Industrial waste recycling approach: An ecofriendly geopolymer binder for clean and sustainable environments (A 24-h green recycling process).

Bypass cement waste dust (BCWD) significantly threatens human health and the environment due to its high concentrations of fine, respirable crystalline silica, chlorine, and sulfates. This study introduces an eco-friendly recycling approach that processes BCWD at a low temperature of 80 °C for 24 h. The method combines 50% BCWD with an equal proportion of natural black volcanic ash (BVA) and varying concentrations of NaOH to produce an innovative material known as Green Geopolymer Bypass Binder (GGBB).

Integrated machine learning-based model and WQI for groundwater quality assessment: ML, geospatial, and hydro-index approaches.

The demands upon the arid area for water supply pose threats to both the quantity and quality of social and economic activities. Thus, a widely used machine learning model, namely the support vector machines (SVM) integrated with water quality indices (WQI), was used to assess the groundwater quality. The predictive ability of the SVM model was assessed using a field dataset for groundwater from Abu-Sweir and Abu-Hammad, Ismalia, Egypt.

Evaluation insight into Abu Zenima clay deposits as a prospective raw material source for ceramics industry: Remote Sensing and Characterization.

The rapid development and mutations have heightened ceramic industrialization to supply the countries' requirements worldwide. Therefore, the continuous exploration for new reserves of possible ceramic-raw materials is needed to overwhelm the increased demand for ceramic industries. In this study, the suitability assessment of potential applications for Upper Cretaceous (Santonian) clay deposits at Abu Zenima area, as raw materials in ceramic industries, was extensively performed.

Hybrid-based Bayesian algorithm and hydrologic indices for flash flood vulnerability assessment in coastal regions: machine learning, risk prediction, and environmental impact.

Natural hazards and severe weather events are a matter of serious threat to humans, economic activities, and the environment. Flash floods are one of the extremely devastating natural events around the world. Consequently, the prediction and precise assessment of flash flood-prone areas are mandatory for any flood mitigation strategy.