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Detecting gaseous emissions from either industrial storage sites or natural environments is a major challenge when it comes to controlling harmful emissions and greenhouse gases.
With the announced drastic reduction of the amount of fossil energy resources in the European energy mix, it is important to define viable alternatives to petrochemicals. The transformation of lignocellulosic biomass and the various synthesis processes make it possible to provide a wide variety of families of compounds with high added value.
Under the European Green Deal, the demand for advanced secondary batteries is a pressing challenge. Critical for the impending energy transition, these batteries are instrumental for advancing the electric vehicle market, a linchpin for EU industrial and economic expansions.
Understanding the hydro-sedimentary dynamics at the watershed scale in response to daily or multi-year forcing is a key challenge in assessing the impact of climate change on water resources.
Pour répondre aux défis du domaine de l’énergie, IFPEN propose aujourd’hui un procédé qui permet de produire de l’éthanol à partir de biomasse lignocellulosique.
INRIA and IFP Energies nouvelles, leading French research laboratories, are seeking a talented and motivated master's student to join their team for a PhD position. As numerical simulation plays a pivotal role in our research and industrial applications, optimizing the performance of our parallel simulators is crucial.
Electric cars contribute to the de-carbonization of the transport sector and their massive deployment is foreseen. In this context, the battery industry strives for ever improved technologies, both in terms of performance and safety.
It is now established that molecular hydrogen (H2) exists naturally on the planet in the form of diffuse or continuous emanations. However, many questions remain unanswered as to its origin, formation mechanisms and real potential for exploitation.
The numerical discretization of physical models representing evolutionary problems in many fields leads to nonlinear algebraic systems of very large dimensions. The process of solving these systems, which must be carried out robustly and rapidly at each time-step in order to increase software efficiency, comes up against a number of obstacles.
The numerical discretization of physical models in many fields leads to very large nonlinear algebraic systems. The resolution of these systems, which is usually achieved by successive linearization like Newton's method, needs to be fast in order to increase software efficiency.
In the context of reducing the environmental impact in polymer manufacturing, the use of recycled plastics will rise. Mechanical recycling is simple and economic, but faces limitations in product quality and appearance.
The importance of air quality cannot be underestimated as it represents a major public health issue: today, nearly 91% of the global population is exposed to air pollution levels exceeding the exposure thresholds set by the WHO. This thesis lies at the intersection of three scientific domains: numerical modeling, air quality, and deep learning.