natural-fiber-reinforced biocomposites, taking into account not only materials science but also process engineering and design aspects.

More information and the latest developments can be found on the website or on LinkedIn

The CZS Center KRAFt is managed by Trier University of Applied Sciences at the Birkenfeld Environmental Campus.

Project management at the Aalen site is handled by:

• Prof. Dr. Iman Taha, Institute for Sustainable Polymers and Composites (iSPC)

Project partners at Aalen University of Applied Sciences:

• Prof. Dr. Harald Riegel, Laser Application Center (LAZ)
• Prof. Dr. Markus Merkel, Center for Virtual Product Development (ZVP)
• Dr. Timo Bernthaler, Institute for Materials Research (IMFAA)

Reintegration of weathered end-of-life plastics into the circular economy, taking into account microplastic release and greenhouse gas emissions

Using an interdisciplinary approach and with active participation from industry and civil society, RewitAl aims to close material loops and promote recycling in the plastics industry. The focus is on highly weathered plastics—which have been largely neglected to date but are significant in terms of volume—using sports facilities with plastic surfacing systems as an example. The research activities focus on (i) the environmentally sound dismantling of these systems, taking into account the distribution of microplastics in the environment; (ii) the analysis of the optimal suitability of various recycling processes for the different plastic components of the overall system; and (iii) the investigation of possible bioplastic-based alternatives. Of particular relevance is the accompanying and comparative economic and ecological assessment of materials and processes. Along with a transparent description of material properties, possible application scenarios and business models are being developed. Special attention is also given to the transfer of knowledge to the business sector and civil society at various levels and through diverse media, in order to actively support the implementation of the innovation and bioeconomy strategy of the state of Baden-Württemberg.

Increasing the utilization rate of plastic waste through an AI-based combination of manual sorting and micro-automation

Plastics such as PET and PE are produced from petroleum. Due to their excellent properties, they are resistant to many environmental influences and chemicals. However, this makes it difficult for them to degrade naturally. Despite their short service life, packaging represents the largest application area for plastics, resulting in considerable amounts of waste every day. To reduce waste, conserve valuable resources, and ensure their optimal reintegration into the material cycle, recycling will play an even more important role in the future. Material-based recycling of plastics is primarily carried out using mechanical processes. In this process, plastic waste is sorted by type, cleaned, and processed. Above all, the purity of the sorted materials is crucial for achieving a high recycling rate. However, the sorting process today is very labor-intensive and prone to errors. Often, manual sorting or inspection sorting is performed either before or after an automated sorting system.

The goal of the RecycleBot project is to increase the recycling rate of plastic waste by optimizing the sorting process using artificial intelligence. This leads to a higher utilization rate of plastics from packaging and commercial waste. To achieve this, in addition to large automated sorting systems, smaller collaborative robots (RecycleBot) are deployed to take over tasks that were previously performed manually. This work is based on so-called deep learning (DL) algorithms. They improve the entire recycling process by better distinguishing between different types of plastic, thereby not only facilitating sorting but also making it less prone to errors. Furthermore, the focus is on new and critical plastics as well as complex composite packaging.

The RecycleBot can increase the recycling rate of plastic-based packaging and commercial waste from the Dual System. It is also expected that bioplastics—which are bio-based or biodegradable—will be used more frequently in the future. These are already being taken into account in the development of the RecycleBot. The development also prioritizes human-robot collaboration and the concept of “Human Supervisory Control”: waste management employees are involved in the development process to leverage the synergy between AI and human experience. A key focus is on the human-machine interface for AI visualization to enable manageable, self-organizing systems. This ensures that employees are always able to review and monitor the system’s decisions. In this way, the project contributes to a sustainable circular economy.

The plastics industry faces major challenges in meeting the growing demands for sustainability and resource conservation. In particular, the management of post-consumer municipal solid waste is gaining importance in this context, as it represents a valuable source of plastic recyclates. The effective use of this waste offers the opportunity to reduce the consumption of virgin plastics. At the same time, innovative approaches are needed to improve the quality and processability of recycled materials so that they meet the requirements of the plastics processing industry. The use of modern technologies such as artificial intelligence opens up new possibilities here for optimizing existing processes and laying the foundation for a circular plastics economy.

The goal of the project is to use artificial intelligence, combined with material science parameters, to increase the usability of plastic recyclates derived from post-consumer municipal solid waste. This is intended to close loops in the plastics industry and increase recycling rates. In addition to the environmental goal of a more sustainable economy, new legislative changes in the Packaging Act (VerpackG) are also compelling the plastics processing industry to increase its use of recycled materials. However, significant fluctuations in processing properties—even within individual batches—result in unreliable quality of the end products. To counteract this, the project aims to take processing properties into account as early as the sorting stage, thereby enabling more accurate predictions about the future quality and processability of the recycled materials. This will enable plastic-processing SMEs, in particular, to use recycled plastics more reliably without encountering additional problems in the processing stage. In practice, this means that parameters detectable during sorting must be correlated with material properties. In addition to sorting by material type, the project also distinguishes between different quality classes, each described by material science parameters.

AI-Supported Process Optimization for the Recycling of Post-Industrial Waste

The goal of the project is to use artificial intelligence (AI) to enable the recycling of post-industrial waste into new components in such a way that the quality requirements for a new product are met.

The motivation behind this is, on the one hand, to reduce the significant amounts of industrial waste generated by plastics processors—particularly injection molders—in the form of sprues or scrap. On the other hand, the new Commercial Waste Ordinance (GewAbfV) and the new Circular Economy Act (KrWG) have tightened recycling targets: the material recycling rate is to be increased from the current 7% to at least 30%, thereby significantly reducing the amounts of commercial and industrial waste sent to incineration.

Thus, KI-ProWita contributes to the intelligent closure of material cycles in the plastics industry. This leads to the conservation of valuable and scarce resources as well as a reduction in negative environmental impacts caused by thermal recovery. Of great importance to SMEs are the cost savings achieved through the recycling of such industrial waste (with volumes ranging up to several metric tons annually). In practice, this means that, if successful, depending on the quality of the post-industrial waste, either 100% of it or at least a portion of it can be incorporated into a new component. Accordingly, compared to virgin material, the material behavior during the process (e.g., melting temperature, viscosity) changes, and thus the required process parameters. The proportion of recycled material to be used and the process parameters to be set in order to meet the component requirements are determined with the support of AI. Due to the thermal nature of the injection molding process, Long Short-Term Memory (LSTM) networks are used.

In the SmartPro research network at Aalen University of Applied Sciences, over 60 partners from industry, technology transfer, and research are working to increase energy efficiency and conserve resources. In the three application areas of energy converters, energy storage, and lightweight construction—closely integrated with the cross-cutting technologies of additive manufacturing and machine learning—the foundations are being laid for energy-efficient and resource-conserving products. The Federal Ministry of Education and Research has been funding SmartPro since 2017 with approximately 10 million euros.

The exploratory SmartPro project SmartCycle, comprising five subprojects, covers the three application areas of SmartPro and aims to develop recycling strategies and reintegrate waste products and recycled materials into the production cycle of magnets, batteries, and lightweight structures. Thanks to the development of innovative methods for recycling and reusing raw materials, the manufacture of these products will be more sustainable and environmentally friendly.

The RecyLIGHT subproject focuses on returning hybrid materials—which are commonly found in lightweight construction applications—to the cycle through microbial degradation at the interface between the bonded materials. Initially, a suitable interfacial structure for a bond between fiber-reinforced plastic and metal must be systematically developed. Laser-based surface pretreatment is intended, on the one hand, to ensure high-performance bonds during the service life and, on the other hand, to allow microorganisms access to the bio-based matrix at the end of life so that they can break it down in a targeted manner. Various laser structures and aspects of the joint—such as temperature, pressure, and duration—are evaluated in terms of their influence on the degradation rate.

Project Leader
Prof. Dr. Iman Taha, Chair of Sustainable Materials in Plastics Engineering

Project Partners
Prof. Dr. Volker Knoblauch, Institute for Materials Research Aalen

Prof. Dr. Harald Riegel, Laser Application Center