SUM4Re proposes a comprehensive approach to creating materials banks from the built environment by combining urban mining and technologies for automated on-site data acquisition and building materials identification and asset components. The project aims to achieve nine objectives, including developing a traceability system for building materials, developing a holistic methodological framework for assessing circular use of construction products, and developing on-site and off-site smart digital solutions to identify construction entities and analyse their properties. The methodology of SUM4Re is based on a systemic approach that encompasses three main activities: identification, analysis, and contribution to circularity. The project aims to develop software tools and databases based on robust identification assisted by AI and other digital techniques, supported by blockchain solutions, and consider circular economy processes such as Reduce, Reuse, Repair, Recycle, and Renovate. SUM4Re will improve the BIM standard to support current circular (C-BIM) challenges, following open standards and ensuring interoperability with commercial databases. SUM4Re proposes three demonstration pilots linked to construction projects to validate the methodology and a strategy for skill development to upskill the workforce in the construction sector and facilitate the uptake of the solutions developed. Overall, SUM4Re aims to support the transition towards circular construction practices and reduce the amount of construction and demolition waste sent to landfills. The relevance of the project lies in the need to address the increasing generation of construction and demolition waste, which is the largest waste stream in the EU, as well as the problems associated with CO2 emissions and climate change. The project emphasizes the use of new techniques and technologies to rapidly identify materials and support circular construction practices.

Everyday our customs workers need to tackle counterfeit goods and piracy to protect the health and safety of our citizens, yet it is estimated that only a small fraction of cargo is inspected and even smaller fraction of illegal goods are detected. Today, the most widely used technology for scanning vehicles, ranging from vans and trucks to railcars, is gamma-ray and X-ray radiography. But new technologies are required for overcoming current technological shortcomings like inability to detect the materials, usage of radioactive and harmful source, low throughput to name some. Cosmic-ray tomography (CRT) is considered as beyond the state-of-the-art technology in cargo screening. Cosmic-ray muons are highly penetrating, their average energy is about 10,000 times the energy of a typical X-ray and they are practically non-absorbable. They are suitable to identify materials hidden inside of shielded material, too thick or deep for other imaging methods. The CRT is completely passive, exploiting naturally occurring secondary cosmic radiation. Contrary to conventional X-ray or gamma-based imaging techniques it allows to distinguish between different materials and localizes it inside the cargo or vehicle by providing visualised 3D image. We will bridge the major security gap for fast and safe inspection of large number of cargos by developing the Multi-Functional Passive Detection System. The detection capability is based on using high accuracy sensors for particle tracking in combination with beyond state-of-the art tomographic reconstruction and material classification algorithms. The main objective of SilentBorder is to develop and validate a new high-technology CRT scanner for border guard, customs and LEAs that enables safe and fast screening, detection and identification of hazardous and illegal goods (e.g. SNM), contraband (e.g. tobacco or explosive) as well as hidden persons in up to 20’ iso containers.

New technologies of compact accelerators, in particular plasma accelerators, and laser-based x-ray sources, are on the verge of reaching maturity in this decade, making today the perfect time to steer them towards a broader scope of applications in academia, medicine and the industry. Training the next generation of entrepreneur-minded early-stage researchers on such a disruptive technology will enable them to start successful careers with significant societal impact. This is the goal we pursue with the Marie Skłodowska Curie Action Doctoral Network EPACE (European compact accelerators, their applications, and entrepreneurship). EPACE fosters a culture of excellence, innovation and critical thinking to help the next generation explore opportunities and guide it towards significant contributions in line with the EU missions. Emphasis is put on applications in industry (muon tomography), medicine (FLASH effect with particle beams from plasma accelerators), and impactful progress (reduced energy consumption of particle accelerators). An extensive curriculum from a world-class European business school will help the students identify and transfer the most promising innovations into commercial products. Coordinated by DESY, EPACE gathers 31 industrial and academic partners in Europe, to provide 15 PhD students with great scientific expertise, a thorough awareness of EU values and a drive towards entrepreneurship.

The number of goods and parcels shipped is growing with unstoppable speed. With more individual shipments the means of logistics have changed from central locations to small logistics companies, postal agencies, airports, ports, private vehicles etc. However, the analysis and detection capabilities of such locations are very low, making it an easy target for transporting illicit goods. Currently, there are no effective technologies available that would be able to cope with this growing problem. Despite the widespread use of X-ray technologies, they are still inefficient when it comes to mobile scenarios. In addition, their detection capability is based solely on visual imaging with no way to examine the exact material content of small shipments. We are proposing a completely novel, yet highly effective solution for this. The CosmoPort project will develop the next generation of scanner systems using Atmospheric Ray Tomography (ART). Such systems are equipped with advanced Machine Learning-based risk assessment tool. As muon tomography itself is a technique already in use, then we will develop the first mobile solution combined with AI/ML tools to enhance material and object classification for the first time ever.