New strategies on the application of artificial intelligence in the field of phytoremediation.

Artificial Intelligence (AI) is expected to play a crucial role in the field of phytoremediation and its effective management in monitoring the growth of the plant in different contaminated soils and their phenotype characteristic such as the biomass of plants. This review focuses on recent applications of various AI techniques and remote sensing approaches in the field of phytoremediation to monitor plant growth with relevant morphological parameters using novel sensors, cameras, and associated modern technologies. Novel sensing and various measurement techniques are highlighted.

In-situ stabilization of sedimented ash deposit by partial penetrating chemical columns.

This paper highlights the efficacy of partial penetrating chemical columns of sodium hydroxide (NaOH) in improving the geo-engineering and leaching characteristics of sedimented ash deposits through a comprehensive laboratory model testing program. Sedimented ash beds were formed in cylindrical tanks and treated with centrally installed chemical columns of either 9M or 18M concentration. After specified curing periods the in-situ moisture content, dry density, unconfined compressive strength (UCS), hydraulic conductivity, pH and concentration of major and trace elements were measured at different locations.