10 research outputs found
Probing the Mechanism of Silica Polymerization at Ambient Temperatures using Monte Carlo Simulations
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Probing the Mechanism of Silica Polymerization at Ambient Temperatures using Monte Carlo Simulations
We have developed a model for silica polymerization at ambient temperatures and low densities and have studied this using reactive Monte Carlo simulations. The model focuses on SiO4 coordination with the energetics of hydrolysis and condensation reactions treated via the reaction ensemble. The simplicity of the model makes large system sizes accessible on a modest computation budget, although it is necessary to make additional assumptions in order to use the reactive Monte Carlo method as a simulation of the system dynamics. Excellent agreement for the evolution of the Qn distribution is obtained upon comparing the simulation results to experimental observations. The analysis of simulation trajectories provides mechanistic insight into the polymerization process, showing the following three regimes: oligomerization (0−1 h), ring formation (1−2.6 h), and cluster aggregation (2.6−5.6 h)
Impacts of Land Use Change on Water Quality Index in the Upper Ganges River near Haridwar, Uttarakhand: A GIS-Based Analysis
The water quality of rivers is deteriorating due to human interference. It is essential to understand the relationship between human activities and land use types to assess the water quality of a region. GIS is the latest tool for analyzing this spatial correlation. Land use land cover, and change detection are the best illustration for showing the human interactions with land features. This study assessed water quality index of the upper Ganges River near Haridwar, Uttarakhand, and spatially correlated it with changing land use to reach a logical conclusion. In the upper course of Ganges, along a 78-km stretch from Kaudiyala to Bhogpur, water samples were collected from five stations. For water quality index, physicochemical parameters like pH, EC, DO, TDS, CaCO3−, CaCO3, Cl−, Ca2+, Mg2+, Na+, K+, F−, Fe2+ were considered. The results of the spatial analysis were evaluated through error estimation and spatial correlation. The root mean square error between spatial land use and water quality index at the selected sampling sites was estimated to be 0.1443. The spatial correlation between land use change and site-wise differences in water quality index also showed a high positive correlation, with R2 = 0.8455. The degree of positive correlation and root mean square error strongly indicated that the water quality of the river in the upper course of the Ganges is highly impacted by human activities