Sustainable Plasma Gasification Treatment of Plastic Waste: Evaluating Environmental, Economic, and Strategic Dimensions.

The conversion of waste to energy is an essential process in the Middle East, especially in Saudi Arabia, where it plays a crucial role in waste management. The annual analysis of the decomposition hazards of the landfills in the city of Makkah showed that they ranged from 168,000 Mg in 1994 to 297,000 Mg in 2022. The emission costs of pollution ranged from 4 million in 1994 to 7 million in 2022.

Plasma gasification of refuse derived fuel in a single-stage system using different gasifying agents.

The renewable evolution in the energy industry and the depletion of natural resources are putting pressure on the waste industry to shift towards flexible treatment technologies with efficient materials and/or energy recovery. In this context, a thermochemical conversion method of recent interest is plasma gasification, which is capable of producing syngas from a wide variety of waste streams. The produced syngas can be valorized for both energetic (heat and/or electricity) and chemical (ammonia, hydrogen or liquid hydrocarbons) end-purposes.

Dislocation mechanism of deuterium retention in tungsten under plasma implantation.

We have developed a new theoretical model for deuterium (D) retention in tungsten-based alloys on the basis of its being trapped at dislocations and transported to the surface via the dislocation network with parameters determined by ab initio calculations. The model is used to explain experimentally observed trends of D retention under sub-threshold implantation, which does not produce stable lattice defects to act as traps for D in conventional models. Saturation of D retention with implantation dose and effects due to alloying of tungsten with, e.

Development of the gas-puff imaging diagnostic in the TEXTOR tokamak.

Gas puff imaging (GPI) [S. J. Zweben, D.

A probabilistic model for the identification of confinement regimes and edge localized mode behavior, with implications to scaling laws.

Pattern recognition is becoming an important tool in fusion data analysis. However, fusion diagnostic measurements are often affected by considerable statistical uncertainties, rendering the extraction of useful patterns a significant challenge. Therefore, we assume a probabilistic model for the data and perform pattern recognition in the space of probability distributions.