Deciphering runaway mechanisms in Lithium-ion batteries by in mortem spectroscopic approaches
Deciphering runaway mechanisms in Lithium-ion batteries by in mortem spectroscopic approaches
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Deciphering runaway mechanisms in Lithium-ion batteries by in mortem spectroscopic approaches
Currently, most industrial H₂ is derived from natural gas and oil, emitting significant CO₂. “Green H₂” represents only 1% of production and is mainly produced via water splitting using scarce and expensive noble metal catalysts like Pt, which have a high carbon footprint.
As plastic waste defines the present era, efforts towards the development of recycling technology are ramping up. For polyolefins (PO), common packaging materials, the available technologies of mechanical recycling and of pyrolysis (thermal conversion) have several drawbacks and can process only a fraction of waste.
Context: Currently, only 10-20% of end-of-life catalysts are recycled after their use in refineries. However, these catalysts contain critical metals (Ni, Co) and the management of these resources is becoming increasingly constrained and regulated. This makes catalyst recycling a major environmental and economic challenge.
Context
IFPEN aims to position itself as a provider of innovative, cleaner, and more efficient processes. The proposed PhD thesis falls within the framework of the implementation and optimization of liquid-liquid extraction for metal recovery in the context of battery recycling.
This PhD position deals with Physics Informed Machine Learning (PIML) modeling methodologies, a novel generation of deep-learning architectures that combines physical laws with data-driven approaches.
Plastic wastes recycling is a major environmental issue. Although European regulations are initiating major changes in terms of collection and incorporation of recycled materials, technologies for recycling such complex streams still must be developed.
With the rise of new technologies and the rapid evolution of transportation modes, understanding mobility behaviors becomes a significant challenge to optimize infrastructure, anticipate transportation demand, and guide public policies.
Per- and polyfluoroalkyl substances (PFAs) represent a family of over 4,000 compounds synthesized since the 1950s, used in various industrial sectors for their exceptional properties (non-stick, waterproof, and heat-resistant).