Projects funded by the European Commission

SONAR – Better Batteries for Electricity from Renewable Energy Sources

Organic redox flow batteries (RFBs) are a promising approach to store temporary surpluses of renewable energy. The SONAR project aims to digitally capture the entire development process with all relevant aspects to accelerate screening for suitable substances and optimize a battery system's design for specific operating conditions. The project partners are developing tools and workflows to investigate electroactive materials up to entire battery systems. To do this, they are combining simulation methods at different physical scales – from the electronic/quantum mechanical level to visible, macroscopic behavior. Factors such as cost, lifetime, and performance are comprehensively considered to compare competing energy storage technologies.
Project duration: 01/2020 – 12/2023

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VirtualBrainCloud – Personalized Recommendations for Neurodegenerative Diseases

In the VirtualBrainCloud project, Fraunhofer SCAI is working with 16 European partners on a cloud-based IT platform that enables the simulation of communication paths in the brain. The individual simulation of patient brains supports physicians in finding the right diagnosis and therapy for people with neurodegenerative diseases. This is usually difficult because the course and symptoms of diseases such as Alzheimer's are often very different. With this platform, it will be possible to record the state of health of the brain with little effort. Regular routine examinations will enable physicians to detect and treat Alzheimer's disease at an early stage.
Project duration: 12/2018 – 11/2022

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RADAR-AD (Remote Assessment of Disease and Relapse – Alzheimer's Disease)

In the RADAR-AD project, the project partners will develop methods with which the functional loss in the brain of Alzheimer patients can be measured at an early stage - not only in hospitals but also on an outpatient basis. So-called remote measurement tools (RMT) will enable remote assessments and thus improve patient care. The project is funded by the Innovative Medicine Initiative (IMI), a public-private partnership between the European Union and the European Federation of Pharmaceutical Industries and Associations (EFPIA).
Project duration: 01/2019 – 06/2022



New analysis methods improve evaluation of complex engineering data

A further increase in the performance of supercomputers is expected over the next few years. So-called exascale computers will then be able to deliver more accurate simulation results. Fraunhofer SCAI is developing efficient data analysis methods for the much larger amounts of data generated in this way, which will also provide the engineer with detailed insights into the complex technical interrelationships.
Project duration: 12/2018 – 02/2022


PHAGO – a New Approach to Help Patients with Alzheimer's Disease

It was only recently discovered that the innate immunoreceptor genes TREM2 and CD33 / SGLEC3 play a role in Alzheimer's disease. However, the significance of the identified genes and of the cellular mechanism has not been sufficiently investigated. The PHAGO project is designed to close these knowledge gaps and develop new tools and test methods that work on these immune receptors and open the way to the development of drugs that inhibit the course of the disease. This will allow new therapies for Alzheimer's patients. The project is funded by the Innovative Medicine Initiative (IMI), a public-private partnership between the European Union and the Federation of Pharmaceutical Industries in Europe (EFPIA).
Project duration: 11/2016 – 10/2021

Projects funded by the German Federal Ministry of Economic Affairs and Energy (BMWi)


The BonoKeram project is about increasing the flexibility, efficiency and cost-effectiveness of gas turbines for power generation by providing components made of monolithic advanced ceramics.
Project duration: 04/2020 - 03/2023

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Projects funded by the German Federal Ministry of Education and Research (BMBF)

TransHyDE-Sys − System Analysis of Transport Solutions for Green Hydrogen

One approach in the context of the energy transition is to also feed green hydrogen into the existing German network for gas transport. In order to be able to plan, control and analyze such scenarios, existing simulation models must be extended so that they can represent gas mixtures with high hydrogen content. In addition, the coupling to the relevant power grids must be advanced. These are the goals of the TransHyDE-Sys project. This project is part of the BMBF flagship project TransHyDE.
Project duration: 04/2021 - 03/2025

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DIGIPD – Validating DIGItal biomarkers for better personalized treatment of Parkinson’s Disease

The European project DIGIPD, funded with around 1.6 million euros and coordinated by the Fraunhofer Institute for Algorithms and Scientific Computing SCAI, is investigating the extent to which digital techniques (sensors, speech recognition, recognition of facial expressions) can be used to make a more precise and individualized diagnosis and prognosis of Parkinson's disease. The project is funded by the European network for personalized medicine, ERA PerMed, in the "Joint Transnational Call 2020". The German share of DIGIPD is funded by the Federal Ministry of Education and Research (BMBF).
Project duration: 04/2021 until 03/2024

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Computer Aided Manufacturing (CAM) systems enable computer-aided planning of manufacturing processes. CAM software is used to create the control code for Computerized Numerical Control (CNC) machine tools.The CAM2030 project aims to develop a new generation of CAM systems characterized by reduced planning effort, optimized process planning and long-term knowledge acquisition and retention. To this end, the project uses user-centric enrichment of CAM systems with novel digital optimization tools - such as evolutionary algorithms, cloud computing and artificial intelligence.
Project duration: 10/2020 - 09/2023

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MaGriDo – Mathematics for Machine Learning Methods for Gaph-Based Data with Integrated Domain Knowledge

MaGriDo's goal is to (further) develop and analyze deep neural networks (NNs) for industrial problems, which allow existing domain knowledge to be incorporated into the architecture of the networks. Such a hybrid approach can make use of the complementary strengths of "end-to-end" learning approaches and "a-priori models/rules". This approach promises more efficient solutions for many fields of application. For example, the amount of data required is reduced, or the predictions of the ML model are consistent with existing knowledge.

Project duration: 04/2020 – 03/2023

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ViPrIA – Virtual Product Development Using Intelligent Assistance Systems

The goal of the project ViPrIA is the development of intelligent assistance systems based on artificial intelligence and machine learning approaches to support engineers in simulation-based, virtual product development. With the help of intelligent assistance functions, calculation engineers are to be supported in the development process with complex decisions and relieved of routine tasks.
Project duration: 10/2019 – 09/2022

COMMITMENT – Comorbidity Modeling via Integrative Transfer Machine Learning in Mental Illness

The project "COMMITMENT – COMorbidity Modeling via Integrative Transfer machine-learning in MENTal illness" will establish an interdisciplinary research framework for the identification of systems-molecular hallmarks of psychotic and comorbid somatic diseases. The identification of shared and distinct biological profiles and their underlying pathophysiological processes will allow disentangling patient heterogeneity and provide the basis for objective tools for a personalized clinical management of psychotic disorders.
Project duration: 09/2019 – 08/2022

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NanoINHAL – In-vitro test method for airborne nanomaterials for the investigation of toxic potential and uptake after inhalative exposure using innovative organ-on-a-chip technology

The inhalative route is an important path for nanomaterials and other innovative materials in the nano- and microscale range. The lung is therefore an important target organ for acute toxic effects. At the same time, the barrier function of the lung determines the systemic uptake of the materials and the resulting effects on other organs. The aim of this project is to develop an innovative testing system for airborne nanomaterials based on the partners' existing know-how in the field of in vitro testing procedures. The project is funded within the scope of the topic Nano Safety Research: "NanoCare4.0 - Application-safe Material Innovations".
Project duration: 06/2019 - 05/2022

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KI Lernlabor

Entering and further training in artificial intelligence

The "Artificial Intelligence Learning Lab" is being set up at the Fraunhofer Institute Center Schloss Birlinghoven in Sankt Augustin. It supports small and medium-sized enterprises (SMEs) in particular in getting started in artificial intelligence (AI), learning about concrete applications, and qualifying employees.
Project duration: 11/2019 - 04/2022

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Using machine learning for the early detection of anomalies helps to avoid damages

The analysis of sensor data of machines, plants or buildings makes it possible to detect anomalous states early and thus to avoid further damage. For this purpose, the monitoring data is searched for anomalies. By means of machine learning, anomaly detection can already be partially automated.
Project duration: 10/2018 - 09/2021

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ORKA-HPC: OpenMP for Reconfigurable Heterogeneous Architectures

The project "OpenMP for Reconfigurable Heterogeneous Architectures" (ORKA-HPC) aims to support the use of field programmable gate arrays (FPGAs) in heterogeneous HPC architectures. The parallel programming interface for the productive use of the FPGAs will be OpenMP. FPGAs are reconfigurable and allow very efficient implementation of algorithms; but their programming is currently very time-consuming. The developments in ORKA-HPC will significantly reduce the porting effort on FPGAs.
Project duration: 11/2017 - 07/2021


VMAP – Virtual Material Modelling in Manufacturing

The VMAP project aims to gain a common understanding of interoperable definitions for virtual material models in CAE. Using industrial use cases from major material domains and with representative manufacturing processes, new concepts will be created for a universal material exchange interface for virtual engineering workflows.
Project duration: 09/2017 - 10/2020

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Further funded projects


The overall goal of NFDI4Health is to best support the clinical and epidemiological research community in sharing their data with the user community in accordance with privacy regulations and ethical principles, and to create new opportunities for data analysis within the Nationalen Forschungsdateninfrastruktur (NFDI) in the interest of improving population health. NFDI4Health is funded by the Deutschen Forschungsgemeinschaft (DFG) under the Bund-Länder Agreement on the Establishment and Funding of the NFDI of November 26, 2018.
Project duration: 10/2020 - 09/2025


The zet-o-map project aims to develop better tools for the identification of teratogenic compounds. One of the most promising assays is the zebrafish embryo teratogenicity assay (ZETA). In human risk assessment the evaluation of developmental toxicity or teratogenicity requires the testing of rodents (preferably rats) and non-rodents (preferably rabbits) as described in the OECD 414 guideline. Currently human safety assessment is undergoing a paradigm shift moving towards mechanistic risk assessment and there is a high demand to replace, reduce or refine animal tests where possible for ethical and economic reasons. zet-o-map is funded by the Long Range Research Initiative (LRI) of the European Chemical Industry Council (CEFIC).
Project duration: 03/2021 - 02/2023

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The big vision of Industry 4.0 is the automatic adaptation of production processes to rapidly changing requirements. The new Fraunhofer Leitprojekt EVOLOPRO wants to come a step closer to this vision. The project is part of the Fraunhofer initiative "Biological Transformation". Starting in 2019, seven institutes will jointly investigate how developmental and evolutionary biological principles can be transferred to man-made production processes. Transfer and multi-task learning play an important role here - as well as the concept of so-called "digital twins". Biology is the great role model for the work in EVOLPRO and provides important impulses for the further development of procedures.
Project duration: 01/2019 - 12/2022

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ManuBrain – universal, scalable AI-platform for industrial applications

In the »ManuBrain« project, a universal, scalable, and open platform for artificial intelligence applications in medium-sized industrial companies is being developed. The state of North Rhine-Westphalia and the European Fund for Regional Development are supporting the project over three years with a total of 1.8 million euros. Fraunhofer SCAI develops and evaluates machine learning methods for engineering applications.
Project duration: 01/2020 - 12/2022

digitalTPC – digital twins for thermoplast lightweight construction

The potential of digital twins is still largely untapped for cross-value-added chain and material-triggered process control. The digitalTPC project is intended to demonstrate this potential by means of the hybrid injection moulding technology, which is capable of large series production. digitalTPC aims at the comprehensive and holistic consideration of all sub-process steps from semi-finished product to component production. Relevant material, process and component characteristics are to be measured, recorded and virtually modelled and analyzed in a digital twin in local resolution across the entire real value chain. The challenge of the project is the material- and process-related intelligent acquisition of sensor data and their linkage with the integrated simulation chain within the framework of the digital twin by SCAI. The project is funded by Fraunhofer's internal PREPARE program.
Project duration: 02/2019 - 01/2022

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Material models and determination of characteristic values for the industrial application of forming and crash simulation taking into account the thermal treatments during coating in the process for high-strength materials. The project is funded by the Arbeitsgemeinschaft industrieller Forschungsvereinigungen (AiF) - Forschungsvereinigung Automobiltechnik e.V. (FAT).
Project duration: 01/2018 - 12/2021

COPERIMOplus – COronavirus PErsonalized RIsk MOdels

The Fraunhofer institutes cooperating in COPERIMOplus want to use rational, data-driven modeling to enable individual risk assessments in order to improve the prognosis of disease progression and to optimize personalized therapies and their evaluation based on objective, standardized criteria. Thus, the project contributes to making it possible to live with the pandemic and return to economic and social normality. The project is funded in the Fraunhofer Anti-Corona program.
Project duration: 10/2020 - 12/2021

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Human Brain Pharmacome – Prediction and Experimental Validation of Agents for the Prevention of Dementia

The aim of this project is to combine intelligent methods of information extraction, mechanistic modeling of diseases and prediction of active substances with biological drug screening in such a way that possible candidate molecules for the prevention of Alzheimer's disease can be identified very quickly. For this purpose, an integrative approach (a workflow) will be developed and implemented in a prediction engine that uses the systematic acquisition and modeling of drug-target relationships for the prediction of pharmacological effects in the human brain. The project focuses on active substances that are already approved for the treatment of other diseases. This drug repurposing significantly reduces the time and cost required for the clinical development of new, preventive therapies. The project is funded by Fraunhofer's internal PREPARE program.
Project duration: 02/2018 - 06/2021

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