The projected use of GaAs and CIGS solar panel will lead to 137 tonnes deficit of Ga in 2020. As the Ga can only be economically mined as a by-product of bauxite mining which is not going to increase dramatically in near future, the only way to meet the projected EU requirement is by the recovery of Ga from scraps (LED waste) or GaAs fabrication industry wastewater. However, there is so far no commercially viable technology available. The objective of this project is to develop a commercially viable green technology for the recovery of Ga from GaAs fabrication industry wastewater. This proposal exploits the high affinity of siderophores towards Ga(III) to selectively recover Ga from GaAs fabrication industry wastewater. The biggest challenge in developing siderophores based Ga recovery technology is achieving efficient solid-liquid separation and easy scalability. This study proposes to anchor, entrap and immobilize selected siderophores on solid surfaces, gels and cellulose filter, respectively, thus easing solid-liquid separation and scalability. Batch adsorption and desorption experiments will be carried out to optimize the experimental conditions for the recovery of Ga from the GaAs fabrication industry wastewater. The interaction of Ga(III) and siderophores will be studied at molecular level. This understanding will help us to apply the developed technology to different critical metals as well and develop siderophores based bioleaching process and biosensors. The next phase of the project would involve semi-continuous and continuous experiments to scale-up the best possible configuration selected during the batch study. Finally, economic modeling will be carried out to support the commercialization of the developed technology. This proposal will train the experienced researcher in developing green technology and soft skills, make host the forte of innovative biotechnology and increase the competitiveness of EU at global scale in critical raw metals.

Matter at extreme densities and temperatures is ubiquitous in nature and occurs, e.g., in planetary interiors. In addition, such warm dense matter (WDM) conditions are of high importance to technological applications such as nuclear fusion. Therefore, there has been a remarkable investment in the experimental realization of WDM in large research facilities around the globe, leading to a number of spectacular discoveries. Yet, the absence of a reliable theoretical description of WDM is severely hampering this progress. This is best illustrated by considering hydrogen, the most simple and abundant element in the universe. Even here, a multitude of pressing questions continues to be unanswered: What is the nature of the insulator-to-metal phase transition of hydrogen at high pressure? How do electronic properties of hydrogen impact the evolution of giant planets and brown dwarfs? And how can a hydrogen pellet best be compressed to efficiently produce electrical power in a fusion reactor? The central obstacle on the path towards answers to these questions is the fermion sign problem, one of the most fundamental computational bottlenecks in physics, chemistry, and related disciplines. Recently, a number of methodological breakthroughs has allowed me to present the first accurate data for the electronic properties of WDM over substantial parts of the relevant parameter space. This was achieved using supercomputers and the data-driven construction of AI surrogate models. In PREXTREME, I propose to explore a hitherto unattempted complete solution to the sign problem, which will allow me to answer many questions about warm dense hydrogen and heavier elements with a direct impact on applications in material science, astrophysical models, and nuclear fusion. Moreover, my envisioned approach will revolutionize quantum many-body theory, with important implications for a gamut of fields including high-temperature superconductivity, high-pressure-physics and ultracold atoms.

The recycling rates of critical metals like In, and Ga are very less and it is high time to improve their recovery from secondary sources in an environmentally friendly way. However, the low concentration of target metals and presence of other metals in the industrial wastewater makes the recovery challenging. BioFlot aims to explore the use of amphiphilic siderophores (marinobactins) from Marinobacter sp. as highly specific extractants for recovery of CRMs (In, and Ga) from secondary sources (industrial wastewater) by means of bio-flotation technique. Marinobactins are composed of amphiphilic and hydroxamate functional groups which makes them an ideal candidate for bioflotation. The marinobactin-CRM interactions will be studied at molecular levels which will shed the light on their unexplored capacities and form the basis for the development of recovery process. The project proposes to employ the marinobactins as green flotation extractants in bioflotation technique for metal recovery and subsequent extraction and optimization of process parameters for maximum selective binding of metals and marinobactins so as to increase the flotation yield. And further optimization for separation of marinobactin from metals in flotation product to regenerate marinobactin and recover target metal. The next phase of the project would involve semi-continuous and continuous experiments to scale-up the best possible configuration selected during the batch study. Finally, an economic evaluation will be carried out to support the commercialization of the developed technology. This project will develop a novel and ecofriendly recycling process which will increase the recycling rates, reduce the waste and proliferate the circular economy in EU and also contribute in reducing its CRM dependency on non-EU countries. It will also train the experienced researcher in developing green technology and soft skills and make the host eminent in innovative biotechnology.

Disruptive development of brain-inspired computing, machine learning and deep neural networks for electronic assistants in smartphones, autonomous driving systems or chatGPT require new logic and storage concepts, which are beyond conventional von Neumann computer architectures. Materials known as multiferroics are identified as key enablers of these technologies. In contrast to ferromagnets, where the magnetic state is controlled by magnetic fields (energy inefficient due to flowing currents), magnetoelectric multiferroics allow manipulation of magnetic states by electric fields. The great promise of multiferroic materials towards energy efficient computing is compromised by the limited material portfolio. Literally, after decades of research, we have only one multiferroic (i.e. BiFeO3) potentially promising for room temperature spintronic devices. Even this most advanced material meets challenges outperforming state-of-the-art CMOS elements. The mainstream approach to design magnetoelectrics is to induce ferroelectric ordering in magnets to control non-volatile magnetic states electrically. Although intuitively understandable, this concept failed providing a technologically-relevant multiferroics. Here, we propose a paradigm shift in the design of multiferroic materials. Instead of trying to induce ferroelectricity, we will realize curvilinear multiferroics by imposing ferrotoroidal order in geometrically curved magnetic thin films. Fundamentally, we predict that effects of geometric curvature and inhomogeneous mechanical strain will induce sizeable ferrotoroidal order parameter in any magnetically ordered material, rendering this material multiferroic. Hence, curvilinear systems will turn rare ferrotoroidic materials in a broadly populated material class, available for material science and technologies similar to the conventional ferromagnets. This project will enable curvilinear multiferroics and validate their application potential for memory and logic devices.