MetaMagIC offers a low cost and highly effective way to address current technological concerns regarding the efficiency and sustainability of magnetic devices in Information and Communication Technologies. Driven by an increasing need to achieve the precise control of magnetic fields on progressively smaller length scales – down to the nanoscale - improving the current performance of magnetic devices by the homogeneous concentration of magnetic fields in small and targeted volumes can drastically enhance the device energy efficiency. In this project, we will address the two key challenges of device efficiency and sustainability simultaneously. Our project introduces a novel and ground-breaking approach targeting the conception, design, development, and implementation of magnetic metasurfaces for controlling lowfrequency magnetic fields at the meso/microscale. Combining cutting-edge theory and modelling with state-of-the-art techniques for fabricating and characterizing magnetic thin-film devices, we will address important technological challenges: enhancing the sensitivity of magnetic sensors by incorporating them in specially designed planar metamaterials; reducing the negative effects of demagnetizing fields that limit device performance by using metasurfaces, exploiting the non-linear properties of magnetic materials to introduce novel functionalities into magnetic devices such as self-protection of sensitive equipment to damaging high magnetic fields; exploiting the developed metasurfaces to improve the efficiency of small-scale energy harvesting materials with the goal of generating enough energy to operate low-power electronic devices, combining the field expulsion and concentration properties of metasurfaces to optimize a source and receiver pair for high efficiency wireless energy transfer.

A key issue hindering discoverability, attribution and reusability of open research software is that its existence often remains hidden within the manuscript of research papers. For these resources to become first-class bibliographic records, they first need to be identified and subsequently registered with persistent identifiers (PIDs) to be made FAIR (Findable, Accessible, Interoperable and Reusable). To this day, much open research software fails to meet FAIR principles and software resources are mostly not explicitly linked from the manuscripts that introduced them or used them. This project will extend the capabilities of critical and widely used open scholarly infrastructures (CORE, Software Heritage, HAL) and tools (GROBID) operated by the consortium partners, delivering and deploying an effective solution for the management of the research software assets lifecycle, including: 1) ML-assisted identification of software assets from within the manuscripts of scholarly papers, 2) validation of the identified assets by authors, 3) registration of software assets with PIDs and their archival. The solution will be optimised for deployment over open content available through the global network of open repositories aggregated by CORE (core.ac.uk), which constitutes with over 32 million full texts and 250m+ metadata records from over 10k repositories currently the world's largest collection of open access documents. Our ML software for extraction and disambiguation of software assets will be realised as an extension of the state-of-the-art GROBID tool. We will build on established protocols, such as OpenAIRE Guidelines v4.0, RIOXX v3 and Codemeta, to encode information about software assets and their links to research manuscripts establishing an interoperable and extensible workflow connecting open repositories (represented by HAL), aggregators (represented by CORE) and software archives (represented by Software Heritage). The efficacy of the developed tools and workflow will be validated in three use cases: 1) social science with links to DARIAH, 2) life sciences demonstrator (Europe PubMed) and 3) a multi-disciplinary demonstrator (HAL).