Subsurface modelling using geoscientific data is essential to understand the Earth and to sustainably manage natural resources. Geology and geophysics are two critical aspects of such modelling. Geological and geophysical models have different resolutions and are sensitive to different features. Considering only geological or geophysical aspects often leads to contradictions as creating an Earth model is a highly non-unique problem. In addition, the sensitivity of the data is limited and many objects cannot be differentiated by a single discipline. The only way to address this is solving the longstanding challenge of integrating of geological data and knowledge (orientation data, contacts and ontologies) and geophysical methods (physical fields). Recent techniques usually focus on features the data is sensitive to and merely use one discipline to falsify hypotheses from the other. Such approach prevents considering the full range of potential outcomes, and fails to exploit the sensitivity of both approaches. This project proposes a different philosophy to solve the challenge of connecting geological and geophysical modelling. It first involves the development of a novel method integrating the two model types in a single framework giving them equal importance. Geological and geophysical data will be modelled simultaneously through an implicit functional mapping one domain into the other by linking their respective models. This will allow the simultaneous recovery of compatible geological and geophysical models. Secondly, this project will use a new hybrid deterministic-stochastic optimisation technique to explore the range of subsurface scenarios to estimate the diversity of features that cannot be differentiated based on the available data. Thirdly, after proof-of-concept, the method will be applied to two cases: imaging of a mantle uplift in the Pyrenees Mountains (France/Spain), and study of potential new subsurface scenarios around the Kevitsa mine (Finland).

Light elements such as hydrogen and nitrogen present large isotope variations among solar system objects and reservoirs (including planetary atmospheres) that remain unexplained at present. Works based on theoretical approaches are model-dependent and do not reach a consensus. Laboratory experiments are required in order to develop the underlying physical mechanisms. The aim of the project is to investigate the origins of and processes responsible for isotope variations of the light elements and noble gases in the Solar System through an experimental approach involving ionization of gaseous species. We will also investigate mechanisms and processes of isotope fractionation of atmophile elements in planetary atmospheres that have been irradiated by solar UV photons, with particular reference to Mars and the early Earth. Three pathways will be considered: (i) plasma ionisation of gas mixtures (H2-CO-N2-noble gases) in a custom-built reactor; (ii) photo-ionisation and photo-dissociation of the relevant gas species and mixtures using synchrotron light; and (iii) UV irradiation of ices containing the species of interest. The results of this study will shed light on the early Solar System evolution and on processes of planetary formation.

The Internet of Things (IoT) is the next technological revolution. 12.2 billion IoT devices were already connected in 2021 and the proliferation rate forecast is very high. Most of these devices are wireless, operate indoors and are powered through a primary battery, whose lifetime is about 8-25 months for such applications. In few years, hundreds of millions of IoT batteries may have to be replaced every day, which may doom the sustainability of the IoT ecosystem. Recent developments in low-power electronics and low-energy wireless communication protocols have considerably lowered the energy and power demand for IoT devices and opened new perspectives for powering them through artificial light energy harvesting. Indoor photovoltaic harvesters have a high Power Conversion Efficiency (PCE) potential because of the narrow-band photon light spectra of the Light Emitting Diode (LED) sources. Efficiencies at laboratory scale are yet dramatically lower than expected, because the quality of the material is crucial at low irradiance. Organic or hybrid organic-inorganic solar cells show the highest PCE for such indoor light applications but suffer from stability issues. Inorganic III-V or amorphous silicon devices have been developed but have low PCE. Among Indium-free chalcogenide absorbers, CuGaSe2 (CGS) is the most promising candidate but the synthesis of homogeneous and single phase CGS thin films at a temperature compatible with a lightweight and flexible substrate, mandatory for IoT applications, is difficult. We recently demonstrated that metal halide post-deposition treatments can be used to drastically decrease the synthesis temperature of CGS films as well as produce single phase thin film with large grains. This new and unique approach consisting in using metal halides as transport agent has therefore all the ingredients to break the technological locks that, to date, restrain the use of stable and industrially compatible CGS for indoor PV applications.