The TNT-Sensor-IA project aims in designing of a new generation of multiplexed array microsensors integrating a metamaterials whose porosity can be spatially programmed. Such a direct laser writing approach associates the latest advances in multiphoton stereolithography (SLA) with those in the artificial intelligence. A progressive sensor specialization processing based on deep learning methods will be performed in order to detect TNT (2,4,6-trinitrotoluene) traces in complex gas mixtures. Note that the majority of the sensors use machine learning only through a unidirectional procedure that provides a simple feed back analysis of the sensor performance. The originality of our project is to propose an iterative algorithmic strategy to reprogram the sensor after each learning cycle. This advantage stems from the computational flexibility proposed by SLA to reprogram on demand the porosity of this metamaterial over a wide space of possible configurations. Hence, beyond the strategic issue to target TNT, the principal constituent of 85 % of unexploded land mines worldwide, the great ability of our multiplexed sensors for learning make them very promising candidates for other sensing applications.

PHOTOCAT aims at studying the reaction mechanisms of two alternative photo-catalytic processes. One deals with recycling CO2 into organic “platform” chemicals such as methanol. The other produces clean/renewable hydrogen fuel from water. Both of these processes involve transition metal clusters as photo-catalytic centers. The idea is to use an ion trap mass spectrometer as a molecular reactor in the gas-phase, where selected ions (reactive intermediates) can react under controlled conditions with neutral reagents and the progress of the reaction is monitored by mass spectrometry (MS). This will permit to evaluate the reactive properties of intermediates at every step of the catalytic cycle and to understand the details of the mechanism. A virtuous iterative cycle between synthesis and MS will lead to metallic clusters with optimal performances.

UltimSMM project proposes original synthetic pathways to generate ideal lanthanide-based sandwich metallocene complexes towards ground-breaking insights into the field of lanthanide Single Molecule Magnets (SMMs). Bulky cyclopentadienyl-based trivalent dysprosium complexes have recently led to impressive progress in the field of lanthanide SMMs, however, so far the perfect geometry has not been obtained in these sandwich complexes (Cp-Dy-Cp angle of 180°). This project aims to synthesize such unprecedented linear trivalent complexes based on pentaarylcyclopentadienyl ligands starting from zero-valent lanthanides and exploring straightforward C-FG bond cleavage (FG = P, Si, halides) routes driven by prospective quantum chemical calculations. The reactions will be performed in solution or, for the first time, under solvent-free ball-milling techniques. Variation of the aryl groups, introduction of heteroelements in the cyclopentadienyl ring and employing lanthanide metals beyond dysprosium are among the target modifications, providing complexes designed to lead the race in the field of high-temperature nanomagnets.

CHIFTS is an exploratory project aiming at investigating the potential of chiral materials as spin filters for electrical spin injection into 2D Transition Metal Dichalcogenide (TMDs). Those chiral materials allow for efficient spin filtering with an out of plane spin polarization which is a key asset for 2D spin opto-electronics. The objective of this project is to demonstrate the potential of chiral organic or hybrid organic-inorganic materials to be integrated on 2D TMDs for outstanding spin injection efficiency. The objectives of CHIFTS are: (i) to develop and integrate 2D chiral organic-inorganic hybrid perovskites on TMDs, (ii) to investigate the interface electronic and spin-dependent transport properties and (iii) develop new spin optronics devices based on these systems. Preparation of prototypical spin optronic devices based on these Chiral/2D TMD hybrid systems will be a major outcome in the context of actual rapid development of 2D spintronics.

MARCEL 2.0 proposes an original concept where metallic nanocatalysts (Au, Ag, Cu nanoparticles) are functionalized with molecular hosting cavities bearing metallic complexes in order to direct the reactivity in ORR and CO2RR electrocatalysis. Both of these processes are complex and require efficient and highly selective catalysts as the metalloenzymes. Inspired form such biological systems whose functioning is based on confinement and supramolecular effects, MARCEL seeks the rational control of forming and stabilizing intermediates to guide specific reaction pathways. This innovative design that relies on surface supramolecular effects will be further combined to plasmonic effect in order to enhance the electrocatalytic performance. The reactivity and interfacial phenomena will be thoroughly investigated by combining experimental (electrochemistry, in situ spectroscopies) and computational analyses.