Description

The material and energy recovery of industrial and household waste has become a major challenge in addressing the environmental and energy issues facing our society. Converting waste into valuable resources is fully aligned with the principles of the circular economy. Numerous processes have been developed to treat and valorize waste, including combustion, pyrolysis, pyrogasification and microbial degradation. Although highly effective, these technologies are not always suitable for highly aqueous feedstocks such as sewage sludge, manure, industrial sludges, or certain waste solvents.
Hydrothermal gasification is an innovative technology particularly well suited to this type of feedstock. It involves processing organic matter in an aqueous medium under high-pressure and high-temperature conditions, above the critical point of water (221 bar, 374°C). In this process, the mineral fraction of the waste (salts, ash, and minerals) can be separated, while the dissolved organic matter is converted into a gas mixture rich in methane, hydrogen, and carbon dioxide. This process therefore offers strong potential for the production of renewable gases while reducing the volume of waste requiring disposal.
The optimization of hydrothermal gasification and its scale-up to industrial applications require detailed knowledge of the thermophysical properties of the fluids involved. Among the most important properties are density, viscosity, heat capacity, absorption coefficient and thermal conductivity, which govern heat and mass transfer, the energy consumption of the process, and the overall performance of the reactor.
The feedstocks considered are complex multicomponent mixtures. In this context, the correlations available in the literature are not sufficiently accurate to predict their thermophysical properties. In addition, the extreme operating conditions make experimental measurements difficult, costly, and time-consuming. These limitations highlight the value of numerical modeling approaches, which nevertheless require reliable experimental data for their development and validation.
The main objective of this PhD project is therefore to design and develop a miniaturized experimental device based on millifluidic technology. This setup will enable the measurement of thermophysical properties under high-pressure and high-temperature conditions with precise control of operating parameters.
In an initial phase, the experimental setup will be designed, instrumented, and validated using simple single-component, single-phase model systems. In a second phase, mixtures of increasing complexity will be investigated in order to progressively reproduce the characteristics of real feedstocks. The data obtained will allow analyzing the influence of composition, temperature, and pressure on the measured properties.
Ultimately, these results will be used to develop new equations of state and predictive correlations adapted to the complex media encountered in hydrothermal gasification. These correlations will be integrated into numerical simulation tools to improve process design, energy optimization, and performance assessment.
This work, at the interface of chemical engineering, experimental thermodynamics, and data science, will provide significant advances for the development of innovative waste valorization processes.