The DIA-SOLAIRE project aims to develop integrated diagnostic and prognostic approaches for existing and future photovoltaic (PV) power plants. These approaches will be hybrid, integrating both physical models and models based on experimental data, while exploring the potential of statistical and machine learning methods. The aim is to extend the lifetime of PV power plants and to optimize the management of their energy performance, while taking into account technological, human and environmental factors of influence, over the medium and long term, in a context of climate change. Energy production drifts and their causes can be identified, and performance and profitability projections can be proposed by introducing degradation distributions and economic models. Finally, changes in maintenance practices brought about by the implementation of artificial intelligence tools will be analyzed with PV plant operators. The tools developed will incorporate a man-machine interface enabling users and operators to support them in making decisions in real time, based on adapted performance criteria.

This project unifies four teams stemming from research laboratories in mathematics and theoretical physics having high world-wide scientific reputation of experts in the field of the classical and quantum integrable systems. It aims at developping new themes of research in the field of the quantum integrable systems, their underlying algebraic structures, mainly the elliptic algebras and the dynamical algebras; algebraic methods of resolutions of these systems: the representation theory of quantum groups and algebras, the methods of the Bethe Ansatz. To this more mathematical aspects the project crosses a "transversal" physical theme - the calculation of correlation functions of quantum integrable models of the " spin chain " types which represents at the moment the major challenge and the key domain of activity for a relevant use of the quantum integrable systems in physics. This theme overlaps partially to three "tasks" described below: Task 2. Development of the Bethe Ansatz techniques: through the generalization of " Manin's matrices"; in a calculation of correlation functions through the " form-factor "approach, and by fermionic representation; in a calculation of scalar products of Bethe vectors in a hierarchical BA. Spot 3. Elliptic algebras: elliptic Gaudin models, partition functions of the SOS-models and 8 - vertex model with DWBC boundary conditions; Sklyanin-Odesskii-Feigin quantum and Poisson algebras. Task 4. Dynamical Yang-Baxter algebras: correlations functions of open XXZ-model ; " dynamical Manin's matrices ", construction of new dynamical YB algebras (with non-commutative parametres and non-zero weights).

Resistance to traditional antimicrobial therapies is a rapidly increasing problem that in a few years could make infections impossible to treat and bring the state of medical care back to the pre-antibiotic era from the beginning of the last century. Indeed, the extensive use of antimicrobials worldwide (such as antibiotics) during the last decades has led to the apparition of a growing multiresistance phenomenon. Hence, if the strategy of combating infections is not significantly changed in the coming years, the problems related to resistant bacteria will escalate even further. At the same time, medicine faces many technological shortcomings that the development of new therapeutic systems tries to overcome, as Drug Delivery Systems (DDS) which unmistakably took an important place in human therapeutics. As a result, development of new effective antimicrobial compounds and alternative treatments is now a real issue and an important part of the European action plan against the rising threats from antimicrobial resistance. During the last decades, DDS definitely revealed essential in human therapeutics. DDS are obtained by the effective encapsulation of drugs in carriers allowing a safe and efficient controlled delivery in the body. Therefore, it is necessary to develop formulation processes which are green, flexible and respectful of Good Manufacturing Practices. The project challenge is to develop a sustainable continuous process producing nanostructured calcium carbonate (nCC) and biocompatible particles for antimicrobials delivery as Antibiotics or Antimicrobial peptides (AMP). The project team expertise and its complementarity provide the capacity to cover all the necessary competences to develop such an innovative drug product. The innovation of the CarboMIC project is to develop the Galenic-on-chip concept leading to the production of carriers and allowing the integration of ex situ and in situ physicochemical characterization close to the final product. Moreover, the proposed approach will allow a fine control of the physicochemical characteristics of drug carriers (size, structure, surface properties, drug loading), depending on the geometry of the microreactor, thermodynamics and hydrodynamics of the process. Besides on longer terms thanks to the use of a microfluidic device, it could be expected an easy scale-up at industrial- scale of this innovative antimicrobial carrier production. In addition, this approach leads to the minimization of energy consumption and environmental impacts which is an important issue for industrial processes development. In this way, the eco-design methodology will be deployed far upstream during the development of the encapsulation process. Finally, full physicochemical and biological characterization of the Antimicrobial-nCC carriers will be carried out to tune their functionalities in order to improve their therapeutic potential on the infected site and to choose the local administration route which is the most suitable.

The project deals with the functionalization of conductive surfaces via the reduction of diazonium precursors. This efficient process is booming but classically leads to the non reproducible elaboration of structurally disorganized multilayers, which are very difficult to characterize. The objective is to develop a methodology allowing the grafting control of the organic entities on the substrate in terms of thickness and organization. The main idea is to control the polymerization which represents a major barrier for obtaining reproducible and organized layers. Instead of playing with the molecular structure of the grafts as reported by recent works, the project proposes to directly act on the mechanism via the use of radical traps. This approach allows, in one hand, to avoid the synthesis of complex sterically hindered precursors, and in the other hand, to extend the control of the layers to every kind of structures without resorting to the post-functionalization The project aims a significant progress in the control of the two main functionalization methods using diazonium precursors : electrografting and spontaneous grafting. Those two methods experimentally differ by the use of an electrochemical assistance in the first case, whereas the second exploits the intrinsic reducing character of the substrate to be modified. A common radicalar mechanism is admitted until now to explain the generation of polymeric layers, but recently acquired knowledge tends to differentiate the two ways. This fact commands to separately consider the grafting problematic depending on whether electro-induction is used or not. The first part of the project will be dedicated to the validation and development of the control strategy for electrografting and spontaneous grafting on various substrates via the adding of radical scavengers. This way will allow to knock down the scientific barriers identified (nature of the substrate, structure of radical scavengers) and optimize the condition of the grafting control in order to get close to near monolayer materials. The impact of the diazonium precursor substitution on the organic film growth in the presence of radical scavenger will be of special interest. The second part of the project will deal with the comprehension of the grafting control and with the development of mechanistic aspects. This approach will bring to a new point of view on the key factors that lead to uncontrolled polymerization of diazoniums. The last part of the project will take advantage of the scientific knowledge acquired during the two first parts to study the properties and reactivity of the organic layers. The aim is to quantify the gain obtained by the radicalar control strategy and extend the knowledge to the accessibility of the confined species on the surface. The establishment of structure/properties relationships will be investigated on nanomaterials functionalized by absorbent and/or fluorescent moieties, whereas studies of the interfacial reactivity will be focused on electrocatalytic surfaces incorporating nitroxyl radicals, whose behaviour is known by the team. The multidisciplinary team will be composed of three physico-chemists, one organic chemist, and one physicist, all located at the MOLTECH-Anjou laboratory.

Europe urgently needs to find pathways towards agroecological transition of agroecosystems in support to food security, climate change resilience, biodiversity and soil carbon stocks restoration. In PHENET, the European Research Infrastructures (RI) on plant phenotyping (EMPHASIS), ecosystems experimentation (AnaEE), long-term observation (eLTER) and data management and bioinformatics (ELIXIR) will join their forces to co-develop, with a diversity of innovative companies, new tools and methods - meant to contribute to new RI services - for the identification of future-proofed combinations of species, genotypes and management practices in front of the most likely climatic scenarios across Europe. Ambitioning to go beyond current highly instrumented but often spatially and temporally limited RI installations, PHENET derived services will allow wide access to enlarged sources of in-situ phenotypic and environmental data thanks to (i) new AI-based multi (agroecology-related) traits multi-sensors devices (ii) to unleashed access to high resolution Earth Observation data connected to ground based data, (iii) FAIR data support for connection with (iv) new generation of predictive modeling solutions encompassing AI and digital twins. Developments will be challenged by and implemented in a series of eight Use Cases covering a large range of agroecosystems but also of ecosystems to demonstrate portability of solutions. Several of these Use Cases will mobilize on-farm data. A large effort will be devoted to training RI staff and beyond through a sustained collection of training material fed by experts. Outreaching activities will aim at enlarging the range of RI users. PHENET will not only strengthen RI but will also have major impact on the development of innovative companies on phenotyping, envirotyping and precision agriculture as well as on the emergence of climate smart crop varieties and innovative practices fitted to climate change and agroecological transition.