Glass recycling uses mature technology limited by high energy consumption to melt tons of glass and the inflexibility of a heavy-duty system. Current technology only allows the recycling of certain glasses and a very small amount of waste generated. A new technology is required to allow the integral recycling of all types of glass, drastically reducing the carbon footprint. EverGLASS proposes to develop a radically new technology called "glass laser transformation" for on-site glass recycling and the generation of customized or technical products. Users will feed waste into a new machine and select which new product to get. The vision is ambitious, as it aims to bring to the consumer market a novel technology to enable virtually infinite reuse of glass. It is also radical since, through a multipurpose system capable of being located on any site, it proposes an alternative approach to the traditional centralized recycling process (particularly where this model is not possible, generating thousands of tons of glass waste annually taken to landfills). The new technology goes beyond the current limitations of the systems (high energy use, expensive and rigid process, strong logistical requirement), adopting a highly environmentally friendly model that will allow flexibility in the use of the material and in the process. Therefore, EverGLASS has the potential to revolutionize recycling as a concept. It also addresses one of the main problems with recycling, user participation, in an innovative way by allowing the personalization of recycled items of different use. Finally, it aims to encourage the use and reuse of glass as a quality material, displacing more environmentally problematic materials, such as plastics. This project brings together experts from advanced laser technologies (UVIGO), glass and ceramics science (ICV-CSIC), glass processing and engineering (TnUAD), risk and impact assessment (ACTALIA), Social Sciences (ESCI) and numerical simulation (ITWM).

Many industries are transitioning to I4.0 production models by adopting robots in their processes. In parallel, XR technologies have reached sufficient maturity to also enter the domain of industrial applications, with early success cases often related to the training of workers, remote assistance, access to contextual information and interaction with digital twins. This project looks at the intersection of both technologies: robots and XR. The use of robots in industry will be increasingly enhanced with XR applications, and workers must be able to understand both technologies and use hybrid solutions confidently. Achieving this is a challenge that education and training programs must meet. The objective of MASTER is to boost the XR ecosystem for teaching and training of robotics in manufacturing by providing an Open XR platform that integrates key functionalities for creating safe robotic environments, programming flexible robotic applications (programming by demonstration in flexible robotic application development) and integrating advanced interaction mechanisms (innovation in gaze-based interaction). MASTER will also deliver rich training content on robotics. MASTER proposes integrating third party contributions through two Open Calls: The first one aims to provide the platform with additional technologies and functionalities. The selected companies will have the opportunity to integrate their technology in the platform and test it with a wide range of end-users. The second Open Call is aimed at the education sector, by offering the possibility to test first-hand the platform and tools to create their own content.

Microalgae can play a critical role in meeting EU targets to increase the share of Sustainable Aviation Fuels (SAFs) in the aviation industry from 2% in 2025 to 64% by 2050. SusAlgaeFuel will develop integrated approaches in a circular production model towards the first cost-competitive (reduced by 49% from 12.3 to 6.3 $/kg HEFA) and efficient microalgae SAF: a) direct capture of CO2 emissions from biogas upgrading from Anaerobic Digestion (AD) and utilisation of waste liquid digestate as low-cost nutrient source to support algae growth; b) novel in-line process analytical technology complemented with machine learning and selective UV irradiation to monitor and purify bacterial contamination in algae culture; c) cascading biorefinery that relies on energy-saving autolysis and maximises solvent recycling to fractionate biomass into lipids (for jet fuel), protein serum (for feed) and cellulose-rich biomass residue (for further fuel conversion) at low energy & solvent requirements; d) algae-specific thermocatalytic pathways for efficient conversion of algae-lipids to Hydroprocessed Esters Fatty Acids-Synthetic Paraffinic Kerosene (HEFA-SPK) and residue to kerosene followed by a range of purification methods for fuel refinement to meet international aviation standards & certification. Process simulations, techno economic & LCA will be performed to assess scalability from economic, social & environmental perspectives and to identify process improvements. A dedicated commercialisation plan and policy recommendations will be produced to guide future technology transfer from lab to industry. SusAlgaeFuel will culminate in the building & operation of a pilot-scale algal facility on an AD operator site in Ireland (TRL5) with the capacity to directly capture CO2 from AD flue gas, use waste digestate and produce ≥10 kg of algae lipids per year. Successful future scaling of the technology has the potential to deliver 20% of EU’s projected SAF requirements of 5Mt in 2030.

The wastewater sector is going through a profound transformation with energy efficiency and resource recovery as key priorities in wastewater treatment plants (WWTP) and these installations started to be perceived as Water Resource Recovery Facilities (WRRF). Under this context, the exploitation of data through artificial intelligence tools with the objective of accelerating the transition of WWTP to WRRF has not been fully addressed yet. When compared to treatment technologies, the deployment of AI-powered tools in production is much faster and, therefore, provides immediate benefits. In that sense, three main barriers have been identified in this domain: i) Mechanistic mathematical models involve complex formulations and specific terminology that are difficult to understand for plant operators; ii) WRRF are harsh environments with strong impact on the quality of data; iii) Essential information in WRRFs is limited and not continuously available. In particular, to overcome these challenges, DARROW will build and demonstrate into an operational environment, an innovative, optimised, modular, and flexible data-driven AI solution to make existing WWTP more autonomous, more energy efficient and better prepared for their transformation into WRRF. DARROW will take advantage of existing AI & Data analysis techniques with the final objective of contributing to a greener planet by: i) Reducing energy consumption of WRRF; ii) Reducing Greenhouse Gas Emissions of WRRF; iii) Increasing Resource Recovery iv) Improving water quality.To do so, DARROW gathers the necessary experience, knowledge and resources through a multi-stakeholder approach that covers the whole value chain of the project. It consists of a multidisciplinary team of 8 entities from 4 different EU countries (Spain, Belgium, Germany and Netherlands), among which, 3 RTOs, 1 university,1 NPO, and 3 SMEs to ensure market exploitation (2 industrial companies and 1 water company).

The INNOVEAS project is an initiative promoted by 10 partners, from 6 EU countries, to build and deliver a capacity building programme, aiming at addressing the major non-technical barriers that most often hamper the adoption the energy auditing practice, in particular among those actors, such as SMEs where such audits are not required by law. The ultimate goal is to consolidate a structured, permanent and expandable offer to help develop continuous self-sustainable services to raise awareness and build capacity in the field of energy auditing and related energy saving measures in SMEs. The project therefore aims at designing and deploying staff trainings and capacity building programmes to enhance corporate policy towards energy efficiency, energy culture (motivations, behaviour change, mitigation of perceived risks and barriers) and sustainable supply-chain initiatives. It therefore intends to: i) Advanced analysis of behavioural barriers to energy audits, to identify and analyse the enabling conditions and non-technical barriers hindering the adoption of energy auditing practice; ii) Delivery of self-sustainable capacity building programmes, in order to systematise awareness raising procedures to overcome the psychological and organisational barriers to energy audits in SMEs, deliver a training offer to SMEs and formulate a capacity building programme targeting stakeholders such as intermediaries, policy makers and financing institutes; iii) Create an institutional structure to sustain the project’s objectives and results and lay the basis for the creation and consolidation of a pan-European network of enablers likely to support in the coming years the growth and expansion of the training offer to on energy efficiency for European business.