Fraunhofer-Publica

The Fraunhofer-Publica has been successfully documenting the research results of the Fraunhofer-Gesellschaft for over 30 years. The platform enables the collaborative linking of research-relevant objects and disseminates within the international scientific community.

The Fraunhofer-Publica thus fulfils its responsibility to promote the transfer of knowledge and know-how to industry and society.

Research outputs

As an application-oriented research organisation, Fraunhofer aims to conduct highly innovative and solution-oriented research - for the benefit of society and to strengthen the German and European economy.

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Projects

Fraunhofer is tackling the current challenges facing industry head on. By pooling their expertise and involving industrial partners at an early stage, the Fraunhofer Institutes involved in the projects aim to turn original scientific ideas into marketable products as quickly as possible.

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Researchers

Scientific achievement and practical relevance are not opposites - at Fraunhofer they are mutually dependent. Thanks to the close organisational links between Fraunhofer Institutes and universities, science at Fraunhofer is conducted at an internationally first-class level.

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Institutes

The Fraunhofer-Gesellschaft is the leading organisation for applied research in Europe. Institutes and research facilities work under its umbrella at various locations throughout Germany.

Recent Additions

Hochleistungsfähige Tapes aus recycelten Carbonfasern für den Leichtbau - CO2-Reduktion durch hochwertige Recyclingprozesse und Materialien

( 2024-04-23)
Stienemann, Jan
;
Fliescher, Stefan
;
Ellermann, Nils
;
Guth, Johannes
;
Giesgen, Lazlo
;
Weitmeier, Felix
;
Preinfalck, Miriam
;
Theiss, Julian
;
Haj Ahmad, Perwan
;
Angerer, Kerstin

Der Einsatz carbonfaserverstärkter Kunststoffe (CFK) zur Substitution metallischer Werkstoffe hat eine nicht mehr wegzudenkende Rolle im Leichtbau eingenommen. Die Herstellung von Primär-Carbonfasern basiert jedoch zumeist auf fossilen Rohstoffen und geht mit einem massiven CO2-Fußabdruck einher. Ziel des Projekts Infinity war daher die Entwicklung und Etablierung eines nachhaltigen Prozesskreislaufs für CFK zur maßgeblichen Treibhausgasreduktion im Leichtbau. Dies wurde erreicht durch die Implementierung eines effizienten und faserschonenden Recycling- und Weiterverarbeitungsprozesses für Carbonfasern (CF), der diese hochwertige Ressource wieder zu einem Halbzeug für leistungsfähige Strukturanwendungen umwandelt und somit die Substitution von CF-Primärmaterials durch Recyclingmaterial ermöglicht. Die Qualität des Tapes konnte dabei mit Hilfe eines neuartigen Prüfgerätes, welches im Projektrahmen entwickelt wurde, im Vergleich zu Neumaterial evaluiert und verbessert werden. Anhand eines thermoplastischen Strukturbauteils wurde der faserschonende Recyclingprozess dargestellt und das CO2-Einsparpotential der entwickelten Prozesskette in einer Ökobilanz aufgezeigt. Zudem wurden die Potentiale der Direktverarbeitung von sekundärer CF untersucht und darüber hinaus die Anwendung des physikalischen Schäumens in der Direktverarbeitung umgesetzt. Das Projekt zeigt somit den Weg auf für eine echte Substitution von Neufaser-CFK durch Recyclingmaterial, statt des Downcyclings zu teilorientierten Strukturen samt den miteinhergehenden Festigkeitsverlusten.
Investigating Graph Representation Learning Methods for Link Prediction in Knowledge Graphs

( 2023-11-03)
Ali, Mehdi
;
Lehmann, Jens
;
Wrobel, Stefan

Knowledge graphs (KGs) have become a fundamental approach to represent structured data and are employed in academic and industrial applications. KGs are used in various machine learning applications, such as question answering, dialogue systems, and recommendation systems. Although realworld KGs contain up to billions of links, they are usually still incomplete, which can severely impact downstream applications. Link prediction in KGs is the task of predicting missing links and can be performed in a transductive or inductive setting. In the past, a wide range of link prediction approaches have been proposed, encompassing rule-based and machine learning-based approaches. One promising line of research has been link prediction based on graph representation learning methods. In particular, a large number of knowledge graph embedding models (KGEMs) have been proposed and recently, also graph neural network (GNN) based approaches are used for link prediction within KGs. Despite the intensive research efforts in KGEMs, their capabilities are often not transparent. It has been shown that baseline models can obtain competitive results to the stateof-the-art models when configured appropriately, indicating that the performance of a KGEM may not merely depend on its model architecture, but on the interplay of various components. Link prediction within KGs has been investigated mainly within the transductive setting, prohibiting inference over unseen entities. However, lately, inductive link prediction approaches have obtained increased attention since they are capable of predicting links involving unseen entities. In this thesis, we propose an extensive ecosystem for investigating the performance of KGEM-based link prediction. We used the developed ecosystem to first perform a reproducibility study in which we investigated the reproducibility crisis of KGEM-based link prediction experiments. Second, we performed the most extensive KGEM-based link prediction study in which we investigated whether incremental performance improvements reported for KGEMs can solely be attributed to the model architectures or the combination of the KGEM’s components. After providing an in-depth analysis of transductive link prediction within triple-based KGs, we focus on inductive link prediction within hyper-relational KGs. We bridge the concepts of inductive link prediction and hyper-relational KGs and demonstrate that hyper-relational information improves semi- and fully-inductive link prediction. Finally, we demonstrate the effectiveness of knowledge graph representation learning for addressing biomedical applications.
Bio-based epoxy and unsaturated polyester resins: Research and market overview

( 2024)
Baron, Christian
;
Donadio, Federica
;
Scherdel, Michael
;
Iman Taha

The presented study provides an overview of the current research achievements and the emerging market of bio-based thermosetting polymers. Environmental attributes related to bio-based polymers trigger a steadily growing interest in this novel and promising field. Due to their importance among thermosets in terms of composite applications and quantity, this review focusses on epoxy and unsaturated polyester resins. Current studies are mainly concerned with alternative renewable raw materials to substitute fossil content and their synthesis to improve their end-properties. A common target is the increase of bio-based content within the cured resin. In spite of today’s efforts in research, the recent market review reveals only few commercially available bio-based thermosetting resin systems. However, they are commonly suited for a broad variety of processing methods and applications with bio-contents up to 75%.
How Environmental Policy Stringency, Foreign Direct Investment, and Eco-Innovation Supplement the Energy Transition: New Evidence from NICs

( 2024)
Azam, Anam

Several researchers have studied the environmental policy stringency and ecological innovation regarding CO2 emissions and renewable energy consumption; however, the impact of environmental policy stringency, technological innovation, FDI, and ecological innovation on energy transition has not been studied in the case of NICs. For this purpose, panel quantile regression models are applied in the context of NICs from 2000 to 2021. Our empirical results show that the effect of foreign direct investment is positive and statistically significant on energy transition. On the other hand the variables environmental policy stringency, eco-innovation, and ICT-trade have an inverse effect on energy transition. Therefore, the findings of the study also provide policy implications that indicate NICs need to optimize their trade structure and re-innovate the latest innovation spillovers, and strict environmental policies should be introduced to facilitate energy transition in NICs.

Most viewed

Laser pulse energy conversion on sequence-specifically bound metal nanoparticles and its application for DNA manipulation

( 2005)
Garwe, F.
;
Czaki, A.
;
Maubach, G.
;
Steinbrück, A.
;
Weise, A.
;
König, K.
International Solid-State Circuits Conference 1994
Measurement of Local Recombination Activity in High Diffusion Length Semiconductors

( 2023)
Heinz, Friedemann
;
Oezkent, Maximilian
;
Rittmann, Clara
;
Schindler, Florian
;
Schubert, Martin
;
Kwapil, Wolfram
;
Glunz, Stefan

We present a conceptual approach for the localisation and characterisation of local sites of recombination in high diffusion length semiconductors under photovoltaic field conditions. While established imaging techniques operate in this very regime of uniform "1 sun" illumination, inevitable lateral diffusion of charge carriers veils the origin and severity of localised recombination sites. To reduce this limitation due to lateral diffusion the natural choice is using focussed charge carrier excitation and detection in combination with scanning the specimen. The resulting photoluminescence intensity maps are of high spatial resolution and may be composed of a superposition of a multitude of recombination active defects influencing each other due to the high bulk diffusion length. We demonstrate the feasibility of a self-consistent calibration of the setup quantum efficiency in such experimental condition which delivers a charge carrier density map in absolute units. A solution is presented to disentangle the superposition of local sites of recombination to isolate the actual recombination activity of every site. We demonstrate the feasibility of the approach experimentally on the high diffusion length semiconductor silicon.
27th International Symposium on Ballistics 2013. Proceedings. Vol.1: Interior Ballistics, Exterior Ballistics, Launch Dynamics, Vulnerability & Survivability, Explosion Mechanics

(DEStech Publications, 2013)