CO2-AMIGOS · Unlocking CO2 to acrylate using Mechanistic Investigation Guided by Operando Spectroscopy and Active Learning

I will integrate operando spectroscopy, modelling and active learning to increase the durability and ac-tivity of Ni-catalysts for CO2-to-acrylate conversion. Systematic understanding of catalyst deactivation and rational optimization of additives will provide transferrable methodologies to unlock sustainable C–C bond formation.The synthesis of alkali acrylates by Ni-catalysed carboxylation of ethene using CO2 is emerging as an alternative route to acrylate monomers. It relies on Ni(0)-phosphine catalysts promoted by combinations of Lewis-acidic metals with Brønsted bases. This approach promises: i) CO2 conversion to high-added-value polymers such as super-absorbents, ii) phasing out propene in favour of ethene, which has more secure pric-ing and can be derived from biomass via bio-ethanol, and iii) reliance on earth-abundant Ni. Yet, fast deac-tivation and slow turnover frequency (TOF) limit turnover numbers (TON) under 1000, preventing commercial applications which requires TONs above 105. I propose an integrated approach to overhaul the catalyst, promoter and reaction conditions to surpass these limitations. My first objective is to design an operando approach to investigate catalyst deactivation, from the ex-perimental setup design to the kinetic data resolution needed to quantify deactivation phenomena. My second objective is to achieve a molecular understanding of the system using molecular modelling informed by spectroscopic and kinetic data. My third objective is to develop an active learning methodology to rationally design catalytic CO2-to-acrylate promoters. I propose a mechanism- and data-driven overhaul of reaction conditions and additives to produce transferable principles to improve Ni catalysts.The fellowship will provide me with a comprehensive and tailored training program combining scientific skills with professional development, to enable my growth into an internationally visible independent researcher.